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| Citation |
- Permanent Link:
- https://ufdc.ufl.edu/UF00084178/00001
Material Information
- Title:
- Productivity measurements and simulation models of a shallow estuarine ecosystem receiving a thermal plume at Crystal River, Florida
- Creator:
- Smith, Wade Hampton Barnes, 1944- ( Dissertant )
Odum, H. T. ( Thesis advisor )
Brezonik, P. L. ( Reviewer )
Bullock, T. E. ( Reviewer )
Ewel, J. J. ( Reviewer )
Snedaker, S. C. ( Reviewer )
- Publisher:
- University of Florida
- Publication Date:
- 1976
- Language:
- English
- Physical Description:
- xx, 426 leaves : ill. ; 28 cm.
Subjects
- Subjects / Keywords:
- Dissertations, Academic -- Environmental Engineering Sciences -- UF
Environmental Engineering Sciences thesis, Ph.D.
Estuarine ecology -- Florida -- Crystal River ( lcsh )
Thermal pollution of rivers, lakes, etc ( lcsh )
City of Crystal River ( flgeo )
City of St. Petersburg ( flgeo )
Oxygen ( jstor )
Water temperature ( jstor )
Crystals ( jstor )
- Spatial Coverage:
- United States -- Florida -- Crystal River
- Coordinates:
- 28.9 x -82.6
Notes
- Abstract:
- The effects of the heated discharge of two power
plants on the receiving estuarine ecosystem near Crystal. Benthic populations dominated total metabolism low of 3.3 g 02/m2.day to a spring high of 8.8 g 02/m2-day.
In the discharge area it was relatively constant, remain-
ing about 4 g 02/m -day in all seasons. Phytoplankton
production normally was about 5 percent of total produc-
tion in the unaffected areas and about 23 percent in the
discharge area. In the spring its contribution increased
greatly to 25 percent in the unaffected area and 70 per-
cent in the discharge area.
Total biomass was less in the discharge than
in unaffected areas. Lower standing stock of primary
producers and benthic invertebrates in the discharge
area accounted for almost all the difference.
Diversity was lower in the discharge bay than in
the unaffected area. Mixed macroalgae and seagrasses
were the dominant benthic producers in the unaffected
areas, while the seagrass Halodule wright was virtually
the only species in the discharge bay. Species diversity
was lower for oyster reef organisms, and fewer species
of fish were caught in drop nets in the discharge bay
than in the unaffected bay.
A shift toward more cycling of material and energy
through the phytoplankton and filter feeders and away
from the benthic components of the system may have
occurred in the discharge area as an adaptation to the
thermal plume. Simulation of the model of diurnal system proper-
ties with coefficients representing those for discharge
conditions gave patterns similar to those measured in the
discharge bay. The model was relatively insensitive to
adjustments in water temperature within the range expected
in the future at Crystal River. A change in the quantity
of daily insolation produced a larger change in model
response.
The simulation model of seasonal system proper-
ties was also more sensitive to light than to water
temperature. Increasing temperature alone increased
primary production and total respiration somewhat, espe-
cially in the spring. Fish and invertebrate biomass
remained the same, while detrital storage declined,
perhaps indicating their importance as an energy source
for offsetting increased respiratory drains on consumers
because of increased temperature. Increases in light
alone greatly increased system storage and flows, sug-
gesting the importance of turbidity in controlling
metabolism in the discharge area. Increasing temperature
but decreasing light lowered metabolism.
Adjustments to the seasonal model tested the
theory that systems with prominent seasonal pulses may
be exploited by populations that move in during the period
of plenty, experience rapid exponential growth, and then
move away. With some migration the fish stock could main-
tain itself in a stable oscillating yearly pattern.
Results of other adjustments to the seasonal model
suggested that seasonal substitution of species of primary
producers may be the most effective way to make maximum
use of available energies at all times of the year.
in both systems. Community gross primary production
varied seasonally in.the unaffected areas from a winter
River on the west coast of Florida were investigated with
measurements and simulation models to help understand
relationships and predict the consequence of a third
power plant under construction. Energy circuit models
emphasizing diurnal and seasonal aspects of ecosystem
responses were used to assess the effect of power plant
operation on estuarine ecosystems. Field measurements
were taken in the discharge-affected and -unaffected
areas nearby.
- Thesis:
- Thesis--University of Florida.
- Bibliography:
- Bibliography: leaves 414-425.
- General Note:
- Typescript.
- General Note:
- Vita.
- Statement of Responsibility:
- by Wade Hampton Barnes Smith.
Record Information
- Source Institution:
- University of Florida
- Holding Location:
- University of Florida
- Rights Management:
- Copyright Wade Hampton Barnes Smith. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
- Resource Identifier:
- 025624501 ( ALEPH )
03105860 ( OCLC )
AAU4575 ( NOTIS )
Aggregation Information
- FAST1:
- Sciences and Technologies
- UFIR:
- Institutional Repository at the University of Florida (IR@UF)
- FEOL:
- Florida Environments Online
- ODUM:
- Howard T. Odum Center for Wetlands Publications
- UFETD:
- University of Florida Theses & Dissertations
- IUF:
- University of Florida
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PRODUCTIVITY MEASUREMENTS AND SIMULATION MODELS
OF A SHALLOW ESTUARINE ECOSYSTEM
RECEIVING A THERMAL PLUME AT CRYSTAL RIVER, FLORIDA
By
WADE HAMPTON BARNES SMITH
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1976
AC K NOWL E DGEM ENT S
Many of the ideas presented here were shaped in discussions among the entire systems ecology group of the Department of Environmental Engineering Sciences. Special acknowledgements go to major professor H. T. Odum for his stimulation, guidance, and the distinct privilege of participating in this program. My supervisory committee included P. L. Brezonik, T. Bullock, J. Ewel, and S. C. Snedaker.
This work was supported.by contract No. GEC 159, 918-200-188.19 (Models and Measurements for Determining the Role of the Power Plants a nd Cooling Alternatives at Crystal River, Florida) between the Florida Power Corporation and the University of Florida Systems Ecology Program, Department of Environmental Engineering Sciences, H. T. Odum, principal investigator.
Many people helped in the field and with data workup: J. Bevis, N. Black, W. Boynton, C. High, D. Hinck, M. Homer, M. Kemp, M. Lehman, H. McKellar, A. Merriarm, F. Ramsey, and D. Young. Analog computers used in this study were maintained by A. Copsey, and J. Murphey, who also provided programming assistance. Progress in
this study was much facilitated by K. Garrison, J. Johnson, D. McMullin, and W. Trowell of the Florida Power Corporati on.
Use of the R. V. Susio was provided by the State University System Institute of Oceanography.
ii i
TABLE'OF CONTENTS
Page
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . ii
LIST OF TABLES . . . . . . . . . . . . . . . . . . vii
LIST OF FIGURES . . . . . . . . . . . . . . . . . X
ABSTRACT . . . . . . . . . . . . . . . . . . . . . xvii
INTRODUCTION . . . . . . . . . . . . . . . . . . . I
System Adaptation, Environmental Impact,
and Thermal Loading of the Estuary at
Crystal River, Florida . . . . . . . . 5
Models for Gaining an Overview of the
Estuary and Power Plant at Crystal
River . . . . . . . . . . . . . . . . 9
Previous Studies of Thermally Affected
Aquatic Ecosystems . . . . . . . . . . 16
Description of Audy Area at crystal
River . . . . . . . . . . . . . . . . 21
Other Studies of the Crystal River
Region . . . . . . . . . . . . . . . . 31
Previous Simulation Models of Marine Ecosystems, Diurnal Oxygen Dynamics,
Temperature, and the Effects of Power
Plants on Ecosystems . . . . . . . . . 33
Plan of Study . . . . . . . . . . . . . . 39
. . . . . . . . . . . . . . . . . . . . .
Metabolism Measurements . . . . . . . . .
Model Diagrams for Comparing Ecosystems
Affected and Unaffected by the
Discharge Plume . . . . . . . . . . .
Simulation Model of Diurnal Properties
of the Inner Bay Ecosystem . . . . . .
Simulation Model of Seasonal Proper-ties
of the Inner Bay Ecosystem . . . . . .
ON . . . . . . . . . . . . . . . . . . . .
Seasonal Patl.erns of the Ecosystems at
Crystal River . . . . . . . . . . . .
Comparisons of the Ecosystems at Crystal
River and Adaptation to the Thermal
Discharge . . . . . . . . . . . . . .
Predictions of the Effect of tile Operation
of Unit Three at Crystal River . . . .
Energy Costs of Alternatives to Estuarine
Cooling of the Thermal Discharge at
Crystal River . . . . . . . . . . . .
Page
41 41 62 69 69 78 116 116
149 154 201 223 223 239 252 253
METHODS . . . . . . . . . . . . . . . . . . . .
Metabolic Measurements . . . . . . . . .
Other Field Measurements . . . . . . . . DATA ASSEMBLED FROM OTHER PHASES OF THE CRYSTAL
RIVER PROJECT AND ELSEWHERE . . . . . .
Energy Sources and Inflows Affecting the
Inner Bay . . . . . . . . . . . . .
Stocks of the Inner Bay . . . . . . . .
RESULTS DISCUSS
Paqe
APPENDICES . .
256
A EXPLANATION OF THE ENERGY SYMBOLS
USED IN THIS STUDY . . . . .
. . . . 257
B GRAPHICAL ANALYSES OF DIURNAL STUDIES
OF COMMUNITY METABOLISM IN THE INNER BAY AFFECTED BY THE THERMAL DISCHARGE
PLUME AND IN THE FORT ISLAND AND HODGES ISLAND AREAS AWAY FROM THE INFLUENCE OF THE THERMAL DISCHARGE
C INITIAL AND MAXIMUM VALUES OF STOCKS AND
FLOWS, HEAT BUDGET CALCULATIONS, CALCULATION OF TRANSFER COEFFICIENTS,
SCALED EQUATIONS, POTENTIOMETER SETTINGS, FUNCTION GENERATOR SET-UP,
AND ANALOG COMPUTER PATCHING DIAGRAM
FOR DIURNA SIMULATION MODEL OF
INNER BAY . . . . . . . . . . . . .
262 311
D INITIAL AND MAXIMUM VALUES OF STOCKS
AND FLOWS, CALCULATION OF TRANSFER
COEFFICIENTS, SCALED EQUATIONS,
POTENTIOMETRIC SETTINGS, FUNCTION GENERATOR SET-UP, AND ANALOG COMPUTER PATCHING DIAGRAM FOR SEASONAL
SIMULATION MODEL OF THE INNER BAY
E DOCUMENTATION OF DATA USED IN SUMMARY
DIAGRAMS OF SUMMER STOCKS AND FLOWS
FOR THE INNER DISCHARGE BAY AND
SOUTH INTAKE AREA . . . . . . . . .
LITERATURE CITED . . . . . . . . . . . . . . . .
BIOGRAPHICAL SKETCH . . . . . . . . . . . . . .
356
407 414 426
LIST OF TABLES
Table- Page
1 Results of a technique test of the
Winkler method to determine the effect
of the presence or absence of acid in
fixed bottles which have been stored
for eight hours before titration. 44
2 Seasonal comparison of average wind speed
at Crystal River site. 75
3 Record of metabolism for the inner discharge bay as measured by diurnal free water oxygen changes and light and dark
bottles. 117
4 Record of metabolism for the Fort Island
and Hodges Island areas away from ' the
influence of the power plant discharge as
measured by diurnal free water oxygen
changes and light and dark bottles. 121
5 Diffusion rates measured in the power
plant discharge and Fort.Island study
areas. 146
6 Average extinction coefficients for light
penetration of water on the inner discharge bay affected by the power plant discharge plume and unaffected areas to
the north and south. 148
7 Differential equations for dilurnal model
of inner bay given in Figure 40. 157
V i i
Table Page
8 Differential equations for seasonal
model of inner bay system given in
Figure 55. 202
9 Comparison of gross primary production and total respiration measured
at Crystal River with some values from
other areas in Florida and similar
systems elsewhere. 225
C-1 Documentation of values used for forcing
functions, standing stocks, and exchange rates in the diurnal simulation model of
the inner bay. 312
C-2 Initial and maximum values of storages
for diurnal simulation model of inner
bay. 329
C-3 Initial and maximum values of forcing
functions for simulation model of inner
bay. 330
C-4 Calculation of radioactive, evaporative,
and convective heat losses for use in
diurnal simulation model of inner bay. 331
C-5 Calculation of transfer coefficients for
diurnal simulation model of inner bay. 333
C-6 Equations of Table 7 scaled for simulation
of diurnal model of the inner bay given
in Figure 40. 339
C-7 Scaling of terms associated with photosynthesis in equations in Table 10 for
diurnal simulation model of the inner bay. 347
C-8 Potentiometer settings for initial run
of diurnal simulation model of inner bay. 349
C-9 Potentiometer settings for the EAI 580
variable diode function generator used to
produce the tidal volume exchange function
given in Figure 42 for the diurnal model
of the inner bay. 352
V i i i
Table Page
D-1 Documentation of values used for standing stocks and exchange rates in the
seasonal model of the inner bay. 356
D-2 Initial and maximum values of forcing.
functions and storages for seasonal
simulation model of inner bay. 376
D-3 Calculation of transfer coefficients for
seasonal simulation model of inner bay. 377
D-4 Equations of Table 11 scaled for simulation of seasonal model of the inner bay
given in Figure 54. 387
D-5 Scaling of terms associated with photosynthesis in equations in Table 8 for
seasonal simulation model of the inner
bay. 398
D-6 Potentiometer settings for initial run
of simulation of the seasonal model of
the inner bay. 402
D-7 Potentiometer settings for EAI 580 variable diode function generator used to
produce the seasonal cycle of sunlight
given in Figure 55 for the simulation
of the seasonal model of the inner bay. 404
E-1 Documentation of numbers appearing on
Figure 38 of the inner discharge bay
ecosystem affected by the thermal discharge of the power plant. 408
E-2 Documentation of numbers appearing on
Figure 38 of the south intake area ecosystem unaffected by the thermal plume of
the power plant. 411
LIST OF FIGURES
Figure Pg
1 Location of Florida Power Corporation's
power plants near Crystal River, Florida, in relation to the major features of the
regional coastline. 3
2 Energy diagrams of producer and consumer
modules indicating the push-pull effects
of temperature on internal processes. 8
3 Aggregated energy diagram of the main
features believed important in the ecosystem of the inner discharge bay at
Crystal River. 12
4 Energy diagram of the ecosystem of the
inner discharge bay, which includes much
of the complexity omitted from Figure 3. 15
5 Bathymetry of power plant discharge area
at Crystal River. 23
6 Thermally affected area showing location
of the shallow inner bay system dominated
by the seagrass, Halodule wrightii, and
the deeper outer bay system. 27
7 Typical daily tidal cycle at Crystal River
site indicating unequal high and low tides. 29
8 Model of factors affecting oxygen dynamics
in water. 46
9 Example of graphical format for calculation
of community metabolism-i at Fort Island, 24-25
August, 1973, using full diurnal curve of
oxygen. 50
Figure Laqe
10 Graphical format for calculation of
community metabolism using dawn-duskdawn data. 57
11 Comparison of community metabolism
estimates obtained from complete
diurnal measurements of oxygen versus
estimates obtained from dawn-duskdawn calculations made using the same
data. 60
12 Example of two experiments to determine oxygen diffusion coefficients by measuring the rate of return of oxygen into a
nitrogen-filled dome floating on the
water's surface. 65
13 Examples of submarine photometer measurements of light penetration through the water column taken at Fort Island away
from the influence of the power plant discharge plume and in the inner bay
influenced by the plume. 68
14 Average daily insulation by month at Tampa, Florida. 71
15 Wind direction by season at Crystal River site. 74
16 Monthly mean air temperature at Tampa, Florida. 77
17 Monthly mean precipitation at 'Tampa, Florida. 80
18 Weekly averages of surface water temperatures for the plume-affected inner discharge bay and ambient water of the south
intake area. 83
19 Weekly average of electricity generated by power units at Crystal River, and weekly
average intake and discharge water temperature for unit 1. 86
Figure Page
20 Average diel water temperatures measured during community metabolism studies of the inner discharge bay and the Fort
Island and Hodges Island control areas. 88
21 Diurnal patterns of electricity generated, water temperatures at three locations,
and tidal stage in the discharge area of
May 24-27, 1974. 91
22 Average salinities measured on the inner discharge bay and Fort Island and Hodges
Island study areas during the community
metabolism studies. 94
23 Seasonal patterns of benthic macrophytes in the thermally affected inner bay and
inshore portion of the south intake area. 97
24 Map of summer standing crop of attached macrophytic plants in the region near the
Crystal River power plants. 100
25 Seasonal diversity of benthic macrophytes in the inner discharge bay and the south
intake area. 102
26 Seasonal record of biomass of benthic macroinvertebrates in the inner discharge
bay and south intake areas. 105
27 Seasonal record of biomass of fish caught with drop nets in the inner discharge bays
and south intake areas. 107
28 Carbon, nitrogen, and phosphorus measurements at the mouth of the discharge canal
and a station in the south intake area. 110
29 Measurements of live chlorophyll-a and phytoplankton biomass at a station in the south intake area and at the mouth of the
discharge canal. 114
xii
Figure Page
30 Daytime net photosynthesis and night respiration in the inner discharge bay
affected by the thermal plume and the
Fort Island and Hodges Island area
away from the influence of the power
p 1 a n t 125
31 Daytime net photosynthesis plus night respiration as a measure of gross
primary production in the inner discharge bay affected by the thermal plume
and the Fort Island and Hodges Island
areas away from the influence of the
thermal plume. 127
32 All daytime net photosynthesis and night respiration values from Tables 6 and 7
and Figure 30 plotted on 12-month graph. 129
33 All daytime net photosynthesis plus night respiration values from Tables 6 and 7
and Figure 31 plotted on 12-month graph. 131
34 Average oxygen values from all summertime diurnal measurements taken in the inner
discharge bay and Fort Island control bay. 135
35 Seasonal averages of daytime net photosynthesis and night respiration in the
inner discharge bay and control areas. 138
36 Seasonal averages of daytime net photosynthesis plus night respiration as a
measure of gross primary production for plume-affected inner bay discharge area
and unaffected control areas. 141
37 Seasonal trends of the ratio of daytime net photosynthesis divided by night
respiration for plume-affected inner bay
area and unaffected Fort Island and Hodges
Island areas. 144
38 Summary energy diagram of summer stocks and flows for the inner discharge bay. 151
x i i i
Figure Page
39 Summary energy diagram of summer stocks of
biomass or material and flows of energy and organic matter for the south intake
area away from the influence of the power
plant discharge. 153
40 Energy diagram for simulation model of inner discharge bay emphasizing the
diurnal properties of the system. 156
41 Computer plots of forcing functions of tidal volume exchange, depth, offshore oxygen, and offshore water temperature
used in the diurnal simulation model. 163
42 Simulation results of diurnal model of inner bay with coefficients set as
originally scaled. 166
43 Data gathered from the inner bay during the community metabolism study of June
21-22, '1973, against which the simulation
of the model of Figure 20 was compared. 170
44 Solar insulation for June 21, 1973, as recorded by a pyranometer located at the
Crystal River power plant site. Total
radiation received is indicated. 172
45 Simulation results of diurnal model of inner bay with original scaling, but
sunlight reduced to a daily total
similar to June 21-22, 1973. 174
46 Simulation results of diurnal model of inner bay with equal amounts of canal and offshore water contributed to the
inner bay on a rising tide. 178
47 Simulation results of diurnal model of the inner bay with two parts canal water to one part offshore water contributed to
the inner bay on a rising tide.
48 Simulation results of diurnal model of inner bay with canal water alone being
contributed to the inner bay on a rising
tide. 182
x i v
Figure Page
49 Simulation results of diurnal model of the inner bay with a PC differential of discharge canal water
over ambient water and a mixing ratio
on a rising tide of one part canal
water to one part offshore water. 185
0
Simulation results of diurnal model of
the inner bay with a 7'C differential of discharge canal water over ambient
water and a mixing ratio of 2 parts
canal water to 1 part offshore water
on a rising tide. 187
51 Simulation results of diurnal model of the inner bay with a 7'C differential of discharge canal water over ambient water and with canal water alone flow-ing onto the inner bay on a rising tide. 192
52 Simulation results of diurnal model of the inner bay with no discharge of
cooling water from the power plant discharge canal and original scaling of
insulation. 194
53 Simulation results of diurnal model of the inner bay with no discharge from the
power plant discharge canal and insulation
reduced to one-half original scaling. 196
54 Simulation results of diurnal model with timing of occurrence of high and low tide
reversed from previous runs. 198
55 Energy diagram of simulated model of inner discharge bay emphasizing seasonal
properties of the ecosystem. 200
56 Seasonal patterns of insulation and temperature used as forcing functions in the
seasonal model of the inner bay ecosystem. 200
57 Simulation results with initial scaling of seasonal model of the inner bay. 210
Figure Page
58 Simulation results of seasonal model of the inner bay with seasonal pattern
of temperature increased 3'C. 214
59 Response of seasonal simulation model of the inner bay to increased temperature and turbidity. 217
60 Response of seasonal simulation model of the inner bay to decreased turbidity
and a seasonal temperature range as
originally scaled. 220
61 Response of seasonal simulation model of inner bay to decreased turbidity and a seasonal temperature range of
180C - 360C. 222
62 Energy diagram and analog computer patching diagram of simulation model of
producer module with temperature affecting both photosynthetic and respiratory
pathways. 231
63 Simulation results of model of producer module in Figure 62 with seasonally varying light and temperature. 233
64 Simulation response of seasonal model of the inner discharge bay to the addition of pathways of exchange of fish and fish
larvae with offshore waters. 237
65 Simulation results of seasonal model of inner bay as modified in Figure 64 with larger photosynthetic coefficient added
in winter. 241
C-1 Analog computer patching diagram of
scaled equations given in Tables C-6 and
C-7 for the diurnal simulation model of
the inner bay. 354
D-1 Analog computer diagram of scaled equations given in Tables D-4 and D-5 for the
seasonal Simulation model of the inner
bay. 406
x v i
Abstract of Dissertation Presented to the Graduate Council of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
PRODUCTIVITY MEASUREMENTS AND SIMULATION MODELS
OF A SHALLOW ESTUARINE ECOSYSTEM
RECEIVING A THERMAL PLUME AT CRYSTAL RIVER, FLORIDA
By
Wade Hampton Barnes Smith
August, 1976
Chairman: Howard T. Odum
Major Department: Environmental Engineering Sciences
The effects of the heated discharge of two power plants on the receiving estuarine ecosystem near Crystal River on the west coast of Florida were investigated with measurements and simulation models to help understand relationships and predict the consequence of a third power plant under construction. Energy circuit models emphasizing diurnal and seasonal aspects of ecosystem responses were used to assess the effect of power plant operation on estuarine ecosystems. Field measurements were taken in the discharge-affected and -unaffected areas nearby.
Benthic populations dominated 'total metabolism in both systems. Community gross primary production varied seasonally in.the unaffected areas from a winter
x v i .
low of 3.3 g 02/m2. day to a spring high of 8.8 g 02/m2-day.
2o ay.3.
In the discharge area it was relatively constant, remain2
ing about 4 g 02/m -day in all seasons. Phytoplankton production normally was about 5 percent of total production in the unaffected areas and about 23 percent in the discharge area. In the spring its contribution increased greatly to 25 percent in the unaffected area and 70 percent in the discharge area.
Total biomass was less in the discharge than in unaffected areas. Lower standing stock of primary producers and benthic invertebrates in the discharge area accounted for almost all the difference.
Diversity was lower in the discharge bay than in the unaffected area. Mixed macroalgae and seagrasses were the dominant benthic producers in the unaffected areas, while the seagrass Halodule wrightii was virtually the only species in the discharge bay. Species diversity was lower for oyster reef organisms, and fewer species of fish were caught in drop nets in the discharge bay than in the unaffected bay.
A shift toward more cycling of material and energy through the phytoplankton and filter feeders and away from the benthic components of the system may have occurred in the discharge area as an adaptation to the thermal plume.
xviii
Simulation of the model of diurnal system properties with coefficients representing those for discharge conditions gave patterns similar to those measured in the discharge bay. The model was relatively insensitive to adjustments in water temperature within the range expected in the future at Crystal River. A change in the quantity of daily insulation produced a larger change in model response.
The simulation model of seasonal system properties was also more sensitive to light than to water temperature. Increasing temperature alone.increased primary production and total respiration somewhat, especially in the spring. Fish and invertebrate biomass remained the same, while detrital storages declined, perhaps indicating their importance as an energy source for offsetting increased respiratory drains on consumers because of increased temperature. Increases in light alone greatly increased system storages and flows, suggesting the importance of turbidity in controlling metabolism in the discharge area. Increasing temperature but decreasing light lowered metabolism.
Adjustments to the seasonal model tested the
theory that systems with prominent seasonal pulses may be exploited by populations that move in during the period of plenty, experience rapid exponential growth, and then
x i X
move away. With some migration the fish stock could maintain itself in a stable oscillating yearly pattern.
Results of other adjustments to the seasonal model suggested that seasonal substitution of species of primary producers may be the most effective way to make maximum use of available energies at all times of the year.
This is a study of shallow, benthic-dominated estuarine ecosystems on the Florida west coast, one of which received a thermal discharge from two electric generating stations of the Florida Power Corporation. Water was drawn from the deeper offshore Gulf of Mexico, passed through the power plant condenser system, where its temperature was increased about 5'C, and discharged onto the shallow inshore coastal area (Figure 1). This study was made to increase understanding of the structure and function of estuarine ecosystems, the relationship of individual parts to the functioning of the total pattern as an integrated unit, and the effects of temperature change. Specifically investigated was the nature of an estuarine system which had been receiving thermal effluent for six years. How does an entire ecosystem adjust and adapt to these new energy conditions imposed on it? How does the new system., serve as an interface b between the economy of man and that of nature?
Energy diagrams were drawn to organize, summarize and synthesize data in models, and as a conceptual tool
INTRODUCTION
Figure 1. Location of Florida Power Corporation's power plants near Crystal
River, Florida, in relation to the major features of the regional
coastline. Oyster bars are indicated by dotted outlines.
0 i 2 3
KILOMETERS
0 0.5 1
NAUTICAL MILES
i*~:~ C~ i., \ I
for illustrating ideas about the ecosystem at Crystal River and the role of thermal loading in shaping its pattern. Total metabolism, including photosynthetic production and total respiration, was measured as the primary indicator of the main system functions. Using simpler models, computer simulations of seasonal and diurnal trends were run and compared with measured data. This study was part of a much larger project funded by the Florida Power Corporation evaluating questions related to the impact of its power plants at Crystal River on the adjacent estuarine ecosystems. As required by our contract, efforts were made to summarize data from other studies in developing an overview of the ecosystem.
As fossil -fuels for powering man's economy become
scarcer and more expensive, the need increases for recognizing, utilizing, and protecting the important work contributions of nature in support of man's economy, and establishing effective feedback pathways from man to protect his life support system. A regional system of man and nature which allows its natural components to contribute work services in support of the overall pattern may avoid unnecessary technolooical constructions and be most successful in utilizing all available energies when use of the environmerit constitutes more useful work than is lost by environinental impact. For example, should coastal and estuarine waters be used for cooling, of the thermal effluent from
electric generating stations, or is it necessary to build technological alternatives such as cooling towers for this purpose?
System Adaptation, Environmental Impact,
and Thermal Loading of the Estuary at Crystal River, FloridaAt Crystal River, and wherever thermal effluents flow into an ecosystem, potential energy is carried with it. This energy, like all other energy sources impinging there, is available for doing work in the environment, although its exact way of doing work may not be known (Odum, 1974b).
Other changes besides thermal loading are caused by power plant installations. At Crystal River the construction of dikes and the pumping of cooling water through the canal system (see Figure 1) may modify the current and flushing characteristics of the surrounding waters. Turbidity in the discharge area may have increased because of scouring of the discharge canal and from sediments carried through the power plant from the intake canal where they had been stirred up by barge traffic. Canal construction caused changes in drainage patterns and morphology of adjacent salt marshes.
The most important impact, however, may be the effect of higher temperature on biological processes.
Adaptation and acclimation of metabolism of individual organisms to offset temperature changes is well established (Bullock, 1955). Much less is known about the response of whole ecosystems to changed thermal regimes. How does system structure adapt so that the new pattern that emerges is best coupled to the changed thermal regime? What is the nature of this new system linked to man's technology? These questions may begin to be answered by observing such system properties as total community metabolism, species diversity, and seasonal patterns.
OThe effect of thermal loading on biological processes may be important at both the level of individual organisms and the ecosystem (Kelley, 1971; Odum, 1974b; McKellar, 1975). Since all processes are stimulated equally below the threshold of rapid thermal enzyme destruction, temperature acts to increase processes building structure as well as those degrading it (Figure 2). 'For a plant (Figure 2a),the dark reactions of photosynthesis may be stimulated as much as respiratory pathways, so that the overall effect on biomass may be neutral. However, if photosynthesis is limited by energy and material shortages so that respiratory losses are not offset, biomass may decline. The same holds true for a consumer (Figure 2b). I-If the metabolic pathways of digestion and rebuilding of structural animal biomass are affected at the same rate as those degrading this biomass, inetabolism increases but
Figure 2. Energy diagrams of producer and consumer
modules indicating the push-pull effects of
temperature on internal processes. See
Appendix A for meaning of symbols.
(a) Producer module with temperature acting
on both photosynthetic primary production and respiration processes.
(b) Consumer module with temperature acting
on processes of biomass formation through
food gathering, digestion, and assimilation as well as the respiratory degrada-tion of biomass.
b
FOOD
SOURCE
the amount of biomass is unaffected. However, if food is limited the population loses mass because it cannot compensate for respiratory losses.
For the ecosystem, if it is to compete at th.e new steady state, respiration degrading structure induced by higher temperatures must be compensated for by the larger push of increased rates of production of system structure.
-Can accelerated cycling of nutrients from increased respiration offset nutrient limitations to primary production? Is this increased production enough to supply energy demands of larger consumers?
Models for Gaining an Overview of the
Estuary and Power Plant at Crystal River
Proposed in Figures 3 and 4 are the energy ci rcuit models at different levels of complexity of the system of estuary and power plants at Crystal River. Their purpose is to organize in overview concepts of system structure, processes, pathways, interactions, and relationships. Inherent in the diagrams are patterns important on both daily and seasonal time scales. An explanation of symbols used in this dissertation is given in Appendix A. More complete discussions and additional symbols are given by Odum (1971, 1972, 1974a, 1975).
Simplified Model of the Inner Bay
Given in Figure 3 is a model diagram of the inner bay ecosystem from which details have been eliminated leaving only the basic system structure of water storage, benthic macrophytes, consumer populations and tidal exchanges with the saltmarsh, offshore, and canal ecosystems. On a rising tide surface water from the power plant discharge canal is forced onto the inner bay by the damming effect of water flowing on from offshore and the increasing height of head of the approaching wave of the tide. On a falling tide canal water flows directly down the channel beside the inner bay, where it receives water flowing off the bay. Diffusive oxygen exchange with the atmosphere occurs driven largely by turbulence induced by tidal exchange. Gains of heat result from solar insolation and atmospheric longwave radiation. Heat losses occur from conduction, back radiation, and evaporation.
Primary production occurs in the phytoplankton
and the benthic macrophytes, which take up nutrients and oxygen from the water column while returning oxygen and organic matter to it. Storages of organic matter are in the water column and sediments, which are consumed by populations of microbes. Two classes of consumers are shown. In the water column are free living animals feeding on detritus, phytoplankton, benthic invertebrates, and
Figure 3. Aggregated energy diagram of the main features believed important in the ecosystem
of the inner discharge bay at Crystal
River. Details within the compartments
have been omitted to emphasize basic system structure and function in overview.
Symbol shown as T indicates a connection
I
from heat sinks (4-). See Appendix A for
definition of symbols.
I !
! SALT MARSH
* SUBSYSTEM I
* !
EVAPORATION
EXCHANGE WITH CANAL ONLY ON RISING TIDE
INNER BAY WATER COLUMN
CONTAINING HEAT,
NUTRIENTS, TURBIDITY, ORGANIC MATTER, OXYGEN, AND /
PHYTOPLANKTON
SXAHANGES Wl SHORE ARE
BENTHIC
MACROPHYTES
AND EPIPHYTES
each other. Many of the larger members of this compartment migrate seasonally to and from the offshore regions. Benthic invertebrates and oysters feed largely on detritus and phytoplankton. Nutrients are regenerated into the water column from all respiratory pathways.
Detailed Model of the Inner Bay
In Figure 4, more of the complexity of detail within the compartments has been added to the model of Figure 3. Sunlight penetrating the water column of the inner bay is attenuated by turbidity, shading of phytoplankton biomass, and the natural extinction properties of water. Primary production utilizes the remaining light, and is concentrated in the benthic macrophytes and their associated epiphytes with a smaller contribution from the phytoplankton. This production moves to the higher trophic levels primarily through a storage of detritus and its associated microbes in the sediments. A much smaller amount is stored in the water column. A small amount is transferred by direct grazing of epiphytes. Larger consumer populations are represented by benthic invertebrates and oysters, zooplankton and larval forms, shrimps arid crabs, and resident and migratory fish. Seasonal migratory movements of shrimps, crabs, and migratory fish stocks are indicated. All respiratory pathways are shown returning nutrients into the water column storage. Various
Figure 4. Energy diagram of the ecosystem of the inner
discharge bay, which includes much of the
complexity omitted from Figure 3. Pathways
of oxygen uptake and temperature effects
have been abbreviated for clarity. Pathways
from storages of heat and oxygen labeled T and 0, respectively, are assumed to be connected with similarly labeled pathways on work gates and consumer modules. Pathway
marked as T indicates a connection from
heat sink symbols ( -L ).
OFFSHORE
exchanges with the adjuacent saltmarsh, power plant canal, and immediate offshore ecosystems occur with the rise and fall of the tide.
Heat in the water is lost and gained through physical processes as well as advective exchanges. Gains occur from solar insolation, atmospheric longwave radiation, and heat generated from all biological processes. Losses result from back radiation and evaporation. Conduction is a gain or loss depending on the direction of the gradient between air and water. Oxygen has a diffusive exchange with the air driven largely by water turbulence.
In summary, this detailed model serves to emphasize issues related to the interactions of power plants with estuaries, helps the reader visualize the system studied at Crystal River, summarizes initial understanding of its characteristics, helps to plan the research program, and provides a basis for simpler models for simulation.
Previous Studies of Thermally Affected Aquati c Ecosystems
Most work on the effect of temperature on life processes has been at the level of the whole organism or at smaller (e. g. subcellular) levels; less work has been concerned with its effect on whole ecosystems. Perhaps because of their simplicity the most thoroughly studied ecosystems to date have been thermal spring
ecosystems. System structure has been discussed by most authors (Brock, 1967a, 1967b, 1969; Brock and Brock, 1969; Kuliberg, 1966; Stockner, 1967, 1968; Wiegert and Fraleigh, 1972). Zonation of alga] or bacterial mat communities associated with temperature gradients, both down and across spring runs, with a vertical zonation of structure at any given point were the main characteristics of these ecosystems. Filamentous bacteria were dominant in the hotest
portion of the stream, being replaced by blue-green algae as the water cooled. Green algae, in turn, replaced the blue-green at still lower temperature cooling. Species diversity was very low overall, tending to increase down the temperature gradient.
Community metabolism in thermal springs has also been measured (Brock, 1967b; Duke, 1967; Phinney and Mclntire, 1965; Stockner, 1968; Wiegert and Fraleigh, 1972). ValIues measu red generallIy fellI wi thin ranges reported for many other types of aquatic ecosystems. Brock (1970) reviewed work on high temperature systems.
The work reported above is mostly on springs with temperatures in excess of 45'C, which is generally above.
the thermal limits for enzyme destruction of most organisms. Available work on thermally affected systems within temperature ranges more normally encountered in nature has mostly involved microcosm studies. Allen and Brock (1968) reported that microcosms held at a range of temperatures
from 2'C to 75'C and all seeded alike from a wide variety of sources; each developed its own characteristic combination of species. Buyers (1962) found only small responses in community metabolism to 36-hour increases in temperature. Davis (1971), studying experimental estuarine ecosystems contained in large plastic swimming pools, found increased gross community primary production and respiration during spring, summer, and fall in those heated 4-6'C above controls. Kelley (1971) studied high-nutrient freshwater microcosms subject to constant low, constant high, and fluctuating temperature regimes. Mean values of net production and night respiration over the study period were higher in those microcosms which had higher mean temperatures. Various aspects of the biology of Par Pond, a freshwater reactorcooling pond at the Savannah River Plant, South Carolina, have been studied for a number of years by investigators at the Savannah River Ecology Laboratory of the University
of Georgia (Gibbons and Sharitz, 1974b)
A general assessment of researchrelated to the environmental effects of the operation of power plants is difficult because much of it is contained in reports to Federal agencies concerned with licensing, and is generally unavailable for review. Zieman (1970) has reported on the early effects of the operation of power plants at Turkey Point on Biscayne Bay, near Miami, Florida. Conditions of flow rate and teri,perature rise of the cooling water were very similar -to those at Crystal River. The receiving
ecosystem was dominated by a mixture of macroalgae and seagrasses (mostly Thallassia testudinum). By the end of the second summer of operation 50-60 acres of bay bottom adjacent to the mouth of the discharge canal had been denuded of this community and replaced by a blue-green algal mat community. An additional 70-75 acres had some Thallassia, but were still devoid of macrophytic algae, while 160-170 more acres exhibited some stress to the existing macroalgae populations.
Other available power plant data have dealt with
more northern situations involving phytoplankton.-dominated ecosystems. The effects of increased temperature on primary production were usually measured by the uptake of carbon-14, often in bottles held in illuminated light boxes. Results have been mixed. Several studies involving both estuarinie and freshwater cooling systems have found stimulation of photosynthesis in the cooler months and a depressing effect in the warmest months (Morgan and Stross, 1969; Smith et -al., 1974). Tilly (1974), using carbon-14 mneasuyements incubated in situ in Par Pond, South Carolina, found primary production to be somewhat greater in the surface water at the warmer station. This tendency was more pronounced during the warm months of the year. Gurtz and Weiss (1974), also using carbon-14 methods, found inhibition of photosynthesis at all times of the year. A trend toward greater inhibition at higher ambient water temperatures was suggested by the data.
Only several reports appear to be available on aspects of ecosystems which have been adapting to power plant discharges for a number of years. North (1968) studied the discharge area affected since 1957 at Morro Bay, California. He found abundance and diversity of plants and animals to be reduced in a transitional reason over a distance of approximately 200 m from the end of the discharge canal. Recovery to conditions typical of the area occurred in a relatively short horizontal distance of 10 m at the end of the transitional region. J. R. Adams et al. (1974) could find no difference in intertida-I sandy beach populations located near the discharge versus ones further away.
Few power plant studies appear to have synthesized the diverse data into an overview of the ecosystem responding as an integrated unit to the new set of environmental forcing functions. Emphasis has generally been placed on individual aspects of power plant operation, such as
4
entrainment through the condenser cooling system and entrapment on the screens protecting the cooling water intake pumps (Jensen, 1974c), or on individual species or components of the ecosystem. Typical studies might examine mortality of phytoplankton from passage through the condenser system, diversity and biomass of benthic organisms and fish in the discharge area, or primary production of the phytoplankton component of the ecosystem.
Often these studies have been done in the laboratory. Chesapeake Science, volume 10 (1969), and proceedings of
symposia edited by Gibbons and Sharitz (1974a) and Esch (in press) contain many papers of this type.
Several studies have been published which contain most research results for a particular power plant in one volume (Jensen, 1974a, 1974b; Central Electricity Generating Board). Discussion of results, however, is by subsystems with little attempt to synthesize the findings with text, diagrams, or simulation models into a picture of the functioning of the whole ecosystem.
Decitono td Area atCrystal River
The power plant site in Citrus County (Figure 1) is on the low wave energy portion of the Florida west coast as defined by Tanner (1960). The shallow sloping bottom (46 km to the 5 fathom contour) is part of the drowned karst topography of this portion of west central Florida. The topography of the immediate offshore region is a series of shallow basins separated by oyster reefs (Figure 5). Freshwater sources influencing the area are the Crystal River 4.8 km to the south (mean flow 1500 m 3/mini; 400,000 gpm), and the Withlacoochee River and Cross Fl orida Barge Canal 6.4 and 5.8 km to the north, respectively, with a combined flow of 2150 m 3 Min (570,000 gpifl.
Figure 5. Bathymetry of power plant discharge area at Crystal River. Location
of inner bay has been circled. Contour interval is 1.0 feet. Datum
based on mean sea level. (Adapted from Rodgers et al ., 1974)
A/V 5 . INNER
024 , DISCHARGE
NTS 94
0I(ADAPTED FROM ' "I'S--.': '.-. CNA GE
NAUTICAL MILE RODGERS, et al A974
The power plants are on the landward edge of a
tidal saltmarsh dominated by Juncus roemerianas bordered on the seaward edge by a narrow fringe of Spartina alterniflora. Two units were in operation during this study--unit 1 since July, 1966, and unit 2 since November, 1969--giving a combined total output of 897 megawatts electrical (MWe). A nuclear powered unit of 885 MWe output was under construction. The two operating units cycle water for once-through cooling at a combined flow of 2430 m3 /min (640,000 gpm) through canals dredged across the shallow offshore region and saltmarsh. Maximum condenser temperature rise is 6.1�C.
The power plant intake canal extends approximately 4.8 km into the Gulf with an average depth of 6-7 m and a width of about 75 m, serving also as the passageway for delivery of fuel oil in barges by large ocean-going -tow boats. Cooling water passes down the canal at about 8 cm/sec before being pumped through the power plant condensers, where its temperature rises 5-6�C. The discharge canal is about 1.6 km long with an average depth and width of about 4.5 m and 50 m, respectively. The smaller cross-sectional area causes the stream velocity to be about twice that in the intake canal. The residence time of water masses in the canal system is about 20 hours for the intake canal and about
3.5 hours for the discharge canal.
Two types of bay systems are affected by the
thermal plume (Figure 6). Immediately adjacent to the saltmarsh is the shallow bay of this study averaging about 1 m in depth, composed of a mixture of bottom covered with seagrass, some oyster reef associations, and areas of sand and mud. Seaward of a row of oyster bars is a deeper outer basin of about 2 m average depth in which the plankton and reef ecosystems become important. The "bays" referred to here are actually the immediate landward edge of the Gulf of Mexico.
The plume-affected inner bay of this study is a shallow benthic seagrass-dominated system composed almost exclusively of Halodule (Diplanthera) wrightii during the warm months, while in the winter of 1972-73 mixed Ectocarpaceae proliferated and covered much of the bottom area. It did not return during the milder winter of 1973-74. The unequal semi-diurnal tide (see Figure 7) has an average tidal amplitude of about one meter exposing much of the bay bottom on the lowest of the two daily low tides, and draining the entire bay o n the lowest spring tides. In addition, strong northerly winds associated with passages of cold fronts in winter occasionally push the regional water mass offshore and drain -the bay and the nearby coastal area for several days. With normal weather and tides, the heated plume moves back and forth ac;coss portions of the bay in
Figure 6.
Thermally affected area showing location of the shallow inner bay system dominated by the seagrass, Halodule wrightii, and the deeper outer bay system. Lettered dots indicate inner bay locations of remote telemetry buoys maintained by Florida Power Corporation for recording water temperatures. Location lettering is as designated by the Florida
Power Corporation.
0 0.5
KILOMETERS
OUTER
BAY
Figure 7. Typical daily tidal cycle at Crystal River site
indicating unequal high and low tides. Amplitude changes were taken from tide tables (U. S.
Department of Commerce, 1972) for June 12,
1973.
2.0 1.0
0
0600 1200 1800
TIME OF DAY
response to the tidal cycle. The shallow areas near the power plant which were unaffected by the thermal plume were dominated by a diverse mixture of benthic macroalgae and seagrasses.
Areas away from the influence of the power plant discharge at Fort Island, Hodges Island, and in the south intake area (Figure 1) were used as comparison areas. The south intake area was located immediately south of the southern intake canal dike. Measurements taken there by others included stocks of fish, benthic invertebrates, benthic macrophytes, zooplankton, sediment organic content, and nutrient concentrations. The benthic macrophytic producers were a diverse mixture of macroalgae and seagrasses.
Total metabolism measurements were made at Fort Island and Hodges Island. Most measurements were made in a funnel-shaped bay south of Fort Island. This area, which was somewhat deeper than the inner discharge bay area, was characterized by a benthic flora similar to the south intake area. The extreme clarity of the water influenced by the nearby Crystal River allowed much greater light penetration to the bottom as measured with a submarine photometer than in the power plant discharge area. Hodges Island to the north of the Withlacoochee River (Figure 1) was away from freshwater influences. This bay had more turbid water with little growth of benthic macrophytic plants.
Other Studies of the Crystal River Region
Little work is available on the Crystal River
region prior to power plant construction. Dawson (1955) provided data on oyster populations and hydrography, including measurements at stations now well within the influence of the power plant.
After construction and operation of the plants were initiated, many studies were made as part of the larger research program undertaken by Florida Power Corporation. Benthic seagrasses and algae were inventoried by Steidinger and Van Breedveld (1971), while quantitative measurements of biomass were made by Van Tyne (1974). Benthic invertebrates were inventoried by Lyons et al. (1971) and measured quantitatively by Evink and Green (1974).
Trawl samples of fish were reported by Grimes
(1971), Grimes and Mountain (1971), and Mountain (1972). C. A. Adams (1974) analyzed data on fish caught in dropnets from the shallow inshore areas, while Carr and Adams (1973) discussed the food habits of juvenile fish in the beds of benthic seagrasses and macrophytes. Homer (1975) studied seasonal patterns of tidal creek fishes.
Trace metal content of oysters from the intake and discharge canals was reported by Grimes (1971) and
Mountain (1972). Biomass, diversity, and metabolism of oyster bars were measured by Lehman (1974a, 1974b).
Blue crab movements in the intake canal area
were monitored by Adams, Oesterling, and Snedaker (1974). Nutrients, chlorophyll, and phytoplankton numbers and diversity were measured by Gibson (1975). Zooplankton biomass and diversity were studied by Maturo (1974).
Fish and other organisms trapped on the screens
protecting the condenser water intake pumps were monitored by Adams, Bilgere, and Snedaker (1974). Entrainment of larval fish and zooplankton through the condenser system was measured by Maturo (1974) and Snedaker and Johnson (1975).
Total community metabolism was measured and studied with simulation models for the saltmarsh by Young (1974), for the oyster reefs by Lehman (1974a, 1974b), for the deeper outer bays by McKellar (1974, 1975), and for the power plant canals by Kemp (1974). A larger scale analysis of the energetic costs associated with estuarine cooling compared to technological alternatives was done by Odum (1974b), Odum et al. (1974), and Kemp et al. (1975).
Physical measurements of the hydrography of the area were reviewed by Carder (1975). These were used by Klausewitz (1973) for verification of a computer simulation model of the behavior of the thermal discharge
plume. Bedient (1972) simulated the flushing of water from the discharge canal as it related to dispersion of radioactive wastes in the discharge water. Swindler (1973) examined the sedimentology of the region between the Crystal River and Withlacoochee River. Cottrell (1974) studied sediment composition and sedimentation rates in the more immediate plant area.
Previous Simulation Models of Marine Ecosystems,
Diurnal Oxygerp Dynamics-_, Temperature, and the
Effects of Power Plants on Ecosystems
Several previous attempts at modeling marine ecosystems have appeared in the literature. Chen and Orlob (1972) developed an extensive simulation of the San Francisco Bay and Delta region incorporating spacial as well as temporal elements. The geographical region was divided into a network of nodes and connecting pathways. Mass balance equations were used to transfer materials between nodes with tidal dynamics as the forcing function. Up to 22 parameters could be considered: dissolved oxygen, biochemical oxygen demand, alkalinity, pH, temperature, nitrogen (three forms), phosphorus, suspended sediment, three types of algae, zooplankton, three types of fish, and berthic animals. For conservative elements, only -terms for diffusion, advection, input, arid output were included in the mass
balance. For biological elements, appropriate terms for rates of growth, respiration, mortality, and chemical transformations were added. Temperature linearly affected respiratory pathways of fish and zooplankton, and affected both photosynthesis and respiration of algae. Growth rate coefficients were based on Michaelis-Mention kinetics. Model calibration to real data was presented for only several parameters with fit being quite good. Subsequent runs evaluated the effect on the bay of proposed regional sewage treatment and water diversion alternatives.
Steele (1974) simulated a simple model of the North Sea using storages of nutrients, phytoplankton, zooplankton weight, and zooplankton numbers. Sunlight was considered nonlimiting and was omitted as a forcing function, so that changes in phytoplankton biomass were a function only of nutrients, mixing below the thermocline, and zooplankton grazing. Nutrient cycling was included as excretion by zooplankton respiration. Equation terms for nutrient uptake and zooplankton grazing were derived from observed experimental data and were given the form of Michaelis-Menton kinetics.
Brylinsky (1972) performed a sensitivity analysis on a model of the English channel, which included storages of phytoplankton, zooplankton, benthic fauna, pelagic fish, demersal fish, and bacteria. Photosynthesis was considered a constant external input. Pathways of
I
exchange between compartments were linear and controlled solely by the donor compartment. Since nutrients were not included as a variable, cycling was not a model feature. It was stated that the model was not intended to be realistic, but, instead, to illustrate the application and usefulness of the tool of sensitivity analysis.
An early attempt to simulate diurnal oxygen
dynamics of an ecosystem was made by Odum, Beyers, and Armstrong (1963) using a passive analog circuit. Results supported the theoretical discussion of the effect of a small organic storage capacity in the nannoplankton on the measurement of primary production in tropical
s e a s .
Several authors have obtained very good fit for data from microcosms to relatively simple models of their diurnal properties. Collins (1970), studying a blue-green algal mat, followed oxygen through compartments of producers, consumers, detritus, dissolved oxygen, CO 2 (total in solution), atmospheric oxygen, and water. All flows between compartments were controlled by the upstream compartment only (donor control). Using a square-wave regime of light input, the model produced simulated curves of oxygen very similar to measured curves and their rates of change.
Kelley (1971) included only storages of carbon dioxide and labile and structural organic matter in his
Simulation of a nutrient-rich -freshwater microcosm of mixed plankton. Since his study was partially concerned with the effects of temperature, it was included in a push-pull fashion as an action on every pathway. Rates of flow between compartments were otherwise controlled only by the donor compartments, as in the model by Sollins. Excellent fit was obtained to the measured oxygen data.
Nixon and Odum (1970) considered only storages of organic material and nutrients in a model of hypersaline algal mat community. Transient responses of this very simple model were compatible with those observed in the microcosm.
Simulations based on the more variable data gathered from open ecosystems in nature have been carried out. A model of Bissel Cove, Rhode Island (Nixon and Oviatt, 1913) was basically an oxygen balance consisting of a single storage of oxygen with inputs from primary production of plankton, macroalgae, and benthic microflora. Respiratory oxygen losses occurred tO producers, sediments, detritus, shrimp, and fish. Diffusion exchange with the atmosphere and tidal exchange with a constant oxygen source were losses or gains depending on the saturation level of the water and the stage of the tide. Rates of oxygen losses or gains for each pathway were empirically derived from regression
equations calculated from observed data. No feedback or cycling pathways were included. Model response fit reasonably well to observed diurnal curves of oxygen.
Boynton (1975) simulated a river-dominated
estuary to examine issues of river discharge schedules and potential effects of human development on nearby lands and its relation to an oyster fishery existing in the bay. Using a simplified energy symbol model, diurnal curves of oxygen very similar to data measured in the area were obtained.
Several simulations have included temperature
actions. An early one emphasizing the effect of temperature as an exponential function on zooplankton populations of the North Sea was done by Riley (1946, 1947). Odum (1975) translated these equations into models. using the energy circuit language.
Hall (1974) briefly reported on a simulation model of the effect of po*,-;Pr plants on the striped bass fishery of the Hudson River. Details of the model were not giver.
Odum (1974b) discussed some general principles regarding temperature and system responses, including the push-pull effect on both ordering and disordering processes. Examples were given of simulations of equations proposed by Eyring and Eyring (1963) and Morowitz (1968) which incorporated the push-pull feature of temperature action.
38
Nixon and Oviatt (1973) included temperature actions only on respiratory pathways in their simulation model of Bissel Cove. As a result, a decline in oxygen was predicted as the effect of the action of a hypothetical power plant on the cove.
Miller (1974) simulated thle effect of maintaining mangrove vegetation in power plant canals to aid in cooling the water before recirculation through the power plant. Increased, but not severely detrimental, water stress was predicted for the trees.
Several simulation models of other ecosystems at Crystal River have been run. Young (1974) observed increased photosynthesis, respiration, and live and dead standing crop in simulations of the effect of elevated water temperatures on thle fringing Spatina_ saltmarshes. Lehman (1974b) simulated -the intertidal oyster reefs. Model responses included faster turnover rates for plume-affected conditions. Simulations of effects of adding thermal waters of another power plant suggested reduced seasonal variation of reef standing stocks. Kemp (1974), in a preliminary simulation of the comm,,unity of fish, plankton, and benthos of the power plant intake canal, found fish stocks to be most sensitive -to water flow rates and immigration. Plankton was relatively insensitive to most parameters, being controlled principally by concentrations carried in from outside
the canal. McKellar (1975) simulated the outer bay of the discharge area (see Figure 6). Raising the water temperature to that measured in the discharge area produced only small increases in total metabolism and some component storages. Water exchanges were shown to be a stabilizing influence by dampening large fluctuations in zooplankton, phosphorus, and detritus. Simulation of the conditions expected with future power plants produced no large changes in total community metabolism.
Plan of Study
The structure and function of the thermally affected inner bay ecosystem at Crystal River and unaffected areas to -the north and south were determined from field measurements of biomass of organisms and system metabolism, and from the behavior of ecosystem simulation models evaluated with these and other data. The conceptual model shown in Figure 4 was developed as an overview to show the relation of the main energy exchanges with the outside, and of the main storages of the inner bay ecosystem among themselves. Simpler models which aggregated the main stocks and processes were simulated on an analog computer.
Total community metabolism was determined from diurnal changes in free-water oxygen concentrations and was used as an indication of the ability of the
ecosystem to process the energies available to it. Comparison of metabolism of the thermally affected area with areas away from the influence of the power plants indicated the degree to which these processing abilities had been altered. Measurements were taken from June, 1972 through May, 1974 representing all seasons and establishing general seasonal trends of metabolism.
Efforts using bottle experiments were made to partition total metabolism between its planktonic and benthic components. Measurements were made of penetration of light through the water column.
Models were evaluated with data obtained in this study and gathered concurrently by other researchers, with other supporting measurements, information from 'he literature, and some necessary calculations and assumptions. These models were translated directly into a set of differential equations, which were programmed for analog computer simulation. Simulation runs were made with coefficients set for conditions with and without the influence of the power plant. Results were compared to the observed data. Sensitivity of the models was examined with respect to changes in water temperature and ratios of discharge canal water to offshore water mixing on the inner bay. Finally, simulations were run with conditions expected when the new power plant begins operation.
METHODS
Metabolic Measurements
Community metabolism was measured with diurnal sampling of oxygen following Odum and Hoskins (1958), Odum and Wilson (1962), and Odum (1967), and an abbreviated method using dawn-dusk-dawn oxygen samples (McConnell, 1962). Oxygen was measured by the azide modification of the Winkler technique (Amer. Publ. Health Assoc., 1971), but adapted for use with smaller sample collection
bottles.
Mini-Winkler Field Kit and Winkler Method Modification
Because of the large number of samples to be
processed and the need for compactness, a mini-Winkler field kit developed at the University of Texas Institute of Marine Sciences was used in this study. Standard flat-topped 125-ml reagent bottles were used for sample collection in place of 300-ml BOD bottles. Samples were fixed with 0.5 ml of manganous sulfate and azide reagent carried in dropping bottles in the field kit. After
acidification with 0.5 nil concentrated sulfuric acid, 100-mi subsamples were titrated with 0.012 N sodium thiosulfate. This normality allowed direct reading of milliliters of titrant as mg/i of oxygen.
Variability between replicate pairs of oxygen
samples could have arisen from many sources. Since the small reagent bottles used were inexpensive, variation in their individual volumes was expected. A test of a 54-bottle subsample of those in use gave an average volume of 122.8 ml with a standard error of 0.22. Because each bottle was filled from a separate sample of bay water taken 30 seconds to one minute apart, variations due to water mass differences could also have occurred. Other sources of variation could have included differences in reagent volumes added and differences in sample volumes titrated.
Actual differences in titrant volume encountered between replicate pairs of samples were small, however. Based on a subsample of 486 replicate pairs, 72.6 percent differed by 2 drops (0.1 ml) or less. Since titrant volume was generally in the range of 4-8 ml, this gave an average error of 1.3-2.5 percent. Loss of accuracy due to increased sources of variability was, therefore, considered minimal, and was far outweighed by convenience in handling in the field. More samples could be processed, permitting better estimates for the whole bay.
Significance of Delay in Fixing 1.4inkler Bottles with Acid
A test was made of the effect of an eight-hour
delay in adding acid to the sample bottles in the Winkler analysis of oxygen. Thirty bottles were filled with thoroughly mixed salt water from a bucket, and immediately fixed with the manganous sulfate and azide reagents. Ten bottles were picked at random, acidified, and titrated within 30 minutes. The remaining bottles were split into two groups, one group of 10 bottles receiving acid, while the other did-not. Both groups were stored in the dark for eight hours. At the end of that time, acid was a dded to the bottles which had not received it earlier, and both groups were titrated. Table 1 gives the results of the three treatments. Differences between treatments were significant (95% level), but were considered too small to have any significant effect on the measurements.
Complete Diurnal Sampling of Oxygen
The calculation of total community primary production and respiration from free-water measurements of oxygen is based on the model given in Figure 8. As indicated, the oxygen concentration in the water column at any moment and changes in concentration with time are a function primarily of the production of oxygen during photosynthesis, its consumption in respiratory
Table 1 .
Results of a technique test of the Winkler method to determine the effect of the presence or absence of acid in fixed bottles which have been stored for eight hours before titration. Each treatment contained 10 bottles. Results are given in milliliters of titrant.
Bottles fixed, Bottles fixed and Bottles fixed
acidified, and acidified immedi- immediately;
titrated ately; titrated acidified and
immediately 8 hours later titrated 8 hours
later
Average 5.45 5.43 5.48
Std. Error 0.02 0.01 0.01
Figure 8. Model of factors affecting oxygen dynamics
in water.
SATURATION
---- ADVECTIVE
- EXCHANGE
PHOTOSYNTHESIS
RESPIRATION
processes, gains or losses because of advective exchange with adjacent water masses, and diffusive exchanges with the atmosphere. The contribution to oxygen dynamics of the nonbiological processes of advection and diffusion may be corrected for if their magnitudes are known or can be estimated. Subtracting their effect allows a calculation of changes resulting only from the biological processes of photosynthesis and respiration, and, thus, a cal cul ati on of producti on and respiration.
After correcting for diffusion and advection, any gain in oxygen concentration during daylight hours would be a consequence of the greater production of oxygen in photosynthesis than its concurrent use in respiration, thereby providing a measure of net primary production. At night, when there would be no production of oxygen by photosynthesis, the rate of oxygen decline would be an estimate of community respiration. By assuming a similar respiration rate for daylight hours (which would be a conservative assumption), an estimate of the rate of gross primary production may be obtained by adding daytime photosynthesis and night respiration.
Stations were sampled approximately every three hours over a 24-hour period. Two buckets of surface water were collected 30 seconds to one minute apart at each station, and sample bottles were filled from the bottom by siphoning through rubber tubing. Late night
samples were sometimes stored without acidification for titration the following morning (see above for effect on Winkler analysis). Time, temperature, salinity, and depth were noted at each station.
Because of the large tidal flushing, advection of water.masses from outside areas was at first thought to be important. In order to assess this effect on the diurnal oxygen curve in the study areas, four or five stations were sampled in the early part of the project. Analysis indicated a general similarity in the daily ,increase and decrease of oxygen at all stations, suggesting that advection was from areas of similar metabolism. Thus, errors introduced by advection were thought to be small, and the number of stations was usually reduced to two or three to meet field schedules.
Diurnal metabolism graphs were constructed using a standard format (Figure 9) to allow easy visual comparison among all diurnal samples taken at Crystal River as well as with others in the literature (Odum and Hoskins, 1958). The data were analyzed several different ways as the study progressed. At first, a graph for each station was plotted and analyzed separately. Later, all points from separate stations were plotted on one graph, but only the mean curve was analyzed (Figure 9). Each oxygen point was the average of duplicate Winkler analyses. Oxygen per square meter (Figure 9c) was
Figure 9. Example of graphical format for calculation of
community metabolism at Fort Island, 24-25
August, 1973, using full diurnal curve of oxygen. Open circles represent average of measurements at four stations, each of which are shown
as solid points. (See text for detailed discussion of [g] and [h].)
(a) Oxygen concentration.
(b) Depth.
(c) Areal oxygen obtained by multiplying (a)
and (b).
(d) Temperature.
(e) Salinity.
(f) Percent saturation of oxygen calculated
using oxygen values in (a).
(g) Rate-of-change of oxygen. Dotted line is
rate-of-change of (c). Solid line with
solid dots (e - ) is rate-of-change corrected for depth changes. Solid line with open circles (o- o) is rate-of-change
curve corrected for diffusion using coefficient values given across the top of the
diagram. Units of diffusion coefficients
are g02/m /hr./100% deficit.
(h) Rate-of-change of oxygen. Solid line with
solid dots (- - ) is rate-of-change of
(a) multiplied by average depth at each
hour. Solid line with open circles
(o.-o) is curve corrected for diffusion using same coefficients as in (g).
PERCENT
SATURATION
0 0 NX 4s M
SALINITY,
ppt
TEMPERATURE,
�C
oc0 OWOw
OXYGEN QUANTITY,
g 02/m2
o0
OXYGEN
DEPTH, CONCENTRATION, M. g 02/m3
o ~ oW I) oo
w I . I \\ylt
(D (g) PH0TOSYN\
o F+0.5 LL
<\.,,\\,\\
w I
0 7
0 1.0 /
I 'NIGHT RESPIRATIC
+1.0 I I
(h)
w
CDl DAYTIME NET
z PHOTOSYNTHESIS
I
CDj
r"0 E./J ,
w - 0.5
x NIGHT RESPIRATION0600 1200 1800 TIME OF DAY
Figure 9 continued
obtained by multiplying oxygen concentration (Figure 9a) by depth at that time. Percent saturation (Figure 9f)
was calculated for the temperature and salinity at each time using the formula of Truesdale et al. (1955). The divergence of Truesdale's saturation values from those presented in Standard Methods (Amer. Publ . Health Assoc., 1955) was reviewed by Churchill et al. (1962), who showed deviations at temperatures less than 25'C. Maximum deviations, however, were less than 5% of the values from Standard Methods, so the errors incurred in this study by using Truesdale's values were considered small.
An oxygen rate-of-change curve (Figure 9g) was constructed from the graph of average oxygen per squar e meter. The amount of change of oxygen during each hour was measured and plotted on the half hour. This raw curve reflected changes in oxygen concentration under one square meter due to changing depth from tidal exchange and diffusive exchange with the atmosphere, as well as photosynthesis and respiration. The effect of changing depth was eliminated by multiplying the incremental depth change for each hour by the average oxygen concentration during that hour. This value was added to the rate curve if the tide was falling or subtracted if the tide
was rising.
The final adjustment to the rate-of-change curve was for oxygen lost or gained by diffusion between the
water and atmosphere (see more complete discussion on page 62). In general, in the discharge bay only a falling tide from a high high to a low low stage had a sufficient current producing a diffusion rate large enough to make an appreciable correction in the metabolism calculation. Both rising and falling tidal current velocities were greater in the control areas making diffusion corrections more important at all tidal stages. For daytime net photosynthesis the average difference between the area under the curves adjusted and unadjusted for diffusion in the inner bay was 8 percent. At the Fort Island control area it was 24 percent, while at Hodges Island (only two measurements) it was 2 percent. Any diffusion estimate that was incorrect for the discharge bay would have a relatively / small effect on the metabolism calculation. At Fort Island the effect would be only somewhat larger.
This laborious method was later modified; average oxygen concentration, temperature, depth, salinity, and percent saturation were plotted as before, but the area-based oxygen curve was not calculated. The rateof-change curve (Figure 9h) was obtained by multiplying the hourly rate-of-change of oxygen concentration by the average depth at that hour giving the rate-of-change on an areal basis. The adjustment for diffusion was made as before.
In all methods the final rate-of-change graph showed the rise of oxygen resulting from net photosynthesis during the day, and decrease because of respiration at night. Net daytime photosynthesis was taken as the area under the rate-of-change curve above the zero rate-of-change line. Nighttime respiration was taken as the area under the rate-of-change curve below the zero rate-of-change curve (Figure 9g and 9h). Dawn-Dusk-Dawn Measurements
In order to gain more data as a check on dayto-day variability of total metabolism and to reduce the amount of field labor involved, the dawn-dusk-dawn method (McConnell, 1962) was used after the first year. The low point of oxygen at dawn, the high point at dusk, and the low point the following dawn were measured as a short-cut method of approximating the true diurnal curve. Experience in the field showed that the time of the minimum and maximum was not always at dawn or dusk. Clouds in the east at sunrise tended to delay the onset of rising oxygen by an hour or more. Similarly, afternoon thunderstorms often caused the downturn of oxygen well before dusk. Even on clear days full diurnal curves showed that oxygen concentration often would not increase any more in the last two hours before sunset. The times of dawn and dusk sampling, then, were
often adjusted to the prevailing conditions. Dawn samples were delayed if the morning was cloudy in the east. Dusk samples were generally taken about 1-112 hours before dusk.
Water samples were drawn, fixed, and titrated as described before. Diurnal graphs of averaged data were drawn in the same way as for full diurnals (Figure 10) but, of course, used only three points. Straight lines were used to connect points for, oxygen, temperature, and percent saturation. Because depth was important to the metabolism calculation, the actual daily pattern was estimated from the observed measurements and the expected tidal amplitudes for the Crystal River area published in the U. S. Department of Commerce tide tables. Because the daily pattern of salinity change was complex, no attempt was made to extrapolate between the measured values.
With the three-point dawn-dusk-dawn method,
net production and/or night respiration would be underestimated if the minimum and maximum points of oxygen were not sampled when they occurred. The method also used fewer replications so that any one unusual measurement would have a greater effect on the calculation of metabolism. McKellar (1975) gives a more complete discussion of errors associated with the method.
Figure 10. Graphical format for calculation of community
metabolism using dawn-dusk--dawn data. Open circles are the average of measurements at
individual stations indicated by solid dots.
Numbers across top of the rate-of-change
graph are diffusion coefficients.
OXYGEN RATE-OF-CHANGE,
9 02 /m2 hr
0 0 0
PERCENT
SATURATION
SALINITY,
ppt
0 ~ 0 N
II0
0
I I
TEMPERATURE,
�C
DEPTH,
m
0 .-N0 Po o b o
OXYGEN, g 02o/m3
U-I 3
An analysis of the difference in metabolism estimates calculated by the dawn-dusk-dawn and full diurnal curve methods is given in Figure 11. Data points were read from a subsample of the graphs of full diurnal curves of oxygen as if that day had been sampled by the dawn-dusk-dawn method, and daytime net photosynthesis and night respiration were calculated. Daytime net photosynthesis would have been underestimated by the dawn-dusk-dawn method three times in the inner bay by an average of 33 percent and overestimated twice by a small amount. Agreement was better at Fort Island and Hodges Island but would have been over- or underestimated by up to 25 percent.
Night respiration by the dawn-dusk-dawn method was only an average of 58 percent of that calculated by the full diurnal curve method in the inner discharge bay. At Fort Island the three-point method was only 75 percent of the full curve method on three occasions, while the full curve value was only 88 percent of the three-point value two times.
McKellar (1975) for the outer discharge and
control bays at Crystal River found the dawn-dusk-dawn method to underestimate gross production values (daytime net production plus night respiration) usually by less than 10 percent. The average difference between the two methods was not significant at the 0.05 level.
Figure 11. Comparison of community metabolism estimates
obtained from complete diurnal measurements
of oxygen versus estimates obtained from
dawn-dusk-dawn calculations made using the
same data.
(a) Daytime net photosynthesis.
(b) Night respiration.
s
D
0
z
0
_-) IL
)-4E
41
6 8
0/m2 .day
(b) NIGHT RESPIRATION
000
0
0
0
- oo 0o
0 INNER DISCHARGE BAY
E] FORT ISLANDA HODGES ISLAND
I.
21
C'
0o2 4
DAWN -DUSK-DAWN,
hi
02/m2-
8
day
DAWN- DUSK- DAWN, g
Eley (1970) found that dawn-dusk-dawn estimates averaged 91 percent of gross production and 87 percent of total respiration in eight laboratory microcosms and 71 percent of gross production and 52 percent of total respiration in Keystone Reservoir, Oklahoma when compared to the full diurnal curve analysis. In this study 61 percent of the metabolism measurements from the inner bay and 68 percent from the outer bay were made with the dawn-dusk-dawn method. Since the apparent underestimation was largest in the inner bay, these values may be conservative estimates .
Effects of Advection on Calculation of Metabolism
If an increase in oxygen occurred at night because of advection, an artifact in the rate-of-change curve was produced which made it appear as if photosynthesis was occurring. Net producti on would be overestimated because the nighttime gain in oxygen would be added to the actual net production occurring during daylight hours. Night respiration would be underestimated because the area of positive oxygen gain would not be counted in the calculation of respiration. By measuring this omitted area, night respiration was found to be underestimated by an average of 1.5 g/m2.day on the full diurnal curves from the inner bay.
Light and Dark Bottle Me'asurements
Light and dark bottle studies were made in the later stages of the project to estimate metabolic components of the water column as apart from the metabolism of the sediments and larger consumer organisms. Bottles (300 ml, BOD) were suspended at about 0.5 m depth by small chains secured to a four-foot length of 3/4-inch PVC pipe floated at each end by a plastic milk carton. Generally, five replicates each of both light and dark bottles were put out as soon as the dawn diurnal run was completed, and picked up at the same time the following day. Fixation and titration were as in American Public Health Association (1971), except that only a l0O-ml subsample was titrated because of the 0.0125 N thiosulfate used. The increase in the light bottle was taken as 24hour net production, the decrease in the dark bottle was t aken as 24-hour respiration, and the sum of the oxygen gained plus that used up was taken as gross photosynthesis.
Other Field Measurements
Di ffu sion Measurements
At Crystal River the rate of diffusion of oxygen into and out of the water column tended to be largely a function of tidal current velocity. Diffusion was measured at various stages of the tidal cycle using a
small nitrogen-filled plastic dome, which floated on the water surface (Hall, 1970, based on original work of Copeland and Duffer, 1964). An oxygen probe measured the return of oxygen into the dome from the water under the normal conditions of underwater circulation. A linear regression was calculated from the raw data. Although the increase in oxygen in the dome is not linear, the early response approximates a straight line. The diffusion rate as g/m 2 /hr/100 percent deficit was calculated from the linear regression, area of water surface covered, volume of the dome, and the observed saturation value of dissolved oxygen in the water. This was the maximum rate of diffusion into oxygen-free water or out of water 200 percent saturated with oxygen. Figure 12 shows a typical diffusion measurement.
Because of the small number of measurements taken, assigning diffusion rates to time periods on the graph was a combination of actual measured values and estimates based on field experience with the general magnitudes of tidal currents at different stages of the tidal cycle in the study areas. "rhe actual diffusion correction for each hour was calculated by multiplying the maximum rate selected for that hour by the actual saturation deficit during that hour.
Example of two experiments to determine oxygen diffusion coefficients by measuring the rate of return of oxygen into a nitrogen-filled dome floating on the water's surface. Line through points was obtained by calculating a linear regression. Meter was calibrated to give a reading of 10 in air. Data obtained at Fort Island study area.
Fi gure 12 .
30
u
U. JUNE 25, 1973
.1 FALLING TIDE (HIGH HIGH
TO LOW LOW )
Sy.= 0.175 + 0.021 x Uw 20- r2= 0.998
0
F
z
LJ
C-"
LU
0
Z 6
0
LI 0o JUNE 24, 197.3L- RISING T1DE (LOW -LOW
TO LOW HIGH)
-~*y0.139+0.0085 x
o r20.988
30 60 90 120
TIME FROM START, MINUTES
Light Penetration of the Water Column
Light penetration through the water column was measured with a submarine photometer (Tsurumi Precision Instrument Co., S/N 88130). Light intensity was measured at 0.1-meter depth intervals from the surface to the bottom and compared to a deck cell reading insolation incident to the water surface. Results were graphed on semi-log paper (Figure 13). The extinction coefficient was calculated was
ln (11/12)
K =
z2 - Z1
where I 1 was light intensity at the shallower depth
(ZI) and 12 was light intensity at the deeper depth
(Z2). K was in units of meter-1.
r 'igure 13.
Examples of submarine photometer measurements of light penetration through the water column taken at Fort Island away from the influence of the power plant discharge plume and in the inner bay influenced by the plume. Lines through points were fitted by eye. k, extinction coefficient.
PERCENT
OF SURFACE LIGHT INTENSITY
50 100
10 0 f-
DATA ASSEMBLED FROM OTHER PHASES OF THE
CRYSTAL RIVER PROJECT AND ELSEWHERE
One of the major objectives of the overall research program at Crystal River was to synthesize the knowledge of -the forcing functions outside of the system and the storages and process operating within the system. To this end, records of many of these variables from other phases of the project and elsewhere are included here to provide a total view of the estuarine ecosystem. These data are used for obtaining values for the model simulations and in determining if the simulation results are reasonable.
Energy Sources and Inflows
Affecting the Inner Bay
Seasonal and diurnal patterns of some of the external factors shown in Figure 4 are given below.
Sunl ight
In Figure 14 is the average daily insulation by month measured at Tampa, Florida, 97 km to the south of Crystal River (Water Information Center, Inc., 1974).
Figure 14. Average daily insolation by month at Tampa,
Florida (Water Information Center, Inc.,
1974).
8000 6000
4000 2000
0
10
0
tE
I
0
J F M A M J JY A
S 0 N D
2
Peak insulation months (about 6000 Kcal/m . day) were April and May at the very end of the winter-spring dry season. Daily summer values were lower due to frequent cloudiness from convective storms. Wind Direction and Speed
Wind rose diagrams by season are given in-Figure 15 (Fla. Power Corp., 1972). Summer winds were predominantly westerly and easterly as influenced by the large-scale circulation about the shifting position of the subtropical high-pressure system and by the more local regional land-sea breeze system. With the change in the fall and winter to weather patterns dominated by frontal systems, the predominant wind direction shifted to northerly directions. Average wind speed as given in Table 2 (Fla. Power Corp., 1972) was lowest in the summer and highest in fall and winter due to the strong winds associated with frontal passages. Ambient Air Temperature
In Figure 16 are monthly mean, mean maximum, and mean minimum daily temperatures at Tampa, Florida (Fla. Power Corp., 1972). Diurnal variation was smallest during the summer months when the climate was primarily under the influence of the subtropical high pressure system, and frontal systems usually remained well north
Figure 15. Wind direction by season at Crystal River site.
Bars are percent of readings occurring from each compass bearing (Florida Power Corporation, 1972).
DEC., %JAN., FEB. MAR. ,APR., MAY
JUN.,JUL., AUG.
SEP,OCT., NOV.
Table 2. Seasonal comparison of average wind speed at
Crystal River site (Fla. Power Corp., 1972)
Season
Average wind speed, mph
S p r i n g Summer Autumn
Winter
11.1
9.5
12.0 12.0
11 .4
Annual average
Figure 16. Monthly mean air temperature at Tampa,
Florida (Water Information Center, Inc.,
1974) .
I I I I i I I I I
_EXTREME HIGH---' AVERAGE DAILY MAXIMUM ---.
MONTHLY MEAN AVERAGE DAILY.1INIMUM
- M
-- \
/ /
EXTREME LOW
J F M A M J JYA S 0 N D
100 80 60
40 20
0
of the area. Minimum temperatures dropped sharply in October as cold fronts began penetrating into Florida, and remained low through the winter when the climate was characterized by cold air advection following frequent frontal passages.
Precipitation
Monthly mean precipitation at Tampa is presented in Figure 17 (Fla. Power Corp., 1972). About 60 percent of the yearly rainfall occurred from June through September and was associated with showers and thunderstorms in tropical air masses. During the extensive eight-month dry period extending through May, precipitation was mainly associated with frontal systems.
Stocks of the Inner Bay
Assembled below are data on stocks of organisms and other quantities important within the inner bay system.
Water Temperatures
Weekly average water temperatures at various
locations in the discharge canal, discharge study area, and intake area during the course of this study are given in Figure 18. Buoy locations are given in Figure 6. Weekly average electricity generated by units I and 2
Figure 17. Monthly mean precipitation at Tampa,
Florida (Water Information Center, Inc.,
1974) .
15
10
z
0
lij
J F NI A M J JY A S 0 N D
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lish a free school, that being one of the largest, if not the'
largest, school community of the Territory, having 341
children between the ages of 5 and 15 years. In the year-
1832, of these, 137 were reported as attending school. The
public school ardor seems to have been soon quenched, how
ever, nothing being recorded of the success of the attempt,
and the educational societies themselves ceased to exist shortly;
after this time.
The Territory, however, had school lands [which had been-
donated by an act of Congress. The first form of legal or
ganization to utilize the benefits to be derived therefrom, was
perfected by an Act of the Legislature in March, 1839, which
provided for three school trustees in each townshipthough:
many townships had not a single inhabitant. The duty of'
these trustees was to look after the sixteenth section of land
in their respective townships, and to see that the rents or
profits accruing-from the same were applied to the common
schools.
A few years later, it was made the duty of the sheriffs of
the several counties to give special attention to the education
of the children of the poor.
Several succeeding Legislatures made different amendments
to the law, and in 1845 the County Judges of Probate were
entrusted with partial supervision of the township trustees,
and required to perform some of the present functions of a
County Superintendent of Schools. The trustees were to
report to the judge, and these officers were required to con
solidate tvese reports and submit the same to the Secretary of
State, which by him were to be embodied in his report to the
Legislature.
The first legislation found upon the subject, after the Terri
tory became a State, was an Act in 1849, which provided for
an increase in the school fund by adding to the sale of school
lands the net proceeds of 5 per cent, of other public lands, of
all escheated property, and of all property found on the coasts
of the State; and also provided for the establishment of a
crude system, as it would now be called, of common schools.
In 1850, taxation by the counties for the support of schools
was authorized, but the results showed little disposition to
educate by means of taxation. The people, few as they were,
were too proud- to avail themselves of the benefits of. a.free-
school fund, which, though small, was by common consent
applied almost exclusively toward the payment of the tuition,
of the children of the poor. i ,
So few townships organized to get the benefit of the town,
ship fund (it being the original intention of the general gov-
ACKNOWLEDGEMENTS
Many of the ideas presented here were shaped in
discussions among the entire systems ecology group of
the Department of Environmental Engineering Sciences.
Special acknowledgements go to major professor H. T.
Odum for his stimulation, guidance, and the distinct
privilege of participating in this program. My super
visory committee included P. L. Brezonik, T. Bullock,
J. Ewel and S. C. Snedaker.
This work was supported, by contract No. GEC 159,
918-200-188.19 (Models and Measurements for Determining
the Role of the Power Plants and Cooling Alternatives
at Crystal River, Florida) between the Florida Power
Corporation and the University of Florida Systems Ecology
Program, Department of Environmental Engineering Sciences,
H. T. Odum, principal investigator.
Many people helped in the field and with data
workup: J. Bevis, N. Black, W. Boynton, C. High, D.
Hinck, M. Homer, M. Kemp, M. Lehman, H. McKellar, A.
Merriam, F. Ramsey, and D. Young. Analog computers used
in this study were maintained by A. Copsey, and J. Murphey,
who also provided programming assistance. Progress in
this study was much facilitated by K. Garrison, J. Johnson,
D. McMullin, and W. Trowell of the Florida Power Corpora
tion.
Use of the R. V. Susio was provided by the State
University System Institute of Oceanography.
i11
TABLE'OF CONTENTS
Page
ACKNOWLEDGEMENTS ii
LIST OF TABLES vii
LIST OF FIGURES x
ABSTRACT xvii
INTRODUCTION 1
System Adaptation, Environmental Impact,
and Thermal Loading of the Estuary at
Crystal River, Florida 5
Models for Gaining an Overview of the
Estuary and Power Plant at Crystal
River 9
Previous Studies of Thermally Affected
Aquatic Ecosystems 16
Description of Study Area at Crystal
River 21
Other Studies of the Crystal River
Region 3 1
Previous Simulation Models of Marine Eco
systems, Diurnal Oxygen Dynamics,
Temperature, and the Effects of Power
Plants on Ecosystems 33
Plan of Study
39
Page
METHODS 41
Metabolic Measurements 41
Other Field Measurements . 62
DATA ASSEMBLED FROM OTHER PHASES OF THE CRYSTAL
RIVER PROJECT AND ELSEWHERE 69
Energy Sources and Inflows Affecting the
Inner Bay 69
Stocks of the Inner Bay 78
RESULTS 116
Metabolism Measurements 116
Model Diagrams for Comparing Ecosystems
Affected and Unaffected by the
Discharge Plume 149
Simulation Model of Diurnal Properties
of the Inner Bay Ecosystem 154
Simulation Model of Seasonal Proper1 ties
of the Inner Bay Ecosystem 201
DISCUSSION 223
Seasonal Patterns of the Ecosystems at
Crystal River 223
Comparisons of the Ecosystems at Crystal
River and Adaptation to the Thermal
Discharge 239
Predictions of the Effect of the Operation
of Unit Three at Crystal River .... 252
Energy Costs of Alternatives to Estuarine
Cooling of the Thermal Discharge at
Crystal River 253
v
Page
APPENDICES 256
A EXPLANATION OF THE ENERGY SYMBOLS
USED IN THIS STUDY 257
B GRAPHICAL ANALYSES OF DIURNAL STUDIES
OF COMMUNITY METABOLISM IN THE INNER
BAY AFFECTED BY THE THERMAL DISCHARGE
PLUME AND IN THE FORT ISLAND AND
HODGES ISLAND AREAS AWAY FROM THE
INFLUENCE OF THE THERMAL DISCHARGE . 262
C INITIAL AND MAXIMUM VALUES OF STOCKS AND
FLOWS, HEAT BUDGET CALCULATIONS, CAL
CULATION OF TRANSFER COEFFICIENTS,
SCALED EQUATIONS, POTENTIOMETER SET
TINGS, FUNCTION GENERATOR SET-UP,
AND ANALOG COMPUTER PATCHING DIAGRAM
FOR DIURNAL SIMULATION MODEL OF
INNER BAY 311
D INITIAL AND MAXIMUM VALUES OF STOCKS
AND FLOWS, CALCULATION OF TRANSFER
COEFFICIENTS, SCALED EQUATIONS,
POTENTIOMETRIC SETTINGS, FUNCTION
GENERATOR SET-UP, AND ANALOG COM
PUTER PATCHING DIAGRAM FOR SEASONAL
SIMULATION MODEL OF THE INNER BAY . 356
E DOCUMENTATION OF DATA USED IN SUMMARY
DIAGRAMS OF SUMMER STOCKS AND FLOWS
FOR THE INNER DISCHARGE BAY AND
SOUTH INTAKE AREA 407
LITERATURE CITED 414
BIOGRAPHICAL SKETCH 426
LIST OF TABLES
Table Page
1 Results of a technique test of the
Winkler method to determine the effect
of the presence or absence of acid in
fixed bottles which have been stored
for eight hours before titration. 44
2 Seasonal comparison of average wind speed
at Crystal River site. 75
3 Record of metabolism for the inner dis
charge bay as measured by diurnal free
water oxygen changes and light and dark
bottles. 117
4 Record of metabolism for the Fort Island
and Hodges Island areas away from the
influence of the power plant discharge as
measured by diurnal free water oxygen
changes and light and dark bottles. 121
5 Diffusion rates measured in the power
plant discharge and Fort Island study
areas. 146
6 Average extinction coefficients for light
penetration of water on the inner dis
charge bay affected by the power plant
discharge plume and unaffected areas to
the north and south. 148
7 Differential equations for diurnal model
of inner bay given in Figure 40. 157
v i i
Table Page
8 Differential equations for seasonal
model of inner bay system given in
Figure 55. 202
9 Comparison of gross primary produc
tion and total respiration measured
at Crystal River with some values from
other areas in Florida and similar
systems elsewhere. 225
C-l Documentation of values used for forcing
functions, standing stocks, and exchange
rates in the diurnal simulation model of
the inner bay. 312
C-2 Initial and maximum values of storages
for diurnal simulation model of inner
bay. 329
C-3 Initial and maximum values of forcing
functions for simulation model of inner
bay. 330
C-4 Calculation of radioactive, evaporative,
and convective heat losses for use in
diurnal simulation model of inner bay. 331
C-5 Calculation of transfer coefficients for
diurnal simulation model of inner bay. 333
C-6 Equations of Table 7 scaled for simulation
of diurnal model of the inner bay given
in Figure 40. 339
C-7 Scaling of terms associated with photo
synthesis in equations in Table 10 for
diurnal simulation model of the inner bay. 347
C-8 Potentiometer settings for initial run
of diurnal simulation model of inner bay. 349
C-9 Potentiometer settings for the EAI 580
variable diode function generator used to
produce the tidal volume exchange function
given in Figure 42 for the diurnal model
of the inner bay.
v i i i
352
Table
Page
D-l Documentation of values used for stand
ing stocks and exchange rates in the
seasonal model of the inner bay. 356
D-2 Initial and maximum values of forcing
functions and storages for seasonal
simulation model of inner bay. 376
D-3 Calculation of transfer coefficients for
seasonal simulation model of inner bay. 377
D-4 Equations of Table 11 scaled for simula
tion of seasonal model of the inner bay
given in Figure 54. 387
D-5 Scaling of terms associated with photo
synthesis in equations in Table 8 for
seasonal simulation model of the inner
bay. 398
D-6 Potentiometer settings for initial run
of simulation of the seasonal model of
the inner bay. 402
D-7 Potentiometer settings for EAI 580 vari
able diode function generator used to
produce the seasonal cycle of sunlight
given in Figure 55 for the simulation
of the seasonal model of the inner bay. 404
E-l Documentation of numbers appearing on
Figure 38 of the inner discharge bay
ecosystem affected by the thermal dis
charge of the power plant. 408
E-2 Documentation of numbers appearing on
Figure 38 of the south intake area eco
system unaffected by the thermal plume of
the power plant. 411
LIST OF FIGURES
Fiqure
Page
1 Location of Florida Power Corporation's
power plants near Crystal River, Florida,
in relation to the major features of the
regional coastline. 3
2 Energy diagrams of producer and consumer
modules indicating the push-pull effects
of temperature on internal processes. 8
3 Aggregated energy diagram of the main
features believed important in the eco
system of the inner discharge bay at
Crystal River. 12
4 Energy diagram of the ecosystem of the
inner discharge bay, which includes much
of the complexity omitted from Figure 3. 15
5 Bathymetry of power plant discharge area
at Crystal River. 23
6 Thermally affected area showing location
of the shallow inner bay system dominated
by the seagrass, Halodule wrigh11i, and
thedeeperouterbaysystem. 27
7 Typical daily tidal cycle at Crystal River
site indicating unequal high and low tides. 29
8 Model of factors affecting oxygen dynamics
in water. 46
9 Example of graphical format for calculation
of community metabolism at Fort Island, 24-25
August, 1973, using full diurnal curve of
oxygen. 50
x
Figure
10 Graphical format for calculation of
community metabolism using dawn-dusk-
dawn data.
11 Comparison of community metabolism
estimates obtained from complete
diurnal measurements of oxygen versus
estimates obtained from dawn-dusk-
dawn calculations made using the same
data.
12 Example of two experiments to determine
oxygen diffusion coefficients by measur
ing the rate of return of oxygen into a
nitrogen-filled dome floating on the
water1s surface. 65
13 Examples of submarine photometer measure
ments of light penetration through the
water column taken at Fort Island away
from the influence of the power plant
discharge plume and in the inner bay
influenced by the plume. 68
14 Average daily insolation by month at
Tampa, Florida. 71
15 Wind direction by season at Crystal River
site. 74
16 Monthly mean air temperature at Tampa,
Florida. 77
17 Monthly mean precipitation at Tampa,
Florida. 80
18 Weekly averages of surface water temper
atures for the plume-affected inner dis
charge bay and ambient water of the south
intake area. 83
19 Weekly average of electricity generated by
power units at Crystal River, and weekly
average intake and discharge water temper
ature for uni t 1 86
Page
57
60
xi
Figure
Page
20 Average diel water temperatures meas
ured during community metabolism studies
of the inner discharge bay and the Fort
Island and Hodges Island control areas. 88
21 Diurnal patterns of electricity generated,
water temperatures at three locations,
and tidal stage in the discharge area of
May 24-27, 1974. 91
22 Average salinities measured on the inner
discharge bay and Fort Island and Hodges
Island study areas during the community
metabolism studies. 94
23 Seasonal patterns of benthic macrophytes
in the thermally affected inner bay and
inshore portion of the south intake area. 97
24 Map of summer standing crop of attached
macrophytic plants in the region near the
Crystal River power plants. 100
25 Seasonal diversity of benthic macrophytes
in the inner discharge bay and the south
intake area. 102
26 Seasonal record of biomass of benthic
macroinvertebrates in the inner discharge
bay and south intake areas. 105
27 Seasonal record of biomass of fish caught
with drop nets in the inner discharge bays
and south intake areas. 107
28 Carbon, nitrogen, and phosphorus measure
ments at the mouth of the discharge canal
and a station in the south intake area. 110
29 Measurements of live chi orophyl 1 -a and
phytoplankton biomass at a station in the
south intake area and at the mouth of the
discharge canal. 114
x 1 1
Figure
Page
30 Daytime net photosynthesis and night
respiration in the inner discharge bay
affected by the thermal plume and the
Fort Island and Hodges Island area
away from the influence of the power
plant. 125
31 Daytime net photosynthesis plus night
respiration as a measure of gross
primary production in the inner dis
charge bay affected by the thermal plume
and the Fort Island and Hodges Island
areas away from the influence of the
thermal plume. 127
32 All daytime net photosynthesis and night
respiration values from Tables 6 and 7
and Figure 30 plotted on 12-month graph. 129
33 All daytime net photosynthesis plus night
respiration values from Tables 6 and 7
and Figure 31 plotted on 12-month graph. 131
34 Average oxygen values from all summertime
diurnal measurements taken in the inner
discharge bay and Fort Island control bay. 135
35 Seasonal averages of daytime net photo
synthesis and night respiration in the
inner discharge bay and control areas. 138
36 Seasonal averages of daytime net photo
synthesis plus night respiration as a
measure of gross primary production for
plume-affected inner bay discharge area
and unaffected control areas. 141
37 Seasonal trends of the ratio of daytime
net photosynthesis divided by night
respiration for plume-affected inner bay
area and unaffected Fort Island and Hodges
Island areas. 144
38 Summary energy diagram of summer stocks and
flows for the inner discharge bay. 151
x i i i
Figure
Page
39 Summary energy diagram of summer stocks of
biomass or material and flows of energy
and organic matter for the south intake
area away from the influence of the power
plant discharge.
40 Energy diagram for simulation model of
inner discharge bay emphasizing the
diurnal properties of the system.
41 Computer plots of forcing functions of
tidal volume exchange, depth, offshore
oxygen, and offshore water temperature
used in the diurnal simulation model.
42 Simulation results of diurnal model of
inner bay with coefficients set as
originally scaled.
43 Data gathered from the inner bay during
the community metabolism study of June
21-22, 1973, against which the simulation
of the model of Figure 20 was compared.
44 Solar insolation for June 21, 1973, as
recorded by a pyranometer located at the
Crystal River power plant site. Total
radiation received is indicated.
45 Simulation results of diurnal model of
inner bay with original scaling, but
sunlight reduced to a daily total
similar to June 21-22, 1973.
46 Simulation results of diurnal model of
inner bay with equal amounts of canal
and offshore water contributed to the
inner bay on a rising tide.
47 Simulation results of diurnal model of
the inner bay with two parts canal water
to one part offshore water contributed to
the inner bay on a rising tide.
48 Simulation results of diurnal model of
inner bay with canal water alone being
contributed to the inner bay on a rising
tide.
153
156
163
1 66
170
172
174
178
182
x i v
Figure
49 Simulation results of diurnal model
of the inner bay with a 7C dif
ferential of discharge canal water
over ambient water and a mixing ratio
on a rising tide of one part canal
water to one part offshore water.
50 Simulation results of diurnal model of
the inner bay with a 7C differential
of discharge canal water over ambient
water and a mixing ratio of 2 parts
canal water to 1 part offshore water
on a rising tide.
51 Simulation results of diurnal model of
the inner bay with a 7C differential
of discharge canal water over ambient
water and with canal water alone flow
ing onto the inner bay on a rising tide.
52 Simulation results of diurnal model of
the inner bay with no discharge of
cooling water from the power plant dis
charge canal and original scaling of
insolation.
53 Simulation results of diurnal model of the
inner bay with no discharge from the
power plant discharge canal and insolation
reduced to one-half original scaling. 196
54 Simulation results of diurnal model with
timing of occurrence of high and low tide
reversed from previous runs. 198
55 Energy diagram of simulated model of
inner discharge bay emphasizing seasonal
properties of the ecosystem. 200
56 Seasonal patterns of insolation and tempera
ture used as forcing functions in the
seasonal model of the inner bay ecosystem. 200
57 Simulation results with initial scaling
of seasonal model of the inner bay. 210
Page
185
187
1 92
1 94
xv
Simulation results of seasonal model
of the inner bay with seasonal pattern
of temperature increased 3C.
Response of seasonal simulation model
of the inner bay to increased tempera
ture and turbidity.
Response of seasonal simulation model
of the inner bay to decreased turbidity
and a seasonal temperature range as
originally scaled.
Response of seasonal simulation model
of inner bay to decreased turbidity
and a seasonal temperature range of
18C 36C.
Energy diagram and analog computer patch
ing diagram of simulation model of
producer module with temperature affec
ting both photosynthetic and respiratory
pathways.
Simulation results of model of producer
module in Figure 62 with seasonally vary
ing light and temperature.
Simulation response of seasonal model of
the inner discharge bay to the addition
of pathways of exchange of fish and fish
larvae with offshore waters.
Simulation results of seasonal model of
inner bay as modified in Figure 64 with
larger photosynthetic coefficient added
in winter.
Analog computer patching diagram of
scaled equations given in Tables C-6 and
C-7 for the diurnal simulation model of
the inner bay.
Analog computer diagram of scaled equa
tions given in Tables D-4 and D-5 for the
seasonal simulation model of the inner
bay.
Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
PRODUCTIVITY MEASUREMENTS AMD SIMULATION MODELS
OF A SHALLOW ESTUARINE ECOSYSTEM
RECEIVING A THERMAL PLUME
AT CRYSTAL RIVER, FLORIDA
By
Wade Hampton Barnes Smith
August, 1976
Chairman: Howard T. Odum
Major Department: Environmental Engineering Sciences
The effects of the heated discharge of two power
plants on the receiving estuarine ecosystem near Crystal
River on the west coast of Florida were investigated with
measurements and simulation models to help understand
relationships and predict the consequence of a third
power plant under construction. Energy circuit models
emphasizing diurnal and seasonal aspects of ecosystem
responses were used to assess the effect of power plant
operation on estuarine ecosystems. Field measurements
were taken in the discharge-affected and -unaffected
areas nearby.
Benthic populations dominated total metabolism
in both systems. Community gross primary production
varied seasonally in the unaffected areas from a winter
x v 11
2 2
low of 3.3 g 0 ^ / m -day to a spring high of 8.8 g O^/m-day.
In the discharge area it was relatively constant, remain-
2
ing about 4 g O^/m -day in all seasons. Phytoplankton
production normally was about 5 percent of total produc
tion in the unaffected areas and about 23 percent in the
discharge area. In the spring its contribution increased
greatly to 25 percent in the unaffected area and 70 per
cent in the discharge area.
Total biomass was less in the discharge than
in unaffected areas. Lower standing stock of primary
producers and benthic invertebrates in the discharge
area accounted for almost all the difference.
Diversity was lower in the discharge bay than in
the unaffected area. Mixed macroalgae and seagrasses
were the dominant benthic producers in the unaffected
areas, while the seagrass Ha 1 odu1e wrightii was virtually
the only species in the discharge bay. Species diversity
was lower for oyster reef organisms, and fewer species
of fish were caught in drop nets in the discharge bay
than in the unaffected bay.
A shift toward more cycling of material and energy
through the phytoplankton and filter feeders and away
from the benthic components of the system may have
occurred in the discharge area as an adaptation to the
thermal plume.
x v i i i
Simulation of the model of diurnal system proper
ties with coefficients representing those for discharge
conditions gave patterns similar to those measured in the
discharge bay. The model was relatively insensitive to
adjustments in water temperature within the range expected
in the future at Crystal River. A change in the quantity
of daily insolation produced a larger change in model
response.
The simulation model of seasonal system proper
ties was also more sensitive to light than to water
temperature. Increasing temperature alone increased
primary production and total respiration somewhat, espe
cially in the spring. Fish and invertebrate biomass
remained the same, while detrital storages declined,
perhaps indicating their importance as an energy source
for offsetting increased respiratory drains on consumers
because of increased temperature. Increases in light
alone greatly increased system storages and flows, sug
gesting the importance of turbidity in controlling
metabolism in the discharge area. Increasing temperature
but decreasing light lowered metabolism.
Adjustments to the seasonal model tested the
theory that systems with prominent seasonal pulses may
be exploited by populations that move in during the period
of plenty, experience rapid exponential growth, and then
x i x
move away. With some migration the fish stock could main
tain itself in a stable oscillating yearly pattern.
Results of other adjustments to the seasonal model
suggested that seasonal substitution of species of primary
producers may be the most effective way to make maximum
use of available energies at all times of the year.
xx
INTRODUCTION
This is a study of shallow, benthic-dominated
estuarine ecosystems on the Florida west coast, one of
which received a thermal discharge from two electric
generating stations of the Florida Power Corporation.
Water was drawn from the deeper offshore Gulf of Mexico,
passed through the power plant condenser system, where
its temperature was increased about 5C, and discharged
onto the shallow inshore coastal area (Figure 1). This
study was made to increase understanding of the structure
and function of estuarine ecosystems, the relationship of
individual parts to the functioning of the total pattern
as an integrated unit, and the effects of temperature
change. Specifically investigated was the nature of an
estuarine system which had been receiving thermal effluent
for six years. How does an entire ecosystem adjust and
adapt to these new energy conditions imposed on it? How
does the new system serve as an interface between the
economy of man and that of nature?
Energy diagrams were drawn to organize, summarize
and synthesize data in models, and as a conceptual tool
1
Figure 1. Location of Florida Power Corporation's power plants near Crystal
River, Florida, in relation to the major features of the regional
coastline. Oyster bars are indicated by dotted outlines.
4
for illustrating ideas about the ecosystem at Crystal River
and the role of thermal loading in shaping its pattern.
Total metabolism, including photosynthetic production and
total respiration, was measured as the primary indicator
of the main system functions. Using simpler models, com
puter simulations of seasonal and diurnal trends were run
and compared with measured data. This study was part of
a much larger project funded by the Florida Power Corpora
tion evaluating questions related to the impact of its
power plants at Crystal River on the adjacent estuarine
ecosystems. As required by our contract, efforts were made
to summarize data from other studies in developing an over
view of the ecosystem.
As fossil fuels for powering man's economy become
scarcer and more expensive, the need increases for recognizing,
utilizing, and protecting the important work contributions
of nature in support of man's economy, and establishing
effective feedback pathways from man to protect his life
support system. A regional system of man and nature which
allows its natural components to contribute work services
in support of the overall pattern may avoid unnecessary
technological constructions and be most successful in
utilizing all available energies when use of the environ
ment constitutes more useful work than is lost by environ
mental impact. For example, should coastal and estuarine
waters be used for cooling of the thermal effluent from
5
electric generating stations, or is it necessary to build
technological alternatives such as cooling towers for this
purpose?
System Adaptation, Environmental Impact,
and Thermal Loading of the Estuary at
'Crystal River, Florida
At Crystal River, and wherever thermal effluents
flow into an ecosystem, potential energy is carried with
it. This energy, like all other energy sources impinging
there, is available for doing work in the environment,
although its exact way of doing work may not be known
(Odum, 1974b).
Other changes besides thermal loading are caused
by power plant installations. At Crystal River the con
struction of dikes and the pumping of cooling water through
the canal system (see Figure 1) may modify the current
and flushing characteristics of the surrounding waters.
Turbidity in the discharge area may have increased because
of scouring of the discharge canal and from sediments
carried through the power plant from the intake canal
where they had been stirred up by barge traffic. Canal
construction caused changes in drainage patterns and mor
phology of adjacent salt marshes.
The most important impact, however, may be the
effect of higher temperature on biological processes.
6
Adaptation and acclimation of metabolism of individual
organisms to offset temperature changes is well estab
lished (Bullock, 1955). Much less is known about the re
sponse of whole ecosystems to changed thermal regimes.
How does system structure adapt so that the new pattern
that emerges is best coupled to the changed thermal
regime? What is the nature of this new system linked to
man's technology? These questions may begin to be answered
by observing such system properties as total community
metabolism, species diversity, and seasonal patterns.
The effect of thermal loading on biological pro
cesses may be important at both the level of individual
organisms and the ecosystem (Kelley, 1971; Odum, 1974b;
McKellar, 1975). Since all processes are stimulated equally
below the threshold of rapid thermal enzyme destruction,
temperature acts to increase processes building structure
as well as those degrading it (Figure 2). "For a plant
(Figure 2a), the dark reactions of photosynthesis may be
stimulated as much as respiratory pathways, so that the
overall effect on biomass may be neutral. However, if
photosynthesis is limited by energy and material shortages
so that respiratory losses are not offset, biomass may
decline. The same holds true for a consumer (Figure 2b).
If the metabolic pathways of digestion and rebuilding of
structural animal biomass are affected at the same rate
as those degrading this biomass, metabolism increases but
Figure 2. Energy diagrams of producer and consumer
modules indicating the push-pull effects of
temperature on internal processes. See
Appendix A for meaning of symbols.
(a) Producer module with temperature acting
on both photosynthetic primary produc
tion and respiration processes.
(b) Consumer module with temperature acting
on processes of biomass formation through
food gathering, digestion, and assimila
tion as well as the respiratory degrada
tion of biomass.
(b)
FOOD
SOURCE
9
the amount of biomass is unaffected. However, if food is
limited the population loses mass because it cannot compen
sate for respiratory losses.
For the ecosystem, if it is to compete at the new
steady state, respiration degrading structure induced by
higher temperatures must be compensated for by the larger
push of increased rates of production of system structure.
Can accelerated cycling of nutrients from increased res
piration offset nutrient limitations to primary production?
Is this increased production enough to supply energy demands
of larger consumers?
Models for Gaining an Overview of the
Estuary and Power Plant at Crystal River
Proposed in Figures 3 and 4 are the energy circuit
models at different levels of complexity of the system of
estuary and power plants at Crystal River. Their purpose
is to organize in overview concepts of system structure,
processes, pathways, interactions, and relationships.
Inherent in the diagrams are patterns important on both
daily and seasonal time scales. An explanation of symbols
used in this dissertation is given in Appendix A. More
complete discussions and additional symbols are given by
Odum ( 1 971 1 972 1 974a, 1 975 ).
10
Simplified Model of the Inner Bay
Given in Figure 3 is a model diagram of the inner
bay ecosystem from which details have been eliminated
leaving only the basic system structure of water storage,
benthic macrophytes, consumer populations and tidal ex
changes with the saltmarsh, offshore, and canal ecosystems.
On a rising tide surface water from the power plant dis
charge canal is forced onto the inner bay by the damming
effect of water flowing on from offshore and the increasing
height of head of the approaching wave of the tide. On
a falling tide canal water flows directly down the channel
beside the inner bay, where it receives water flowing off
the bay. Diffusive oxygen exchange with the atmosphere
occurs driven largely by turbulence induced by tidal
exchange. Gains of heat result from solar insolation
and atmospheric longwave radiation. Heat losses occur
from conduction, back radiation, and evaporation.
Primary production occurs in the phytoplankton
and the benthic macrophytes, which take up nutrients and
oxygen from the water column while returning oxygen and
organic matter to it. Storages of organic matter are in
the water column and sediments, which are consumed by
populations of microbes. Two classes of consumers are
shown. In the water column are free living animals feed
ing on detritus, phytoplankton, benthic invertebrates, and
Figure 3. Aggregated energy diagram of the main fea
tures believed important in the ecosystem
of the inner discharge bay at Crystal
River. Details within the compartments
have been omitted to emphasize basic sys
tem structure and function in overview.
Symbol shown as indicates a connection
j
from heat sinks [-==?). See Appendix A for
definition of symbols.
1 2
each other. Many of the larger members of this compart
ment migrate seasonally to and from the offshore regions.
Benthic invertebrates and oysters feed largely on detritus
and phytoplankton. Nutrients are regenerated into the
water column from all respiratory pathways.
Detailed Model of the Inner Bay
In Figure 4, more of the complexity of detail
within the compartments has been added to the model of
Figure 3. Sunlight penetrating the water column of the
inner bay is attenuated by turbidity, shading of phyto
plankton biomass, and the natural extinction properties
of water. Primary production utilizes the remaining
light, and is concentrated in the benthic macrophytes
and their associated epiphytes with a smaller contribution
from the phytoplankton. This production moves to the higher
trophic levels primarily through a storage of detritus and
its associated microbes in the sediments. A much smaller
amount is stored in the water column. A small amount is
transferred by direct grazing of epiphytes. Larger con
sumer populations are represented by benthic inverte
brates and oysters, zooplankton and larval forms, shrimps
arid crabs, and resident and migratory fish. Seasonal
migratory movements of shrimps, crabs, and migratory fish
stocks are indicated. All respiratory pathways are shown
returning nutrients into the water column storage. Various
15
Figure 4. Energy diagram of the ecosystem of the inner
discharge bay, which includes much of the
complexity omitted from Figure 3. Pathways
of oxygen uptake and temperature effects
have been abbreviated for clarity. Pathways
from storages of heat and oxygen labeled T
and 0, respectively, are assumed to be con
nected with similarly labeled pathways on
work gates and consumer modules. Pathway
marked as T indicates a connection from
heat sink symbols (
exchanges with the adjuacent saltmarsh, power plant canal,
and immediate offshore ecosystems occur with the rise and
fall of the tide.
Heat in the water is lost and gained through physi
cal processes as well as advective exchanges. Gains occur
from solar insolation, atmospheric longwave radiation, and
heat generated from all biological processes. Losses re
sult from back radiation and evaporation. Conduction is
a gain or loss depending on the direction of the gradient
between air and water. Oxygen has a diffusive exchange
with the air driven largely by water turbulence.
In summary, this detailed model serves to emphasize
issues related to the interactions of power plants with
estuaries, helps the reader visualize the system studied
at Crystal River, summarizes initial understanding of its
characteristics, helps to plan the research program, and
provides a basis for simpler models for simulation.
Previous Studies of Thermally Affected
Aquatic Ecosystems
Most work on the effect of temperature on life
processes has been at the level of the whole organism
or at smaller (e. g. subcellular) levels; less work has
been concerned with its effect on whole ecosystems.
Perhaps because of their simplicity the most thoroughly
studied ecosystems to date have been thermal spring
17
ecosystems. System structure has been discussed by most
authors (Brock, 1967a, 1967b, 1969; Brock and Brock, 1969;
Kullberg, 1966; Stockner, 1967, 1968; Wiegert and Fraleigh,
1972). Zonation of algal or bacterial mat communities
associated with temperature gradients, both down and across
spring runs, with a vertical zonation of structure at any
given point were the main characteristics of these eco
systems. Filamentous bacteria were dominant in the hotest
portion of the stream, being replaced by blue-green algae
as the water cooled. Green algae, in turn, replaced the
blue-green at still lower temperature cooling. Species
diversity was very low overall, tending to increase down
the temperature gradient.
Community metabolism in thermal springs has also
been measured (Brock, 1967b; Duke, 1967; Phinney and
Mclntire, 1965; Stockner, 1968; Wiegert and Fraleigh, 1972).
Values measured generally fell within ranges reported
for many other types of aquatic ecosystems. Brock (1970)
reviewed work on high temperature systems.
The work reported above is mostly on springs with
temperatures in excess of 45C, which is generally above
the thermal limits for enzyme destruction of most organisms.
Available work on thermally affected systems within temper
ature ranges more normally encountered in nature has mostly
involved microcosm studies. Allen and Brock (1968) re
ported that microcosms held at a range of temperatures
from 2C to 75C and all seeded alike from a wide variety
of sources; each developed its own characteristic combina
tion of species. Beyers (1962) found only small responses
in community metabolism to 36-hour increases in temperature.
Davis (1971), studying experimental estuarine ecosystems
contained in large plastic swimming pools, found increased
gross community primary production and respiration during
spring, summer, and fall in those heated 4-6C above con
trols. Kelley (1971) studied high-nutrient freshwater micro
cosms subject to constant low, constant high, and fluctuat
ing temperature regimes. Mean values of net production
and night respiration over the study period were higher in
those microcosms which had higher mean temperatures. Vari
ous aspects of the biology of Par Pond, a freshwater reactor
cooling pond at the Savannah River Plant, South Carolina,
have been studied for a number of years by investigators
at the Savannah River Ecology Laboratory of the University
of Georgia (Gibbons and Shari tz, 1 974b).
A general assessment of research related to the
environmental effects of the operation of power plants
is difficult because much of it is contained in reports
to Federal agencies concerned with licensing, and is gen
erally unavailable for review. Zieman (1970) has reported
on the early effects of the operation of power plants at
Turkey Point on Biscayne Bay, near Miami, Florida. Condi
tions of flow rate and temperature rise of the cooling water
were very similar to those at Crystal River. The receiving
ecosystem was dominated by a mixture of macroalgae and sea-
grasses (mostly Tha 11 assi a testudinum). By the end of the
second summer of operation 50-60 acres of bay bottom adja
cent to the mouth of the discharge canal had been denuded
of this community and replaced by a blue-green algal mat
community. An additional 70-75 acres had some Tha11assia ,
but were still devoid of macrophytic algae, while 160-170
more acres exhibited some stress to the existing macro
algae populations.
Other available power plant data have dealt with
more northern situations involving phytoplankton-dominated
ecosystems. The effects of increased temperature on pri
mary production were usually measured by the uptake of
carbon-14, often in bottles held in illuminated light
boxes. Results have been mixed. Several studies in
volving both estuarine and freshwater cooling systems
have found stimulation of photosynthesis in the cooler
months and a depressing effect in the warmest months
(Morgan and Stross, 1969; Smith et al., 1974). Tilly
( 1 974 ), using carbon-14 measurements incubated i_n_ situ
in Par Pond, South Carolina, found primary production to be
somewhat greater in the surface water at the warmer station.
This tendency was more pronounced during the warm months of
the year. Gurtz and Weiss (1974), also using carbon-14
methods, found inhibition of photosynthesis at all times
of the year. A trend toward greater inhibition at higher
ambient water temperatures was suggested by the data.
20
Only several reports appear to be available on
aspects of ecosystems which have been adapting to power
plant discharges for a number of years. North (1968)
studied the discharge area affected since 1957 at Morro
Bay, California. He found abundance and diversity of
plants and animals to be reduced in a transitional
region over a distance of approximately 200 m from the
end of the discharge canal. Recovery to conditions
typical of the area occurred in a relatively short hori
zontal distance of 10 m at the end of the transitional
region. J. R. Adams ejt a_K ( 1 974) could find no differ
ence in intertidal sandy beach populations located near
the discharge versus ones further away.
Few power plant studies appear to have synthesized
the diverse data into an overview of the ecosystem respond
ing as an integrated unit to the new set of environmental
forcing functions. Emphasis has generally been placed
on individual aspects of power plant operation, such as
entrainment through the condenser cooling system and
entrapment on the screens protecting the cooling water
intake pumps (Jensen, 1974c), or on individual species
or components of the ecosystem. Typical studies might
examine mortality of phytoplankton from passage through
the condenser system, diversity and biomass of benthic
organisms and fish in the discharge area, or primary
production of the phytoplankton component of the ecosystem
21
Often these studies have been done in the laboratory.
Chesapeake Science, volume 10 (1969), and proceedings of
symposia edited by Gibbons and Sharitz (1974a) and Esch
(in press) contain many papers of this type.
Several studies have been published which contain
most research results for a particular power plant in one
volume (Jensen, 1974a, 1974b; Central Electricity Generat
ing Board). Discussion of results, however, is by sub
systems with little attempt to synthesize the findings
with text, diagrams, or simulation models into a picture
of the functioning of the whole ecosystem.
Description of Study Area at Crystal River
The power plant site in Citrus County (Figure 1)
is on the low wave energy portion of the Florida west
coast as defined by Tanner (1960). The shallow sloping
bottom (46 km to the 5 fathom contour) is part of the
drowned karst topography of this portion of west central
Florida. The topography of the immediate offshore region
is a series of shallow basins separated by oyster reefs
(Figure 5). Freshwater sources influencing the area are
the Crystal River 4.8 km to the south (mean flow 1500
m /min; 400,000 gpm), and the Withlacoochee River and
Cross Florida Barge Canal 6.4 and 5.8 km to the north,
3
respectively, with a combined flew of 2150 m /min
(570,000 gpm).
Figure 5. Bathymetry of power plant discharge area at Crystal River. Location
of inner bay has been circled. Contour interval is 1.0 feet. Datum
based on mean sea level. (Adapted from Rodgers et_ al 1 974 )
NAUTICAL
(ADAPTED FROM
RODGERS, ei aL 1974)
*P&D\S CHARGE/^
CANAL ^
DO
GO
24
The power plants are on the landward edge of a
tidal saltmarsh dominated by Juncus roemerianas bordered
on the seaward edge by a narrow fringe of Spartina
alternif1 ora. Two units were in operation during this
study--unit 1 since July, 1966, and unit 2 since November,
1 969 giving a combined total output of 897 megawatts
electrical (MWe). A nuclear powered unit of 885 MWe
output was under construction. The two operating units
cycle water for once-through cooling at a combined flow
3
of 2430 m /min (640,000 gpm) through canals dredged
across the shallow offshore region and saltmarsh.
Maximum condenser temperature rise is 6.1C.
The power plant intake canal extends approxi
mately 4.8 km into the Gulf with an average depth of
6-7 m and a width of about 75 m, serving also as the
passageway for delivery of fuel oil in barges by large
ocean-going tow boats. Cooling water passes down the
canal at about 8 cm/sec before being pumped through
the power plant condensers, where its temperature rises
5-6C. The discharge canal is about 1.6 km long with
an average depth and width of about 4.5 m and 50 m,
respectively. The smaller cross-sectional area causes
the stream velocity to be about twice that in the intake
canal. The residence time of water masses in the canal
system is about 20 hours for the intake canal and about
3.5 hours for the discharge canal.
25
Two types of bay systems are affected by the
thermal plume (Figure 6). Immediately adjacent to the
saltmarsh is the shallow bay of this study averaging
about 1 m in depth, composed of a mixture of bottom
covered with seagrass, some oyster reef associations,
and areas of sand and mud. Seaward of a row of oyster
bars is a deeper outer basin of about 2 m average depth
in which the plankton and reef ecosystems become impor
tant. The "bays" referred to here are actually the
immediate landward edge of the Gulf of Mexico.
The plume-affected inner bay of this study is
a shallow benthic seagrass-dominated system composed
almost exclusively of Ha 1odu1e (Diplanthera) wrightii
during the warm months, while in the winter of 1972-73
mixed Ectocarpaceae proliferated and covered much of the
bottom area. It did not return during the milder winter
of 1973-74. The unequal semi-diurnal tide (see Figure
7) has an average tidal amplitude of about one meter
exposing much of the bay bottom on the lowest of the
two daily low tides, and draining the entire bay on
the lowest spring tides. In addition, strong northerly
winds associated with passages of cold fronts in winter
occasionally push the regional water mass offshore and
drain the bay and the nearby coastal area for several
days. With normal weather and tides, the heated plume
moves back and forth across portions of the bay in
Figure 6. Thermally affected area showing location of
the shallow inner bay system dominated by the
seagrass, Ha 1odule wrightii and the deeper
outer bay system. Lettered dots indicate
inner bay locations of remote telemetry
buoys maintained by Florida Power Corporation
for recording water temperatures. Location
lettering is as designated by the Florida
Power Corporation.
27
Figure 7. Typical daily tidal cycle at Crystal River site
indicating unequal high and low tides. Ampli
tude changes were taken from tide tables (U. S.
Department of Commerce, 1372) for June 12,
1 973.
DEPTH,
29
30
response to the tidal cycle. The shallow areas near
the power plant which were unaffected by the thermal
plume were dominated by a diverse mixture of benthic
macroalgae and seagrasses.
Areas away from the influence of the power plant
discharge at Fort Island, Hodges Island, and in the south
intake area (Figure 1) were used as comparison areas.
The south intake area was located immediately south
of the southern intake canal dike. Measurements taken
there by others included stocks of fish, benthic inverte
brates, benthic macrophytes, zooplankton, sediment organic
content, and nutrient concentrations. The benthic macro-
phytic producers were a diverse mixture of macroalgae
and seagrasses.
Total metabolism measurements were made at Fort
Island and Hodges Island. Most measurements were made
in a funnel-shaped bay south of Fort Island. This area,
which was somewhat deeper than the inner discharge bay
area, was characterized by a benthic flora similar to
the south intake area. The extreme clarity of the water
influenced by the nearby Crystal River allowed much
greater light penetration to the bottom as measured with
a submarine photometer than in the power plant discharge
area. Hodges Island to the north of the Withlacoochee
River (Figure 1) was away from freshwater influences.
This bay had more turbid water with little growth of
benthic macrophytic plants.
31
Other Studies of the Crystal River Region
Little work is available on the Crystal River
region prior to power plant construction. Dawson (1955)
provided data on oyster populations and hydrography,
including measurements at stations now well within the
influence of the power plant.
After construction and operation of the plants
were initiated, many studies were made as part of the
larger research program undertaken by Florida Power
Corporation. Benthic seagrasses and algae were inven
toried by Steidinger and Van Breedveld (1971), while
quantitative measurements of biomass were made by Van
Tyne (1974). Benthic invertebrates were inventoried
by Lyons et al. (1971) and measured quantitatively by
Evink and Green (1974).
Trawl samples of fish were reported by Grimes
(1971), Grimes and Mountain (1971), and Mountain (1972).
C. A. Adams (1974) analyzed data on fish caught in
dropnets from the shallow inshore areas, while Carr and
Adams (1973) discussed the food habits of juvenile fish
in the beds of benthic seagrasses and macrophytes.
Homer (1975) studied seasonal patterns of tidal creek
fishes.
Trace metal content of oysters from the intake
and discharge canals was reported by Grimes (1971) and
32
Mountain (1972). Biomass, diversity, and metabolism of
oyster bars were measured by Lehman (1974a, 1974b).
Blue crab movements in the intake canal area
were monitored by Adams, Oesterling, and Snedaker (1974).
Nutrients, chlorophyll, and phytoplankton numbers and
diversity were measured by Gibson (1975). Zooplankton
biomass and diversity were studied by Maturo (1974).
Fish and other organisms trapped on the screens
protecting the condenser water intake pumps were monitored
by Adams, Bilgere, and Snedaker (1974). Entrainment of
larval fish and zooplankton through the condenser system
was measured by Maturo (1974) and Snedaker and Johnson
(1975).
Total community metabolism was measured and
studied with simulation models for the saltmarsh by
Young (1974), for the oyster reefs by Lehman (1974a,
1974b), for the deeper outer bays by McKellar (1974, 1975),
and for the power plant canals by Kemp (1974). A larger
scale analysis of the energetic costs associated with
estuarine cooling compared to technological alternatives
was done by Odum ( 1 974b), Odum et_ al. (1 974), and Kemp
ejt aj ( 1 975).
Physical measurements of the hydrography of the
area were reviewed by Carder (1975). These were used
by Klausewitz (1973) for verification of a computer
simulation model of the behavior of the thermal discharge
33
plume. Bedient (1972) simulated the flushing of water
from the discharge canal as it related to dispersion of
radioactive wastes in the discharge water. Swindler
(1973) examined the sedimentology of the region between
the Crystal River and Withlacoochee River. Cottrell
(1974) studied sediment composition and sedimentation
rates in the more immediate plant area.
Previous Simulation Models of Marine Ecosystems,
Diurnal Oxygen Dynamics;, Temperature, and the
Effects of Power Plants on Ecosystems
Several previous attempts at modeling marine
ecosystems have appeared in the literature. Chen and
Orlob (1972) developed an extensive simulation of the
San Francisco Bay and Delta region incorporating spacial
as well as temporal elements. The geographical region
was divided into a network of nodes and connecting path
ways. Mass balance equations were used to transfer
materials between nodes with tidal dynamics as the
forcing function. Up to 22 parameters could be con
sidered: dissolved oxygen, biochemical oxygen demand,
alkalinity, pH, temperature, nitrogen (three forms),
phosphorus, suspended sediment, three types of algae,
zooplankton, three types of fish, and benthic animals.
For conservative elements, only terms for diffusion,
advection, input, and output were included in the mass
34
balance. For biological elements, appropriate terms
for rates of growth, respiration, mortality, and chemical
transformations were added. Temperature linearly affected
respiratory pathways of fish and zooplankton, and affected
both photosynthesis and respiration of algae. Growth rate
coefficients were based on Michaelis-Mention kinetics.
Model calibration to real data was presented for only
several parameters with fit being quite good. Subsequent
runs evaluated the effect on the bay of proposed regional
sewage treatment and water diversion alternatives.
Steele (1974) simulated a simple model of the
North Sea using storages of nutrients, phytoplankton,
zooplankton weight, and zooplankton numbers. Sunlight
was considered nonlimiting and was omitted as a forcing
function, so that changes in phytoplankton biomass were
a function only of nutrients, mixing below the thermo-
cline, and zooplankton grazing. Nutrient cycling was
included as excretion by zooplankton respiration.
Equation terms for nutrient uptake and zooplankton
grazing were derived from observed experimental data
and were given the form of Michaelis-Menton kinetics.
Brylinsky (1972) performed a sensitivity analysis
on a model of the English channel, which included storages
of phytoplankton, zooplankton, benthic fauna, pelagic
fish, demersal fish, and bacteria. Photosynthesis was
considered a constant external input. Pathways of
35
exchange between compartments were linear and controlled
solely by the donor compartment. Since nutrients were
not included as a variable, cycling was not a model fea
ture. It was stated that the model was not intended to
be realistic, but, instead, to illustrate the applica
tion and usefulness of the tool of sensitivity analysis.
An early attempt to simulate diurnal oxygen
dynamics of an ecosystem was made by Odum, Beyers, and
Armstrong (1963) using a passive analog circuit. Results
supported the theoretical discussion of the effect of
a small organic storage capacity in the nannoplankton
on the measurement of primary production in tropical
seas.
Several authors have obtained very good fit
for data from microcosms to relatively simple models
of their diurnal properties. Sollins (1970), studying
a blue-green algal mat, followed oxygen through compart
ments of producers, consumers, detritus, dissolved oxy
gen, CO^ (total in solution), atmospheric oxygen, and
water. All flows between compartments were controlled
by the upstream compartment only (donor control). Using
a square-wave regime of light input, the model produced
simulated curves of oxygen very similar to measured
curves and their rates of change.
Kelley (1971) included only storages of carbon
dioxide and labile and structural organic matter in his
simulation of a nutrient-rich freshwater microcosm of
mixed plankton. Since his study was partially concerned
with the effects of temperature, it was included in a
push-pull fashion as an action on every pathway. Rates
of flow between compartments were otherwise controlled
only by the donor compartments, as in the model by
Sollins. Excellent fit was obtained to the measured
oxygen data.
Nixon and Odum (1970) considered only storages
of organic material and nutrients in a model of hyper
saline algal mat community. Transient responses of this
very simple model were compatible with those observed
in the microcosm.
Simulations based on the more variable data
gathered from open ecosystems in nature have been
carried out. A model of Bissel Cove, Rhode Island
(Nixon and Oviatt, 1973) was basically an oxygen balance
consisting of a single storage of oxygen with inputs
from primary production of plankton, macroalgae, and
benthic microflora. Respiratory oxygen losses occurred
to producers, sediments, detritus, shrimp, and fish.
Diffusion exchange with the atmosphere and tidal exchange
with a constant oxygen source were losses or gains
depending on the saturation level of the water and the
stage of the tide. Rates of oxygen losses or gains for
each pathway were empirically derived from regression
37
equations calculated from observed data. No feedback
or cycling pathways were included. Model response fit
reasonably well to observed diurnal curves of oxygen.
Boynton (1975) simulated a river-dominated
estuary to examine issues of river discharge schedules
and potential effects of human development on nearby
lands and its relation to an oyster fishery existing
in the bay. Using a simplified energy symbol model,
diurnal curves of oxygen very similar to data measured
in the area were obtained.
Several simulations have included temperature
actions. An early one emphasizing the effect of temper
ature as an exponential function on zooplankton popula
tions of the North Sea was done by Riley (1946, 1947).
Odum (1975) translated these equations into models
using the energy circuit language.
Hall (1974) briefly reported on a simulation
model of the effect of power plants on the striped
bass fishery of the Hudson River. Details of the model
were not given.
Odum (1974b) discussed some general principles
regarding temperature and system responses, including
the push-pull effect on both ordering and disordering
processes. Examples were given of simulations of equa
tions proposed by Eyring and Eyring (1963) and Morowitz
(1968) which incorporated the push-pull feature of
temperature action.
38
Nixon and Oviatt (1973) included temperature
actions only on respiratory pathways in their simula
tion model of Bissel Cove. As a result, a decline in
oxygen was predicted as the effect of the action of a
hypothetical power plant on the cove.
Miller (1974) simulated the effect of maintain
ing mangrove vegetation in power plant canals to aid in
cooling the water before recirculation through the power
plant. Increased, but not severely detrimental, water
stress was predicted for the trees.
Several simulation models of other ecosystems
at Crystal River have been run. Young (1974) observed
increased photosynthesis, respiration, and live and dead
standing crop in simulations of the effect of elevated
water temperatures on the fringing Spartina saltmarshes.
Lehman (1974b) simulated the intertidal oyster reefs.
Model responses included faster turnover rates for
plume-affected conditions. Simulations of effects of
adding thermal waters of another power plant suggested
reduced seasonal variation of reef standing stocks.
Kemp (1974), in a preliminary simulation of the com
munity of fish, plankton, and benthos of the power plant
intake canal, found fish stocks to be most sensitive to
water flow rates and immigration. Plankton was rela
tively insensitive to most parameters, being controlled
principally by concentrations carried in from outside
39
the canal. McKellar (1975) simulated the outer bay of
the discharge area (see Figure 6). Raising the water
temperature to that measured in the discharge area
produced only small increases in total metabolism and
some component storages. Hater exchanges were shown to
be a stabilizing influence by dampening large fluctua
tions in zooplankton, phosphorus, and detritus. Simula
tion of the conditions expected with future power plants
produced no large changes in total community metabolism.
Plan of Study
The structure and function of the thermally
affected inner bay ecosystem at Crystal River and
unaffected areas to the north and south were determined
from field measurements of biomass of organisms and
system metabolism, and from the behavior of ecosystem
simulation models evaluated with these and other data.
The conceptual model shown in Figure 4 was developed as
an overview to show the relation of the main energy
exchanges with the outside, and of the main storages
of the inner bay ecosystem among themselves. Simpler
models which aggregated the main stocks and processes
were simulated on an analog computer.
Total community metabolism was determined from
diurnal changes in free-water oxygen concentrations
and was used as an indication of the ability of the
40
ecosystem to process the energies available to it.
Comparison of metabolism of the thermally affected
area with areas away from the influence of the power
plants indicated the degree to which these processing
abilities had been altered. Measurements were taken
from June, 1972 through May, 1974 representing all
seasons and establishing general seasonal trends of
metabo1ism.
Efforts using bottle experiments were made to
partition total metabolism between its planktonic and
benthic components. Measurements were made of penetra
tion of light through the water column.
Models were evaluated with data obtained in this
study and gathered concurrently by other researchers,
with other supporting measurements, information from
the literature, and some necessary calculations and
assumptions. These models were translated directly into
a set of differential equations, which were programmed
for analog computer simulation. Simulation runs were
made with coefficients set for conditions with and without
the influence of the power plant. Results were compared
to the observed data. Sensitivity of the models was
examined with respect to changes in water temperature
and ratios of discharge canal water to offshore water
mixing on the inner bay. Finally, simulations were run
with conditions expected when the new power plant begins
operation.
METHODS
Metabolic Measurements
Community metabolism was measured with diurnal
sampling of oxygen following Odum and Hoskins (1958),
Odum and Wilson (1962), and Odum (1967), and an abbrevi
ated method using dawn-dusk-dawn oxygen samples (McConnell,
1962). Oxygen was measured by the azide modification of
the Winkler technique (Amer. Publ. Health Assoc., 1971),
but adapted for use with smaller sample collection
bottles.
M i n i W1 n k 1 e r Field Kit and Winkler Method
Modification
Because of the large number of samples to be
processed and the need for compactness, a mini-Winkler
field kit developed at the University of Texas Institute
of Marine Sciences was used in this study. Standard
flat-topped 125-ml reagent bottles were used for sample
collection in place of 300-ml BOD bottles. Samples were
fixed with 0.5 ml of manganous sulfate and azide reagent
carried in dropping bottles in the field kit. After
41
42
acidification with 0.5 ml concentrated sulfuric acid,
100-ml subsamples were titrated with 0.012 N sodium
thiosulfate. This normality allowed direct reading of
milliliters of titrant as mg/1 of oxygen.
Variability between replicate pairs of oxygen
samples could have arisen from many sources. Since the
small reagent bottles used were inexpensive, variation
in their individual volumes was expected. A test of a
54-bottle subsample of those in use gave an average
volume of 122.8 ml with a standard error of 0.22.
Because each bottle was filled from a separate sample
of bay water taken 30 seconds to one minute apart, vari
ations due to water mass differences could also have
occurred. Other sources of variation could have included
differences in reagent volumes added and differences in
sample volumes titrated.
Actual differences in titrant volume encountered
between replicate pairs of samples were small, however.
Based on a subsample of 486 replicate pairs, 72.6 percent
differed by 2 drops (0.1 ml) or less. Since titrant
volume was generally in the range of 4-8 ml, this gave
an average error of 1.3-2.5 percent. Loss of accuracy
due to increased sources of variability was, therefore,
considered minimal, and was far outweighed by convenience
in handling in the field. More samples could be processed,
permitting better estimates for the whole bay.
43
Significance of Delay in Fixing Winkler Bottles
with Acid
A test was made of the effect of an eight-hour
delay in adding acid to the sample bottles in the Winkler
analysis of oxygen. Thirty bottles were filled with
thoroughly mixed salt water from a bucket, and immediately
fixed with the manganous sulfate and azide reagents. Ten
bottles were picked at random, acidified, and titrated
within 30 minutes. The remaining bottles were split
into two groups, one group of 10 bottles receiving acid,
while the other did' not. Both groups were stored in the
dark for eight hours. At the end of that time, acid was
added to the bottles which had not received it earlier,
and both groups were titrated. Table 1 gives the results
of the three treatments. Differences between treatments
were significant (95% level), but were considered too
small to have any significant effect on the measurements.
Complete Diurnal Sampling of Oxygen
The calculation of total community primary pro
duction and respiration from free-water measurements
of oxygen is based on the model given in Figure 8.
As indicated, the oxygen concentration in the water
column at any moment and changes in concentration with
time are a function primarily of the production of oxygen
during photosynthesis, its consumption in respiratory
44
Table 1. Results of a technique test of the Winkler
method to determine the effect of the
presence or absence of acid in fixed bottles
which have been stored for eight hours before
titration. Each treatment contained 10
bottles. Results are given in milliliters
of titrant.
Bottles fixed,
Bottles fixed and
Bottles fixed
acidified, and
acidified immedi-
immediately;
titrated
ately; titrated
acidified and
immediately
8 hours later
titrated 8 hours
later
Average
5.45
5.43
5.48
Std. Error
0.02
0.01
0.01
Figure 8. Model of factors affecting oxygen dynamics
in water.
46
47
processes, gains or losses because of advective exchange
with adjacent water masses, and diffusive exchanges with
the atmosphere. The contribution to oxygen dynamics of
the nonbiological processes of advection and diffusion
may be corrected for if their magnitudes are known or can
be estimated. Subtracting their effect allows a calcu
lation of changes resulting only from the biological
processes of photosynthesis and respiration, and, thus,
a calculation of production and respiration.
After correcting for diffusion and advection,
any gain in oxygen concentration during daylight hours
would be a consequence of the greater production of oxygen
in photosynthesis than its concurrent use in respiration,
thereby providing a measure of net primary production.
At night, when there would be no production of oxygen
by photosynthesis, the rate of oxygen decline would be
an estimate of community respiration. By assuming a
similar respiration rate for daylight hours (which would
be a conservative assumption), an estimate of the rate
of gross primary production may be obtained by adding
daytime photosynthesis and night respiration.
Stations were sampled approximately every three
hours over a 24-hour period. Two buckets of surface
water were collected 30 seconds to one minute apart at
each station, and sample bottles were filled from the
bottom by siphoning through rubber tubing. Late night
48
samples were sometimes stored without acidification for
titration the following morning (see above for effect
on Winkler analysis). Time, temperature, salinity, and
depth were noted at each station.
Because of the large tidal flushing, advection
of water masses from outside areas was at first thought
to be important. In order to assess this effect on the
diurnal oxygen curve in the study areas, four or five
stations were sampled in the early part of the project.
Analysis indicated a general similarity in the daily
increase and decrease of oxygen at all stations, sug
gesting that advection was from areas of similar metabo
lism. Thus, errors introduced by advection were thought
to be small, and the number of stations was usually re
duced to two or three to meet field schedules.
Diurnal metabolism graphs were constructed using
a standard format (Figure 9) to allow easy visual com
parison among all diurnal samples taken at Crystal River
as well as with others in the literature (Odum and
Hoskins, 1958). The data were analyzed several different
ways as the study progressed. At first, a graph for each
station was plotted and analyzed separately. Later, all
points from separate stations were plotted on one graph,
but only the mean curve was analyzed (Figure 9). Each
oxygen point was the average of duplicate Winkler
analyses. Oxygen per square meter (Figure 9c) was
Figure 9. Example of graphical format for calculation of
community metabolism at Fort Island, 24-25
August, 1973, using full diurnal curve of oxy
gen. Open circles represent average of measure
ments at four stations, each of which are shown
as solid points. (See text for detailed dis
cussion of [g] and [h].)
(a) Oxygen concentration.
(b) Depth.
(c) Areal oxygen obtained by multiplying (a)
and (b).
(d) Temperature.
(e) Salinity.
(f) Percent saturation of oxygen calculated
using oxygen values in (a).
(g) Rate-of-change of oxygen. Dotted line is
rate-of-charige of (c). Solid line with
solid dots ( ) is rate-of-change cor
rected for depth changes. Solid line with
open circles (o o) is rate-of-change
curve corrected for diffusion using coef
ficient values given across the top of the
diagram. Units of diffusion coefficients
are g02/mVhr./100% deficit.
(h) Rate-of-change of oxygen. Solid line with
solid dots ( ) is rate-of-change of
(a) multiplied by average depth at each
hour. Solid line with open circles
(o o) is curve corrected for diffu
sion using same coefficients as in (g).
TIME OF DAY
PERCENT
SALINITY,
SATURATION
PPt
150
100
16
14
12
10
TEMPERATURE,
C
ro m w
CO O
OXYGEN
QUANTITY,
g 0z/m2
OXYGEN
DEPTH, CONCENTRATION,
m. g Oz//m^
OXYGEN RATE-OF-CHANGE OXYGEN RATE-OF-CHANGE
51
TIME OF DAY
Figure 9 continued
52
obtained by multiplying oxygen concentration (Figure 9a)
by depth at that time. Percent saturation (Figure 9f)
was calculated for the temperature and salinity at each
time using the formula of Truesdale e_t a_l_. ( 1 955). The
divergence of Truesdale's saturation values from those
presented in Standard Methods (Amer. Publ. Health Assoc.,
1 955 ) was reviewed by Churchill et_ aK ( 1 962), who showed
deviations at temperatures less than 25C. Maximum
deviations, however, were less than 5% of the values
from Standard Methods, so the errors incurred in this
study by using Truesdale's values were considered small.
An oxygen rate-of-change curve (Figure 9g) was
constructed from the graph of average oxygen per square
meter. The amount of change of oxygen during each hour
was measured and plotted on the half hour. This raw
curve reflected changes in oxygen concentration under
one square meter due to changing depth from tidal exchange
and diffusive exchange with the atmosphere, as well as
photosynthesis and respiration. The effect of changing
depth was eliminated by multiplying the incremental depth
change for each hour by the average oxygen concentration
during that hour. This value was added to the rate
curve if the tide was falling or subtracted if the tide
was rising.
The final adjustment to the rate-of-change curve
was for oxygen lost or gained by diffusion between the
53
water' and atmosphere (see more complete discussion on
page 62). In general, in the discharge bay only a falling
tide from a high high to a low low stage had a sufficient
current producing a diffusion rate large enough to make
an appreciable correction in the metabolism calculation.
Both rising and falling tidal current velocities were
greater in the control areas making diffusion corrections
more important at all tidal stages. For daytime net
photosynthesis the average difference between the area
under the curves adjusted and unadjusted for diffusion
in the inner bay was 8 percent. At the Fort Island
control area it was 24 percent, while at Hodges Island
(only two measurements) it was 2 percent. Any diffusion
estimate that was incorrect for the discharge bay would
have a relatively small effect on the metabolism calcu
lation. At Fort Island the effect would be only somewhat
larger.
This laborious method was later modified; average
oxygen concentration, temperature, depth, salinity, and
percent saturation were plotted as before, but the
area-based oxygen curve was not calculated. The rate-
of-change curve (Figure 9h) was obtained by multiplying
the hourly rate-of-change of oxygen concentration by the
average depth at that hour giving the rate-of-change
on an areal basis. The adjustment for diffusion was
made as before.
54
In all methods the final rate-of-change graph
showed the rise of oxygen resulting from net photosyn
thesis during the day, and decrease because of respira
tion at night. Net daytime photosynthesis was taken as
the area under the rate-of-change curve above the zero
rate-of-change line. Nighttime respiration was taken
as the area under the rate-of-change curve below the
zero rate-of-change curve (Figure 9g and 9h).
Dawn-Dusk-Dawn Measurements
In order to gain more data as a check on day-
to-day variability of total metabolism and to reduce
the amount of field labor involved, the dawn-dusk-dawn
method (McConnell, 1962) was used after the first year.
The low point of oxygen at dawn, the high point at dusk,
and the low point the following dawn were measured as
a short-cut method of approximating the true diurnal
curve. Experience in the field showed that the time
of the minimum and maximum was not always at dawn or
dusk. Clouds in the east at sunrise tended to delay
the onset of rising oxygen by an hour or more. Simi
larly, afternoon thunderstorms often caused the downturn
of oxygen well before dusk. Even on clear days full
diurnal curves showed that oxygen concentration often
would not increase any more in the last two hours before
sunset. The times of dawn and dusk sampling, then, were
55
often adjusted to the prevailing conditions. Dawn
samples were delayed if the morning was cloudy in the
east. Dusk samples were generally taken about 1-1/2
hours before dusk.
Water samples were drawn, fixed, and titrated
as described before. Diurnal graphs of averaged data
were drawn in the same way as for full diurnals (Figure
10) but, of course, used only three points. Straight
lines were used to connect points for oxygen, tempera
ture, and percent saturation. Because depth was impor
tant to the metabolism calculation, the actual daily
pattern was estimated from the observed measurements
and the expected tidal amplitudes for the Crystal River
area published in the U. S. Department of Commerce
tide tables. Because the daily pattern of salinity
change was complex, no attempt was made to extrapolate
between the measured values.
With the three-point dawn-dusk-dawn method,
net production and/or night respiration would be under
estimated if the minimum and maximum points of oxygen
were not sampled when they occurred. The method also
used fewer replications so that any one unusual measure
ment would have a greater effect on the calculation of
metabolism. McKellar (1975) gives a more complete
discussion of errors associated with the method.
0600 1200 1800
OXYGEN RATE-OF-CHANGE,
g 02/ti2- hr
r -f-
p p o
ui b In
PERCENT
SATURATION
8
150
SALINITY,
ppt
TEMPERATURE, DEPTH, OXYGEN,
C m gOg/m3
Figure 10. Graphical format for calculation of community
metabolism using dawn-dusk~dawn data. Open
circles are the average of measurements at
individual stations indicated by solid dots.
Numbers across top of the rate-of-change
graph are diffusion coefficients.
58
An analysis of the difference in metabolism
estimates calculated by the dawn-dusk-dawn and full
diurnal curve methods is given in Figure 11. Data points
were read from a subsample of the graphs of full diurnal
curves of oxygen as if that day had been sampled by the
dawn-dusk-dawn method,and daytime net photosynthesis
and night respiration were calculated. Daytime net
photosynthesis would have been underestimated by the
dawn-dusk-dawn method three times in the inner bay by
an average of 33 percent and overestimated twice by a
small amount. Agreement was better at Fort Island and
Hodges Island but would have been over- or underestimated
by up to 25 percent.
Night respiration by the dawn-dusk-dawn method
was only an average of 58 percent of that calculated
by the full diurnal curve method in the inner discharge
bay. At Fort Island the three-point method was only
75 percent of the full curve method on three occasions,
while the full curve value was only 88 percent of the
three-point value two times.
McKellar (1975) for the outer discharge and
control bays at Crystal River found the dawn-dusk-dawn
method to underestimate gross production values (daytime
net production plus night respiration) usually by less
than 10 percent. The average difference between the
two methods was not significant at the 0.05 level.
Figure 11. Comparison of community metabolism estimates
obtained from complete diurnal measurements
of oxygen versus estimates obtained from
dawn-dusk-dawn calculations made using the
same data.
(a) Daytime net photosynthesis.
(b) Night respiration.
FULL DIURNAL CURVE, g 02/m day FULL DIURNAL CURVE, g 02/nrf day
60
INNER DISCHARGE BAY
0 FORT ISLAND
A HODGES ISLAND
"02468
DAWN-DUSK-DAWN, g 02/m2day
61
Eley (1970) found that dawn-dusk-dawn estimates averaged
91 percent of gross production and 87 percent of total
respiration in eight laboratory microcosms and 71 percent
of gross production and 52 percent of total respiration
in Keystone Reservoir, Oklahoma when compared to the full
diurnal curve analysis. In this study 61 percent of the
metabolism measurements from the inner bay and 68 percent
from the outer bay were made with the dawn-dusk-dawn
method. Since the apparent underestimation was largest
in the inner bay, these values may be conservative esti
mates.
Effects of Advection on Calculation of Metabolism
If an increase in oxygen occurred at night because
of advection, an artifact in the rate-of-change curve
was produced which made it appear as if photosynthesis
was occurring. Net production would be overestimated
because the nighttime gain in oxygen would be added to
the actual net production occurring during daylight hours.
Night respiration would be underestimated because the
area of positive oxygen gain would not be counted in the
calculation of respiration. By measuring this omitted
area, night respiration was found to be underestimated
by an average of 1.5 g/m^.day on the full diurnal curves
from the inner bay.
62
Light and Dark Bottle Measurements
Light and dark bottle studies were made in the
later stages of the project to estimate metabolic com
ponents of the water column as apart from the metabolism
of the sediments and larger consumer organisms. Bottles
(300 ml, BOD) were suspended at about 0.5 m depth by
small chains secured to a four-foot length of 3/4-inch
PVC pipe floated at each end by a plastic milk carton.
Generally, five replicates each of both light and dark
bottles were put out as soon as the dawn diurnal run
was completed, and picked up at the same time the follow
ing day. Fixation and titration were as in American Public
Health Association (1971), except that only a 100-ml sub
sample was titrated because of the 0.0125 N thiosulfate
used. The increase in the light bottle was taken as 24-
hour net production, the decrease in the dark bottle was
taken as 24-hour respiration, and the sum of the oxygen
gained plus that used up was taken as gross photosynthesis.
Other Field Measurements
Diffusion Mea su remen ts
At Crystal River the rate of diffusion of oxygen
into and out of the water column tended to be largely
a function of tidal current velocity. Diffusion was
measured at various stages of the tidal cycle using a
Figure 12. Example of two experiments to determine oxygen
diffusion coefficients by measuring the rate
of return of oxygen into a nitrogen-filled
dome floating on the water's surface. Line
through points was obtained by calculating
a linear regression. Meter was calibrated
to give a reading of 10 in air. Data obtained
at Fort Island study area.
63
small nitrogen-fi 11ed plastic dome, which floated on the
water surface (Hall, 1970, based on original work of
Copeland and Duffer, 1964). An oxygen probe measured
the return of oxygen into the dome from the water under
the normal conditions of underwater circulation. A
linear regression was calculated from the raw data.
Although the increase in oxygen in the dome is not
linear, the early response approximates a straight line.
2
The diffusion rate as g/m /hr/100 percent deficit was
calculated from the linear regression, area of water
surface covered, volume of the dome, and the observed
saturation value of dissolved oxygen in the water. This
was the maximum rate of diffusion into oxygen-free water
or out of water 200 percent saturated with oxygen.
Figure 12 shows a typical diffusion measurement.
Because of the small number of measurements
taken, assigning diffusion rates to time periods on
the graph was a combination of actual measured values
and estimates based on field experience with the general
magnitudes of tidal currents at different stages of the
tidal cycle in the study areas. The actual diffusion
correction for each hour was calculated by multiplying
the maximum rate selected for that hour by the actual
saturation deficit during that hour.
METER READING, PERCENT OF FULL SCALE
65
66
Light Penetration of the Water Column
Light penetration through the water column was
measured with a submarine photometer (Tsurumi Precision
Instrument Co., S/N 88130). Light intensity was mea
sured at 0.1-meter depth intervals from the surface
to the bottom and compared to a deck cell reading insola
tion incident to the water surface. Results were graphed
on semi-log paper (Figure 13). The extinction coefficient
was calculated was
In (I-,/I2)
where I-j was light intensity at the shallower depth
(Z-|) and Ig was light intensity at the deeper depth
(Z2). K was in units of meter-^.
Figure 13. Examples of submarine photometer measurements
of light penetration through the water column
taken at Fort Island away from the influence
of the power plant discharge plume and in
the inner bay influenced by the plume. Lines
through points were fitted by eye. k, extinc
tion coefficient.
DEPTH,
68
PERCENT OF SURFACE LIGHT INTENSITY
10 50 100
DATA ASSEMBLED FROM OTHER PHASES OF THE
CRYSTAL RIVER PROJECT AND ELSEWHERE
One of the major objectives of the overall
research program at Crystal River was to synthesize
the knowledge of the forcing functions outside of the
system and the storages and process operating within
the system. To this end, records of many of these
variables from other phases of the project and elsewhere
are included here to provide a total view of the estuarine
ecosystem. These data are used for obtaining values for
the model simulations and in determining if the simula
tion results are reasonable.
Energy Sources and Inflows
Affecting the Inner Bay
Seasonal and diurnal patterns of some of the
external factors shown in Figure 4 are given below.
S u n 1 i g h t
In Figure 14 is the average daily insolation by
month measured at Tampa, Florida, 97 km to the south of
Crystal River (Water Information Center, Inc., 1974).
69
Figure 14. Average daily insolation by month at Tampa,
Florida (Water Information Center, Inc.,
1974).
SOLAR INSOLATION, Kcal/rn2 -day
71
72
o
Peak insolation months (about 6000 Kcal/m -day) were
April and May at the very end of the winter-spring dry
season. Daily summer values were lower due to frequent
cloudiness from convective storms.
Wind Direction and Speed
Wind rose diagrams by season are given in' Figure
15 (Fla. Power Corp., 1972). Summer winds were pre
dominantly westerly and easterly as influenced by the
large-scale circulation about the shifting position of
the subtropical high-pressure system and by the more
local regional land-sea breeze system. With the change
in the fall and winter to weather patterns dominated by
frontal systems, the predominant wind direction shifted
to northerly directions. Average wind speed as given
in Table 2 (Fla. Power Corp., 1972) was lowest in the
summer and highest in fall and winter due to the strong
winds associated with frontal passages.
Ambient Air Temperature
In Figure 16 are monthly mean, mean maximum,
and mean minimum daily temperatures at Tampa, Florida
(Fla. Power Corp., 1972). Diurnal variation was smallest
during the summer months when the climate was primarily
under the influence of the subtropical high pressure
system, and frontal systems usually remained well north
Figure 15. Wind direction by season at Crystal River site.
Bars are percent of readings occurring from
each compass bearing (Florida Power Corpora
tion, 1972).
74
NENW
E W
E SW
DEC., JAN., FEB.
MAR., APR., MAY
JUNJUL., AUG.
SEP,OCT., NOV.
75
Table 2.
Seasonal comparison of average wind speed at
Crystal River site (Fla. Power Corp., 1972)
Season
Average wind speed, mph
Spring
11.1
Summer
9.5
Autumn
12.0
Winter
12.0
Annual average
11.4
Figure 16. Monthly mean air temperature at Tampa,
Florida (Water Information Center, Inc.
1974).
TEMPERATURE,
77
JFMAMJJY ASONO
73
of the area. Minimum temperatures dropped sharply in
October as cold fronts began penetrating into Florida,
and remained low through the winter when the climate was
characterized by cold air advection following frequent
frontal passages.
Precipita tion
Monthly mean precipitation at Tampa is presented
in Figure 17 (Fla. Power Corp., 1972). About 60 percent
of the yearly rainfall occurred from June through Sep
tember and was associated with showers and thunderstorms
in tropical air masses. During the extensive eight-month
dry period extending through May, precipitation was mainly
associated with frontal systems.
Stocks of the Inner Bay
Assembled below are data on stocks of organisms
and other quantities important within the inner bay
system.
Water Temperatures
Weekly average water temperatures at various
locations in the discharge canal, discharge study area,
and intake area during the course of this study are given
in Figure 18. Buoy locations are given in Figure 6.
Weekly average electricity generated by units 1 and 2
Figure 17. Monthly mean precipitation
Florida (Water Information
1974).
at Tampa,
Center, Inc.,
PRECIPITATION, inches
0010 a1
CO
o
81
and temperature rise of cooling water across the condensers
for unit 1 are shown in Figure 19. The average temperature
differential across the plant was about 5 to 6C, varying
somewhat with power plant operation. The seasonal ambient
water temperature cycle was indicated by a monitoring
buoy located at the Gulf end of the south intake dike
(Figure 18) and by water entering the intake pumps of unit
1 (Figure 19). For 1973 lowest temperatures of 12 to 15C
occurred in January and February rising through the spring
to a plateau of 28-30C in the summer months of June through
September. Rapid cooling began in October. Winter water
temperatures were generally higher during the mild 1973-74
winter. These data were very similar to monthly average
data for Cedar Key 25 miles to the north.
Discharge area temperatures (Figure 18) had the
same seasonal pattern as ambient areas, but with a con
sistent temperature increase due to the thermal plume.
Canal temperatures (buoys F and G) were about 5C higher
than ambient, corresponding to the average temperature
rise across the power plant condensers. Over the shallow
inner bay (buoys GA, GB, GC) the average temperature in
crease was only about 3C over ambient, indicating evapora
tive and radiative cooling and mixing with some ambient
water.
Average diurnal temperatures measured during com
munity metabolism studies are given in Figure 20.
Figure 18. Weekly averages of surface water temperatures
for the plume-affected inner discharge bay
and ambient water of the south intake area.
See Figure 6 for buoy locations. Bars super
imposed on ambient temperature record are
monthly means and extremes measured at Cedar
Key 25 miles to the north of Crystal River.
Gap in buoy record indicates lack of data
for that period at that, location.
TEMPERATURE
83
1972 1973 1974
TEMPERATURE
84
1972 1973 1974
Figure 18 continued
Figure 19. Weekly average of electricity generated by
power units at Crystal River, and weekly
average intake and discharge water temperature
for unit 1.
(a) Weekly average of electricity generated
by units 1 and 2.
(b) Weekly average intake and discharge
temperatures of water for cooling
pumped through the steam condenser
system for unit 1. Gap in record
indicates unit shut down for repairs
during that period.
ELECTRICITY GENERATED,
TEMPERATURE, C megawatts electrical
86
Figure 20. Average die! water temperatures measured during community metabolism
studies of the inner discharge bay and the Fort Island and Hodges
Island control areas. O Inner discharge bay; South intake
area.
1972 1973 1974
89
Patterns noted were similar to those discussed for
Figure 18.
Diurnal temperature patterns are given in Figure
21 for four days picked at random in late May, 1974.
Ambient daily change was about 3C. Canal temperatures
(buoy G) were about 5C above ambient but the pattern
was variable. Tidal effects were evident in the record
with buoys G and GD exhibiting opposite behavior. In
the canal (buoy G) surface temperature decreased at high
tide, probably as cooler offshore water flowed in over
the warmer but more saline and dense plume. At the north
boundary of the discharge bay (buoy GD), a rising tide
pushed warm plume water across the bay, which finally
reached the buoy sensor at full tide stage. The tempera
ture quickly dropped to ambient as cooler water from the
north flowed past on the falling tide.
The effect of plant load on temperature is ap
parent in the data pattern for May 26 and 27 when unit 1
went offline, while unit 2 continued to operate at a
fairly constant load factor (Figure 21). Since both units
continued to pump ambient water, the canal temperature
dropped several degrees because of dilution of the heat
from unit 2. Because of mixing and cooling the tempera
ture of the plume reaching buoy GD dropped closer to
ambient levels. Very little solar heating was evident for
May 27 because of the cloudy conditions for that day.
Figure 21. Diurnal patterns of electricity generated,
water temperatures at three locations, and
tidal stage in the discharge area of May 24-
27, 1974.
(a) Electricity generated (MWe) by units 1
and 2.
(b) Water temperatures at three locations
near the power plant at Crystal River.
Buoys G and G D were in the discharge
area. The buoy measuring amient water
was in the intake area (see Figure 6).
(c) Tidal stage in discharge area. Recorder
was located at the end of the bulkheaded
portion of the north discharge canal
spoil bank.
TIDAL STAGE, TEMPERATURE,C ELECTRICITY GENERATED,
meter units megawatts electrical
91
92
Salinity
Plotted in Figure 22 are average salinities
measured in the study areas during the community metabo
lism studies. Salinities were generally 5-15 parts per
thousand higher in the discharge area because of the
mixing of more saline discharge plume water with lower
salinity inshore water. At Fort Island salinities were
influenced by the freshwater discharging from the Crystal
River nearby. The study area at Hodges Island was away
from the influence of freshwater sources and had salini
ties similar to the discharge bay.
Variations in salinity with the tidal cycle may
be noted from the graphs drawn as part of the community
metabolism studies (Appendix B). In the discharge bay
salinity varied depending on the tidal stage and its
influence on the mixture and position on the bay of the
more saline discharge plume and less saline ambient
water. At Fort Island variations in salinity with the
tidal cycle were large. On a falling tide fresher water
from the Crystal River flowed over the study area; on a
rising tide it was replaced by saltier water from further
offshore. At Hodges Island very little variation was
encountered.
Figure 2 2. Average salinities measured on the inner discharge bay and Fort
Island and Hodges Island study areas during the community metabolism
studies. O Inner discharge bay; South intake area.
1972
1973
1974
95
Benthic Macrophytes
Seasonal patterns of biomass of benthic macro
phytes in the thermally affected inner bay and the in
shore portion of the south intake area are given in
Figure 23 (Van Tyne, 1974). Each point represents the
average 50-150 quarter square meter samples harvested
using a hand-held dredge with an attached 1/16-inch
mesh nylon bag. Total biomass in the intake area was
generally 1.5 to 2.5 times that on the inner bay area.
The seasonal pattern in both areas was similar, with
highest values in the spring and summer and lower values
in the fall and winter. The very low values for fall in
the inner bay may be anomalous (see Van Tyne, 1974).
Figure 23b, which breaks down the total of
Figure 23a into the contributions of seagrasses and
macroalgae, indicates that macrophyte biomass in the
inner bay was composed almost exclusively of the seagrass
H^. w r i g h t i i Macroalgae were dominant in the south
intake area composing about 70 to 75 percent of the total
biomass at all times of the year.
Seasonal biomass of macroalgae by taxon is
given in Figure 23c for the south intake area. Seasonal
switching of biomass dominance may be evident, with red
algae most important in the spring, reds and greens
about equally important in the summer, and reds and browns
dominating in winter with its lower light intensities.
Figure 23. Seasonal patterns of benthic macrophytes in
the thermally affected inner bay and inshore
portion of the south intake area. Sp, spring;
S, summer; F, fall; W, winter (data from
Van Tyne, 1 974 ).
(a) Total macrophyte biomass on the inner
bay and south intake areas.
(b) Biomass of seagrasses and macroalgae
in the inner bay and south intake
areas.
(c)
Biomass of red, green, and brown
macroalgae in the south intake area.
97
£
o>
CO
CO
<
o
m
98
A map of summer standing crop of attached macro
phytes for both the discharge-affected areas and the
unaffected south intake area is given in Figure 24.
Distribution of macrophytes on the inner bay (almost
exclusively jl. wriqhtii--see above) was confined mostly
to the western two-thirds of the bay. The shoreward
portion was devoid of attached macrophytes and was
the area most immediately affected by the heated effluent
from the discharge canal on the rising tide. No con
spicuous and widespread bare areas are noted on the south
intake area.
Diversity of macrophytes was measured by calcu
lating an average number of species per sample (Figure
25). Total macrophyte diversity (Figure 25a) was low
in the inner bay, with less than two species encoun
tered on an average square meter of bottom sampled.
Diversity on the south intake area was two to seven
times larger with six to eight species per square meter
of sampled area.
Total diversity has been broken down into its
seagrass and macroalgae components in Figure 25b. The
complete dominance of the inner bay by FL wriqhtii
and the lack of macrophytic algae are emphasized by
this plot. Seagrass diversity was larger on the south
intake area (1-2), but much less than the macroalgae
diversity (4-6).
Figure 24. Map of summer standing crop of attached macrophytic plants in the
region near the Crystal River power plants. Values are g/m^ and
are approximate. Cross hatching indicates areas devoid of
macrophytes (adapted from Van Tyne, 1975).
00 L
Figure 25. Seasonal diversity of benthic macrophytes
in the inner discharge bay and the south
intake area. See text for diversity calcu
lation. Sp, spring; S, summer; F, fall;
W, winter (data from Van Tyne, 1974).
(a) Total macrophyte diversity.
(b) Diversity of seagrasses and macroalgae.
DIVERSITY no. species/sample
SP S F W
Benthic Macroinvertebrates
Dry weight biomass of benthic macroinvertebrates
in the inner discharge bay and south intake area is given
in Figure 26 (Evink and Green, 1974). One-square-meter
areas were sampled with a Venturi pump arrangement and
filtered through a nylon mesh bag. Core samples were
also taken for small organisms missed by the Venturi
sample, but only several were sorted. These indicated
that the Venturi method was sampling only about one-half
the actual biomass. Biomass in the inner bay was lower
by a factor of four to ten. Seasonal variation in bio
mass was small in both areas. The low value measured
in the intake area in the November, 1973 samples may
have been anomalous.
Resident Fishes
Seasonal values of fish biomass caught with
dropnets in the inner bay and south intake area are
plotted in Figure 27. This technique was selective
for juvenile life stages and grass- and bottom-dwelling
species, and did not sample the more mobile species
such as sharks, mullets, jacks, and rays (Adams, 1974).
Seasonal biomass was very similar in the two
areas except for Fall, 1972, which represents a small
number of samples. A seasonal pattern was evident in
Figure 26. Seasonal record of biomass of benthic macro
invertebrates in the inner discharge bay and
south intake areas (data fron Evink and Green,
1974).
CM
e
\
%
>
v_
O
E
cn
CO
CO
<
o
GO
15
10
0
j t iiiiit] n,TrTTn",rr r
(ADAPTED FROM 1
EVINK AND GREEN,1974)
INTAKE AREA
1 I M I I It t M I 1 1 1 I I M 1
1973
1974
Figure 27. Seasonal record of biomass of fish caught with
drop nets in the inner discharge bays and
south intake areas. F, fall; W, winter, Sp,
spring; S, summer (data from Adams, 1974).
BIOMASS, gm dry-
1 07
C\J
F W SP S F W SP S
1972 1973 1974
108
both areas with the largest biomass in the spring and
summer and lower values in the fall and winter.
Nutrients
Nutrient data measured by Gibson (1975) at a
station in the south intake area and at the mouth of the
discharge canal are presented in Figure 28. No samples
were regularly collected in the inner discharge bay it
self.
Total organic carbon (Figure 28a) was very simi
lar at both stations during the periods studied, values
ranging generally from 3 to 8 ppm. No prominent seasonal
patterns were evident.
Seasonal measurements of PO^-P, NO^-N, and NH^-N
are presented in Figures 28b and 28c. Both stations
generally had similar levels of nutrients throughout
the measurement period except for NH^-N during June,
July, and August, which was two to nine times more
abundant in the south intake area during those months.
Seasonal patterns were also similar for both
sampling stations. Nitrate and phosphate were less
than 50 ppb and usually less than 20 ppb from November
through May. Phosphate increased in June, decreased
below detectable limits in the July samples, but in-
creased to very large values during most of August.
Nitrate also exhibited an increase to much larger values
Figure 28. Carbon, nitrogen, and phosphorus measurements
at the mouth of the discharge canal and a
station in the south intake area (data from
Gibson, 1975).
(a)
Total
organic carbon.
(b)
n3 -
mouth
N, NH3 N, and P04 P at
of the discharge canal.
the
(c)
NO. -
south
N, NH3 N, and PO^ P in
intake area.
the
parts per million
no
c
o
CD
Q.
1973 1974
parts per billion
Figure 28 continued
112
during July and August, returning to levels below 20 ppm
in late August and September.
Ammonia values were similar to nitrate and phos
phate at both stations through the fall and winter. In
late March or early April both stations exhibited a pulse
in abundance with values dropping back to levels somewhat
higher than previously through late April, May, and June.
The large increase which occurred in phosphate and
nitrate in July and August occurred for ammonia only at
the south intake station. Levels in both areas declined
in late August and September.
Chi orophyl 1-a, and Phytoplankton Biomass
Data on chi orophyl 1 -a_ and phytoplankton biomass
are presented in Figure 29 for stations in the south
intake area and at the mouth of the discharge canal
(Gibson, 1 975). Values of biomass and chi orophyl 1-a^
were similar at both stations throughout the sampling
period except for early April, when the discharge station
was considerably higher than the intake station.
Seasonal patterns of biomass and chlorophyll
were similar at both stations. The records of chloro
phyll and biomass tracked each other closely from sample
to sample. Low values were measured during the fall
and winter, being lowest in late December and early
January. A spring increase occurred during March, April,
Figure 29. Measurements of live ch 1 orophy 11 -a. and phyto
plankton biomass at a station in the south in
take area and at the mouth of the discharge
canal (data from Gibson, 1975).
(a) Live chi orophyl 1 -a..
(b) Phytoplankton biomass.
gm dry-wt/m3 parts per billion
114
NDJFMAMJJYAS
1973 1974
and May, being somewhat larger at the discharge station
than at the intake station. Low values were once again
measured during mid-July, but increased again during the
rest of the summer.
RESULTS
Given below are measurements and models done as
part of this phase of the Crystal River project.
Metabolism Measurements
All total metabolism measurements obtained by
the free water diurnal methods and water column metabo
lism as measured by light-dark bottles are given in
Tables 3 and 4 for the discharge bay and unaffected bays.
Graphs of all individual diurnal measurements are given
in Appendix B. Total metabolism measurements are plotted
graphically by date of measurement in Figures 30 and 31,
and combined and plotted on one 12-month graph in Figures
32 and 33. Seasonal averages are given in Figures 35 and
36.
Complete Diurnal Measurements of Oxygen
Twelve complete diurnal measurements of oxygen
for estimation of community metabolism were made in the
inner bay between June, 1972 and May, 1974 using one
to five sampling stations. Graphs of these data are
116
Table 3. Record of metabolism for the inner discharge bay as measured by diurnal
free water oxygen changes and light and dark bottles. Dates marked with
an asterisk were complete diurnal measurements. Unmarked dates were dawn-
dusk-dawn measurements.
P
R
Change
Change
Gross
Daytime Net
Night
in Light
in Dark
Produc-
Photosynthesis
Respiration
P + R
Bottles
Bottles
tion
Insolation
Date
g 02/m2-day
2
g O^/m -day
g O^/m2 -day
g/m2
g/m2
g/m2
2
Kcal/m -day
Winter:
Dec. 14-15, 1972*
2.3
2.7
5.0
Jan. 22-23, 1973*
1.8
1.3
3.1
Jan. 31-
Feb. 1, 1973*
1.2
3.6
4.8
Mean
1.8
2.5
4.3
Std. error
0.1
0.5
0.4
Spring:
May 10-11, 1973
4.8
4.3
9.1
May 11-12, 1973
2.9
3.3
6.2
May 24-25, 1974
2.6
1.1
3.7
6500
Table 3 continued
P
Daytime Net
Photosynthesis
R
Ni ght
Respiration
P + R
Change
in Light
Bottles
Change
in Dark
Bottles
Gross
Produc
tion
Insolation
Date
g 02/m2-day
g Og/m2-day
g 02/m2-day
g/m2
g/m2
g/m2
Kcal/m2. day
Sprinq (cont.):
May 25-26, 1974
1.7
0.7
2.4
6409
May 26-27, 1974
2.3
1.8
4.1
+1.2
-0.4
1.6
5834
June 14-15, 1972*
1.9
2.5
4.4
June 29-30, 1972*
2.3
2.6
4.9
June 17-18, 1973
3.2
2.4
5.6
June 17-18, 1973*
5.4
4.8
10.2
June 18-19, 1973
2.1
0.9
3.0
June 19-20, 1973
0.0
1.3
1.3
June 20-21, 1973
2.4
1.9
4.3
+2.5
-2.2
4.7
June 21-22, 1973*
1.0
3.0
4.0
June 22-23, 1973
1.0
1.2
2.2
Mean
2.4
2.3
4.6
1.9
1.3
3.2
Std. error
0.1
0.1
0.4
0.4
0.8
2.4
Table 3 continued
Date
P
Daytime Net
Photosynthesis
?
g 02/m -day
R
Ni ght
Respiration
2
g O^/m day
Summer:
July 7-8, 1972*
6.3
4.5
July 26-27, 1973
3.5
2.6
Aug. 2-3, 1972*
4.4
4.5
Aug. 2-3, 1973
0.9
1.3
Aug. 22-23, 1973*
1.1
2.3
Aug. 23-24, 1973
1.2
1.3
Aug. 24-25, 1973
1 .4
1.5
Aug. 25-26, 1973
0.1
2.3
Aug. 26-27, 1973
0.6
1.8
Aug. 27-28, 1973
1.1
2.6
Mean
2.1
2.5
Std. error
0.4
0.1
P + R
,/m2- day
Change
in Light
Bottles
g/m2
Change
in Dark
Bottles
g/m2
Gross
Produc
tion
g/m2
Insolation
2
Kcal/m day
10.8
6.1
+0.7
-0.3
1.0
6115
8.9
2,2
+0.5
-0.1
0.6
2889
3.1
2.5
+0.9
-0.4
1.3
2.9
2.4
2.4
3.7
4.5
0.7
0.3
1.0
0,9
0.01
0.01
0.04
Table 3 continued
Chage Change Gross
Daytime Net
Photosynthesis
Night
Respiration
P + R
in Light
Bottles
in Dark
Bottles
Produc
tion
Insolation
Date
g 02/m2;day
g 02/m2-day
g 02/m2* day
g/m2
g/m2
g/m2
2
Kcal/m -day
Fall:
Oct. 29-30, 1973
1.1
1.6
2.7
+0.5
-0.2
0.7
Oct. 30-31, 1973*
1.6
2.8
4.4
+0.5
-0.2
0.7
Oct. 31-
Nov. 1, 1973
+0.7
-0.2
0.9
3850
Nov. 1-2, 1973
1.3
2.2
3.5
+0.6
-0.4
1.0
4490
Mean
1.3
2.2
3.5
0.6
0.3
0.8
Std. error
0.02
0.1
0.2
0.003
0.003
0.006
Table 4. Record of metabolism for the Fort Island and Hodges Island areas away from
the influence of the power plant discharge as measured by diurnal free
water oxygen changes and light and dark bottles. Dates marked with an
asterisk were complete diurnal measurements. Unmarked dates were dawn-dusk-
dawn measurements.
Date
P
Daytime Net
Photosynthesis
2
g 02/m -day
R
Ni ght
Respiration
2
g 02/m -day
P + R
2
g 02/m -day
Change
in Light
Bottles
g/m2
Change
in Dark
Bottles
g/m2
Gross
Produc
tion
g/m2
Insolation
2
Kcal/m -day
Wi nter:
Feb. 13-14, 1973*
2.0
1.3
3.3
Feb. 22-23, 1973
1.5
1.7
3.2
Mean
1.8
1.5
3.3
Std. error
0.06
0.8
0.003
Sprinq:
May 25-26, 1974
5.4
4.5
9.9
+2.7
-0.8
3.5
6409
May 26-27, 1974
4.7
4.3
9.1
+2.5
-0.9
3.4
5834
June 25-26, 1973
1.9
3.1
5.0
-3.2
-5.2
2.0
3037
Table 4 continued
Date
P
Daytime Net
Photosynthesis
2
g 02/m -day
R
Night
Respiration
2
g 02/m -day
Spring (cont.):
June 26-27, 1973
5.1
5.4
June 26-27, 1973
6.2
5.7
June 27-28, 1973
5.2
5.8
June 28-29, 1973
5.6
5.0
Mean
4.9
4.8
St. error
0.3
0.1
Summer:
Aug. 02-03, 1972*
4.7
6.5
Aug. 16-17, 1972*
1.6
4.1
Aug. 10-11, 1972
2.6
3.4
Aug. 24-25, 1973*
4.0
6.2
Change Change Gross
in Light in Dark Produc-
P + R Bottles Bottles tion Insolation
2 2 2 2 2
g O^/m -day g/m g/m g/m Kcal/m -day
10.5
+1.1
-0.7
1.7
6543
11.9
6343
11.0
6144
ro
10.6
+0.9
-0.3
1.2
6648
r\}
9.7
0.8
1.6
2.4
0.7
1.1
0.8
0.2
11.2
5.7
6.0
10.2
Table 4 continued
Date
P
Daytime Net
Photosynthesis
2
g 02/m day
R
Night
Respiration
2
g O^/m day
P + R
2
g 02/m day
Change
in Light
Bottles
g/m
Change
in Dark
Bottles
2
g/m
Gross
Produc
tion
g/m2
Insolation
2
Kcal/m day
Summer (cont.):
Aug. 26-27, 1973
1.6
6.9
8.5
Aug. 27-28, 1973
3.8
7.3
11.1
Mean
3.1
5.7
8.8
Std. error
0.3
0.4
1.0
Fall:
Nov. 12-13, 1973
2.1
3.4
5.5
+0.2
-0.3
0.4
3100
Nov. 13-14, 1973
4.0
4.4
8.4
+0.3
-0.2
0.4
4140
Nov. 14-15, 1973
4.3
4.2
8.5
+0.2
-0.2
0.4
4280
Nov. 15-16, 1973
3.4
5.1
8.5
+0.3
-0.1
0.4
Mean
3.5
4.3
7.7
0.3
0.2
0.4
Std. error
0.2
0.1
0.6
0.001
0.002
0.0
1 23
Figure 30. Daytime net photosynthesis and night respiration in the inner dis
charge bay affected by the thermal plume and the Fort Island and
Hodges Island area away from the influence of the power plant.
O Inner discharge bay; Fort Island and Hodges Island areas.
1972 1973 B ¡974
NIGHT RESPIRATION,
gm 02/m2 day
DAYTIME NET
PHOTOSYNTHESIS,
gm 02/m2* day
I I I -j- + +
CD -P* ro o ro 4^
9 Z L
Figure 31. Daytime net photosynthesis plus night respiration as a measure of
gross primary production in the inner discharge bay affected by the
thermal plume and the Fort Island and Hodges Island areas away from
the influence of the thermal plume. Inner discharge bay;
O Fort Island and Hodges Island areas.
1972 1973 1974
DAYTIME NET PHOTOSYNTHESIS
PLUS NIGHT RESPIRATION,
grin 02//m2-day
o cn o
LZ L
Figure 32. All daytime net photosynthesis and night respiration values from
. Tables 6 and 7 and Figure 30 plotted on 12-month graph.
NIGHT RESPIRATION,
gm 02/m2-day
DAYTIME NET
PHOTOSYNTHESIS,
gm 02/m2- day
ill +* -i- -t*
(j> -p* ro o ro o
62 L
Figure 33. All daytime net photosynthesis plus night respiration values from
Tables 6 and 7 and Figure 31 plotted on 12-month graph.
JY A
DAYTIME NET PHOTOSYNTHESIS PLUS
NIGHT RESPIRATION, gm 02/m2day
L£ L
132
given in Appendix B. The range of diurnal oxygen change
was 2-7 ppm for summer samples (8 measurements) and 2-3
ppm for winter samples (3 measurements). In general,
the daily pattern of oxygen changes observed was similar
to that found by others elsewhere, with a gain in oxygen
in the water during the day from photosynthesis and a
loss at night from respiratory activity. The shape of
the oxygen curve for individual days, however, was in
fluenced by the timing of the tidal cycle. Large rapid
increases in oxygen were associated with times of lowest
water during daylight hours, while oxygen gains did not
occur or were much smaller during daylight periods of
highest water. Oxygen increases at night and downturns
of oxygen before dusk noted in some measurements were
associated with a rising tide and an increase in average
water temperature indicating some advection of water
from the discharge canal.
All graphs of diurnal measurements of oxygen
for estimation of community metabolism at Fort Island
south of the mouth of the Crystal River (5 measurements
representing an average of 1 to 5 stations) and Hodges
Island north of the Withlacoochee River (2 measurements
representing an average of 2 or 3 stations) are presented
in Appendix B. The range of diurnal oxygen change was
about 3 ppm in the summer (5 measurements) and about 1 ppm
in the winter (2 measurements). The tidal cycle did not
133
appear to be important in determining the shape of the
oxygen curve at Fort Island. Nighttime increases in
oxygen associated with a rising tide did occur at Hodges
Island indicating some advection of more oxygenated water
from offshore at that location.
To confirm the occurrence of a diurnal curve of
oxygen at the study sites, the average oxygen values from
all summertime diurnal measurements were plotted together
(Figure 34). Each plotted point represents the average
of duplicate oxygen determinations at 1 to 5 stations
taken at that time. Diurnal curves were obtained under
different tidal regimes and sunlight conditions. The
general trend of lowest oxygen near dawn, increasing
values during the day, and larger values near dusk was
evident.
Dawn-Dusk-Dawn Measurements of Oxygen
Dawn-dusk-dawn measurements of oxygen in the
Fort Island area and the inner discharge bay are included
in Appendix B. The general pattern of higher oxygen in
the afternoon and lower at dawn was evident in most
graphs .
Daytime Net Photosynthesis
Seasonal averages of daytime net photosynthesis
are shown in Figure 35 for the discharge and control bays.
OXYGEN, gO/m
1 3 5
CM
J
0
INNER BAY
* :
.
.
v
0600
1200
1800
TIME OF DAY
Figure 34. Average oxygen values from all summertime
diurnal measurements taken in the inner
discharge bay and Fort Island control bay.
136
The only significant seasonal variation was the lower
winter and higher spring production in the control areas.
Comparing the two areas showed that spring,
summer, and fall values of net production in the control
bays were generally 1.5 to 2.5 times those in the dis
charge area with almost identical values in the winter.
Spring and fall values were significantly different
between areas while winter and summer values were not.
Nighttime Respiration
Figure 35 has night respiration by season for
the control and discharge- areas. A marked seasonal
pattern was evident in the control area. The lowest
o
value (1.5 g O^/m -day) occurred in winter, increased
2
to 4.7 g O^/m -day in spring, reached its highest
2
value (5.7 g C^/m -day) in summer, and declined again
in the fall to 4.3 g (^/m^-day. t-tests (95% level)
showed that spring, summer, and fall were not signifi
cantly different from each other, while all were
significantly different from winter.
In the discharge area night respiration values
stayed almost constant, varying between only 2.2
2 2
g 02/m -day and 2.5 g 02/m -day over the four seasons,
t-tests showed no significant difference between any
season .
Figure 35. Seasonal averages of daytime net photosynthe
sis and night respiration in the inner
discharge bay and control areas. Bars about
points represent plus and minus one standard
error. Spring is defined as May and June
measurements, summer as July and August
values. W, winter; Sp, spring; S, summer;
F, fall.
day
138
VV SP S F
SEASON
139
Comparing the two areas in winter showed the
controls to be lower than the discharge bay but not
significantly different (95% level). During spring,
summer, and fall night respiration in the control bays
was larger and significantly different from the dis
charge bay.
Daytime Net Photosynthesis Plus Night Respiration
If daytime respiration was assumed to occur at
the same rate as nighttime respiration, then the sum of
daytime net photosynthesis and night respiration was a
measure of gross production. Figure 36 gives daytime
net photosynthesis plus night respiration (P + R) plotted
by season for the discharge and control bays. Average
P + R in the discharge bay showed virtually no variation
2
with season, remaining about 4 g O^/m -day. There was
no statistical difference between seasons (95% level).
The control bays showed a seasonal pattern of
average P + R, being lowest in winter (3.3 g 02/m -day),
o
highest in spring (9.7 g 0^-day), and declining some
in summer and fall. There was no significant difference
(95% level) between spring, summer, and fall values,
but they were all significantly different from the
winter value.
Average winter P + R in the control area was
slightly lower than that of the discharge bay but the
gu re 36. Seasonal averages of daytime net photosynthe
sis plus night respiration as a measure of
gross primary production for plume-affected
inner bay discharge area and unaffected con
trol areas. Bars about points represent plus
and minus one standard error. W, winter;
Sp, spring; 5, summer; F, fall.
141
>
O
O
(M
E
E
m
142
difference was not significant at the' 95% level. Control
area values were significantly larger (95% level) during
spring, summer, and fall than those measured in the dis
charge area.
Ratio of Net Photosynthesis to Night Respiration
Seasonal trends in the ratio calculated as daytime
net photosynthesis divided by night respiration (P/R
ratio) for the inner discharge bay and control areas
at Fort Island and Hodges Island are given in Figure 37.
This ratio can indicate to what extent the excess of
organic material accumulated above respiratory needs
during the day satisfied the nighttime respiratory re
quirements. In the discharge bay the ratio was less
than one except in the spring, being lowest in the fall.
In the control areas the ratio was considerably greater
than one in the winter based on only two measurements,
declined to about one in the spring, and fell below one
for summer and fall. The ratio was lowest in the summer.
Metabolism of the Water Column
Light and dark bottle measurements of water
column metabolism excluding larger organisms are given
in Tables 3 and 4 for the discharge bay and control
bays. In the discharge bay seasonal water column gross
Figure 37, Seasonal trends of the ratio of daytime net
photosynthesis divided by night respiration
for plume-affected inner bay area and
unaffected Fort Island and Hodges Island
areas. W, winter; Sp, spring, S, summer; F,
fall .
SEASON
DAYTIME NET PHOTOSYNTHESIS
NIGHT RESPIRATION
P
en oi
145
2 2
production ranged from 3.2 g O^/m -day to 0.8 g 02/m -day,
being highest in spring (two measurements), and consider
ably lower in summer and fall. In the control areas
2
the average value ranted from 2.4 g 02/m -day to 0.4
2
g 02/m -day and was also highest in spring and lower in
the fal1.
Plankton production was a larger portion of
total production in the discharge area than in the con
trol areas, ranging from 70 percent of total production
in the spring to about 23 percent in the summer and fall.
In the control area it was 25 percent in the spring and
5 percent in the fall.
Diffusion Measurements
Results of diffusion measurements made in the
discharge bay and the Fort Island control area are given
in Table 5. Values measured in the discharge bay under
different current velocities and wind conditions ranged
from 0.13 to 0.78 g 02/m^/hr/100 percent deficit. Values
2
averaged 0.44 g 02/m /hr/100 percent deficit when currents
were largest (falling tide from high high to low low
stage), and were lower at slack tide (0.13 g 02/m /hr/
100 percent deficit). A measurement during moderate
currents but brisk wind gave the largest value of 0.78
g 02/m^/hr/l00 percent deficit.
Table 5. Diffusion
areas.
rates measured
in the power plant
discharge and Fort
Island study
Diffusion Rate
Location
Date
Tidal Stage
Wind g
Og/m^/hr/l00% deficit
Discharge Bay
Oct. 10, 1972
Falling Low high
to high low
Brisk
white caps
0.78
Discharge Bay
June 28, 1973
Falling High high
to low low
Brisk
0.53
Discharge Bay
July 26, 1973
Falling High high
to low low
Moderate
0.54
Discharge Bay
September 12,
1973
Slack high tide
Calm to light
0.13
Discharge Bay
September 12,
1973
Falling High high
to low low
Calm
0.24
Discharge Bay
September 12,
1973
Falling High high
to low low
Light
0.44
Fort Island
June 24, 1973
Rising, low low
to low high
Light
0.55
Fort -Island
June 25, 1973
Falling High high
to low low
Li ght
1.60
146
147
Measurements at Fort Island generally were larger
possibly because of the stronger currents there. A strong
2
falling tide gave the high reading of 1.6 g Og/m /hr/
100 percent deficit, while a more moderate rising tidal
2
current gave a lower value of 0.55 g 02/m /hr/100 percent
deficit.
Light Penetration of Water Column
Given in Table 6 are light extinction coefficients
calculated from submarine photometer readings from the
inner discharge bay and the Fort Island and Flodges Island
areas away from the power plant. The clearest water
occurred at the Fort Island area, possibly as a result
of the influence of the nearby discharge of the excep
tionally clear Crystal River. The large extinction
coefficient at Hodges Island was possibly a result of
the discharge of the colored water of the Withlacoochee
River about 3 km to the south.
Turbidity contributing to the large extinction
coefficient in the inner discharge bay was contributed
by the water from the power plant discharge canal. On
high tides the delineation between the more brownish-
yellow discharge plume water and somewhat clearer water
mass from a previous tide was occasionally quite distinct
to the eye.
148
Table 6. Average extinction coefficients for light
penetration of water on the inner discharge
bay affected by the power plant discharge
plume and unaffected areas to the north and
south. Units are meters-!.
Area affected by
Area not affected by
discharge plume
discharge plume
Inner discharge bay
Fort Island^
Hodges Island0
1.49
Range (1.15-1.7)
0.90
2.00
Range (1.86-2.28)
3
Eight measurements.
^Two measurements. Both were 0.9.
r
Three measurements
149
Model Diagrams for Comparing Ecosystems
Affected and Unaffected by the Discharge Plume
Figures 33 and 39 summarize knowledge gained
of the inner bay receiving the thermal discharge from
the power plants and the unaffected inshore ecosystem
nearby. Values given are only ones actually measured
at Crystal River or estimated from measured values.
Documentation and calculation of numbers are given in
Appendix E. A somewhat simpler model, which has been
completely evaluated for the inner bay for purposes of
computer simulation, is given in Figure 55.
The ecosystem that had developed in the inner
discharge bay under the influence of the power plant
discharge was one of lower diversity, lower summer com
munity metabolism, and lower standing stock of some
compartments than the adjacent unaffected area. Biomass
of benthic producers in the intake area was only about
66 percent of that in the discharge area. Benthic inver
tebrate biomass in the discharge area was only 25 per
cent of that in the intake area. Total oyster reef bio
mass (Lehman, 1974a,b) and resident fish biomass was
similar in the two areas, although fewer fish were caught
in the warm months in a tidal creek adjacent to the inner
bay than one adjacent to the intake area (Homer, 1975).
Nutrients were very similar between the two areas.
Lehman ( 1 974a,b) found diversity of oyster reef
Figure 38. Summary energy diagram of summer stocks of biomass and material
and flows of energy and organic matter for the inner discharge
bay. Values given are only ones actually measured at Crystal
River or readily estimated from measured values. See Appendix
E for documentation or calculation of numbers. Stocks are in
g/m^, of organic matter or material, flows in g/m^.day of or
ganic matter or kcal/m^-day of sunlight.
OYSTER
REEFS
OFFSHORE
WATER
PHOSPHORUS 'r
vV J PHOSPHORU
VN^ V
2.56
Figure 39. Summary energy diagram of summer stocks of biomass or material
and flows of energy and organic matter for the south intake
area away from the influence of the power plant discharge.
Values given are only ones actually measured at Crystal River
or readily estimated from measured values. See Appendix E
for?documentation or calculation of numbers. Stocks are in
g/m- of organic matter or material, flows in g/m^.day of
organic matter or kcal/m^-day of sunlight.
153
macroorganisms to be lower in the discharge area. Biomass,
however, was similar in both areas. Fewer species of
fish were caught with drop nets in the discharge bay than
in the intake area (Adams, 1974).
Simulation Model of Diurnal Properties
of the Inner Bay Ecosystem
Shown in Figure 40 is a model simplified from
Figure 4, which emphasizes the diurnal aspects of the
flows and storages of the inner discharge bay. This
model was simulated to help in determining the consis
tency of the diurnal measurements of oxygen in the
presence of advection and to test the effects of power
generation operations on the diurnal properties of the
inner bay. Table 7 gives the equations derived from the
diagram. Calculations of transfer coefficients, scaling,
pot settings, and other model functions are given in
Appendix C.
Photosynthetic production in this model was
limited to benthic plants. Phytoplankton were omitted
for simplicity because their contribution to total
photosynthesis during the summer at Crystal River was
small. Light was captured as a function of temperature
and phosphorus after being attenuated in proportion to
Figure 40. Energy diagram for simulation model of inner discharge bay
emphasizing the diurnal properties of the system. Switch
labeled R is open only on a rising tide; switch marked F is
open only on a falling tide. See Appendix C for calculation
of values given on diagram. See Table C-l and C-4 for for
mulae used for radiative and evaporative heat losses from
water, for heat gain from atmospheric back radiation, and
diffusion of oxygen. Unless otherwise noted, flows are
g/m^-day and storages are g/m^ of organic matter or material.
22 R
0.036
J2J^
5^0133
MATTER/ ^EAy X
\ /^k
\ nYVPPMi {TOTAL
^OXYGEN/ ^PHOSPHORUS
OFFSHOREVN^/
cn
cr>
Table 7. Differential equations for diurnal model of inner bay given in Figure 40.
dQ.
dt
P,V 2 PV
u + (i/ A..
K14 3 lK22R 3
- k
Q1V
22F D
^ + k23^6T^3 + k24^7^3T + k27^3T
- k
J Q,T
ovl
13 kR + k^T
dQ
2 (H + C)V T 2HV v<2
QqV
dt kl5 3 J30 + ^k21R 3 "21F D
) k25 (0.97a T ) k2g( 595.9 0.54T)
CJ1
dQ o X,V
9. k _L_
dt k16 3
+ (k
2 X 2 V
20R 3~
Qov
. y ) + i/
'20F D ; K3
J Q, T
oy 1
kR + klQlT
" k12Q6TQ3
k18Q3Q7T k28Q3T
Table 7 continued
= t M,V 2 M0 V
dt 17 ~T~ + k7Q5 ^ k19R 3~
121 = k6Q6TQ3 k7Q5
dQfi JQ,T
= i/ Q 1 b n Tf)
dt k2 kR + k, Q i T k4VQ3
dQ
dt~ = k9Q4q 7
k8Q7Q3T
kl1Q7Q4
V
' 1 9 F D
+ k10Q 7Q4
1 58
1 59
depth, producing oxygen and labile sugars. The sugars
were respired as a function of temperature and oxygen,
some being fixed into structural biomass, but most being
degraded to heat and inorganic nutrients.
All consumers were lumped into one compartment
because changes in biomass were not believed important
on a diurnal basis. Consumers fed on the pool of organic
matter in the water column, assimilating some into
biomass and returning the rest to the organic pool as
feces and pseudofeces. Respiration was modeled as a
multiplicative function of temperature and oxygen.
A storage of bottom organic matter was omitted
from the model because its large quantity precluded any
significant change diurnally. However, benthic microbial
respiration associated with these sediments was large
and was modeled as a function of oxygen and temperature.
Within the water on the inner bay are shown
storages of heat, total phosphorus, oxygen, and organic
matter. All were exchanged tidal 1y with discharge canal
and offshore water. For lack of specific data, one-third
of the water contributed to the inner bay on a rising
tide was assumed to come from the discharge canal and
two-thirds from offshore. On a falling tide, these flows
stopped and water on the inner bay was transported off
shore. Water in the model itself had no interaction
with anything else other than as a vehicle for transporting
I DU
material. Because of this it was omitted and treated
as a forcing function of volume exchange, bringing the
phosphorus organic matter, heat, and oxygen carried in
the water onto or carrying it off the bay. Volume ex
change was derived from the tide table and programmed
on a function generator. The tidal state (rising or
falling) operated switches determining whether materials
were carried on or off the bay.
Phosphorus was taken up in photosynthesis and
returned to the water column once again from all respira
tory pathways. Oxygen was released into the water column
by photosynthesis and removed by all respiratory functions
and the dark reactions of photosynthesis. Because of
equipment constraints, diffusive oxygen exchange with the
atmosphere was programmed as an average daily constant
function rather than varying with current velocity.
Heat losses through radiation and evaporation were
programmed as empirical functions of temperature, obtained
by dividing heat storage by depth. The heat content of
the evaporated water and heat lost by convection were
omitted because they were small in comparison to the losses
from radiation and the heat flux associated with change
of state in evaporation (see Table C-4).
Sunlight was programmed as part of a sine wave to
make a 14-hour day. The tidal cycle was obtained by draw
ing a smooth curve through the actual depth measurements
161
obtained during the sampling of diurnal metabolism for June
21-22, 1973. The rate-of-change of this graph was the
2
volume exchange rate for 1 m This function was programmed
as closely as possible on a function generator and the out
put integrated to obtain the volume of water on the inner
2
bay at any moment. Since this is a model of 1 m of inner
bay, water volume was also depth. The output of the func
tion generator and its integrated value along with the
actual measured points for June 21 are given in Figure 41.
Tidal stage was derived from the volume exchange
rate function, which was positive on a rising tide and nega
tive on a falling tide. A comparator sensed this polarity
and activated the proper switches controlling flows asso
ciated with each tidal stage. Since the computer patching
using the output of the volume exchange function required
positive values only, an absolute value circuit was em
ployed to convert the output (Figure 41b).
Offshore oxygen concentration (McKellar, 1975)
was programmed as a sine wave with a low point at 0600
of 6 g/m^ and a high point at 1800 of 8 g/m^ (Figure 43d).
Offshore (McKellar, 1975) and discharge water temperature
were programmed the same way, varying from 27C to 30C
for offshore water and 32C to 35C for discharge water
(Figure 41c). All other forcing functions were held
constant.
Figure 41. Computer plots of forcing functions of tidal
volume exchange, depth, offshore oxygen, and
offshore water temperature used in the diurnal
simulation model (Figure 40).
(a) Output of function generator programmed
with volume exchange rate calculated for
the tidal cycle in the inner bay on
June 21-22, 1973.
(b) Output of function generator with nega
tive portions converted to positive
with an absolute value circuit.
(c) Water depth obtained by integrating the
volume exchange rate of (a). Actual
data points measured on the inner bay
on June 21-22, 1973, are indicated for
comparison.
(d) Oxygen concentration in offshore water.
(e) Temperature of offshore water. This same
curve raised 5C was also used as the
forcing function for discharge canal
water temperature.
ppm m m
163
10
1 1 r
-(d) OFFSHORE OXYGEN (X2)
0
40
o 20
1 1 1
(e)OFFSHORE TEMPERATURE (H)
JL
0600 1200 1800
TIME OF DAY
1 64
Model Output with Initial Scaling
The diurnal model was run as initially scaled
to observe its general behavior and properties (Figure
42). Pot settings are given in Appendix C, Table C-8.
The daily course of insolation was a sine wave
with a sunrise at 0500 and sunset at 1900, providing
2
a total of 5938 kcal/m for the day, typical of a bright,
sunny day at Crystal River. Sunlight actually reaching
the benthic plants on the bottom was less because of
extinction by the water column. Oxygen in the water
column exhibited a typical diurnal pattern, being lowest
at dawn, rising rapidly in the morning hours immediately
after sunrise to a high point about 1300, and dropping
slowly through the afternoon. Fit was reasonable with
summer oxygen values actually measured in the inner bay.
The rate of gross primary production was limited
after about 1000 by the rapid decline in phosphorus as
it was taken up in photosynthesis. The area under the
production curve was the daily gross primary production
2
and equalled 5.4 g/m somewhat higher than the summer
2
mean of 4.5 g/m -day, which included measurements on
cloudy and clear days.
The dual peaks of total respiration resulted
from respiration being a function of temperature and
total oxygen in the water column. Increasing depth on
Figure 42. Simulation results of diurnal model of inner
bay (Figure 40) with coefficients set as
originally scaled. Independent points plotted
on the graph of oxygen are all summertime
oxygen values measured in the inner bay during
complete diurnal metabolism sampling runs.
Each point is the average of two to ten
individual measurements.
Kcal/m HR
cn
ui
H
UJ
2
600 ¡200 1800
CM
E
N
5
O
CM
E
s
2
o
1200 1800
600
167
a rising tide resulted in a larger storage of oxygen
in the v/ a ter column, causing respiration to increase.
The respiration peak was larger at the afternoon high
tide because temperature was also larger then. The
area under the curve was total 24-hour respiration and
2
was 7.1 g/m The P/R ratio of the simulation was 0.76.
Water temperature declined until about 0900 be
cause of radiative and evaporative cooling,increased to
a peak at about 1500 from solar radiation, and declined
slowly through the afternoon and night.
Total phosphorus exhibited a diurnal swing of
3
about a factor of three from about 0.02 to 0.06 g/m .
Phosphorus increased during the nighttime hours in
response to release by respiratory processes and a
rising tide near dawn and declined to a low point near
noon as it was taken up in photosynthesis. It increased
during the afternoon as photosynthesis was possibly
limited by the low concentration and respiration increased,
and a rising tide brought in water of higher phosphorus
concentration.
Within the benthic plants the labile organic
compartment exhibited a small diurnal cycle with lowest
storage at dawn, rising to a somewhat larger value in
the early afternoon, and declining slowly through the
rest of the afternoon and night. The diurnal swing may
have been small because of the rapid turnover time of
the storage. Structural biomass increased only slightly
during most of the day, turning up more rapidly in the
late afternoon. Organic matter in the water column in
creased somewhat, while consumer biomass was essentially
constant during the 24-hour period.
Results of the initial computer run when com
pared to actual summertime oxygen data suggested that
the model as constructed was a reasonable approximation
of the system existing in the inner discharge bay.
Parameters were now adjusted to those of June 21-22,
1973 for validation against a particular data set
(Figures 43 and 44).
Model Output with Reduced Insolation
The amplitude of the sine wave representing
2
sunlight was set to give about 3000 kcal/m for the
day. All other coefficients were as originally
scaled. Model output is given in Figure 45. Total
daily insolation in the model was similar to the actual
amount received, but the instantaneous rates were often
different, especially in the afternoon when thunder
storms greatly reduced actual light intensity. Simu
lated oxygen values were close to actual measurements
forJune21-22.
Figure 43. Data gathered from the inner bay during the
community metabolism study of June 21-22,
1973, against which the simulation of the
model of Figure 40 was compared. Open circles
are average of individual measurements (solid
dots) made at that time. Numbers across top
of graph of rate-of-change are coefficients
used for diffusion correction. Line with
open circles is rate-of-change corrected
for diffusion.
TIME OF DAY
PERCENT
SATURATION
SALINITY,
7oo
O
CT>
O
o
ro
o
o
CD
O
o
170
Figure 44. Solar insolation for June 21, 1973, as recorded by a
located at the Crystal River power plant site. Total
received is indicated.
pyranometer
radiation
INSOLATION,
1000
21 JUNE, 1973
1/1
-C.
OJ
1800
no
TIME OF DAY
Figure 45. Simulation results of diurnal model of inner
bay (Figure 40) with original scaling, but
sunlight reduced to a daily total similar
to June 21-22, 1973. Points ( O ) are ob
served data from the inner bay.
ppm meters Kcol/ m2 hr
174
20
i.o-
0.5-
0.0-
(d) GROSS PRIMARY
PRODUCTION
CM
(i) BENTHIC PRODUCERS
'BIOMASS
LABILE ORGANIC
MATTER
i l
CM
E
\
O
10
5
(j) CONSUMERS
J i L
0600 1200 1800
0
0600 1200 1800
175
2
The gross primary production of 3.4 g O^-ni was
2
less than the 4.0 g O^-m calculated from the actual
data. The total respiration curve still exhibited the
same shape as the initial run (Figure 42). Total res-
2
piration for this run was 6.1 g O^/m The P/R ratio
of 0.56 was larger than the 0.33 calculated from the
diurnal data.
Water temperature dropped below the measured
values in the afternoon, but still had the same general
shape as the observed data. Because of the reduced
photosynthesis, phosphorus did not undergo as large a
diurnal variation as the initial run. Midday values,
however, still limited gross primary production. The
labile organic pool within the benthic plants exhibited
a small diurnal cycle similar to the initial run.
Organic matter in the water column, plant biomass, and
consumer biomass had patterns essentially similar to the
previous runs.
With adjustment of insolation the simulation
gave a reasonable overall match to the observed data.
Periodic responses were not necessarily expected since
the forcing function of volume exchange was not periodic.
Also, since the diurnal dynamics of water bodies are
generally dependent on forcing functions which are vari
able from day to day, the fact that a quantity such as
176
oxygen does not return to the same value 24 hours later
is more the rule than the exception. The nonperiodici
ties observed were all well within variations known to
occur at Crystal River.
Output of Model with Various Ratios of Canal Water
to Offshore Water on a Rising Tide
Since the relative contributions of water from
the discharge canal and offshore to the inner bay on
a rising tide was only an estimate, the model was rerun
with different proportional contributions of water from
these sources. Coefficients were set for the following
ratios on a rising tide: equal amounts of canal and
offshore water, a 2:1 ratio of canal to offshore water,
and canal water only. Graphs of simulation results
are given in Figures 46-48.
Differences in response of the model to the
different conditions were small. For oxygen, the minimum
value at dawn was lowered slightly and the magnitude of
the maximum value and time of its occurrence reduced
somewhat because of the increasing contribution of canal
water with its lower oxygen content on the rising tides.
The temperature curve rose as the proportion
of canal water increased, matching best when canal water
made up all of the flow into the inner bay on a rising
tide (Figure 48). All other parameters were essentially
Figure 46. Simulation results of diurnal model of the
inner bay (Figure 40) with equal amounts of
canal and offshore water contributed to the
inner bay on a rising tide. Points ( )
are observed data from the inner bay for
June 21-22, 1973.
178
1.0-
0.5-
0.0^
(d) GROSS PRIMARY
PRODUCTION
CJ
'i
o
0600
I2CO 1800
0600 1200 1800
Figure 47. Simulation results of diurnal model of the
inner bay (Figure 40) with two parts canal
water to one part offshore water contributed
to the inner bay on a rising tide. Points
( O ) are observed data from the inner bay
for June 21 -22 1 973.
g 0 y/rr.-hr ppm meters Kcal
180
0600 1200 1800 0600 1200 1300
gure 48. Simulation results of diurnal model of inner
bay (Figure 40) with canal water alone being
contributed to the inner bay on a rising
tide. Points ( O ) are observed data from
the inner bay for June 21-22, 1973.
182
CU
V\
(M
O
c
CVi
(j)
CONSUMERS
1
's.
5
-
-
cr*
f\
. 1
0600 i 200 ¡eoo
0600 1200 1800
183
unchanged from previous runs. The best overall fit of
temperature and oxygen was with a mixing ratio of 2
parts canal water to 1 part offshore water (Figure 47).
Responses of Hod el to Increased Temperature
of Discharge Canal Water
The addition of the third power plant at Crystal
River was expected to raise the temperature of the dis
charge canal 1 to 2C and increase discharge velocity
by about a factor of two, so that an increased tempera
ture and different rising tide mixing ratio might be
expected on the inner bay. The diurnal model was rerun
using the same series of rising tide mixing ratios as
in the previous set but with canal water temperature
raised to 7C over ambient instead of 5C (Figures
49-51). The only discernible effect on model output was
to increase water temperature on the inner bay about 1C
All other model output was essentially unchanged from
previous runs.
Model Response with No Discharge from Power Plant
One cooling alternative at Crystal River was
the construction of closed cycle cooling towers. To
test this possibility, which would eliminate the flow
of any heated effluent from the discharge canal, the
model was run with only offshore water flowing onto the
Figure 49. Simulation results of diurnal model of the
inner bay (Figure 40) with a 7C differential
of discharge canal water over ambient water
and a mixing ratio on a rising tide of one
part canal water to one part offshore water.
10
10
"(h) ORGANIC MATTER
(c) OXYGEN
IN WATER
IO
v E
5
\ 5
-- _
CL
en
0
i i i
i 1
1.0
0.5
0.0
S-
\c
'S
o
o>
1.0
0.5
0.0
0600 1200
1800
0800 1200 1800
Figure 50. Simulation results of diurnal model of the
inner bay (Figure 40) with a 7C differential
of discharge canal water over ambient water
and a mixing ratio of 2 parts canal water to
1 part offshore water on a rising tide.
187
CM
'x
OJ
O
0600 1200 1800
0600 1200 1800
189
10 (h) ORGANIC MATTER
IN WATER
IO
o
v.
JC
o>
20
CO
\£
(i) BENTHIC PRODUCERS
j< BIOMASS
^-LABILE ORGANIC
MATTER
0600 1200 1800
0
0600 1200 1800
Figure 51. Simulation results of diurnal model of the
inner bay (Figure 40) with a 7C differential
of discharge canal water over ambient water
and with canal water alone flowing onto the
inner bay on a rising tide.
190
inner bay on a rising tide (Figures 52 and 53). Oxygen
levels increased and temperature levels decreased some
what over previous runs because canal water with its
lower oxygen content and higher temperature was no longer
being contributed to the inner bay. Other model output
did not change discernibly from previous runs over the
24-hour period of the simulation.
Model Response to Timing of the Tidal Cycle
Because the time of occurrence during the day
of high and low tide on the inner bay was believed to
be important in determining the shape of the oxygen
curve, the model was rescaled and rerun with the tidal
cycle reversed from the previous runs. Simulation results
are given in Figure 54.
The oxygen curve with this tidal regime was
more "classical" in shape with a rapid rise after dawn,
tapering off to a high point near dusk. Gross primary
production was limited by low phosphorus and light
during the midday period. Total respiration exhibited
the same dependence on total oxygen as in previous runs.
Total phorphorus underwent a diurnal cycle in
fluenced by respiratory recycling, advection, and uptake
in photosynthesis. The large peak at dawn was a result
of respiratory regeneration into the smaller volume of
water present on the bay with the low tide at that time.
Figure 5 2. Simulation results of diurnal model of the
inner bay (Figure 40) with no discharge of
cooling water from the power plant discharge
canal and original scaling of insolation.
ppm meters Kcal
192
(i) BENTHIC PRODUCERS
BIOMASS x
LABtLE ORGANIC
MATTER
_L
_L.
w
O
1.0
0.5
0.0
(e) TOTAL RESPIRATION
0600 1200 1800
0
0600 1200 1800
Figure 53. Simulation results of diurnal model of the in
ner bay (Figure 40) with no discharge from the
power plant discharge canal and insolation re
duced to one-half original scaling.
Figure 54. Simulation results of diurnal model (Figure 40)
with timing of occurrence of high and low tide
reversed from previous runs.
ppm meters Kcd
1 94
ro
o
CVJ
o>
0600 1200 1800
20-
ioF
0
10
5
0
(i) BENTHIC PRODUCERS
BIOMASS
VLABILE ORGANIC
MATTER
-j i
(j) CONSUMERS
-
-
_J i
J
0600 1200 1800
1000
500
0
20
1.5
LO
0.5
0.0
15
10
5
O
10
0.5
0.0
on
02
0.0
(c) OXYGEN
(d) GROSS PRIMARY
PRODUCTION
ro
E
o>
<\i
E
o>
CM
Cr>
0600 1200 1800
0600
1200 1800
Figure 55. Energy diagram of simulated model of inner discharge bay empha
sizing seasonal properties of the ecosystem and flows in g/m^.
day. Unless otherwise noted, storages are in g/m2 of organic
matter or material. See Appendix D for calculation of values
given. Pathways indicating the effect of temperature on system
properties have been omitted to simplify the diagram. The path
way entering a work gate marked with a "T"
T
is assumed to come from the symbol
water
temp.
POWER PLANT ~ v
discharge *
CANAL t' \ f V
PHOSPHORUS) phytoplankton
U43O.45 /
f ORGANIC /
MATTER'
LO
CO
Figure 56. Seasonal patterns of insolation and tempera
ture used as forcing functions in the seasonal
model of the inner bay ecosystem (Figure 55).
(a) Seasonal course of sunlight simulated
with a function generator. Solid line
is response of function generator. Inde
pendent points are average daily insola
tion by month at Tampa, Florida, from
Figure 14.
(b) Simulated seasonal cycle of water tempera
ture for the inner bay. Solid line is
sine wave approximation of seasonal cycle
Unconnected points are monthly mean water
temperatures at Cedar Key, Florida, from
Figure 18.
Kcal/m day
200
201
Depletion during the day from uptake in photosynthesis
limited the rate of primary production.
Temperature dropped during the day because back
radiation from the atmosphere was not included as an
input in this run. The general insensitivity of previous
runs to temperature, however, indicated that correction
of this inaccuracy would not alter the model response
very much.
Simulation Model of Seasonal Properties
of the Inner Bay Ecosystem
Given in Figure 55 is an energy diagram of the
model of the inner bay simulated for study of its seasonal
properties. The equations following from the diagram are
given in Table 8. Calculations and documentation of
various other model parameters are given in Appendix D.
All forcing functions were considered constant
except temperature and sunlight because of the lack of
adequate data to program them with any seasonal patterns.
Sunlight (Figure 56a) was programmed on a function gen
erator to match the pattern of average daily insolation
by month at Tampa, Florida. Seasonal temperature was
simulated as a sine wave function with a low of 15C
on January 1st and a peak of 33C on July 1st (Figure
56b). Large deep bodies of water often have a tempera
ture cycle which lags insolation by several months.
Table
d Q -j
dt
d Q 2
dt
d^
dt
dQ4
dt
Differential equations for seasonal model of inner bay system given in
Figure 55.
k2Jo (kR + k TQ 2 Q -j ^ k3QlT = k5Ql k6Ql
J15 + J16 + k29^6T + k30^5T + k31^4T + k32^1T + k33Q3TR + k42^7T + k34^3T k17Q2
TQ2Q1 n TQ2Q7
k4Jo (kR + k 1 TQ2Qi } k40Jo (k4]R + k^TQgQ^
k5Q1 + J7 + 8 k9Q3 kllQ3TR k12Q3TQ5 k13Q3 kl4Q3T k10Q3TQ6
k6^1
k 1 3Q3
k23Q3TR
k22Q6
+ k21Q5 + k20Q4TQ5 f k45Q7TR + k47Q5TQ7 klgQ4TQ5
" k18Q4T
202
Table 8 continued
dQ5 2
dt k24^4T^5+ ^3T^5 ^ + k 46 ^ 7TC} 5 k 2 5 ^ 5T K26Q5Tt^6 k 21 ^!
d Q r p
dT~ = k27^3TQ6 + Q5TtV k28Q6T = k22Q6
dQ 7 ; TQ2Q7
dt~ = k36Jo (k71R + k41TQ2Q7) + J43
k 3 7^ 7T + k38^7TR
k39Q5TQ7 k44Q7
203
205
lost to respiration (J^) and storages of organic matter
in the sediments (Jg) and water column (J^). Phyto
plankton are lost by grazing of filter-feeding benthic
invertebrates (J 3 g) and oysters (J^g), and by exchanges
with offshore and discharge canal populations (J^3, J^).
Storages in the water column of organic matter
(Q3) and phosphorus (Q^) exchange tidal 1y with concen
trations in the discharge and offshore water (Jg, Jg>
J1 6 5 J1 7 ) Inflows from the saltmarsh [Jj, J-jg) are
constant. Loss of organic matter by respiration (J^)
occurs as a product of temperature and the quantity
stored.
Organic matter is gained by the sediments (Q^)
through pathways of settling of plant matter (J^), sedi
mentation from the water column (J13), feces and pseudo
feces from oyster reef organisms (J^g), death of benthic
invertebrates and fish (^31 5 d22anc* ^eces benthic
invertebrates (J^). Losses from the sediments are from
microbial respiration (J-|g) and deposit feeding of
benthic invertebrates (J -j g ).
Oyster reef biomass (R) is modeled as constant
and outside of the model boundaries because more detailed
simulations are available in Lehman (1974). Reef
organisms filter organic material from the water column
as the product of the quantity of organic material
(Qg), temperature (I), and reef biomass (R).
204
However, in the shallow coastal area of west central
Florida water temperature was usually closely in phase
with insolation.
The model itself contained storages of benthic
macrophytes (Q^) phytoplankton (Qy ) total phosphorus
(Q^), organic matter in the water column (Q^), and
sediments (Q^), benthic invertebrates (Qg), and fish
(Q6). Oyster reef biomass (R) was considered a constant
forcing function outside of the model, but its filtering
action on organic matter in the water column was included
as a function of temperature (Galtsoff, 1928; Nelson,
1935; Loosanoff, 1958; all quoted in Lehman, 1974).
Gross primary production (J2) 1s shown as the
product of the action of sunlight, temperature, phos
phorus, and plant biomass. Incident solar radiation
is shown as a constant flow source (JQ) from which some
is drawn for use in photosynthesis (J-|), the remainder
(JP) being used in other physical processes. If all
other factors are nonlimiting, primary production may
increase by capturing more and more sunlight previously
unused in photosynthesis (JR). At some level of produc
tion all incident solar radiation (JQ) is being used in
photosynthesis (J-j now equals J ) so that sunlight becomes
a limiting factor.
The storage of benthic plant biomass produced
in photosynthesis (Q-j ) is not grazed directly, but is
206
Unassimilated material is released to the sediments as
feces and pseudofeces (^ 2 3 ^ '
All benthic invertebrates are lumped into one
compartment (Qg)- Feeding inputs are shown as filter
feeding on organic matter and phytoplankton in the water
column (J12) and deposit feeding on organic matter in
the sediments (J-|g). Ingested food is assimilated (J^)
at an assumed efficiency of 50%, the rest being returned
to the sediment organic storage (J2q). The rate of
these processes is modeled as the product of temperature
(T), the stored quantities of organic matter (Q^ + Q^),
and invertebrate biomass (Qg)- Losses of invertebrate
biomass are by respiration (J 2 5) and predation of fish
(J2g)- Respiration is considered to be the product of
temperature and the square of invertebrate biomass.
The fish compartment includes only resident
species, since the storage value was obtained from the
dropnet measurements. Both carnivorous (J ^ q) and detritus
feeding (J9g) pathways are indicated. Since the propor
tion of intake by each pathway is unknown, the calculated
assimilation is merely divided between the two pathways.
Losses of fish biomass are from death (J^), modeled as
a linear density-dependent drain, and respiration (J28^ 5
modeled as the product of the square of biomass storage
and temperature.
207
Phosphorus is recycled to the water column pool
by all respiratory activity (J 2 g, J3Q, J31, J32, J34, J42).
The amount of phosphorus released was taken as a percentage
of the organic matter respired.
The effect of temperature is included in the model
as a multiplicative function on all biologically mediated
pathways. An exponential or other function was not used
for several reasons. Because of acclimation, respiration
may not actually follow an exponential relationship be
tween winter and summer temperatures, the rate observed
being lower in warmer temperatures than would be predicted
from an exponential extrapolation of rates during cold
temperatures. A linear multiplicative relationship gives
an output approximating this reasoning.
Mechanisms in addition to predation are thought
to operate regulating population size at high population
levels. In this model a square term interaction on drain
ing respiratory pathways of benthic invertebrates and fish
has been used to include this factor in model behavior.
Initial Simulation and Adjustments
When the seasonal model was simulated with co
efficients set for the original scaled values, the stor
ages of fish and benthic plants deviated somewhat from
the observed data. To correct the excursion of fish
2Q3
biomass, which was increasing to about twice the initial
condition value, pathway J^2 representing death and
losses to higher trophic levels was increased to make
inflows to the storage equal outflows. Loss pathways
and Jg from benthic plants were reduced somewhat to
O
maintain the original summer biomass level of 40 g/m .
After adjustment of the parameters described
above, model behavior (Figure 57) was more in line with
available field data and trends of the storages. Benthic
plant biomass follows the observed pattern of low values
in fall and winter, increasing through the spring to the
largest values during summer. The observed summer value
was not quite reached because the 40 g/m used in the
original scaling was chosen before the exact value from
field measurements was available. The trend of the
simulation for the fall and winter was realistic, but
was somewhat off from the data points. Biomass was
probably variable during the cold months, being reduced
drastically when strong cold fronts would drain the
inner bay for several days, as seen in the fall sample,
and recovering to somewhat higher levels afterwards, as
seen in the winter sample.
Deviations from measured values for phytoplankton
biomass may result from several reasons. The observed
values were measured at the mouth of the discharge canal
Figure 57. Simulation results with initial scaling of
seasonal model of the inner bay (Figure 55).
Measured data for benthic plants, resident
fish, benthic invertebrates, gross photo
synthesis, and total respiration have also
been plotted by quarter for comparison.
210
211
and are, thus, only roughly representative of conditions
for the inner bay. Also, the large flushing exchange
with a constant offshore source of biomass, an assumption
which was not entirely correct, tended to dampen any
seasonal variations produced by the model.
Fish biomass simulated in the model matched
fairly well with the 1.5 year's data measured for the
inner bay. Simulated values for benthic invertebrates
was higher than the measured values. However, the sampling
technique used probably was measuring only about half the
actual biomass. When doubled, they fall fairly close to
the simulated values. The initial gain in biomass at the
start of the simulation was well within variations in the
data.
Because of the large size of the storage, organic
matter in the sediments underwent only a small seasonal
change, being lowest in spring and highest in late summer.
Large changes in the storages of phosphorus and organic
matter in the water column were prevented by the large
exchange with the constant offshore source.
No adjustments of coefficients could produce
simulation patterns of respiration and photosynthesis
similar to the observed values. However, the pattern
of a peak in phytoplankton production in the spring
followed by benthic plant production in the summer, and
a P/R ratio of one in the spring were similar to observed
patterns, although the magnitudes were incorrect.
Response of Simulation Model to Increased Temperature
An expected consequence of the operation of the
power plant under construction at Crystal River was a
small increase in the temperature of the discharge canal
water. Coupled with possible modified flushing patterns
in the discharge area because of increased canal veloci
ties, the average temperature of the inner bay could
increase from 1C to 3C. The maximum case was chosen,
and the model was simulated with a seasonal temperature
pattern of 18-36C. All other parameters were left un
changed. Simulation results are given in Figure 58.
Increased temperature was somewhat stimulatory
to gross photosynthesis of benthic plants but not phyto
plankton. Total respiration was also stimulated.
The increased photosynthesis of benthic plants
increased the standing stock somewhat. Resident fish
biomass increased, while benthic invertebrate biomass
remained about the same, possibly in response to increased
predation losses to the larger fish stock. The observed
reduction in the storage of organic matter in the sedi
ments may indicate that this source was being drawn upon
to satisfy the increased consumer demands. Any changes
in the storage of organic matter in the water column
from increased filtering by consumers was obscured by
the exchange with offshore concent rations.
Figure 58. Simulation results of seasonal model of the
inner bay (Figure 55) with seasonal pattern
of temperature increased 3C.
214
T
/'BENTHIC INVERTEBRATES
T T
PHYTOPLANKTON TEMPERATURE, C
215
Response of Simulation Model to Increased Temperature
and Turbidity
Another possible consequence of the operation of
unit three at Crystal River was an increase in turbidity
accompanying the increase in temperature. This possi
bility was tested by simulating the model with seasonal
temperatures of 18-36C as in the previous run, but with
the flow of sunlight utilized in photosynthesis (J-j)
reduced from 50 percent to 30 percent. Simulation results
are given in Figure 59.
Benthic plant photosynthesis was reduced consider
ably despite the previously demonstrated stimulatory
effect of increased temperature alone. Phytoplankton
photosynthesis was largely unaffected, making it a larger
percentage of total gross production. Total respiration
also declined because of the reduction of several storage
compartments.
Biomass of benthic plants decreased considerably,
while phytoplankton biomass was reduced somewhat except
during its spring peak. The higher trophic levels of
invertebrates and fish declined because of the reduced
primary production.
Response of Simulation Model to Decreased Turbidity
The previous simulation indicated the importance
of turbidity in controlling primary production in the
Figure 59. Response of seasonal simulation model of the
inner bay (Figure 55) to increased temperature
and turbidity. The seasonal pattern of tem
perature v/as increased 3C, and the flow of
sunlight utilized in photosynthesis reduced
from 50% to 30%.
217
8000-
cvj
E
\
cn
(a)
0.10-
(b)
200
CM
D>
0.05-
0J
CM,
100-
0L
1 T
BENTHIC PLANTS
PHYTOPLANKTON
-PHOSPHORUS(a)
0.5
/"SEDIMENT ORGANIC MATTER (b)
//WATER ORGANIC MATTER (c)
(c)
c c\J
5
a>
0
PHYTOPLANKTON TEMPERATURE
218
inner discharge bay. To test the effect of a reduction
in turbidity in the discharge water, the model was simu
lated with light available for use in photosynthesis
(J^) increased from 50 percent to 70 percent. Two
seasonal temperature ranges were used to bracket the
temperature increase expected from operation of unit three.
Simulation results with seasonal temperatures of 15-33C
are given in Figure 60, while those for a range 18-36C
are given in Figure 61.
For both temperature conditions (Figures 60 and
61), total gross photosynthesis increased considerably
over the previous runs with the same temperature but
less light (Figures 57 and 58), resulting entirely from
increased benthic plant photosynthesis. Benthic plant
photosynthesis also appeared to be responding more to
the seasonal light pattern than previously, with an
upturn and peak earlier in the year. The same pattern
was reflected in benthic plant biomass with a larger
standing crop at all times of the year and peak biomass
occurring somewhat earlier. Phytoplankton biomass was
unchanged. Large storages of organic matter in the
sediments and biomass of fish and invertebrates could
also be supported by the larger rate of primary produc
tion; Many of the same trends were noted between the two
simulations at the higher light but different temperature
levels (Figures 60 and 61) as between the previous runs
at lower light but different temperatures (Figures 57 and 58).
Figure 60. Response of seasonal simulation model of the
inner bay (Figure 55) to decreased turbidity
and a seasonal temperature range as originally
scaled. The flow of sunlight utilized in
photosynthesis was increased to 70%.
220
8000
g -g
E 4000
CO O
z: o
co
h-
<
_i
a.
o
i
UJ
m
CM
G
N
O'
CM
E
s
cn
'*E
cn
PHT0PLANKT0N TEMPERATURE
Figure 61. Response of seasonal simulation model of inner
bay (Figure 55) to decreased turbidity and a
seasonal temperature range of 18C 36C.
The flow of sunlight utilized in photosynthe
sis was increased to 70%.
222
PHYTOPLANKTON TEMPERATURE,C
g/m2
DISCUSSION
Presented in this section are summary data of the
ecosystems at Crystal River, comparisons with other
estuaries, and discussion of temperature, turbidity,and
ecosystem responses as observed and simulated.
Seasonal Patterns of the
Ecosystems at Crystal River
A dominant feature of temperate ecosystems is
the seasonal variation of many of the external energy
sources such as sunlight and air temperature. In
estuaries many of the behavioral patterns of the creatures
and the processes of metabolism are coupled to the pulsing
of the environmental variables.
Seasonal Patterns of Metabolism
The remarkably constant seasonal pattern of
metabolism found for the inner bay was very unusual,
while that observed at the Fort Island and Hodges Island
areas away from the power plant was typical of patterns
found in other Gulf coast estuaries in Texas (Odum, 1967)
223
224
and Louisiana (Day e_t aj 1 973 ). Further north, shallow
estuarine systems had similar summer values but lower
winter values (Nixon and Oviatt, 1973; Cory, 1974).
Summer metabolism measurements made during this study
are compared in Table 9 with measurements taken else
where in Florida, at other Gulf Coast locations, and
more temperate estuaries of the United States. In
2
general, summer metabolism values of 3-12 g O^/m -day
in the areas at Crystal River unaffected by the power
plant plume were similar to those measured in other
coastal areas.
The generally higher turbidities in the discharge
area may have been responsible for the lower levels of
metabolism there during the warmer months. That the inner
bay was actually capable of high rates of photosynthesis
when conditions were right could be seen from the rapid
oxygen production when shallower water of a low tide
occurred during the mid- to late afternoon. Other
shallow estuaries in which H. wrightii was prominent or
dominant had summer productivities similar to or higher
than the the control areas of this study (Hellier, 1962;
Odum, 1967).
The failure of productivity to drop in the winter
in the inner bay as it did in the areas away from the
plant may indicate a stimulatory effect of the warmer
water temperatures. Respiratory processes may have been
Table 9. Comparison of gross primary production and total respiration measured at
Crystal River with some values from other areas in Florida and similar
systems elsewhere.
S ummer
meta bol ism
Location
System Type
Gross
Production
Total
Respiration
Reference
Inner Bay, Crystal
River, Fla.
Marine meadows
with consumer
reefs
3-4a
3-4b
This study
Inner bay control
areas, Crystal
River, Fla.
Marine meadows
with consumer
reefs
3-9a
3-12b
This study
Outer bay areas,
Crystal River,
Fla.
Marine meadows,
consumer reefs,
plankton important
4-10a
4-8b
McKellar, 1975
Apalachicola Bay,
Fla.
Mid salinity
piankton
3-12a
3-10b
Boynton, 1975
Apalachicola Bay,
Fla.
01igohaline
areas
3-8a
2-10b
Boynton, 1975
Apalachicola Bay,
Fla.
High salinity grass
flats
7-12a
6-10b
Boynton, 1975
225
Table 9 continued
Summer
Meta bo 1ism
Location
Gross
System Type Production
Total
Respiration
Reference
Whitefish Bay,
Fia.
Bottom dominated;
Plankton unimportant
8C
7C
Tabb et al.,
1962
Coot Bay, Fla.
Turbid plankton
7C
14C
Tabb et_ al_., 1962
Long Key, Fla.
Grass bed
34c
Odum, 1957
Redfish Bay,
Port Laguna,
Tex.
Marine meadows
5-26C
5-33C
Odum, 1967
Copano, Lavaca,
Nueces Bays, Tex.
Bays with
consumer reefs
1-14C
2-22C
Odum, 1967
Upper Laguna Madre,
Tex.
Hypersaline thin
grass
8-25C
4-22c
Odum, 1967
Corpus Christi,
Arkansas Bays, Tex.
Mid salinity
plankton
6-27C
11-27C
Odum, 1967
226
Table 9 continued
Summer
Metabolism
Location
System Type
Gross
Production
Total
Respiration
Reference
Airplane Lake, La.
4-7c
3-4c
Day et_ aj_., 1973
Bissel Cove,
R.I.
Mid salinity
1
O
4-10C
Nixon and Oviatt,
1973
aDaytime net production plus night respiration,
bNight respiration doubled.
cAs defined by Odum and Hoskins (1958).
227
228
affected more than photosynthesis because of limited
light. In the seasonal simulation model total respira
tion in the winter was stimulated more than photosynthesis
by a 3C increase in temperature. A P/R ratio less than
one in the inner bay when it was greater than one at
Fort Island may support this idea.
No combination of reasonable coefficient adjust
ments of the seasonal simulation model produced a pattern
of increased winter metabolism as observed for the inner
bay. Although the magnitude of metabolism was incorrect,
model behavior suggested that phytoplankton may have been
dominant in the winter. No light and dark bottle data
are available to test this idea, but if winter plankton
metabolism were of the order of that in the spring, total
metabolism similar to summer values would result.
Met Production and the "Spring Dinner"
The seasonal patterns of several parameters at
Crystal River provided evidence for a spring pulse of
productivity in the phytoplankton. Chiorophyl1-a and
phytoplankton biomass increased in April and May with
some increase in ammonia. Net community production in
the control areas and phytoplankton production as measured
by the light and dark bottle experiments was much larger
in the spring. McKellar (1975) also found much higher
phytoplankton productivity in the spring (one measurement)
229
in the outer discharge and control bay areas. Saville
(1966) found highest phytoplankton production as measured
by the uptake of carbon-14 in May and June in the
Waccasassa estuary, a coastal area 20 kilometers to the
north, which is very similar to the Crystal River region.
Net accumulation of organic matter in a population
such as phytoplankton with rapid turnover may be possible
during periods such as the spring, when insolation is
increasing rapidly and nutrient storages are larger,
but the increase in water temperature is lagging behind.
Under these conditions, processes of organic primary
production stimulated by light and nutrients may outstrip
respiratory processes degrading organic structure, result
ing in a net accumulation of biomass.
A simulation of a producer module was run to
test this idea (Figures 62 and 63). When temperature
and light were varied out of phase the model exhibited
properties of springtime accumulation similar to that
observed in north-temperate oceans (Raymont, 1963).
Simulation of the seasonal model with phytoplankton
embedded within the whole system produced similar results.
In shallow coastal waters such as the Crystal River area
water temperature does not lag light as much as in the
open sea, allowing producer respiration to track photo
synthesis more closely, so that the response observed
was not as large.
Figure 62. Energy diagram and analog computer patching
diagram of simulation model of producer
module with temperature affecting both
photosynthetic and respiratory pathways.
(a) Energy diagram. Flows are in
g/m^-day of organic matter, energy,
or material. Storages are in g/m
of organic matter or material.
(b) Analog computer patching diagram.
Equations following from the energy diagram
were
dQ1
dt
klS k2Ql k31TQ1
dT = k4ITV2 k5^
Pot settings were
Pot setting
k] 0.240
k2 0.165
k3 0.244
k4 0.318
C\J
O'
o
1
Pot setting
k5
0.023
k6
0.035
ICQ.,
0.333
ICQ2
0.500
231
FROM SINE WAVE
Figure 63. Simulation results of model of producer module
in Figure 62 with seasonally varying light and
temperature. Note scale difference for pri
mary production and respiration.
233
(a) (b)
g/m2 day
234
This seasonal pulse of net production may serve
as a "spring dinner" for juveniles and young-of-the-year
of many species, which have adapted to take advantage of
it by linking their periods of migration, reproduction,
or rapid growth to the time of net accumulation. Odum
(1967) summarized several years of work by many investi
gators on the community metabolism and animal stocks
of two Texas bay systems, documenting seasonal trends
in productivity, respiration, and movements of animals.
Seasonal migrations into the estuaries in the late winter
and spring when productivity was rising rapidly was a
dominant feature of these systems.
Some data suggest that stocks at Crystal River
were responding to the spring bloom of phytoplankton since
the P/R ratio for the system was near one. Maturo (1974)
found rapidly rising biomass and numbers of zooplankton
in the spring in the inshore regions around the power
plant, while fish larvae were most numerous and decapod
larvae were increasing rapidly in number. The calcu
lated production rate for zooplankton was also largest
in the spring, while biomass and predation rates of zoo
plankton predators were still low. Resident fish biomass
increased in the warmer months from winter lows (Figure 27),
and oyster spat set increased markedly in June (Lehman,
1974a,b).
235
Seasonal Migrations and System Stabi1ity
Systems with prominent seasonal pulses, such
as temperate estuaries, may be exploited by populations
which move in during the period of plenty, experiencing
rapid exponential growth, and then move away. A system
of this kind may be stable even though it has no controls
on growth internal to its populations.
To test this theory, the seasonal model was modi
fied to add the feature of offshore migration of fish
in the fall months and onshore migration of larvae
and juveniles in the spring. The square term drain of
respiration representing internal controls on population
size was removed. With the migration pathways turned
off, the fish storage was unstable, dying off in several
years. With some migration the stock could maintain
itself in an oscillating yearly pattern (Figure 64),
suggesting that the estuary may have established a stable
pattern through exchange with the open sea.
Seasonal Substitution of Species
Seasonal patterns in the benthic primary pro
ducers similar to ones observed in other estuaries seem
to be important at Crystal River. In the south intake
area the prominence of red and brown algae in the winter
and spring with greens assuming more importance in the
Figure 64. Simulation response of seasonal model of the
inner discharge bay to the addition of path
ways of exchange of fish and fish larvae with
offshore waters. See text for details of
changes made in original model for this simu
lation.
237
PHYTOPLANKTON TEMP,
238
summer may be a response to changing insolation and
temperatures. Species of the family Ectocarpaceae
(a brown algae) were dominant in the inner bay during the
winter of 1972-1973, almost completely covering the areas
of HL wrightii (Van Tyne, 1 973 ). Its failure to return
the following year was possibly attributable to the excep
tionally mild weather that winter. This family was also
reported as an important winter species for some systems
in Texas (Conover, 1964), Louisiana (Day ejt ajk 1973),
and North Carolina (Dillon, 1971).
Changing the relative dominance of species or
substituting entire new ones may be a more effective way
of utilizing a varying energy regime. Maintaining genetic
adaptations within one or several organisms so that it
may function efficiently over the entire range of condi
tions prevalent may be energetically more expensive than
having several more specialized organisms each adapted
to conditions existing only part of the time. Species
substitutions may be the most effective way to make
maximum use of available energies at all times of the
year as expected from the Lotka power principle.
The existence of a pool of species adapted to
various environmental conditions could have been impor
tant at Crystal River in facilitating adaptation of com
ponents of the ecosystem to the added stress of tempera
ture. By eliminating some species and replacing them with
239
others, an ecosystem optimally adapted to the new condi
tions may be maintained.
Seasonal variation of species dominance may be a
mechanism for maximizing photosynthesis under all condi
tions. In a simulation model with all photosynthetic
species lumped into one or two compartments, a changing
photosynthetic efficiency would require a time-varying
coefficient. A rough attempt at simulating this feature
was made by using switches and comparators to switch from
the original scaled coefficient to a larger one during
the winter months. Simulation results are given in
Figure 65. Increasing the coefficient in winter increased
total photosynthesis during that period, although the
action was sharp and abrupt because of the method of sim
ulation. If the coefficient adjustment had been smooth
and gradual with time the simulation result for total
photosynthesis may have been along the dotted pathway,
which would have given a larger winter value than pre
vious simulations, but still not as large as the measured
value.
Comparisons of the Ecosystems at Crystal River
and Adaptation to the Thermal Discharge
After construction of the power plant at Crystal
River the inner bay became an interface system between
the energy flows of the economic systems of man and the
Figure 65. Simulation results of seasonal model of inner
bay as modified in Figure 64 with larger
photosynthetic coefficient added in winter.
Dotted line in total photosynthesis graph is
estimate of curve if coefficient adjustment
was gradual rather than abrupt as in the
simulation.
241
YEARS
PHYTOPLANKTON TEMP.,
242
YEARS
Figure 65 continued
243
estuarine patterns and processes of nature. Previously,
the inner bay had been adapted to its own set of energy
constraints, but with plant operation a new set of energy
forces derived from both systems was at work, requiring
the malleable and adaptable ecosystem components to be
regrouped and adjusted into a new combination, which
once again maximized the power flow according to the new
energy regime.
Temperature and Primary Production at Crystal River
One of the issues considered of major importance
by many regulatory agencies grappling with the problem
of power plant discharges has been the effect of temper
ature on primary production. Will higher temperatures
stimulate chemical pathways so that primary production
increases, or will the producer organisms be stressed
by the heat, lowering their photosynthetic ability?
Evidence from the models and studies by others suggest
that higher temperature alone was not the primary cause
of the lower levels of metabolism found for the inner bay
at Crystal River.
The push-pull model of temperature action as
used in this dissertation predicts that production will
either increase or remain the same depending on input
energies. If they are not limiting, temperature should
stimulate production. Kelley (1971), studying freshwater
244
microcosms started with a rich nutrient medium, observed
highest rates of primary production in the ones with the
higher mean temperature. However, if input energies are
limiting the same rate should be maintained because in
creased respiration would lower the standing stock of
biomass to a steady-state level capable of being supported
by the original rate. Primary production could only be
decreased in this model if input energies were also re
duced.
In the seasonal model, raising the temperature
increased primary production and total respiration, indi
cating heat was an energy subsidy to the system. Large
flushing rates and increased respiratory cycling may have
allowed the phosphorus storage to be maintained at its
original level so as to support the increased uptake
demand.
Other studies indicate that temperature by itself
may not be a stress on ecosystem productivity. Redfish
Bay, Texas, a shallow seaqrass system with naturally occur
ring summertime temperatures similar to those measured
on the inner discharge bay (Hellier, 1962) had a seasonal
range and pattern of metabolism much like the control
areas at Crystal River (Odum, 1967). Duke (1967) found
production values similar to summer values at Fort Island
in a thermal hot spring with an average temperature of
56C. Brock (1970), reviewing the work of others, reported
245
values from other hot springs similar to and higher than
those of Duke. As seen in the diurnal curves, the inner
discharge bay at Crystal River was capable of high rates
of photosynthesis when conditions were right.
Turbidity and Production at Crystal River
Turbidity contributed by the discharge plume from
the power plant may have been primarily responsible for
the reduced primary production during the warmer months
in the inner discharge bay--a fact which became increas
ingly important in discussions of the interagency review
committee concerned with licensing of Crystal River Unit
Three. Support for this conclusion comes from the models
and some field data.
Odum (1963) found reduced community metabolism
under turbid conditions from dredging in Redfish Bay,
Texas, a shallow system dominated by Thallassia and jl.
wrightii. Zieman (1970) noted high turbidities associ
ated with the discharge area for generating units located
at Turkey Point on Biscayne Bay, Florida.
As mentioned previously, reducing input energies,
in this case sunlight reaching the benthic producers, is
the only way primary production can be reduced in the
push-pull model of temperature action. In the simulation
of the seasonal model, gross production increased
246
considerably when turbidity was reduced, and was much
more sensitive to changes in this parameter than to the
temperature changes expected with the operation of unit
three.
Diversity and Biomass at Crystal River
The generally lower diversity of many components
and the lower total biomass of larger consumers in the
inner bay may be adaptations to the combination of high
summertime water temperatures eliminating some intolerant
species and reduced rates of primary production being
unable to support levels of biomass characteristic of
adjacent areas without thermal loading. That H. wrightii
is adapted to naturally occurring higher temperatures or
conditions of stress may account for the overwhelming
dominance of this benthic plant in the inner discharge
bay. Phillips ( 1 960) reported HL wrightii to be found
in Florida most frequently on the shallower bottoms
adjacent to shore where water temperatures reach higher
daytime levels in the summer. Zieman (1970) found the
seagrasses such as T h a 1 a s s i a and II. w r i g h t i i were tolerant
of higher temperatures in the discharge area of the Turkey
Point power plants on Biscayne Bay, Florida than were the
attached macroalgae. In Texas H. wrightii was found
adjacent to shore in Redfish Bay and as the dominant
247
benthic plant in the shallow hypersaline Upper Laguna
Madre estuary. This species may be only a minor component
of a more mixed system because the energetic costs of
maintaining genetic adaptations necessary to survive
under occasionally harsher conditions reduces its competi
tive ability. Temperature and turbidity conditions of
the inner discharge bay, however, may eliminate compe
tition from other species allowing H_. wri ghti i to become
dominant.
The reduction in total biomass of larger consumers
may be a consequence of the lower rate of primary produc
tion; the inner bay with about one-half the rate of gross
primary production of the south intake area had about
one-half the standing stock of higher trophic levels.
The relatively small temperature increase (3C average)
found in this study together with the likelihood of meta
bolic acclimation responses reducing its effect suggest
that temperature was less important in reducing consumer
biomass levels.
Reduction in diversity of consumers may have
resulted from several factors. The smaller energy flow
in the inner bay may not have provided enough support
for the maintenance of the more specialized organisms
of more diverse communities, while the problems of adapt
ing to higher and often abruptly changing temperatures
depending on the location of the thermal plume may have
248
eliminated many species. Kelly (1971) found lower species
diversity in freshwater microcosms subjected to fluctuat
ing temperatures than in those experiencing constant high
or low temperatures.
The Inner Bay as an Ecosystem Adapted to the
Thermal Plume
The widely held belief that systems receiving
thermal discharges are stressed may be true only for
several years after the onset of power plant operation.
Adjustments in the structure and function of an ecosystem
as observed in the inner bay may allow for the relief
of the stresses imposed by the thermal plume through
selection of a combination adapted to the new conditions.
Allen and Brock (1968), using microcosms seeded from a
wide variety of sources and kept at temperatures from 2C
to 75C, found each one to develop and maintain its own
characteristic combination of organisms despite extensive
cross-mixing of systems. Brock (1970) stated that opti
mum temperatures of many hot spring organisms as deter
mined in laboratory experiments was near that of the
environment from which they were collected, indicat
ing that these systems were adapted communities, not
stressed ones.
Behavior of the seasonal model also suggested
that the inner bay system was quite different from the
249
unaffected areas. Model responses similar to patterns
measured in the control areas could not be obtained by
adjusting only temperature, sunlight, and initial biomass
storages to conditions found in the control areas, sug
gesting that pathway coefficients and, thus, the basic
nature of the two systems were different.
Because of the period of adjustment and reorgani
zation within the ecosystem which may occur in response
to thermal alteration, any assessment of environmental
impact during the period of transition may provide a
false picture of the long-term consequences of a thermal
addition. A truer assessment of impact would be the
structure and function of the ecosystem resulting only
after adaptation to the new environmental conditions
has taken place.
Temperature and Selection for Faster Turnover
A major adaptation of the inner discharge bay
to increased temperatures may have been a shift of meta
bolic activity away from the benthic compartments towards
the phytoplankton component in the water column. McKellar
(1975) found a similar trend for the deeper outer bay
areas, and discussed how the push-pull effect of tempera
ture action on system pathways might lead to selection
for smaller biomass with rapid turnover in order to main
tain the same rate of energy flow within the system.
250
In the inner discharge bay, benthic producer biomass and
primary production were lower than in the unaffected
areas, while the much-reduced respiration of the bottom
muds suggested possible selection for a much lower biomass.
The very low biomass of benthic invertebrates in the
inner bay accounted for virtually all the difference
in the total biomass of larger consumers between the
two areas. Plankton primary production, on the other
hand, was much larger in terms of both percentage of
total community production and actual magnitude in the
inner discharge bay than in the unaffected intake area.
Similar standing stocks of phytoplankton, resident
fish, and oyster reef biomass between the two areas may
have indicated that the increased phytoplankton primary
production was available for consumption by higher trophic
levels. For producer organisms such as phytoplankton,
which generally produce more organic material in photo
synthesis than is required to satisfy their individual
respiratory demands, the push-pull temperature model
would predict an increase in standing stock with in
creases in the rate of photosynthesis if no compensa
tory increase in grazing also took place. This occurred
for benthic plants in the seasonal simulation, which were
not grazed directly in that model. Phytoplankton biomass
remained the same, while its productivity increased
slightly, indicating that the increased biomass produced
was being removed through grazing and flushing.
251
For all organisms the model predicts lower stand
ing stock levels with temperature increases unless input
energy sources are nonlimiting. That increased primary
production was supplying higher trophic levels in the
seasonal simulation was indicated by the increased fish
biomass and lack of decline in the invertebrate stocks
from the increased predation. Organic matter in the
sediments declined, while that in the water remained
the same suggesting that they were helping supply the
increased ingestion demand of these consumer populations.
McKellar (1975) found a similar response in a computer
simulation model of the outer bay system at Crystal
River.
In the inner discharge bay, phytoplankton may
have been able to capture more sunlight to support the
increased photosynthesis stimulated by higher temperatures.
This additional production may have been grazed back by
consumers, keeping phytoplankton standing stock at its
former level and allowing the increased consumer respira
tory demands to be matched by ingestion so as to maintain
their previous standing stock levels. Shifting of rela
tive reef composition to a larger total oyster biomass
but smaller quantities of other reef organisms may
further indicate the emphasis on a grazing food chain.
A shift to a detritus diet in middle juvenile stages of
pinfish (Lagodon rhomboides) in the inner discharge bay
from an epiphyte diet in the south intake areas (Adams,
1972) suggested a different food web within the fishes
also.
Predictions of the Effect of the
Operation of Unit Three at Crystal River
The response of the simulation models to condi
tions expected for the operation of Unit Three at Crystal
River may be used as possible predictors of the effect
of this plant when it comes on line. Because validation
of some aspects of the seasonal model was not good, in
ferences drawn from its responses must be used with
caution. Nevertheless, results of these simulation
models may still be better vehicles for predicting future
impact than the mental models often used by decision
makers.
Both simulation models were relatively insensi
tive to the small increase in temperature expected from
the operation of Unit Three. In fact, if a temperature
rise was the only expected effect the models predicted
that metabolism would be stimulated somewhat. However,
the data suggested and behavior of the seasonal simulation
supported the idea that turbidity may have been the major
factor controlling productivity in the inner bay. If
this is true, the effect of Unit Three could be large.
Since the water velocity in the discharge was expected
253
to double, the sediment load of the plume water could
increase because of increased scouring. Couple-d with
an increase in the mixing ratio of canal water to off
shore water contributed to the inner bay on a rising
tide, average turbidities as well as temperature could
increase. In the simulation run using these conditions,
the stimulation of metabolism by increased temperature
was more than offset by the reduction of photosynthesis
from increased turbidity.
Energy Costs of Alternatives to Estuarine Cooling
of the Thermal Discharge at Crystal River
Regulatory agencies concerned with licensing of
Unit Three at Crystal River have suggested closed-cycle
cooling towers as one means of alleviating the reduction
in energy flows in the estuarine environment resulting
from the use of once-through cooling. The dollar cost
of technological alternatives, however, represents an
energy expenditure and effect on the environment which
must be accounted for somewhere else in the economy.
On this basis any man-made substitute for the use of
the natural environment for cooling must pass the test
of returning more energetic benefits than the energy
costs incurred in its construction and alteration and
displacement of natural ecosystems.
254
Such an energy evaluation may be calculated by
examining the total energy costs associated with the alter
natives at Crystal River of cooling towers or a once-through
cooling system. By using energy instead of money, the con
tributions and costs to natural systems with which no direct
money payments are associated are included in the calculation.
In man's economy the magnitude of the money flows circulating
in the opposite direction as energy may be an index of the
quantity of energy flowing (Odum, 1971). In natural systems
energy flows may often be measured directly in energy units.
After conversion of all the different types of energy to the
same concentration or quality level (often fossil fuel
equivalents are chosen), all flows may be added together and
the total energy involvement calculated for both cooling
alternatives.
The difference between the yearly total gross
primary production of the control areas and the inner
bay (difference in the area under the curves in Figure 36)
may be taken as one of the energy costs of once-through
cooling at Crystal River. After converting to a common
denominator of fossil fuel equivalents (FFE) using factors
from Odum ejt aj_. ( 1 974), the energy cost to the region is
9
calculated as 0.17 x 10 FFE kcal/yr. Converting the money
cost of construction and maintenance of mechanical draft
cooling towers to its energy equivalent gives an energy cost
255
of 276 x 10^ FFE kcal/yr (Kemp ejt ajk 1 975 ), much larger
than the energy cost of once-through cooling. Expanding the
calculation for the once-through option to include all other
environmental impacts, such as loss of larvae and juveniles
of many species and impingement losses of fish at the cooling
water intake, still found cooling towers to be much more
energy expensive.
As fossil fuels became scarcer, the system that uses
these fuels for jobs which can be done at a cheaper energy
cost by the natural environment may not remain economically
competitive with systems that utilize the free services of
nature in concert with their economy. At Crystal River, the
construction of cooling towers would appear to be energetical
ly wasteful .
APPENDICES
APPENDIX A
EXPLANATION OF THE ENERGY SYMBOLS USED
IN THIS STUDY
258
Given below are brief explanations of the symbols
of the energy circuit language used in the model diagrams
in this dissertation. More complete discussions of these
and other symbols may be found in H. T. Odum (1971, 1972,
1973).
Energy Source Module. A source of
energy or material external to the
boundaries of the system of inter
est. The driving force may be con
stant or time varying and is inde
pendent of behavior of the system
within the boundary.
Storage Module. Storage of energy
or material within a system. The
quantity in storage fluctuates with
time as a function of the inflows
and outflows (dQ/dt = J-] J2),
where depreciation losses are in
cluded in the outflow pathway.
Self-Maintaining Consumer Module.
An aggregated module representing
a consumer unit. Included inside
are at least one storage module and
one work gate interacting to do
work on input energy to that unit,
providing a logistic response. When
used only as a visual symbol for
organizing model components no path
ways are implied beyond those ac
tually shown.
259
Production and Regeneration Module.
An aggregated module representing
the combination of the capture of
pure energy such as light feeding
a self-maintaining module, and a
work feedback loop controlling
inflow processes. Usually used to
depict green plants. When used as
a visual symbol only, it may repre
sent the production and consumption
of entire ecosystems.
Heat Sink. Energy conversion to
heat with each work process.
Pathway of Energy Exchange. Flow
of energy or materials. Barb indi
cates a one-way flow; no barb indi
cates back forces acting along the
pathway. Heat sink represents
frictional and back force losses.
N2
Adding Junction. Adding of two
flows, where J3 = J] + J2.
Work Gate. An interaction in which
the resultant flow is some specific
function of the interacting forces.
Often the function is considered
multiplicative, giving J = kN]N2.
N] and N2 may be external driving
forces, internal storages, or
forces caused by flows.
260
N2
C>^Ns
Jl
Two Way Work Gate. Flow along path
way driven by N2 may be in either
direction depending on conditions
determined by N], N2 and N3:
J = kN2(N] N3). N-| and N3 may
be sources or sinks external to the
system or storages within the system.
N2 may be a flow, internal storage
or external source.
Force Delivered from a Flow. An
interaction in which a flow of
energy along one pathway (J]) de
livers a force for driving an
energy flow along a second pathway
(J2). The delivered force is pro
portional to the flow from which it
is derived (J-j).
J2 = kNJ-,
An example is transport of sus
pended material by a water flow.
Drag Action Work Gate. Special
type of work gate in which an in
crease in one flow, internal stor
age, or external source (N-|) has a
retarding effect on the output
flow (J) of another source or stor
age (T^)- Sensor symbol indicates
that there is no appreciable loss
from N] in this interaction.
J = k2N2(l k-jN])
261
N
Flow-Limited Interaction. An inter
action in which the resultant flow
(J2) is a function of a constant
flow (JQ). J2 may *3e limited by
J0 because as X increases, J2 may
increase only to the point at which
all of J0 is being utilized. Since
J0 is an independently fixed quantity
of flow, J2 cannot draw more energy
from the source (SJ than is flowing
per unit of time.
Logic Switch. Flow J is turned on
or off by logic processes within
S, controlled by processes of N.
APPENDIX B
GRAPHICAL ANALYSES OF DIURNAL STUDIES OF COMMUNITY
METABOLISM IN THE INNER BAY AFFECTED BY THE THERMAL
DISCHARGE PLUME AND IN THE FORT ISLAND AND HODGES ISLAND
AREAS AWAY FROM THE INFLUENCE OF THE THERMAL DISCHARGE.
DOTTED RATE-OF-CHANGE CURVE IS PLOT OF RAW CURVE OF
OXYGEN PER SQUARE METER. RATE-OF-CHANGE CURVE WITH OPEN
CIRCLES IS CORRECTED FOR TIDAL CHANGES. REMAINING
RATE-OF-CHANGE CURVE IS ALSO CORRECTED FOR OXYGEN
DIFFUSION.
PtfcCENT
S4Tu;aT vOts SAumrry ¡SEPT^
& § ^ ^ to o' N & ^ g Ca ci
263
Inner Discharge Bay
14-15 June 1972
O
%
3,
T~
4
Otoo /Zoo /8ao
264
Inner Discharge Bay
21-22 June 1972
-*V-*uV'co uJo
265
Inner Discharge Bay
29-30 June 1972
1
1
o0
x
266
Inner Discharge Bay
7-8 July 1972
SAUUOY
267
Inner Discharge Bay
2-3 August 1972
0603 tZoa
/Qoa,
268
Inner Discharge Bay
14-15 December 1972
OfcOO
12.00 \Q OO
QVufe
269
Inner Discharge Bay
22-23 January 1973
270
Inner Discharge Bay
31 January and 1 February 1973
271
Crystal River Plant
May 10-11, 1973
272
Crystal River Plant
May 11-12, 1973
aiH
273
Inner Discharge Bay
17-18 June 1973
274
Inner Discharge Bay
17-18 June 1973
1
O
r
s
275
Inner Discharge Bay
June 18-19, 1973
Ofeoc
\ OQ
'i&oo
276
Inner Discharge Bay
June 19-20, 1973
OioOb
1800
17.00
277
Inner Discharge Bay
June 20-21, 1973
278
Inner Discharge Bay
June 22-23? 1973
\ BOC.
279
Inner Discharge Bay
July 26-27, 1973
\6oo
^E.ur
280
Inner Discharge Bay
Aug 2-3, 1973
\e>oo
bOO
I2.O0
281
Inner Discharge Bay
22-23 August 1973
O&oo /zoo /8oc>
'*>**/
282
Inner Discharge Bay
Aug 23-24, 1973
0(oCO
IlOO
\ftoo
283
Inner Discharge Bay
Aug 24-25, 1973
284
Inner Discharge Bay
Aug 25-26, 1973
>'
P
Z b
4 *
\0
0,5'
04 oo
rzoo
285
Inner Discharge Bay
Aug 26-27, 1973
OCoOCi
lioo
/ Bao
Inner Discharge Bay
Aug. 27-28, 1973
287
Inner Discharge Bay
Oct. 29-30, 1973
O&OG
l"2.c>o
iaoo
CE.NT
SAfTO^KTvoM cpm OJ^
288
Inner Discharge Bay
30-31 October 1973
\
5~0
J
06,00
I Zoo
l8co
wl
289
290
Inner Discharge Bay
May 24-25, 1974
C>oC¡C¡
/2.CXJ
J 800
291
Inner Dicsharge Bay
25-26 Nay, 1974
oc.oa
r?_oo V0OO
5Aum\TY
Inner Discharge Bay
26-27 May, 1974
00.00
I ZOO
/Boo
293
Fort Island
Aug 2-3, 1972
294
Fort Island
10-11 August 1972
1
O
:r
T
SAU H \TY TENKf>
295
Fort Island
13-14 Feb, 1973
296
Hodges Island
22-23 February 1973
l Zoo
IBCO
297
Fort Island
25-26 June 1973
O o
/£>£>
298
Foi't Island
26-27 June 1973
| 2-0 £>
/8oo
299
Fort Island
26-27 June 1973
300
Fort Island
27-28 June 1973
O (&C>£>
I luo
\ 0OO
301
Fort Island
28-29 June 1973
7
302
Fort Island
16-17 August 1973
303
Fort Island
26-27 August 1973
O Oo
02.OO
\ So o
304
Fort. Island
27-28 August 1973
OUD
Fort Island
12-13 November 1973
3 0 6
Fort Island
13-14 November 1973
307
Fort Island
14-15 November 1973
17X0
l&Co
308
Fort Island
15-16 November 1973
309
Fort Island
26-27 May 1974
OCc>( o
VZ.00 iBco
310
Fort Island
25-26 May 1974
OfcH lO
APPENDIX C
INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, HEAT
BUDGET CALCULATIONS, CALCULATION OF TRANSFER COEFFICIENTS,
SCALED EQUATIONS, POTENTIOMETER SETTINGS, FUNCTION GEN
ERATOR SET-UP, AND ANALOG COMPUTER PATCHING DIAGRAM FOR
DIURNAL SIMULATION MODEL OF INNER BAY (Figure 40).
Table C-l. Documentation of values used for forcing functions, standing stocks, and
exchange rates in the diurnal simulation model of the inner bay (Figure
40). 1.1 m was used as average depth.
Storage Description
Calculation
Reference
Q-, Total phosphorus in
water column
Qp Heat content of bay
water
Q, Oxygen concentration
in bay water
Q. Total organic carbon
in bay water
Qr Biomass of seagrass
i n bay
1
Aver. cone. = 0.045 g P/m
(0.045 g P/m3) (1.1 m) = 0.05 g/m2
Summer diurnal range: 5-7 mg/1
Assume midnight value half way between
high at dusk and low at dawn = 6 mg/1
(6 g/m3) (1.1 m) = 6.6 g/m2
(5 g/m3) (1.1 m) = 5.5 g/m2
2
Summertime standing stock = 25 g/m
Assume 50% refractory material
(25 g/m2) (0.5) = 12 g/m2
McKellar, 1975
Appendix B
Figure 28
CO
rx>
Table C-l continued
Storage
Description
Calculation
Reference
%
Biomass of labile
organic material in
seagrasses
Assume 50% of seagrass standing stock
is labile
(25 g/m2) (0.5) = 12 g/m2
7
Biomass of consumers
Figures 26, 27
Flow
Description
Calculation
Reference
Jo
Average hourly in
solation reaching
water surface
Average daily insolation in June
= 5610 kcal/m2/day
Figure 13
1-5610 kcal/m /day) ^qq kcal/m2/hr
14 hrs daylight 4UU Kcai/m /nr
JR
Unused solar insolation
Assume 50% of sunlight unused in
photosynthesis
(400 kcal/m2/hr) (0.5) = 200 kcal/m2/hr
J1
Solar insolation
utilized in photosyn
thesis
Assume 50% of sunlight used in
photosynthesis
(400 kcal/m^/hr)(0.5) = 200 kcal/m^/hr
FI ow
Description
Calculation
Reference
Gross production
of labile organic
matter
Summertime daily average gross photosyn- Table 6
thesis
= 3.8 g 02/m2/day
Assume 1 g organic matter produced for
each g 02.
.g/m_7day g 271 a/m2/hr
14 hrs sunlight u'/l g/m /nr
2
Assume rate is 0.3 g/m /hr 0 2 pm.
Gross oxygen
production
Assume daytime net photosynthesis plus
night respiration = gross photosynthesis.
2
Assume rate is 0.3 g/m /hr 0 2 pm.
J* Average hourly
respiration
Assume steady state conditions so that all
labile material produced during daylight
is utilized over 24 hours.
Table C-l continued
Flow Description
Calculation
Reference
J
5
Maintenance
respiration degrad
ing organic matter
into heat
Assume maintenance respiration is 30% of
gross production. Jones (1968) found
Thalassia respiration to be about 10%
of gross production. In steady state
J^ = J^ over 24 hrs.
(0.158 g/m2/hr) (0.3) = 0.048 g/m2/hr
Day et al_., 1973
Jones, 1968
J, Labile organic
material stored as
standing crop
Difference between gross respiration
(J^) and maintenance respiration (J^).
(0.1580 g/m2-hr 0.0474 g/m2-hr
= 0.1106 g/m2.hr
CO
cn
Jy Loss of benthic Assume steady state. Therefore, Jg = J^
producer standing
stock to organic
detritus pool
Table C-l continued
Flow Description
Calculation
Reference
Jg Respiration of Assume respiration rate of 0.085 g dry wt Day et aj_., 1973
consumers respired/g dry body wt/day
2
(6 g/m ) (0.085 g respired/g body wt/ day)
(1 day/24 hrs) = 0.021 g/m2-hr
Jq Assimilation of Assume steady state so that assimilation
ingested organics by (Jg) equals respiration (Jfi)
consumers
J-.Q Feces production of
consumers
Assume 50% assimilation efficiency. There
fore, assimilation (JQ) = feces production
GO
CT>
J,, Total intake by
1 producers
Total intake (J^) = assimilation (Jg)
+ feces (J-jg)
0.021 g/m^-day + 0.021 g/m2-day
= 0.042 g/m2-hr
Table C-l continued
Flow Description
Calculation
Reference
J-I2 Utilization of Assume 1 g 0 used for each gram of
oxygen by plant
respiration organic matter respired.
Therefore, = Jg.
Van Breedveld, 1966
quoted in Jones, 1968
J,o Utilization of phos
phorus in photo
synthesis
Assume organic matter produced is 0.9%
phosphorus.
(0.3 g/m2-hr) (0.009) = 0.0027 g/m2-hr @ 2 pm
J-]4 Advective addition Assume addition from this source only on
of total phosphorus rising tide. Assume power plant cooling
from power plant water 1/3 of total flow on rising tide,
cooling water
(P-|) (V rising) (1/3) = J-,4
(0.045 g/m3) (0.10 m3/hr) (1/3)
= 0.0015 g/hr at midnight
CO
*-0
(0.045 g/m3) (0.12 m3/hr) (10 hrs) (1/3)
2
= 0.018 g/m day
Table C-l continued
Flow Description
Calculation Reference
J16
(cont.)
(5.1 g/m3) (0.12 m3/hr) (10 hr) (1/3)
=2.04 g/day
(5.1 g/m3) (0.1 m3/hr) (1/3) = 0.17 g/hr
at midnight
Advective addition
of organic matter
from power plant
cooling water
Assume addition from this source only on
rising tide. Assume power plant cooling go
water 1/3 of total flow on rising tide. ^
(f^) (V rising) (1/3) = J]7
(5 g/m3) (0.12 m3/hr) (10 hr) (1/3) = 2 g/day
(5 g/m3) (0.1 m3/hr) (1/3) = 0.165 g/m2/hr
at midnight
J-jg Utilization of oxygen
by consumer respir
ation
Assume 1 g 0g utilized for each g organic
matter respired. Therefore, J^g = Jg
Table C-l continued
Flow Description
Calculation Reference
J,r Advective addition of
heat from power plant
cooling water
Assume addition from this source only on
rising tide. Assume power plant cooling
water 1/3 of total flow on rising tide.
Heat content = CpT = (1000 kcal/m3-C)
(33.5C) = 33500 kcal/m3
(H + C) (V rising) (1/3) = J]5
OJ
(33500 kcal/m3) (0.12 M3/hr) (10 hr) (1/3)
= 13400 kcal/day
(33500 kcal/m3) (0.1 m3/hr) (1/3)
= 1117 kcal/'hr at midnight
J,g Advective addition of
oxygen from power
plant cooling water
Assume addition from this source only on
rising tide. Assume power plant cooling
water 1/3 of total flow on rising tide.
(X,) (V rising) (1/3) = J]6
Table C-l continued
Flow Description
Calculation Reference
J,gR Advective exchance
of organic matter
with offshore area
Rising tide: addition from offshore
2/3 of total addition.
(M2) (V rising) (2/3) = JigR
(5 g/m3) (0.12 m3/hr) (10 hr) (2/3)
= 4 g/day
(5 g/m3) (0.1 m3/hr) (2/3)
= 0.333 g/hr at midnight
J19F
Falling tide: entire exchange through
this pathway.
(Q4) (V falling) = Jigf-
(5.0 g/m3) (0.108 m3/hr) (12 hr) = 6.48 g/day
(5 g/m3) (0.19 m3/hr) = 0.95 g/hr @ 2 pm
320
Table C-l continued
Flow Description
Calculation Reference
J?nR Advective exchange
of oxygen with off
shore area
Rising tide: addition from offshore 2/3
of total addition.
(X2) (V rising) (2/3) = J2QR
(7 g/m3) (0.1 m3/hr) (2/3) = 0.465 g/hr
at midnight
(7 g/m3) (0.12 m3/hr) (10 hr) (2/3)
=5.6 g/day
J20F
Falling tide: entire exchange through
this pathway.
(Q3) (V falling) = J2QR
(6 g/m3) (0.19 m3/hr) = 1.14 g/hr 0 2 pm
(6 g/m3) (0.108 m3/hr) (12 hrs) = 7.78 g/day
Table C-l continued
Flow Description
Calculation Reference
J,R Advective exhcange
of heat with
offshore area
Rising tide: addition from offshore 2/3
of total addition.
Heat content C T = (1000 kcal/m3-C) (28.5C)
r
= 28500 kcal/m3
(H) (V rising) (2/3) = J21R
(28500 kcal/m3) (0.12 m3/hr) (10 hrs) (2/3) £
no
= 22800 kcal/day
(28500 kcal/m3) (0.1 m3/hr) (2/3) = 1900
kcal/hr at midnight
J21F
Falling tide: entire exchange through this
pathway.
(Q3) (V falling) + J21fr
(28500 kcal/m3) (0.108 m3/hr) (12 hrs) (2/3)
= 24624 kcal/day
Table C-l continued
Flow Description
Calculation
Reference
J21F
(cont.)
(28500 kcal/m3) (0.19 m3/hr) = 5415 kcal/hr
@ 2 pm
J?R Advective exchange
of total phos
phorus with off
shore area
Rising tide: Addition from offshore 2/3 of
total addition.
(P2) (V rising) (2/3) = J22R
(0.045 g/m3) (0.1 m3/hr) (2/3) = 0.003 g/hr
at midnight
(0.045 g/m3) (0.12 m3/hr) (10 hrs) (2/3)
= 0.036 g/day
J22F
Falling tide: entire exchange through
this pathway.
(Q-,) (V falling) = J22F
323
Table C-l continued
Flow Description
Calculation
Reference
J22F
(cont.)
(0.045 g/m3) (0.108 m3/hr) (12 hrs)
= 0.058 g/day
(0.045 g/m3) (0.19 m3/hr) = 0.0086 g/hr
@ 2 pm
Jp-. Phosphorus re
generated by
respiration of
benthic producers
Assume organic matter is 0.9% phosphorus.
Phosphorus comes from maintenance
respiration.
(1.14 g/m3-day) (0.009)
24 hrs/day
= 0.000428 g/m3'hr
Van Breedveld, 1966,
quoted in Jones,
1968
J?. Phosphorus re
generated by
respiration of
consumers
Assume organic matter 0.5% phosphorus.
1 -5J29/^dayj_jp_,pp5| = 0.000106 g/m2'hr
Radiative heat loss = 0.97oT ^
to atmosphere
324
Table C-l continued
Flow Description
Calculation
Reference
J25 r = (0.97) (1.171 x 10"6 kcal/m2- day- K4)
(cont.) .
(305Kr
d>r = 9829 kcal/m2-day = 410 kcal/m2-hr
Sediment respir- Assume P/R ratio of 1; gross production (O^)
= total respiration. Sediment respiration
= total respiration plant respiration -
consumer respiration.
J26 = J2 J5 J8
= 3.8 g/m2-day 1.14 g/m2;day 0.51 g/m2-day
= 2.66 g/m2-day = 0.1108 g/hr
Assume organic matter 0.5% phosphorus.
J27 = (J26} (-005)
J7 Phosphorus re-
' generated by
sediment
respiration
325
Table C-l continued
Flow Description
Calculation Reference
J27
(cont.)
J27 = (2.66 g/day) (0.005) = 0.0133 g/day
= 5.54 x 10 4 g/hr
Joo Oxygen utilized
in sediment
respiration
Assume 1 gram oxygen required for each gram
organic matter respired.
J28 = 26
Jpq Heat from
evaporation
4> = p(a + boo) (e ^e ) (595.9 0.54 T ) Huber and
Harleman, 1968
Assume everything constant except Ts Table C-4
(water temperature). Ignore heat carried
away by evaporated water.
2
cj>e = 474 kcal/m hr at midnight
Joq Heating of water
by solar radiation
Assume all solar input absorbed by water.
326
Table C-1 continued
Flow Description
Calculation
J
30
(cont.)
J30 Jo
J^g = 400 kcal/m /hr
J
31
J
32
Back radiation from
atmosphere
Diffusion of oxygen
between atmosphere
and water
Assume average 24 hour air temperature of
20C.
J31 = 0.97a T4
J31 = (0.97) (1.171 x 10'6 kcal/m2 day'-K4)
(293K)4
J31 = 8832 kcal/m2-day = 368 kcal/m2;hr
Qo
C3 = oxygen value at 100% saturation
Reference
327
Table C-l continued
Flow Description
J
32
(cont.)
Calculation
= quantity of oxygen in water column
D = depth
Rp = average diffusion coefficient
Evaluated at midnight:
(6.25 y^-) (|^||) = 0.01 g/m2. hr
Reference
328
329
Table C-2. Initial and maximum values of storages for
diurnal simulation model of inner bay (Figure
40). Initial values are for conditions at
midnight.
Storage
Initial
val ue
Maximum value
Water column
Volumetric
Water column
i
0.023 g
0.045 g/m3
0.15 g
q2
16640 kcal
32C
60000 kcal
Q3
3.12 g
6 ppm
18 g
^4
2.6 g
5 g/m3
15 g
5
12 g
20 g
%
12 g
--
20 g
7
6 9
10 g
330
Table C-3. Initial and maximum values of forcing func
tions for simulation model of inner bay
(Figure 40). Initial values are for mid
night.
Forcing function
Initial value
Maximum value
Pl P2
0.045 g/m3
0.10 g/m3
H
28500 kcal/m3
35000 kcal/m3
H + C
33500 kcal/m3
40000 kcal/m3
xi
5.1 g/m3
8.0 g/m3
X2
7.0 g/m3
12.0 g/m3
Mr M2
5.0 g/m3
10.0 g/m3
J0
0
840 kcal/hr
V
0.1 m3/hr
0.2 m3/hr
D
0.52 m
2 m
331
Table C-4. Calculation of radioactive, evaporative,
and convective heat losses for use in
diurnal simulation model of inner bay
(Figure 40). Formulae are from Huber and
Harleman (1968).
Radiative heat loss: <¡> = 0.97a T 4
a = Stefan-Boltzman constant = 4.877 x 10~8 kcal/m2-hr-K
Ts = water temperature (K) = 305K
0.97 = emissivity of water
<|> = (0.97)(1.171 x 10"6 kcal/m2-day-K4)(305K)4 = 9829 kcal/day
Evaporation: = p(a + bu)(e_ ipe_)L
6 S3
3 6 3
p = density of water = 1 g/cm = 10 g/m
-4
a = empirical constant = 3.08 x 10 m/day-mm Hg
-4
b = empirical constant = 1.85 x 10 /sec/day-mm Hg
w = wind speed = 8 mph = 3.58 m/sec
es = saturation vapor pressure of water (32C) = ^36 mm Hg
e, = saturation vapor pressure of water (24C) = ^22.5 mm Hg
a
\p = relative humidity = 0.7
L = latent heat of vaporization
595.9 0.54 T
s
595.9 (0.54)(32C) = 578.6 cal/g
4>e (iO8 kg/m8)[3.08 x 10 4 m/day-mm Hg + (1.85 x 10 4
sec/day-mm Hg)(3.58 m/sec)][(36 mm Hg) (0.7)-
(22.5 mm Hg)](578.6 kcal/kg)
332
Table C-4 continued
Evaporation (continued)
4> = 11365 kcal/m^-day
Heat content of evaporated water:
c Yv s Y a P s
Cp = specific heat of water = 1 kcal/kg-C
4>v = (103 kg/m3)(9.7 x 10 4 m/daymm Hg)(20.25 mm Hg)-
(1 kcal/kg-C)(32C)
4> = 629 kcal/m^-day
Convective heat loss: = Np(a + bw)(T_ T.)
C S d
N = proportionality constant = 269.1 kcal-mm Hg/kg-C
Ts = water temperature (surface) = 32C
T = air temperature (daily average) = 26.7C
<\>c = (269.1 kcal-mm Hg/kg-C)(103 kg/m3)(9.07 x
10"4 m/day-mm Hg)(5.3C)
cf>c = 1294 kcal/m^-day
333
Table C-5. Calculation of transfer coefficients for
diurnal simulation model of inner bay
(Figure 40). All evaluations calculated
for conditions at midnight except those
associated with photosynthesis or falling
tide, which were evaluated at 2 pm.
Coefficient
Calculation
k
o
k
1
k
R
k
2
k
3
JQ k S(l-D) = kQ(780)(0.6) = 429 kcal/hr @ 2 pm
. 429 _
Ko (780)(0.6) 1
J-j = k]JqQ-,T = 215 kcal/hr @ 2 pm
k
215
1 (468)(0.023)(32)
0.6241
Jr = kRJQ =215 kcal/hr 0 2 pm
kR = m -5
J2 = k2Jo TH^T = -3 9/hr 0 2 Pm
. (D0.3)
K2 (439)(0.023TT32T
= 9.501 x 10
Jg = J^; therefore, k^ = k^ = 9.501 x 10
k4 J4 = k4Q6TQ3 = 0.158 g/hr
= 1.32 x 104
. 0.158
k4 (12)(32)(3.12j
335
Table C-5 continued
Coefficient
Calculation
k
12
k
13
k
14
k
17
J12 = k12^3^6T = -0474 g/
0.0474
'12 137127(12) (32)
= 3.96 x 10
-5
QlT
13 k13o kR+k]Q1T = -0024 9/hr @ 2 Pm
(0.0024)(1)
'13 1429) (0.023) (327
= 7.6011 x 10
-6
J14 = k14PlVn(1/3) = 0.0015 g/hr
. (0.0015)(3) ,
K14 16771(0.0451
J15 = ki5HV(l/3) 1117 kcal/hr
k (1117)(3) _
K15 (33500)(0.1) 1
J16 = k16X1 V(l/3) 0.17 g/hr
i k (0.17)(3) i
J16 k16 (5.l)(07l7
J]7 k-j7M1 V( 1 /3) = 0.167 g/hr
, (3)(. 167)
i 7 (5)(0.19)
1
Tab!e C-5 continued
Coefficient
Calculation
Jg = not needed in patching
J6 = k6Q6TQ3 = -1108 9/hr
k. =
0.1108
6 (12)(32)(3.12)
= 9.25 x 10
J^ = kyQg = 0.1106 g/hr
k7 = 'i2^6 = 9,22 x 10"3
Jg = kgQyTQ^ = 0.021 g/hr
x. = 0-021 = o c*i y in-5
k8 (6)(32)(3.12) J,b 10
Jg = kgQ4Q7 = 0.021 g/hr
, 0.021 .. n-3
k9 "(2.6)(6) 1-35 10
v10
JlO = Jg; therefore k^ = kg = 1.35 x 10
-3
'll
Jn = knQ4Q7 = 0,042 g/hr
l, = 0-042 = o :q y -io-3
kll (2.6)(6) 2,69
336
Table C-5 continued
Coefficient
Calculation
'18
J18 = k!8T^3^7 = 021 9//hr
_ 0.021
'18 (32) (3.12) (6T
3.51 x 10'
'19R
J19R = ki9R(M2)(V)(2/3) = -333 9/m /hr
. (3)(0.333) _
k19R T2) (5) (. 1) 1
'19F
V
19F = k19F ~D~ = 0-95 g/hr (2 pm^
, (1.0)(0.95) ,
K19F (5.0)(0.19) 1
'20R
J20R = k20R (x2)(v)(2/3) = -465 9/hr
- (3)(0-465)
'20R (2) (7) (0.1T
20F
Q3V
J20F k20F D = 0,95 g/hr
k 0.0)0.79) ,
K20F (5)(0.19) 1
'21 R
J21r = k21r(h + C)(V)(2/3) = 1900 kcal/hr
(3)(1900)
C21R (2)(28500)(0.1)
= 1
337
Table C-5 continued
Coefficient Calculation
Q2V
k21p J^p = k2(
. _J1.0)(5700) .
K21F ~ (30000)(0.19) 1
k22R J22R = k22(P2)(V)(2/3) = 0.003 g/hr
(3)(0.003) .
22R (2)(0.045)(0.1) 1
Q1V
k22p J22F = k22p -p- = 0.0095 g/hr
(1.0)(0.0095) ,
22F TO.05)(0.19) 1
J23 = k23Q6TQ3 0.000428 g/nf/hr
0.000428
'23 (12)(32)(3.12)
= 3.57 x 10
-7
2^Q^TQ3 = 0.000106 g/m2/hr
0.000106 ,, in-7
24 (6)(32)(3.12) l,// X IU
25(0.97)(a)(T)4 410 kcal/m2/hr
. 410 __
25 (0.97H4.879 x 10") (8.6537 x 109) = 1.0
338
Table C-5 continued
Coefficient
Calculation
'26
Not needed for patching
27
^*27 = k27^3 = -000554 g/m -hr
k = P..r.00054 = 5 55 x ln"6
K27 (32)(3.12) X IU
'28
^28 = ^28^3 = -Hl g/m -hr
1/ 0.111 ,, m-0
k28 (32)(3.12) 111 x 10
'29
^29 = k29 + bL)(es 4ea^b = 11365 kcal/m -day
11365
29 11365
k^Q J30 = k30^ = kcal/h>"
k s = ^ = 1
k30 810 1
k
31
J3i = k^oO^ = 368 kcal/m^-hr
_ 368
31 368
Qo Rn
k32(cs Tr)(c> =0-01
S
k MI ,
k32 0.01 1
Table C-6. Equations of Table 7 scaled
bay given in Figure 40.
d
Q,1
Lo. 15_
(0.1)(0.2)k14kpl
r,i
V
dt
(0.15)(3)
L o. i _
[_0.2 J
(0.15)(0.2) k
(0.15) (21
(10)(18)(40)k24
n'
rv i
.0.15.
.0.2.
*D"
2
ro7i
P3l
L i o _
LIS,
+
0.15
£l-i
for simulation of diurnal model of the inner
j (2)(0.1)(0.2) k22Rkp2
rp2i
V
\ (3)(0.15)
.i
[_0.2 J
(20)(40)(18)k23
Q6]
T
"3l
0.15
20
40
_ 18_
(18)(40)k27
rq3i
t
,k 0 (
0.15
!8
40
13olkR
339
Table C-6 continued
'1
0.15J
dt
(0.0200)
V
0.2.
(0.0400)
V
0.2
(0.1000)
1
V
0.15
0.2.
D
2
+ (0.0343)
r6l
T
r3l
L 20 J
L40_
L 18 J
(0.0084)
rv
Psl
T
rQ3i
T "
Lio.
L 18_
l_40j
+ (0.0267)
L 18j
L 40 J
- k
13Jo
V
kR + klQlTl
*
q2
d
C
1.60000 J
(40000) (0.2)!<15
H 5000
V
840
J30
dt
(60000)(3)
.40000 40000_
0.2
60000
L 840
(continued)
340
Table C-6 continued
/ (2)(40000)(0.2)k2]R
r H2 i
V
l (60000)(3)
[_40000_
[o. 2_J
(9.5979 x 109)(0.97)(4.879 x 10'8L k25
60000
595.9 k29
( 595.9
(40)(0.54)
rT 1
60000
l 595.9
595.9
_40_
(60000)(0.2)k21p
(60000)(2)
^ 313
(0.97)(1.171 x
1O-6)(7.781 x 109)k31
+
60000
Table C-6 continued
.60000.
dt
= (0.0444)
H
40000
+ 0.125
~ V
_0.2 _
+ (0.0140)
J30n
840
+ ^ (0.0889)
H
V
40000
0.2
- (0.1000)
60000
0.2
- (0.0076) (0.1278)
T_
40
+ 0.8727
- (0.0081)(1 0.0362
x
40
) + (0.0058)
293
d
3
. 18.
(8)(0.2)klgkxl
rxii
V
/ (2)(12)(0.2)k2QR
r xzi
V
c
t
(18)(3)
8 ^
0.2
1 (3)(18)
L 12_
|_ 0.2
continued
342
Table C-6 continued
(18)(0.2)k2QF
'Vl
L18_
V
_0.2_
08) (2) 1
i
)'
Mn
3 o
+
(18) (10) (40) k,8
rvi
[V
T
18
_18_
_10_
_40_
+
(0.0189)
V
0.2
^ (0.0889)
- M
QlT
3 0 \ kR + klQlT
+ (0.0316)
Q '
2
o cn
Q-,T ^
(20)(40)(18)k]2
Os"
T
V
kR+ kiQiTy
+ 18
20
40
18
(18)(40)k2g
^3~!
T
18
Lisj
40
rx2i
V
12
L0.2_
T
40
18
- (0.1000)
V
0.2
+ (0.0140)
fal
rtl
T
18
10
40
continued
343
Table C-6 continued
+ (0.0444)
r3*i
T
18
40
d
1 1
LO
O
1 I
(10)(0.2) k17kM1
phi
V ^
(20) k7
dt
(15)(3)
L i_
_0.2_
15
L 20 J
(2)(10)(0.2) k]9RkM2
-M
2
10__
V
(15)(0.2) k]9F
1 H
a- kn
O' |r
1 1
" V
L0.2
(3)(15)
0.2
(15)(2)
-D*
L2J
(10) (15) k1Q
P?]
rvi
(10) (15) kn
P7l
[\1
15
L10^
J 5_
+ 15
_10J
Ll 5J
344
Table C-6 continued
(0.0222)
rMii
V
_1 oj
[_0.2j
- 1.333 (0.0092)
(0.0444)
r M ~i
2
V
L 10-
_0.2_
- (0.1000)
- (0.0135)
r7]
jo.
_15 _
+ (0.0269)
U>
-P*
c_n
dt
(20)(40)(18) k6
r6i
T1
[isl
(20) k7
4.
20
L20_
[_40_
L18U
20
V
T
^3
_20_
[_40_
Ll 8J
(0.0097)
dt
(0.0665)
cji U*
347
Table C-7. Scaling of terms associated with photosynthesis
in equations in Table 10 for diurnal simula
tion model of the inner bay (Figure 40).
d
rii
L 0.15 J
(840) k13
rv
/ (0.15)(40) [A][_
dt
0.15
[_840_
V kR+(0.15)(40)k1[0_]5]
~T
L40J
(840)(6) k
13
(0.15) (5.0) |_S40_
ri
t"
Lo. 1 5
[40
kR
"6^-
-
41
"t
5.0
15. OJ
10
.15.
1_40J
(0.0511)
840
0.15J
(0.1000)+(0.5349)
d
r3]
L18J
(840) k3
rj 1
0
((0.15)(40)
Horn
L0.15J L40J
dt
18
[_840 J
\kR+(0.15) (40)
rQi i fTi
Lo. 15J L40J
- (0.0532)
V
840
rQii
T
Lo.15
L40J
(0.1000)+(0.5349)
fil
"t
0.15 J
[_40J
Table C-6 continued
d
L 20-
/ Qtt \* (20)(40)(18) k4
T
rv
dt
k2Jo 1 kR + k^T ) + 20
[_ 20
[_40J
_ 18 J
k0J
Â¥
2 0 l kR + k-jQ-jT
+ (0.0951)
fie]
T
rVl
. 20.
_ 40_
J8_
(15)(10)kg
r4i
rvi
+
(10)(18)(40) kg
"Â¥
[-Â¥
T
10
L15_|
LioJ
10
.10.
L 18.
_ 40_
dt
(0.0202)
+ (0.0252)
rv
rv
T
_i_
_18_
_40_
*See Table C-7 for scaling.
346
348
Table C-
dt
continued
(840) k2
r j i
0
/ (0.15)(40) [
Qi.l
0.15 J
i 1
L O
20
840
\ kR+(0.15)(40)
rQi i
L0.15J
Vs
i i
= . (0.0479)
Q1 "
T
Lo. 15J
l40
(0.1000)+(0.5349)
0.15
T
40
349
Table C-8. Potentiometer settings for initial run (Figure
43) of diurnal simulation model of inner bay
(Figure 40).
Potentiometer
Setting
Potentiometer
Setting
ki
0.5337
k14kpl
0.0200
10k2
0.4789
kl 5
0.0444
k3
0.0532
k16kxl
0.0189
10k4
0.9510
k,-,k ,
17 ml
0.0022
10
o
7=r
cn
0.2760
10kl 8
0.1400
ik6
0.6650
k19Rkm2
0.0044
k7
0.0092
10
k19F
0.1000
00
o
0.1040
k9
0.0084
k20R
10
0.0089
k10
0.0135
k20F
0.1000
kll
0.0269
k21 R
0.0089
10
10k12
0.3160
k21F
0.1000
kl 3
0.0511
k22Rkp2
0.0040
10
350
Table C-8 continued
Potentiometer
Setting
Potentiometer
Setting
k
2 F
0.1000
icq7
0.6000
1 0k23
0.343
IC depth
0.2600
k24
0.0084
W1
0.4486
100k25
0.7600
m2
0.2617
10k2?
0.2670
1
1 okr
1.0000
CO
C\J
o
r
0.4440
0.0014
k29
0.0081
10
k3 0
10
0.0014
rd
Cs
0.0208
k31
0.1390
A
0.5000
ICQ1
0.1500
B
0.5000
icq2
0.2667
C
0.1000
1 cQ3
0.1667
D
0.1251
icQ4
0.1667
E
0.5833
1 cQ5
0.6000
F
0.0428
icq6
0.6000
G
0.8143
351
Table C-8 continued
Potentiometer
Setting
H
0.0834
10 I
0.3625
J
0.1333
K
0.2083
L
0.7917
M
0.1278
N
0.0872
352
Table C-9. Potentiometer settings for the EAI 580
variable diode function generator used
to produce the tidal volume exchange func
tion given in Figure 42 for the diurnal
model of the inner bay (Figure 40). The
special 12-segment set-up was used.
X
0.000
0.0208
0.0675
0.1459
0.1875
0.3962
0.4375
0.6042
0.7292
0.8959
0.9875
1.0000
f(X)
+0.5000
+0.5000
0.0000
-0.4500
-0.4500
+0.8000
+0.6000
-0.9500
-0.8500
+0.8000
+1.0000
+1.0000
Figure C-l. Analog computer patching diagram of scaled equations
given in Tables C-6 and C-7 for the diurnal simulation
model of the inner bay (Figure 40).
354
APPENDIX D
INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, CALCULA
TION OF TRANSFER COEFFICIENTS, SCALED EQUATIONS, POTEN-
TIOMETRIC SETTINGS, FUNCTION GENERATOR SET-UP, AND ANALOG
COMPUTER PATCHING DIAGRAM FOR SEASONAL SIMULATION MODEL
OF THE INNER BAY (Figure 55).
Table D-l. Documentation of values used for standing stocks and exchange rates in the
seasonal model of the inner bay (Figure 55).
Storage Description
Calculation
Reference
1
Standing stock
of benthic plants
Van Tyne, 1974
^2
Total phosphorus
in water column
Assumed same as outer bay
McKellar, 1975
3
Organic matter in
water column
Measured at Crystal River
Gibson, 1975
Organic matter
in sediments
Measured at Crystal River
Cottrell, 1974
%
Biomass of benthic
invertebrates
Measured at Crystal River,
samples plus core samples,
never worked up. Assumed
samples. Total biomass =
. Venturi pump
. Core samples
same order as Venturi
2 x Venturi samples.
Evink and Green,
1974
%
Biomass of fish
Measured at Crystal River with drop nets.
Assume dry weight 25% of wet weight.
Adams, 1974
R
Oyster biomass
Measured at Crystal River
Lehman, 1975
356
Table D-1 continued
Flow Description Calculation
Reference
J Sunlight reaching
water surface
Average insolation at Tampa, Fla. in
June (1961-72) = 5800 kcal/m2;day x 30
days = 174000 kcal/m2*mo.
Water Information
Center, Inc. (1974)
J, Sunlight used in
photosynthesis
Assume one-half sunlight utilized in
photosynthesis. (174000 kcal/m2-mo) (1/2)
= 87000 kcal/m2-mo.
JR Sunlight unused
in photosynthesis
J J1 = 174000 87000 = 87000 kcal/m2-mo
J~ Gross photosynthesis Total production as measured with the free-
of bottom plants water diurnal method minus phytoplankton
production as measured with light-dark
bottles.
4.12 g/m2-day 0.93 g/m2-day =3.19 g/m2-day
(3.19 g/m2-day) (30 days) = 95.7 g/m2-mo
357
Table D-l continued
Flow Description
Calculation
0- Respiration of
J bottom plants
Assume respiration 30% of gross photo-
synthesis
(3.19 g/m2-day) (0.3) = 0.96 g/m2-day
(0.96 g/m2-day) (30 days) = 28.8 g/m2-mo
J. Uptake of
phosphorus in
photosynthesis
Assume benthic plant matter produced (Jg)
is 0.9% phosphorus.
(3.19 g/m2,day) (0.009) = 0.0287 g/m2-day
(0.0287 g/m2,day) (30 days) = 0.8613 g/m2-mo
Jr Benthic plant
biomass lost to
organic matter
pool in water
col umn
Assume benthic plant storage (Q-|) in steady
state. Therefore, J0 = J~ + J,. + Jr
2 3 5 6
Jj. + Jg = 3.19 g/m2-day 0.96 g/m2-day
=2.23 g/m2-day
Reference
Day et_ aj_., 1973
Van Breedveld, 1966,
quoted in Jones, 1968
358
Table D-l continued
Flow Description
Calculation
J
5
(cont.)
Jg Benthic plant
biomass lost to
organic matter
pool in sedi
ments
J Import of detritus
7 from salt marsh
Therefore, J5 2-'23
=1.12 g/m2-day
(1.12 g/m2-day) (30 days) = 33.6 g/m2-mo
Jg = Jg = 1.12 g/m2-day = 33.6 g/m2-mo
See calculation for Jg.
2
Detrital export from marsh about 1.0 g/m
of marsh area / day. Assume marsh area
draining to inner bay about same area as
inner bay. Therefore, input to inner bay =
1.0 g/m2-day = 30 g/m2 mo
JR Tidal import of
organic matter to
inner bay from
discharge canal
and offshore
Since concentration of organic matter in
discharge water and offshore is similar, total
import to bay is total volume exchange times
concentration.
Reference
Young, 1974
359
Table D-l continued
Flow Description
Calculation
Reference
J,-| Ingestion of
organic matter
by oyster reef
organisms
J, Ingestion of water
:1 column organic
matter by benthic
invertebrates
J,~ Sedimentation of
organic matter
from water column
to sediments
Assume steady state population.
J11 = J23 + J35
J-|i = 0.6 + 0.6 = 1.2 g/m2-day
(1.2 g/m2-day) (30 days) = 36 g/m2-mo
Assume 10% of ingestion by benthic inver
tebrates is by suspension feeding.
J12 = (J20 + J24^ (-1) = 0,106 9/2-day
=3.18 g/m2-mo
Sedimentation rate in inner bay = 5.26
2
g/m -day. Organic matter content of
sediment = 5%
(5.26 g/m2-day) (0.05) = 0.263 g/m2- day
(0.263 g/m2-day) (30 days) = 7.89 g/m2- mo
Cottrel1, 1974
Cottrel1, personal
communication
361
Ia ble D-1 continued
Flow Description
(cont.)
Jq Tidal export of
organic matter
from inner bay
Calculation
(1,030,500 m3/day) (5 g/m3) = ? 5 g/|)12.day
687,000 m2
(7.5 g/m2 day) (30 days) = 225 g/m2-mo
3
Total daily volume exchange = 1,030,500 m
¡1 ,030,500 m3/day) (5 g/mji. = 7.5 g/m2.day
687,000 rri
(7.5 g/m2*day) (30 days) = 225 g/rrf-mo
Reference
J10
Ingestion by fish
of organic matter
J27 J26 + J10
by fish
J10 = J27 J26
J1q = 0.25 g/m2-day = 0.1 g/m2-day
= 0.15 g/m2-day
(0.15 g/m2-day) (30 days) = 4.5 g/m2-mo
360
Table D-l continued
Flow Description
Calculation
Reference
J,, Bacterial
respiration in
water column
Water column respiration as measured with
dark bottles = 0.24 g/m2, day
Water column gross production = 0.93
g/m2-day
Table 6
Table 6
Day et_ al., 1973
Assume phytoplankton respiration is 30% of
gross production.
(0.93 g/m2-day) (0.3) = 0.28 g/m2-day
Bacterial respiration = total water column
respiration minus phytoplankton respiration.
J-|4 = 0.93 0.28 = 0.65 g/m2-day
(0.65 g/m2-day) (30 days) = 19.5 g/m2-mo
J,c Phosphorus input
from salt marsh
to inner bay
2
Detrital input from marsh = 1 g/m -day (see de la Cruz, 1973
calculation for J^). Assume 1 g of detritus
came from 1 g of live plant. Assume 90% of
phosphorus leached from plant upon death.
Juncus roemerianus is 0.15% phosphorus.
Table D-l continued
Flow Description
Calculation
Reference
J-|g Input of
phosphorus from
discharge canal
and offshore to
inner bay
Concentration of phosphorus in canal and
offshore water is the same.
Therefore, J16 = total volume exchange x
concentration
j = (1 ,030,500 m3/da,y) (0.05 q/m3)
16 687,000 m2
= 0.075 g/m day
(0.075 g/m2-day) (30 days) = 2.25 g/m2-mo
J-|7 Tidal exchange of
' phosphorus off
shore
= total volume exchange x concentration
, (1 ,030,500 m3/da.y) (0.05 q/m3)
7 2
17 687,000 ni
= 0.075 g/m3-day
2 ?
(0.075 g/m day) (30 days) = 2.25 g/m mo
363
Table D-l continued
Flow Description
Calculation
Reference
J-|o Sediment By difference after subtracting all other
respiration respiration from total system respiration
as measured by the free-water diurnal oxygen
change method.
Assume total respiration is twice night
respiration.
J
18
total respiration - J..
J18 = 4.34 0.96 0.65 0.30 0.09 0.6
=1.74 g/m^-day
(1.74 g/m2,day) (30 days) = 52.2 g/m2-mo
Jng Ingestion of
sediment organics
by benthic
invertebrates
Assume 90% of ingestion to benthic inverte
brates is by deposit feeding.
^19 ~ (^20 + ^24^ (0.9)
J]9 = (0.53 + 0.53) (0.9) = 0.954 g/m2-day
= 28.62 g/m2,mo
364
Table D-l continued
Flow Description
Calculation
Reference
Feces production
" by benthic in
vertebrates
Assume 50% assimilation of organic intake.
2
Therefore, J^q = = 0.53 g/m -day
2
= 15.9 g/m mo
J2-i Mortality of
benthic inverte
brates
Assume to be 2.5% of standing stock per day.
(3.5 g/m^) (0.025/day) = 0.09 g/m^-day
(0.09 g/m^-day) (30 days) = 2.7 g/m^-mo
Mortality of
fishes
Assume to be 2.5% of standing stock per day.
(2.5 g/m^-day) (0.025/day) = 0.063 g/m^-day
(0.06 g/m^-day) (30 days) = 1.89 g/m^-mo
Oyster feces,
0 pseudofeces
and mortality
Assume 50% assimilation efficiency.
Assume steady state population so that
^23 = ^35 = 9/m^day = 18.05 g/m^- mo
365
Table D-1 continued
Flow Description
Calculation Reference
Gross assimila
tion by benthic
invertebrates
Assume gross assimilation is 15% of
standing stock per day.
(3.5 g/m2) (0.15) = 0.53 g/m2-day
(0.53 g/m2-day) (30 days) = 15.9 g/m2-mo
Respriation of
benthic inverte
brates
Assume respiration rate of 0.085 g dry wt Day et al_., 1973
respired/g dry body wt/day.
(3.5 g/m2) (0.085/day) = 0.30 g/m2.day
(0.3 g/m2-day) (30 days) = 9 g/m2-mo
Predation on
benthic inverte
brates by fish
Assume to be 4% of standing stock per day.
(2.5 g/m2-day) (0.04/day) = 0.1 g/m2-day
(0.1 g/m2-day) (30 days) = 3/gm2-mo
J?7 Gross assimilation
by fish
Assume to be 10% of standing stock per day.
366
Table D-1 continued
Flow Description
Calculation Reference
J27
(cont.)
(2.5 g/m2) (0.1/day) = 0.25 g/m2-day
2 2
(0.25 g/m -day) (30 days) = 7.5 g/m mo
J0 Respiration of
28 fish
Assume to be 3.6% of dry body weight per day. Prosser and
Brown, 1961
(2.5 g/m2) (0.036/day) = 0.09 g/m2-day
2 o
(0.09 g/m -day) (30 days) =2.7 g/m mo
Regeneration of
phosphorus by fish
respiration
Assume organic matter is 0.5% phosphorus
by weight.
J29 = (J28) (0.005)
J2g = (0.09 g/m2-day) (0.005) = 0.00045
g/m2-day
(0.00045 g/m2-day) (30 days) = 0.0135 g/m2-mo
367
Table D-l continued
Flow Description
Calculation
J32 J32 = (0.96 g/m2-day) (0.009)
(cont.) ?
= 0.00864 g/rn -day
(0.00864 g/m2-day) (30 days)
= 0.26 g/m2- mo
Regeneration of
Assume organic matter is 0.5% phosphorus
phosphorus by
by weight.
respiration of
oyster reefs
LO
O
O
O
LO
CO
r_D
II
CO
CO
rD
J33 = (0.6 g/m2-day) (0.005) = 0.003 g/m2-day
(0.003 g/m2-day) (30 days) = 0.09 g/m2-mo
J34 Regeneration of
phosphorus by
respiration of
microbes in water
col umn
Assume organic matter is 0.5% phosphorus
by weight.
J34 = (J]4) (0.005)
Reference
369
Table D-l continued
Flow Description
Calculation Reference
J34
(cent.)
J34 = (0.65 g/m2.day) (0.005)
= 0.00325 g/m2* day
(0.00325 g/m2,day) (30 days)
= 0.0975 g/m2-mo
Jr Oyster reef
respiration
2
Biomass of oyster reef organisms = 290 g/m Lehman, 1974a,b
of reef area.
Assume reef areas is 5% of total bay area.
Reef respiration = 0.083 g 02/g dry wt/day
Assume reef submerged 12 hours a day.
Assume 1 g O2 consumed equals 1 g organic
matter respired.
(290) dry wt/m2) (0.083 g 02/g dry wt/day)
2
= 24.07 g O2 consumed/m .day
(24.07 g 02/m2-day) (0.05) (0.5) = 0.6 g/m2-day
(0.6 g/m2-day) (30 days) = 18.05 g/m2-mo
370
Table D-1 continued
Flow Description Calculation
Reference
Gross photo-
J synthesis of
phytoplankton
As measured with light and dark bottle Table 6
2
experiments =1.0 g/m -day
(1.0 g/m2-day) (30 days) = 30 g/m2-mo
J_7 Respiration of Assume respiration 30% of gross photo- Day et^ al_., 1973
phytoplankton synthesis
(1.0 g/m2-day) (0.3) = 0.3 g/m2-day
(0.3 g/m2-day) (30 days) = 9.0 g/m2-mo
Grazing of
Assume biomass in
steady
state
in summer,
phytoplankton
so that
by oyster reef
organisms
j
+ J +
.1 +
j =
+
u37
u38
39
u43
u36
44
J38
+ J39 '
J36
J37 -
J43 *
J44
J38
+ J39 =
1.0 -
0.3 -
0.45 +
0.45
. 2
= 0.7 g/m day
Table D-1 continued
Flow Description
Calculation
Reference
Regeneration of
phosphorus by
respiration of
benthic inverte
brates
Assume organic matter is 0.5% phosphorus
by weight.
J30 = (J25) (0.005)
J3q = (0.3 g/m2- day) (0.005) = 0.0015 g/m2-day
(0.0015 g/m2-day) (30 days) = 0.045 g/m2-mo
J31 Regeneration of
phosphorus by
respiration of
microbes in
sediment
Assume organic matter is 0.5% phosphorus
by weight.
J31 = (J18) (0.005)
J31 = (1.74 g/m2-day) (0.005) = 0.0087 g/m2-day
(0.0087 g/m2, day) (30 days) = 0.26 g/m2*'mo
J32 Regeneration of
phosphorus by
respiration of
benthic macrophytes
Assume organic matter is 0.9% phosphorus
by weight.
032 = (J3) (0.009)
Van Breedveld,
1966, quoted in
Jones 1968
368
Table D-l continued
Flow Description
Calculation
Reference
38
(cont.)
J,q Grazing of phyto
plankton by benthic
invertebrate filter
feeders
J.q Uptake of
phosphorus in
photosynthesis
Assume 90% of grazing is by oyster
reef organisms
(0.7 g/m2-day) (0.9) = 0.63 g/m2-day
(0.63 g/m2-day) (30 days) = 18.9 g/m2-'mo
Assume 10% of grazing is by benthic
invertebrate filter feeders (see
calculation for J^g).
(0.7 g/m2-day) (0.1) = 0.07 g/rn2* day
(0.07 g/m2-day) (30 days) = 2.1 g/m2- mo
Assume phytoplankton biomass is 0.5%
phosphorus.
(1.0 g/m2-day) (0.005) = 0.005 g/m2-day
(0.005 g/m2-day) (30 days) = 0.15 g/m2*mo
OJ
PO
Table D-l continued
Flow Description
Calculation
Reference
Sunlight avail-
41 able for
photosynthesis
Assume one-half of sunlight available for
photosynthesis.
(5800 kcal/m2-day) (1/2) = 2900 kcal/m2-day
(2900 kcal/m2-day) (30 days)
= 87000 kcal/m2-mo
J.,R Sunlight not used
in photosynthesis
J41R = Jo J41 = 5800 2900
= 2900 kcal/m2-day
(2900 kcal/m2-day) (30 days) =87000 kcal/m2-mo
Phosphorus returned
to the water column
by respiration of
phytoplankton
Assume phtoplankton biomass is 0.5%
phosphorus
(0.3 g/m2-day) (0.005) = 0.0015 g/m2-day
(0.0015 g/m2-day) (30 days) = 0.045 g/m2-mo
373
Table D-l continued
Flow Description
Calculation
Reference
J., Input of phyto
plankton from
discharge canal
and offshore
iL, Tidal exchange of
phytoplankton
biomass offshore
Biomass of phytoplankton in discharge Figure 29
canal water and offshore water identical.
Therefore, = total volume exchange x
concentration
n (1,030,500 m3) (0.3 q/m3)
43 ~ 2
687,000 nr
= 0.45 g/m3-day
(0.45 g/m3-day) (30 days) = 13.5 g/m3-mo
J44 = total volume exchange x concentration
, (1 ,030,500 m3/da.y) (0.3 q/m3)
u44 2
687,000 nr
2
= 0.45 g/m -day
(0.45 g/m3-day) (30 days) = 13.5 g/m3-mo
CO
able D-l continued
Flow
Description
Calculation
Reference
J45
Feces production
by oysters of
unassimilated
phytoplankton
Assume assimilation efficiency for
oysters of 50%
(0.63 g/m2-day) (0.5) = 0.32 g/m2- day
(0.32 g/m2* day) (30 days) = 9.6 g/m2* mo
J46
Assimilation of
phytoplankton
ingested by
benthic inverte
brates
Assumed assimilation efficiency for
invertebrates of 50%.
(0.07 g/m2* day) (0.5) = 0.035 g/m2* day
(0.035 g/m2*day) (30 days) = 1.05 g/m2- mo
J47
Unassimilated
phytoplankton
ingested by
benthic inverte
brates
Assume assimilation efficiency for in
vertebrates of 50%.
(0.07 g/m2* day) (0.5) = 0.035 g/m2* day
(0.035 g/m2-day) (30 days) =1.05 g/m2*mo
375
376
Table
D-2.
Initial and maximum values
and storages for seasonal
inner bay (Figure 55).
of forcing functions
simulation model of
Forcing functions
Initial value
Maximum value
J
0
174000 kcal/m2-mo
240000 kcal/m2-mo
J7
2
30 g/m -mo
2
30 g/m -mo
J8
225 g/m2-mo
225 g/m2-mo
J15
0.0405 g/m2-mo
0.0405 g/m^-mo
J16
2.25 g/m2-mo
2.25 g/m2-mo
T
33C
40C
Storage
Initial value
Maximum value
1
40 g/m2
75 g/m2
q2
0.05 g/m2
0.15 g/m2
03
5 g/m2
10 g/m2
%
160 g/m2
250 g/m2
LO
O'
3.5 g/m2
10 g/m2
6
2.5 g/m2
10 g/m2
7
0.3 g/m2
1.5 g/m2
R
14.5 g/m2
20 g/m2
377
Table D-3.
Calculation of transfer coefficients for
seasonal simulation model of inner bay
(Figure 55). All evaluations were made for
summer conditions.
Coefficient
Calculation
ko
J = k S = 174000 kcal/m^-mo
0 0
. 174000 ,
Ko 17400 1
kr
J It ] 87000 q c
R Vo 174000 U-
, 87000 g r
KR 174000 U
ki
8o^2^1 2
J1 kl kR+k1TQ2Q1 8700 kca1/m -mo
kl (174000) (33) (O'. 05) (40) 007576
k2
TQ2Qi 2
J2 k2o kR+k1TQ2Q1 95'7 g/m 'm0
1. (1 ) (95.7) o oooo in-6
K2 (174000) (33) (0.05) (40) ^ x ,u
k3
= k3^1T = 88-8 9/nl^'mo
k3 t43ST '0218
373
Table D-3 continued
Coefficient
Calculation
tq2q1
J4 = k4Jo kR+k1TQ2Q1 = -8613 g/m 'm0
. (1)(0.8613) 7 c- -in~8
k4 (174000)(33)(0.05)(40) 3 x lu
J5 = k^Q-j = 33.6 g/rri -mo
k = = 1 344
k5 40
Jg = kgQ-| = 33.6 g/m -mo
|< = 33^ 1 244
k6 40
J7 is a constant flow
8
Jg is a constant flow
Jg = kgQ3 = 225 g/m -mo
5
379
Table D-3 continued
Coefficient
Calculation
no
J10 k10^3Tfy> ~ 4-5 9//m
mo
4.5
C10 l5)(33)(2.5)
= 0.01091
'll
J-|1 = = 36 g/m -mo
11 = T5)T33j(14.5)
0.01505
k-j2 J12 = ki2^3T(^5 = 3-18 g/|1l2-mo
kl 2 = T5)(33)(3.5) = -0055
2
k13 J13 = k-|3Q3 = 7.89 g/m -mo
k
13
7.89
5
1.578
J.|4 k.
14
Q3T =19.5 g/m
mo
kl4 T5)My 0-1182
380
Table D 3 continued
Coefficient
Calculation
K-ir- is a constant flow
15 15
k-jg is a constant flow
16
kl7Q2
2.25 g/m -mo
2.25
0.05
45
J18 k18^4T
52.2 g/m -mo
52.2
18 TT601T53T
0.0099
kl 9
J19 = kl9Q4TQ5 = 28-62 9/m2-mo
28.62
19 (160)(33)(3.5)
0.001548
J20 = k2084T^5 = 15-9 9/m
mo
15.9
20 TT60)(33)(3.5J
= 0.000861
381
Table D-3 continued
Coefficient
Calculation
21
J2i 1:1 k2iQ5 = 2.7 g/m-mo
k2, = ftf = 0.7714
22
J22 = k226 = 1-89 9/m 'mo
k22 = = '756
'23
823 = k233TR = 18-05 g/m-mo
k23 (5) (357TT475T 007545
'24
J24 = k24(04T5+03T05) = 15,9 9/m 'mo
24
15.9
[(160)(33)(3.5) + (5) (33)(3.5)j
8.3331 x 10'
25
2 2
25 = k255 4=9 9/m 'mo
25 (3.5)2(33)
= 0.0223
383
Table D-3 continued
Coefficient
Calculation
31
J31 = k31^4T = 0,26 g/m -mo
k3i = rieolfaT = 4'9243 x ,0'5
32
J32 = ^32^1T = O-88 9/m *m
k32 (40)(33) 1-9698 x 10
'33
J33 = I^C^TR = 0.09 g/m
mo
k33 (5) (33 j 04. 5T ~ 3-7617 x 10 5
'34
J34 = I^C^T = 0.0975 g/m -mo
1 0- 0975 r nnm m_4
k34 (57(331 59091 x 10
35
J35 = ^(^TR = 18.05 g/ni -mo
18.05
35 757T33)(14.5)
0.00754
382
Table D-3 continued
Coefficient
Calculation
26
= k
26^5TC^6 3 g/m
mo
6 ~ (3.5)(33)(2.5)
= 0.0104
k27 J27 = k27^3T^6+(W = 7-5 9/m2-mo
7.5
K27 L(5)(33)(2.5)+(3.5)(33)(2.5JJ
= 0.0107
2 2
k28 J28 = k28Q6T =2.7 g/m -mo
k9Q = = 0.01309
2y (2.5;(33)
k29 J2g = k2gQ2T = 0.0135 g/m2-mo
0.0135
(2.5)2(33)
= 6.5455 x 10
30
J30 = k8gQ2T = 0.045 g/m2-mo
30
0.045
(3.5)(33)
1.1132 x 10
-4
384
Table D-3 continued
Coefficient
Calculation
tq2q7
36 = k36J0 k41R+K4kTQ2Q7 =30 g/m 'mo
, 0)(30)
'36 (174000) (33) (0.05)107
3.483 x 10
-4
J37 = l<27Q7T = 9 g/m-mo
'37 (0.3)(33)
= 0.9091
J38 = k2gQ7TR = 18.9 g/m2*mo
k38 = (0.3)(33)(14.5) = 0,1317
J39 = k3gQ7TQ5 = 2.1 g/m2-mo
2.1
k39 = TO.3)(33)(3.5) -0606
tq2q7 2
40 = k40Jo F41r+K4iTQ2Q7 = 0,15 g/m 'm0
. (1)(0.15)
K40 (174000)(33)(0.05)(0.3)
= 1.7416 x 10"6
385
Table D-3 continued
Coefficient
Calculation
41
J/,-, = kn J
tq2q7
41 41 o *<4iR+*<4l^Q2^7
87000 kcal/m -mo
f (1 ) (87000)
Ml (174000)(33)(0.05) (0.3)
= 1.0101
k41 R
J.in = k/,i nJ = 87000 kcal/m -mo
41R 41R o
= 87000
(41R 174000
= 0.5
k42 J42 = k42 = k42Q7T = 0.045 g/m2-day
k42 = (0)133) 004545
J43 is a constant flow
k44 J44 = k44Q7 = 13.5 g/m -mo
13.5
0.3
45
J45 = k45Q7TR = 9'6 9/m *
mo
k45 (0.3)'(33TT 1475T -0669
386
Table D-3 continued
Coefficient
Calculation
46
k46Q7TQ5
1.05 g/m *mo
(0.3)(33)(3.5) 00303
47
- k47Q5TQ7
1.05 g/m -mo
47 TO.3)(33)(3.5)
= 0.0303
Table D-4. Equations of Table 8 scaled for simulation of seasonal model of the
inner bay given in Figure 55.
ru,!
d LtfJ
. tJ ( TQ2qi \
* (75) (40) (k3)
rqii
T
dt
2 0 l kR+ klT2l )
+ 75
L 75 j
[_40 J
(75) (k5)
rqil
(75) (kfi)
+ U
rq,i
75
_ 75_
75
75
dt
V
L 7 5.
10 dt
"k2Jo
T Q2Q-|
+ k ^ T Q 2 Q i
+ (0.0872)
rq,i
" T
_75_
_40_
N
75
+ 3.33 (0.0252)
75.
+ (0.0840)
387
Table D-4 continued
02
J 0.0405
J15
2 25
0.15
. 0.0405
0.15
(100) (40) (k3Q)
psl
2
0.15
Li o_
( 75 ) (40) (k32)
[Oil
T
0.15
L 7 5 _
L40 J
(1.5) (40) k42
r7 1
T
.1.5.
40
+
) 0 1 5 )
J16 1
(100) (40) (k2g)
[o6i
2
~ T "
2.25.
0.15
Li o_
14 Oj
( 250 ) (40) (k31 )
(10) (40) (20) (k33)
(10) (40) (k34)
[o4l
T
|_2 5 0_
L40J
V
T
R
11 o_
u40j
20J
rQ3i
T~
_i 0,
|_40_
380
Table D-4 continued
(0.15) (k1?)
2 1
( T(>21 \
*
\y 1
( TQ2Q7 \ *
0.15
Lo.15_
k4Jo
\ kR + klTQ2Ql /
O
D
O
1
\ k41R + k41TQ2Q7/
d
g2
LO. 15 J
/ n n9 711
J15
+ infn i c;nn 1
J16 1
+ (f) 17 4 5^
rvi
2
T "
1
0 dt
^ U U / U ;
0.0405
L2.25 _
L i oj
L40J
+ (0.2969 )
Hsi
' T 1
Li o_
_ 40 _
(0.3283)
rq4i
T
L 2 5 0 J
L40 J
+ (0.3940)
rq3i
T
R
|_i o_
_ 4 0 J
L20 J
+ (0.2006)
+ (0.1818)
Table D-4 continued
+ (0.1576)
r3i
' t"
Li oj
L40J
- 10(0.4500)
^2
.0.15.
k j I IM] \
4 (kR + XfQ2Q1 )
- k
40Jo
tQ2Q7
k 41R + k41TQ2Q7
*
CO
o
d
L i o J
(75) (k5)
[Oil
30
r7i
225
r j81
(10) (kg)
dt
10
L 7 5 j
10
L30j
10
L 2 2 5J
10
.1 oj
(1 0) (40) (20 ) (kn)
ro3
t"
R
(10) (40) (10) (k12)
Psl
T
p5l
1 0
Li oj
L40j
L20j
F 10
L10J
L40j
L10J
Table D-4 continued
(10) (k13)
P3l
(10) (40) (k14)
rQ3i
T
1 0
Lio_
1 0
L i o_
L40J
(10) (40) (10) (k1Q)
1 0
rq3]
T 1
r^l
.10.
.40.
.1 OJ
tq3
Lto
10 dt
7.3(0.0840)
L75J
(0.3000)
11
38.
10(0.2250)
225
+ 10(0.4500)
_3
10.
OJ
<^o
+ 10(0.1204)
fsl
t"
" r"
Li oj
_40_
_2 0 J
+ (0.2200)
rQ3i
T
q5i
jo.
40
JO.
+ 25(0.0063)
^ 3
10.
+ (0.4728)
r3i
" t"
LioJ
L.40J
+ (0.4364)
rQ3i
T
.1 o.
_40_
JOJ
Table D-4 continued
d
ri4i
L2 5 0.
(75)(k6)
pii
(lo)(k13)
p3
dt
250
.75,
250
Li o
0 o)(k22)
do) (k21)
250
LioJ
250
L i oj
(250) (40) (10) (k-| g)
250
p4 1
T
psl
L250,
L40j
Li oj
( 1 .5) (40)( 20)k45
250
p7 1
T
-
R
Ll 5J
L40J
L20J
10 dt
(0.0252)
.250.
(0.0063)
(10)(40)(20)(k23)
250
r3'
T
R
Li oj
_40_
L 2 0_
(250)(40)(10)(k2Q)
250
1
*d-
O-
1
T
N
L 2 50,
L 4 0 J
L i oj
(250)(40)(k]g)
250
1
0
-p*
1
T
L250J
L 4 0 J
Li oj
(10 ) (40)(1 .5 ) k4?
250
N
T
1
1
Li 0 J
L40J
Li. 5J
(0.0241)
continued
Table D-4 continued
(0.0030)
LI 0J
(0.0031)
21
10
- (0.0344)
rQ2
~T "
r5i
1_2 5 Oj
L40_
Li oj
+ (0.0619)
i
o
1
T
rQ5i
|_2 50j
L40_
Li oj
+ (0.0395)
rvi
T~
.250.
.40.
- (0.0321)
[Q71
T~
R
Ll 5_,
L40_
L20j
(0.0073)
ri5i
T
i
O'
L 2 5 0_
l40_
Li 5j
CO
CD
CO
HO.
dt
(30) (4000) k
10
24
P4l
T
rq5i
100000
L 2 5 0
L4 0
L i o_
30
rq3i
T
Psl
4000
Li oJ
L40j
Li oj
30
(10) (40) (1.5) k
1 0
46
M
T
Li oj
L40J
Ll 5J
(100)(40) (k25)
N
~t"
10
L1 .
[_40j
continued
Table D-4 continued
(10) (40) (10) (k26)
T
10 dt
(1 .000) (0.8333)
r
cr
l
T
L250J
L40j
+ (0.1818)
T
O'
i
u o_
L4 0J
Ll 5J
5
10
25(0.0031)
mo
40.
[el
no) (k21)
rn
Li o^
10
Li oj
(0.0333)
2
T
Li o_
L40j
(0.8920)
(0.4156)
LOO
Table D-4 continued
Li o.
dt
2(4000) k27
To
no) (k22)
TO
10 dt
(0.8560)
(0.5000)
3
T
%
Lio^
L4 0_j
Lioj
(0.5236)
25 (0.0030)
(40) (k2g)
[A]
2
T
1 0
Li o_
L40J
(0.5000)
568
Table D-4 continued
k 36 J 0
tq2q7
k41R + k41TQ2Q 7
( 1.5 ) (40) ( 20) k38
1 5
(1.5) k44
1 5
10 dt
k36J0
TQoQ
2 y7
k +
K 41 R
k41TQ2Q7
13.5
CO
1
(1.5) (40) k37
rQ7i
T
1 5
L 1 3.5_
1 5
Ll 5_|
|_40j
T
R
(10) (40) (1.5) k39
r si
T
L40j
L20J
1 5
j oj
_40 J
CO
CT
+ (0.9000)
43
0.43
10(0.3636)
continued
Table D-4 continued
- 10(0.7639)
r
O'
1
T "
Ll .5j
L 40 J
- 10(0.4500)
*See Table D-5 for scaling.
10(0.2424)
[Q51
T
1
JO
-'j
i
L i o_
L40j
_1 5j
397
Table D-5. Scaling of terms associated with photosynthesis in equations in Table
seasonal simulation model of the inner bay (Figure 55).
d
PM
75
(240000)(40)(0.15)(75)(k2)
1
/
1 1
| 1
LO
CNJ r
O'
O
1 1
rii
.75.
1 Odt
(10)(75)
240000j
l kR
+ (40) (0.15) (75) (k-,)
T '
1
CXJ
o
1
fM
UoJ
L0.15J
L 7 5J
d
rv
.75.
(144000)(k2)
Jo 1
1
f
T
L40^
V
Lo.15_
f
_7 5_
1Odt 4.5
L240000^
{ kR ^ (450) (k-j)
T
'2 1
fQll
75
lOdt
= (0.2667)
240000
T
i
CM
O'
_40_
_0.15_
^1
75
(0.1111) + (0.7575)
t"
r2i
fii
L40J
LO. 15 J
L75J
for
398
Table D-5 continued
0.15
lOdt
(240000)(40)(0.15)(75)(k4)
(10)(0.15)
240000
T
1
(XI
cr
1
riii
L 40
[0.1 5J
L75.
kR +
(40) (0.15) (75) (k-,) TX
140.
r i
rQii
L0.15J
1
oil
(240000)(40)(0.15)(1.5)(k4Q)
(10) (0.15)
240000
0.15
1 Odt
(y^xio'K^)
475
240000
T
40
0.15
4.5
(450)(k1)
"~TT5
rQi
L 75
T
q2
.75,
l_40j
L 0.15_
(1.44xlOD)(k4Q)
To
240000
x
40
0.15
J.5j
k41R
T
XD
ro
1
1
XD
1
10 10
L4OJ
L0.15J
|_1.5 _
399
402
Table D-6. Potentiometer settings for initial run
(Figure 57) of simulation of the seasonal
model of the inner bay (Figure 55).
Potentiometer
Setting
Potentiometer
Setting
1/10 kR
0.9000
k23
0.0241
ki
0.7575
k24
1 .000
k 2
0.2667
k25
0.8920
k3
0.0872
k26
0.4156
k4
0.1200
k27
0.8560
k5
0.0840
k28
0.5236
k6
0.0252
k29
0.1745
J7
0.3000
k30
0.2969
J8
0.2250
k31
0.3283
k9
0.4500
k32
0.3940
k10
0.4364
k33
0.2006
kll
0.1204
k34
0.1576
k 1 2
0.2200
k36
0.5016
k 1 3
0.0063
k37
0.3636
kl 4
0.4728
k38
0.1054
J15
0.0270
k39
0.2424
J16
0.1500
k40
0.2508
kl 7
0.4500
k41
0.9091
00
0.412
1/100 k41R
0.2000
kl 9
0.0619
k42
0.1818
k20
0.0344
J43
0.9000
k21
0.0031
k44
0.4500
k22
0.0030
k45
0.0321
Table D-5 continued
- (0.2508)
"t"
rzi
.O
J
1
_40_
0.15
L.
J.5_
240000^
\ (0.05) + (0.9091
"T"
" Q2 "
rq7i
L40j
L0.15J
Ll -5J
rv
"t"
" Q2 '
Q7l
[1.5 j
(240000)(40)(0.15)(1.5)(k3g)
r j i
0
[_40j
L0.15J
L1 5 J
1 Odt
(10)(1.5)
240000
k4]R + (40)(0.15)(1.5)k41
T
40
0.15 1.5
L. _J L_
400
Table D-5 continued
1.5
1 Odt
(1.44xl03)(k36)
TO
240000
T
_40_
zl
0.15_
rQi i
.5_
k41R (9)(k41)
T
q2
10 10
L40j
L 0.15
1.5
1.5
T
40
0.15
1.5
,odt 10<0-5016)
u
_240000_
\ (0.05) + (0.9091)
T
Q2 1
r7 ]
L40j
_0.15J
[l .5_
403
Table D-6 continued
Potentiometer
Setting
Potentiometer
Setting
k46
0.1818
B
0.2250
k47
0.0073
C
0.7500
ICQ1
0.5333
D
0.2500
icq2
0.3333
E
0.0333
ICQ3
0.5000
F
0.8333
icq4
0.6400
G
0.2500
icq5
0.3500
H
0.5000
CQ6
0.2500
I
0.5000
icq7
0.2000
L
0.2500
CO
0.0523
M
0.3333
Ci!
A
0.0523
0.6000
R
0.7250
404
Table D-7. Potentiometer settings for EAI 580 variable
diode function generator used to produce the
seasonal cycle of sunlight given in Figure 56
for the simulation of the seasonal model of the
inner bay (Figure 55). The function was pro
grammed to begin on July 1st.
X
f (X)
0.0000
0.6875
0.0417
0.6650
0.1250
0.6138
0.2083
0.5525
0.2917
0.5050
0.4583
0.3688
0.5417
0.3888
0.6250
0.4738
0.7917
0.7000
0.8750
0.7488
1 .000
0.6875
Figure D-1. Analog computer diagram of scaled equations
given in Tables D-4 and D-5 for the seasonal
simulation model of the inner bay (Figure
55).
9017
APPENDIX E
DOCUMENTATION OF DATA USED IN SUMMARY DIAGRAMS OF
SUMMER STOCKS AND FLOWS FOR THE INNER DISCHARGE BAY
(Figure 38) AND SOUTH INTAKE AREA (Figure 39)
Table E-l. Documentation of numbers appearing on Figure 38 of the inner discharge bay
ecosystem affected by the thermal discharge of the power plant.
Storage
Description
Calculation
Reference
Total phosphorus
in water column
Assumed similar to
outer discharge bay.
McKellar, 1975
q2
Biomass of
phytoplankton
Measured at Crystal
River.
Figure 29;
Gibson, 1975
^3
Biomass of benthic
macrophytic plants
Measured at Crystal
River.
Figure 25;
Van Tyne, 1974
^4
Organic matter in
water column
Measured at Crystal
Ri ver
as total organic carbon.
Figure 28;
Gibson, 1975
Biomass of resident
fish
Measured at Crystal
of fresh weight.
River.
Dry weight assumed 25%
Figure 27;
Adams, 1974
6
Biomass of benthic
macroinvertebrates
Measured at Crystal
River.
Figure 26;
Evink and
Green, 1974
7
Organic matter in
sediments
Measured at Crystal River,
centimeter of sediment.
Value is content of top
Cottrell, 1974
R
Biomass of oyster
Measured at Crystal River,
of bay area.
(270 g/m2 of reef)(0.05) =
Reefs assumed to be 5%
n>l 4 g/m
Lehman, 1974a,b
408
Table E-1 continued
Flow Description
Calculation
Reference
J1
Sunlight at water
surface
Eleven year average at Tampa, Fla.
Figure
13
J2
Gross production
of phytoplankton
Measured at Crystal River with light and dark
bottles.
Table
3.
J3
Phytoplankton
respiration
Assumed to be 30% of gross production.
(1.0 g/m^day)(0.3) = 0.3 g/m^*day
Day et
al.,
J4
Gross production
of benthic plants
Total community gross primary production minus
phytoplankton primary production.
4.5 g/m^day 1.0 g/m^*day = 3.5 g/m^-day
J5
Respiration of
benthic plants
Assumed to be 30% of gross production.
(3.5 g/m^*day)(0.3) = 1.05 g/m^*day
Day et
al.,
J6
Respiration of
microbes in the
sediments
Assigned by difference after all other respiratory
pathways evaluated.
Jg = Total respiration J3 J5 J7 Jg Jg J-jq
J, = 5 0.3 1.05 0.34 0.07 0.1 0.58
6 2
=2.56 g/m *day
1973
1973
409
Table E-l continued
FI ow
Description
Calculation
Reference
7
Respiration of
benthic macro-
invertebrates
Assume respiration rate of 0.085 g dry wt
respired/g dry body wt/day.
(4 g/m2)(0.085) = 0.34 g/m2*day
Day et a]_., 1973
J8
Respiration of
resident fish
Assume to be 3.6% of dry body weight per day.
(2 g/m2)(0.36) = 0.72 g/m2-day
Prosser and
Brown, 1961
J9
Respiration of
microbes in
water column
Water column respiration from dark bottle measure
ments minus phytoplankton respiration.
2 2 2
0.3 g/m'day -0.3 g/m day = <0.1 g/m -day
J10
Respiration of
oyster reef
organisms
Respiratory rate of reefs measured at Crystal River.
(14 g/m2)(0.083 g/m2*day) = 1.16 g/m2*day
Lehman, 1974a,b
Assume reefs submerged 12 hours per day.
(1.16 g/m2*day)(0.5) = 0.58 g/m2-day
410
Table E-2. Documentation of numbers appearing on Figure 38 of the south intake area
ecosystem unaffected by the thermal plume of the power plant.
Storage
Description
Calculation
Reference
Total phosphorus in
water column
Assumed similar to
outer control bay.
McKellar, 1975
q2
Biomass of
phytoplankton
Measured at Crystal
River.
Figure 29;
Gibson, 1975
^3
Biomass of benthic
macrophytic plants
Measured at Crystal
River.
Figure 25;
Van Tyne, 1974
Organic matter in
water column
Measured at Crystal
River as total organic carbon.
Figure 28;
Gibson, 1975
Biomass of resident
f i sh
Measured at Crystal
of wet weight.
River. Dry weight assumed 25%
Figure 27;
Adams, 1974
%
Biomass of benthic
macroinvertebrates
Measured at Crystal
River.
Figure 26;
Evink and
Green, 1974
^7
Organic matter in
sediments
Measured at Crystal River. Value is content of
top centimeter of sediment.
Cottrell, 1974
R
Biomass of oyster
reef organisms
Measured at Crystal River. Reef assumed to be 5%
of bay area. (290 g/nr*day)(0.05) = M5 g/m^
Lehman, 1974a,b
Table E-2 continued
Flow Description
Calculation
Reference
Sunlight at water
surface
Eleven year average at Tampa, Fla.
Figure 13
J2
Gross production
of phytoplankton
Measured at Crystal River with light and dark
bottles. Assumed same percentage of total gross
production as for fall.
Table 4.
J3
Phytoplankton
respiration
Assumed 30% of gross production.
(0.46 g/m^*day)(0.3) = 0.14 g/m^*day
J4
Gross production
of benthic plants
Total community primary production minus phyto
plankton primary production.
8.8 g/m^*day 0.46 g/m^*day = 8.34 g/m^*day
J5
Respiration of
benthic plants
Assume 30% of gross production.
8.34 g/m^*day)(0.3) = 2.50 g/m^*day
J6
Respiration of
microbes in the
sediments
Assigned by difference after all other respiratory
pathways evaluated.
Jg = Total respiration - Jg Jy Jg Jg J-|q
J, = 11.4 0.14 2.50 1.7 0.07 0.09 0.75
6 2
=6.15 g/m *day
Table E 2 continued
Flow
Description
Calculation
Reference
J7
Respiration of
benthic macro
invertebrates
Assumed respiration rate of 0.085 g dry wt. respired/g
dry body wt/day.
(20 g/m2)(0.085) = 1.7 g/m2*day
Day et al_.,
1973
J8
Respiration of
resident fish
Assumed to be 3.6% of dry body weight per day.
(2 g/m2)(0.036) = 0.072 g/m2-day
Prosser and
Brown, 1961
J9
Respiration of
microbes in
water column
Water column respiration from dark bottle measurements
minus phytoplankton respiration.
0.23 g/m2day 0.14 g/m2*day = 0.09 g/m2*day
J10
Respiration of
oyster reef
organisms
Assume 5% of dry body weight per day.
(15 g/m2)(0.05) = 0.75 g/m2*day
Day et aj_.,
1973
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BIOGRAPHICAL SKETCH
Wade Hampton Barnes Smith was born on July 3,
1944 at Louisville, Kentucky. He received his Bachelor
of Arts degree from Emory University in August, 1966.
He was awarded the Master of Arts in zoology from the
University of North Carolina at Chapel Hill in August,
1971. This program was interrupted from January, 1969
through December, 1970 for employment with the E. I.
DuPont Company. He entered the Systems Ecology program,
Department of Environmental Engineering Sciences, Uni
versity of Florida in March, 1971, and began employment
with the Mitre Corporation, McLean, Virginia in Sep
tember, 1 975.
426
I certify that I have read this study and that in
my opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
H. T. Odum, Chairman
Graduate Research Professor of
Environmental Engineering
Sciences
I certify that I have read this study and that in
my opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
P.
Associate Professor of
Environmental Engineering
Sciences
I certify that I have read this study and that in
my opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
T. E. Bullock
Professor of Electrical
Engineering
I certify that I have read this study and that in
my opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
J. J. Ewel
Assistant Professor of Botany
I certify that I have read this study and that in
my opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.
S. C. Snedaker
Associate Professor of Biology and
Living Resources, Rosenstiel
School of Marine and Atmospheric
Sciences, University of Miami
(Florida)
This dissertation was submitted to the Graduate Faculty of
the College of Engineering and to the Graduate Council, and
was accepted as partial fulfillment of the requirements
for the degree of Doctor of Philosophy.
Dean, Graduate School
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Productivity measurements and simulation models of a shallow
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1970
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PAGE 1
PRODUCTIVITY MEASUREMENTS AND SIMULATION MODELS OF A SHALLOW ESTUARINE ECOSYSTEM RECEIVING A THERMAL PLUME AT CRYSTAL RIVER, FLORIDA By WADE HAMPTON BARNES SMITH A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 1976
PAGE 2
ACKNOWLEDGEMENTS Many of the ideas presented here were shaped in discussions among the entire systems ecology group of the Department of Environmental Engineering Sciences. Special acknowledgements go to major professor H. T. Odum for his stimulation, guidance, and the distinct privilege of participating in this program. My super visory committee included P. L. Brezonik, T. Bullock, J. Ewel, and S . C. Snedaker. This work was suppo r . te ' d , b ~ . contract No. GEC 159, 918-200-188.19 (Models and _ Me _ a ' surem '. ents for Determining the Role of the Power Plants and Cooling Alternatives at Crystal River, Florida) between the Florida Power Corporation and the University of Florida Systems Ecology Program, Department of Environmental Engineering Sciences, H. T. Odum, principal investigator. Many people helped in the field and with data \•Io r k u p : J . Bev i s , N . B l a c k , W . Boyn ton , C . H i g h , D . Hinck, M. Homer, M. Kemp, M. Lehman, H. McKellar, A. Merriam, F. Ramsey, and D. Young. Analog computers used in this study were maintained by A. Copsey, and J. Murphey, who also provided programming assistance. Progress in i i
PAGE 3
this study was much facilitated by K. Garrison, J. Johnson, D. McMullin, and W. Trowell of the Florida Power Corpora tion. Use of the R. V. Susio was provided by the State University System Institute of Oceanography. i i i
PAGE 4
TABLE . OF CONTENTS ACKNOWLEDGEMENTS ii LIST OF TABLES . . vii LIST OF FIGURES x ABSTRACT . . xvii INTRODUCTION l System Adaptation, Environmental Impact, and Thermal Loading of the Estuary at Crystal River, Florida . . . . . . 5 Models for Gaining an Overview of the Estuary and Power Plant at Crystal River . . . . . . . . . . . 9 Previous Studies of Thermally Affected Aquatic Ecosystems . . . . . . . 16 Description of Study Area at Crystal River . . . . 21 Other Studies of the Crystal River Region... 3 1 Previou s Simulation Models of Marine Eco systems, Diurnal Oxygen Dynamics, Temperature, and the Effects of Power Plants on Ecosystems 33 Plan of Study 39 i V
PAGE 5
METHODS 41 Metabolic Measurements 41 Other Field Measurements 62 DATA ASSEMBLED FROM OTHER PHASES OF THE CRYSTAL RESULTS RIVER PROJECT AND ELSEWHERE . . . . . . . 69 Energy Sources and Inflows Affecting the Inner Bay . . . . . 69 Stocks of the Inner Bay 78 11 6 Metabolism Measurements 116 Model Diagrams for Comparing Ecosystems Affected and Unaffected by the Discharge Plume . . . . . . . . . 149 Simulation Model of Diurnal Properties of the Inner Bay Ecosystem . . . . 154 Simulation Model of Seasonal Properties of the Inner Bay Ecosystem 201 DISCUSSION 223 Seasonal P1t t erns of the Ecosystems at Crystal River . . . . . . . 223 Comparisons of the Ecosystems at Crystal Ri1er and Adaptation to the Thermal Discharge . . . . . . . . . 239 Predictions of the Effect of the Operation of Unit Three at Crystal River . . . . 252 Energy Costs of Alt e rnative s to Estuarine Cooling of the Thermal Discharge at Crystal River . . . . . . . . . . . . 253 V
PAGE 6
APPENDICES ... . ........... . A EXPLANATION OF THE ENERGY SYMBOLS USED IN THIS STUDY ..... . B GRAPHICAL ANALYSES OF DIURNAL STUDIES OF COMMUNITY METABOLISM IN THE INNER BAY AFFECTED BY THE THERMAL DISCHARGE PLUME AND IN THE FORT ISLAND AND HODGES ISLAND AREAS AWAY FROM THE 256 257 INFLUENCE OF THE THERMAL DISCHARGE . . 262 C INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, HEAT BUDGET CALCULATIONS, CAL CULATION OF TRANSFER COEFFICIENTS, SCALED EQUATIONS, POTENTIOMETER SET TINGS, FUNCTION GENERATOR SET-UP, AND ANALOG COMPUTER PATCHING DIAGRAM FOR DIURNAL SIMULATION MODEL OF INNER B.~Y . . . . . . . . . . . . 311 D INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, CALCULATION OF TRANSFER COEFFICIENTS, SCALED EQUATIONS, POTENTIOMETRIC SETTINGS, FUNCTION GENERATOR SET-UP, AND ANALOG COM PUTER PATCHING DIAGRAM FOR SEASONAL SIMULATION MODEL OF THE INNER BAY 356 E DOCUMENTATION OF DATA USED IN SUMMARY DIAGRAMS OF SUMMER STOCKS AND FLOWS FOR THE INNER DISCHARGE BAY AND SOUTH INTAKE AREA 407 LITERATURE CITED .. BIOGRAPHICAL SKETCH vi 414 426
PAGE 7
Table 1 2 3 4 LIST OF TABLES Results of a technique test of the Winkler method to determine the effect of the presence or absence of acid in fixed bottles which have been stored for eight hours before titration. Seasonal comparison of average wind speed at Crystal River s-;te. Record of metabolism for the inner dis charge bay as measured by diurnal free water oxygen changes and light and dark bottles. Record of metabolism for the Fort Island and Hodges Island areas away from the influence of the power plant discharge as measured by diurnal free water oxygen changes and light and dark bottles. 5 Diffusion rates measured in the power plant discharge and Fort Island study areas. 6 7 Average extinction coefficients for light penetration of water on the inner dis charge bay affected by the power plant discharge plume and unaffected areas to the north and south. Differential equations for diurnal model of inner bay given in Figure 40. Vi i 44 75 l l 7 l 21 146 148 157
PAGE 8
Table 8 9 C-l C-2 C-3 C-4 C-5 C-6 C-7 C-8 C-9 Differential equations for seasonal model of inner bay system given in Figure 55. Comparison of gross primary produc tion and total respiration measured at Crystal River with some values from other areas in Florida and similar systems elsewhere. Documentation of values used for forcing functions, standing stocks, and exchange rates in the diurnal simulation model of the inner bay. Initial and maximum values of storages for diurnal simulation model of inner bay. Initial and maximum values of forcing functions for simulation model of inner bay. Calculation of radioactive, evaporative, and convective heat losses for use in diurnal simulation model of inner bay. Calculation of transfer coefficients for diurnal simulation model of inner bay. Equations of Table 7 scaled for simulation of diurnal model of the inner bay given in Figure 40. Scaling of terms associated with photo synthesis in equations in Table 10 for diurnal simulation model of the inner bay. Potentiometer settings for initial run of diurnal simulation mo~el of inner bay. Potentiometer settings for the EAi 580 variable diode function generator used to produce the tidal volume exchange function given in Figure 42 for the diurnal model of the inner bay. Vi i i 202 225 312 329 330 331 333 339 347 349 352
PAGE 9
Table 0-l 0-2 0-3 0-4 0-5 0-6 0-7 E-1 E-2 Documentation of values used for stand ing stocks and exchange rates in the seasonal model of the inner bay. Initial and maximum values of forcing functions and storages for seasonal simulation model of inner bay. Calculation of transfer coefficients for seasonal simulation model of inner bay. Equations of Table 11 scaled for simula tion of seasonal model of the inner bay given in Figure 54. Scaling of terms associated with photo synthesis in equations in Table 8 for seasonal simulation model of the inner bay. Potentiometer settings for initial run of simulation of the seasonal model of the inner bay. Potentiometer settings for EAI 580 vari able diode function generator used to produce the seasonal cycle of sunlight given in Figure 55 for the simulation of the seasonal model of the inner bay. Documentation of numbers appearing on Figure 38 of the inner discharge bay ecosystem affected by the thermal dis charge of the power plant. Documentation of numbers appearing on Figure 38 of the south intake area eco system unaffected by the thermal plume of the power plant. ix 356 376 377 387 398 402 404 408 411
PAGE 10
LIST OF FIGURES l Location of Florida Power Corporation's power plants near Crystal River, Florida, in relation to the major features of the regional coastline. 3 2 Energy diagrams of producer and consumer modules indicating the push-pull effects of temperature on internal processes. 8 3 Aggregated energy diagram of the main features believed important in the eco system of the inner discharge bay at Crystal River. 12 4 Energy diagram of the ecosystem of the inner discharge bay, which includes much of the complexity omitted from Figure 3. 15 5 Bathymetry of power plant discharge area at Crystal River. 23 6 Thermally affected area showing location of the shallow inner bay system dominated by the seagrass, Halodule wright ii, and the deeper outer bay system. 27 7 Typical daily tidal cycle at Crystal River site indicating unequal high and low tides. 29 8 Model of factors affecting oxygen dynamics in water. 46 9 Example of graphical format for calculation of community metabolism at Fort Island, 24-25 August, 1973, using full diurnal curve of oxygen. 50 X
PAGE 11
1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 Graphical format for calculation of community metabolism using dawn-dusk dawn data. Comparison of community metabolism estimates obtained from complete diurnal measurements of oxygen versus estimates obtained from dawn-dusk dawn calculations made using the same data . Example of two experiments to determine oxygen diffusion coefficients by measur ing the rate of return of oxygen into a nitrogen-filled dome floating on the water's surface. Examples of submarine photometer measure ments of light penetration through the water column taken at Fort Island away from the influence of the power plant discharge plume and in the inner bay influenced by the plume. Average daily insolation by month at Tampa, Florida. Wind direction by season at Crystal River site. Monthly mean air temperature at Tampa, Florida. Monthly mean precipitation at Tampa, Florida. Weekly averages of surface water temper atures for the plume-affected inner dis charge bay and ambient water of the south intake area. Weekly ave1age of electricity generated by power units at Crystal River, and weekly average intake and discharge water temper ature fo, unit l. xi 57 60 65 68 71 74 77 80 83 86
PAGE 12
Fi9ure 20 21 22 23 24 25 26 27 28 29 Average diel water temperatures measured during community metabolism studies of the inner discharge bay and the Fort Island and . Hodges Island control areas. Diurnal patterns of electricity generated, water temperatures at three locations, and tidal stage in the discharge area of May 24-27, 1974. Average salinities measured on the inner discharge bay and Fort Island and Hodges Island study areas during the community metabolism studies. Seasonal patterns of b2nthic macrophytes in the thermally affected inner bay and inshore portion of the south intake area. Map of summer standing crop of attached macrophytic plants in the region near the Crystal River power plants. Seasonal diversity of benthic macrophytes in the inner discharge bay and the south intake area. Seasonal record of biomass of benthic macroinvertebrates in the inner discharge bay and south intake areas. Seasonal record of biomass of fish caught with drop nets in the inner discharge bays and south intake areas. Carbon, nitrogen, and phosphorus measure ments at the mouth of the discharge canal and a station in the south intake area. Me a surements of live chlorophyll-a and phytoplankton bioma ss at a statio~ in the south inta ke area and at the mouth of the discharge canal . Xi i 88 91 94 97 100 l 02 l 05 l 07 l l 0 114
PAGE 13
Figure 30 Daytime net photosynthesis and night respiration in the inner discharge bay affected by the thermal plume and the Fort Island and Hodges Island area away from the influence of the power plant. 125 31 Daytime net photosynthesis plus night respiration as a measure of gross primary production in the inner dis charge bay affected by the thermal plume and the Fort Island and Hodges Island areas away from the influence of the thermal plume. 127 32 All daytime net photosynthesis and night respiration values from Tables 6 and 7 and Figure 30 plotted on 12-month graph. 129 33 All daytime net photosynthesis plus night respiration values from Tables 6 and 7 and Figure 31 plotted on 12-month graph. 131 34 Average oxygen values from all summertime diurnal measurements taken in the inner discharge bay and Fort Island control bay. 135 35 Seasonal averages of daytime net photo synthesis and night respiration in the inner discharge bay and control areas. 138 36 Seasonal averages of daytime net photo synthesis plus night respiration as a measure of gross primary production for plume-affected inner bay discharge area and unaffected control areas. 141 37 Seasonal trends of the ratio of daytime net photosynthesis divided by night respiration for plume-affected inner bay area and unaffected Fort Island and Hodges Island areas. 144 38 Summary energy diagram of summer stocks and flows for the inner discharge bay. 151 X i i i
PAGE 14
Figure 39 40 41 42 43 44 45 46 Summary energy diagram of summer stocks of biomass or material and flows of energy and organic matter for the south intake area away from the influence of the power plant discharge. Energy diagram for simulation model of inner discharge bay emphasizing the diurnal properties of the system. Computer plots of forcing functions of tidal volume exchange, depth, offshore oxygen, and offshore water temperature used in the diurnal simulation model. Simulation results of diurnal model of inner bay with coefficients set as originally scaled. Data gathered from the inner bay during the community metabolism study of June 21-22, 1973, against which the simulation of the model of Figure 20 was compared. Solar insolation for June 21, 1973, as recorded by a pyranometer located at the Crystal River power plant site. Total radiation received is indicated. Simulation results of diurnal model of inner bay with original scaling, but sunlight r educed to a daily total similar to June 21-22, 1973. Simulation results of diurnal model of inner bay with equal amounts of canal and offshore water contributed to the inner bay on a rising tide. 47 Simulation results of diurnal model of the inner bay with two parts canal water to one part offshore water contributed to the inner bay on a rising tide. 48 Simulation results of diurnal model of inner bay with canal water alone being contributed to the inner bay on a rising tide. xiv 153 156 163 166 170 172 174 178 182
PAGE 15
49 Simulation results of diurnal model of the inner bay with a 7C dif ferential of discharge canal water over ambient water and a mixing ratio on a rising tide of one part canal water to one part offshore water . 185 50 Si~ulation results of diurnal model of the inner bay with a 7C differential of discharge canal water over ambient water and a mixing ratio of 2 parts canal water to l part offshore 1-Jater on a rising tide. 187 51 Simulation results of diurnal model of the inner bay with a 7C differential of discharge canal water over ambient water and with canal water alone flowing onto the inner bay on a rising tide. 192 52 Simulation results of diurnal model of the inner bay with no discharge of cooling water from the power plant dis charge canal and original scaling of insolation. 194 53 Simulation results of diurnal model of the inner bay with no discharge from the power plant discharge canal and insolation reduced to one-half original scaling. 196 54 Simulation results of diurnal model with timing of occurrence of high and low tide reversed from previous runs. 198 55 Energy diagram of simulated model of inner discharge bay emphasizing seasonal properties of the ecosystem. 200 56 Seasonal patterns of ins6lation and tempera ture used as forcing functions in the seasonal model of the inner bay ecosystem. 200 57 Simulation results with initial scaling of seasonal model of the inner bay. 21 0 xv
PAGE 16
Figure 58 59 60 61 62 63 64 65 C-1 D 1 Simulation results of seasonal model of the inner bay with seasonal pattern of temperature increased 3C. Response of seasonal simulation model of the inner bay to increased tempera ture and turbidity. Response of seasonal simulation model of the inner bay to decreased turbidity and a seasonal temperature range as originally scaled. Response of seasonal simulation model of inner bay to decreased turbidity and a seasonal temperature range of l8C 36C. Energy diagram and analog computer patch ing diagram of simulation model of producer module with temperature affec ting both photosynthetic and respiratory pathways. Simulation results of model of producer module in Figure 62 with seasonally vary ing light and temperature. Simulation response of seasonal model of the inner discharge bay to the addition of pathways of exchange of fish and fish larvae with offshore waters. Simulation results of seasonal model of inner bay as modified in Figure 64 with larger photosynthetic coefficient added in winter. Analog computer patching diagram of scaled equations given in Tables C-6 and C-7 for the diurnal simulation model of the inner bay. Analog computer diagram of scaled equa tions given in Tables D-4 and D-5 for the seasonal simulation model of the inner bay. xvi 214 217 220 222 231 233 237 241 354 406
PAGE 17
Abstract of Dissertation Presented to the Graduate Council of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PRODUCTIVITY MEASUREMENTS AND SIMULATION MODELS OF A SHALLOW ESTUARINE ECOSYSTEM RECEIVING A THERMAL PLUME AT CRYSTAL RIVER, FLORIDA By Wade Hampton Barnes Smith August, 1976 Chairman: Howard T. Odum Major Department: Environmental Engineering Sciences The effects of the heated discharge of two power plants on the receiving estuarine ecosystem near Crystal River on the west coast of Florida were investigated with measurements and simulation models to help understand relationships and predict the consequence of a third power plant under construction. Energy circuit models emphasizing diurnal and seasonal aspects of ecosystem responses were used to assess the effect of power plant operation on estuarine ecosystems. Field measurements were taken in the discharge-affected and -unaffected areas nearby. Benthic populations dominated total metabolism in both systems . Community gross primary production varied seasonally in the unaffected areas from a winter xvii
PAGE 18
low of 3.3 g o 2 ;m 2 •day to a spring high of 8.8 g o 2 ;m 2 -day. In the discharge area it was relatively constant, remain ing about 4 g o 2 ;m 2 -day in all seasons. Phytoplankton production normally was about 5 percent of total produc tion in the unaffected areas and about 23 percent in the discharge area. In the spring its contribution increased greatly to 25 percent in the unaffected area and 70 per cent in the discharge area. Total biomass was less in the discharge than in unaffected areas. Lower standing stock of primary producers and benthic invertebrates in the discharge area accounted for almost all the difference. Diversity was lower in the discharge bay than in the unaffected area. Mixed macroalgae and seagrasses were the dominant benthic producers in the unaffected areas, while the seagrass Halodule wrightii was virtually the only species in the discharge bay. Species diversity was lower for oyster reef organisms, and fewer species of fish were caught in drop nets in the discharge bay than in the unaffected bay. A shift toward more cycling of material and energy through the phytoplankton and filter feeders and away from the benthic components of the system ,nay have occurred in the discharge area as an adaptation to the thermal plume. X V i i i
PAGE 19
Simulation of the model of diurnal system proper ties with coefficients representing those for discharge conditions gave patterns similar to those measured in the discharge bay. The model was relatively insensitive to adjustments in water temperature within the range expected in the future at Crystal River. A change in the quantity of daily insolation produced a larger change in model response. The simulation model of seasonal system proper ties was also more sensitive to light than to water temperature. Increasing temperature alone . increased primary production and total respiration somewhat, espe cially in the spring. Fish and invertebrate biomass remained the same, while detrital storages declined, perhaps indicating their importance as an energy source for offsetting increased respiratory drains on consumers because of increased temperature. Increases in light alone greatly increased system storages and flows, sug gesting the importance of turbidity in controlling metabolism in the discharge area. Increasing temperature but decreasing light lowered metabolism. Adjustments to the seasonal model tested the theory that systems with prominent seasonal pulses may be exploitRd by populations that move in during the period of plenty, experience rapid exponential growth, and then xix
PAGE 20
move away. With some migration the fish stock could main tain itself in a stable oscillating yearly pattern. Results of other adjustments to the seasonal model suggested that seasonal substitution of species of primary producers may be the most effective way to make maximum use of available energies at all times of the year. xx
PAGE 21
INTRODUCTION This is a study of shallow, benthic-dominated estuarine ecosystems on the Florida west coast, one of which received a thermal discharge from two electric generating stations of the Florida Power Corporation. Water was drawn from the deeper offshore Gulf of Mexico, passed through the power plant condenser system, where its temperature was increased about 5C, and discharged onto the shallow inshore coastal area (Figure l ). This study was made to increase understanding of the structure and function of estuarine ecosystems, the relationship of individual parts to the functioning of the total pattern as an integrated unit, and the effects of temperature change. Specifically investigated was the nature of an estuarine system which had been receiving thermal effluent for si x years. How does an entire ecosystem adjust and adapt to these new energy conditions imposed on it? How does the ne w syste m serve as an interface between the econo m y of man Rnd that of nature? Energy diagrams were drawn to organize, summarize and synthesize data in models, and as a conceptual tool l
PAGE 22
Figure l. Location of Florida Power Corporation's power plants near Crystal River, Florida, in relation to the major features of the regional coastline. Oyster bars are indicated by dotted outlines.
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CRYSTA~ RIVER POWER PLANT 772 0 100 MILES 0 I 2 3 KILOMETERS p-;.-... 0 0.5 I NAUTICAL MlLES w
PAGE 24
for illustrating ideas about the ecosystem at Crystal River and the role of thermal loading in shaping its pattern. Total metabolism, including photosynthetic production and total respiration, was m~asured as the primary indicator of the main system functions. Using simpler models, com puter simulations of seasonal and diurnal trends were run and compared with measured data. This study was part of a much larger project funded by the Florida Power Corpora tion evaluating questions related to the impact of its power ~lants at Crystal River on the adjacent estuarine ecosystems. As required by our contract, efforts were made to summarize data from other studies in developing an over view of the ecosy s tem. As fossil fuels for powering man's economy become scarcer and more expensive, the need increases for recognizing, utilizing, and protecting the important work contributions of nature in support of man's economy, and establishing effective feedback pathways from man to protect his life support system. A regional system of man and nature which allows its natural components to contribute work services in support of the overall pattern may avoid unnecessary technological constructions and be most successful in utilizing ~11 available energies when use of the environ ment constitutes more useful work than is lost by environmental impact. For example, should coastal and estuarine ' wa t ers be used for cooling of the thermal effluent from
PAGE 25
5 electric generating stations, or is it necessary to build technological alternatives such as cooling towers for this purpose? System Adaptation, Environmental Impact, and Thermal Loading of the Estuary at Crystal River, Florida At Crystal River, and wherever thermal effluents flow into an ecosystem, potential energy is carried with it. This energy, like all other energy sources impinging there, is available for doing work in the environment, although its exact way of doing work may not be known (Odum, 1974b). Other changes besides thermal loading are caused by power plant installations. At Crystal River the con struction of dikes and the pumping of cooling water through the canal system (see Figure 1) may modify the current and flushing characteristics of the surrounding waters. Turbidity in the discharge area may have increased because of scouring of the discharge canal and from sediments carried through the power plant from the intake canal where they had been stirred up by barge traffic. Canal construction caused changes in drainage patterns and mor phology of adjacent salt marshes. The most important impact, however, may be the effect of higher temperature on biological processes.
PAGE 26
6 Adaptation and acclimation of metabolism of individual organisms to offset temperature changes is well estab lished (Bullock, 1955). Much less is known about the re sponse of whole ecosystems to changed thermal regimes. How does system structure adapt so that the new pattern that emerges is best coupled to the changed thermal regime? What is the nature of this new system linked to man's technology? These questions may begin to be answered by observing such system properties as total community metabolism, species diversity, and seasonal patterns. ~he effect of thermal loading on biological pro cesses may be important at both the level of individual organisms and the ecosystem (Kelley, 1971; Odum, 1974b; McKellar, 1975). Since all processes are stimulated equally below the threshold of rapid thermal enzyme destruction, temperature acts to increase processes building structure as well as those degrading it (Figure 2). For a plant (Figure 2a), the dark reactions of photosynthesis may be stimulated as much as respiratory pathways, so that the overall effect on biomass may be neutral. However, if photosynthesis is limited by energy and material shortages so that respiratory losses are not offset, biomass may decline. The same holds true for a consumer (Figure 2b). If the metabolic pathways of digestion and rebuilding of structural animal biomass are affected at the same rate as those degrading this biomass, inetabolism increases but
PAGE 27
Figure 2. Energy diagrams of producer and consumer modules indicating the push-pull effects of temperature on internal processes. See Appendix A for meaning of symbols. (a) Producer module with temperature acting on both photosynthetic primary produc tion and respiration processes. (b) Consumer module with temperature acting on processes of biomass formation through food gathering, digestion, and assimila tion as well as the respiratory degrada tion of biomass.
PAGE 28
lo ) { b) FOOD SOURCE 8 . ______ _, -----------' \ \ I I I /
PAGE 29
9 the amount of biomass is unaffected. However, if food is limited the population loses mass because it cannot compen sate for respiratory losses. For the ecosystem, if it is to compete at the new steady state, respiration degrading structure induced by higher temperatures must be compensated for by the larger push of increased rates of production of system structure. Can accelerated cycling of nutrients from increased res piration offset nutrient limitations to primary production? Is this increased production enough to supply energy demands of larger consumers? Models for Gaining an Overview of the Estuary and Power Plant at Crystal River Proposed in Figures 3 and 4 are the energy circuit models at different levels of complexity of the system of estuary and power plants at Crystal River. Their purpose is to organize in overview concepts of system structure, processes, pathways, interactions, and relationships. Inherent in the diagrams are patterns important on both daily and seasonal time scales. An explanation of symbols used in this disse r tation is giv~n in Appendix A. More complete discu s sion s and additional symbols are given by Odum (1971, 1972, 1974a, 1975).
PAGE 30
l 0 Simplified Model of the Inner Bay Given in Figure 3 is a model diagram of the inner bay ecosystem from which details have been eliminated leaving only the basic system structure of water storage, benthic macrophytes, consumer populations and tidal ex changes with the saltmarsh, offshore, and canal ecosystems. On a rising tide surface water from the power plant dis charge canal is forced onto the inner bay by the damming effect of water flowing on from offshore and the increasing height of head of the approaching wave of the tide. On a falling tide canal water flows directly down the channel beside the inner bay, where it receives water flowing off the bay. Diffusive oxygen exchange with the atmosphere occurs driven largely by turbulence induced by tidal exchange. Gains of heat result fro~ solar insolation and atmospheric longwave radiation. Heat losses occur from conduction, back radiation, and evaporation. Primary production occurs in the phytoplankton and the benthic macrophytes, which take up nutrients and oxygen from the water column while returning oxygen and organic matter to it. Storages of organic matter are in the water column and sediments, which are consumed by populations of microbes. Two ~lasses of consumers are shown. In the water column are free living animals feed ing on detritus, phytoplankton, benthic invertebrates, and
PAGE 31
Figure 3. Aggregated energy diagram of the main fea tures believed important in the ecosystem of the inner discharge bay at Crystal River. Details within the compartments have been omitted to emphasize basic sys tem structure and function in overview. Symbol shown as T indicates a connection from heat sinks I y (--=-)definition of symbols. See Appendix A for
PAGE 32
l 2 r--~----~------~-1 I I SALT MARSH I SUBSYSTEM I I I --------__ , TEMPERATURE INNER BAY WATER COLUMN CONTAINING HEAT, NUTRIENTS, TURBIDITY, ORGANIC MATTER, OXYGEN, AND PHYTOPLANKTON BENTHIC MACROPHYTES AND EPIPHYTES EVAPORATION EXCHANGE WITH CANAL ONLY 0 RISING TIDE N A'fi8_~ NUTRIENT RECYCUNG
PAGE 33
l 3 each other. Many of the larger m~mbers of this compart ment migrate seasonally to and from the offshore regions. Benthic invertebrates and oysters feed largely on detritus and phytoplankton. Nutrients are regenerated into the water column from all respiratory pathways. Detailed Model of the Inner Bay In Figure 4, more of the complexity of detail within the compartments has been added to the model of Figure 3. Sunlight penetrating the water column of the inner bay is attenuated by turbidity, shading of phyto plankton biomass, and the natural extinction properties of water. Primary production utilizes the remaining light, and is concentrated in the benthic macrophytes and their associated epiphytes with a smaller contribution from the phytoplankton. This production moves to the higher trophic levels primarily through a storage of detritus and its associated microbes in the sediments. A much smaller amount is stored in the water column. A small amount is transferred by direct grazing of epiphytes. Larger con sumer populations are represented by benthic invertebrates and oysters, zooplankton and larval forms, shrimps and crabs, and resident and migratory fish. Seasonal migratory movements of shrimps, crabs, and migratory fish stocks are indicated. All respiratory pathways are shown returning nutrients into the water column storage. Various
PAGE 34
Figure 4. Energy diagram of the ecosystem of the inner discharge bay, which includes much of the complexity omitted from Figure 3. Pathways of oxygen uptake and temperature effects have been abbreviated for clarity. Pathways from storages of heat and oxygen labeled T and 0, respectively, are assumed to be con nected with similarly labeled pathways on work gates and consumer modules. Pathway marked as "'f indicates a connection from heat sink symbols ( _{_ ).
PAGE 35
l 5 OFFSHORE: I I ' ' ' I INTAKE : CANAL , POWE PLAN ---------------------
PAGE 36
l 6 exchanges with the adjuacent saltmarsh, power plant canal, and immediate offshore ecosystems occur with the rise and fall of the tide. Heat in the water is lost and gained through physi cal processes as well as advective exchanges. Gains occur from solar insolation, atmospheric longwave radiation, and heat generated from all biological processes. losses re sult from back radiation and evaporation. Conduction is a gain or loss depending on the direction of the gradient between air and water. Oxygen has a diffusive exchange with the air driven largely by water turbulence. In summary, this detailed model serves to emphasize issues related to the interactions of power plants with estuaries, helps the reader visualize the system studied at Crystal River, summarizes initial understanding of its characteristics, helps to plan the research program, and provides a basis for simpler models for simulation. Previous Studies of Thermally Affected Aquatic Ecosystems Most work on the effect of temperature on life processes has been at the level of the whole organism or at smaller (e. g. subcellular) levels; less work has been concerned with its effect on whole ecosystems. Perhaps because of their simplicity the most thoroughly studied ecosystems to date have been thermal spring
PAGE 37
l 7 ecosystems. System structure has been discussed by most authors (Brock, 1967a, 1967b, 1969; Brock and Brock, 1969; Kullberg, 1966; Stockner, 1967, 1968; Wiegert and Fraleigh, 1972). Zonation of algal or bacterial mat communities associated with temperature gradients, both down and across spring runs, with a vertical zonation of structure at any given point were the main characteristics of these eco systems. Filamentous bacteria were dominant in the hotest portion of the stream, being replaced by blue-green algae as the water cooled. Green algae, in turn, replaced the blue-green at still lower temperature cooling. Species diversity was very low overall, tending to increase down the temperature gradient. Community metabolism in thermal springs has also been measured (Brock, 1967b; Duke, 1967; Phinney and McIntire, 1965; Stockner, 1968; Wiegert and Fraleigh, 1972). Values measured generally fell within ranges reported for many other types of aquatic ecosystems. Brock (1970) reviewed work on high temperature systems. The work reported above is mostly on springs with temperatures in excess of 45 C, which is generally above . the thermal li m its for enzyme dest r uction of most organisms. Available work on thermally aff e c t ed systems within temper ature ranges 1nore norm a lly encountered in nature has mostly involved mic r ocos m studies. Allen and Brock (1968) re ported that n1icrocosms held at a range of temperatures
PAGE 38
18 from 2c to 75C and all seeded alike from a wide variety of sources; each developed its own characteristic combina tion of species. Beyers (1962) found only small responses in community metabolism to 36-hour increases in temperature. Davis (1971), studying experimental estuarine ecosystems contained in large plastic swimming pools, found increased gross community primary production and respiration during spring, summer, and fall in those heated 4-6C above con trols. Kelley (1971) studied high-nutrient freshwater micro cosms subject to constant low, constant high, and fluctuat ing temperature regimes. Mean values of net production and night respiration over the study period were higher in those microcosms which had higher mean temperatures. Vari ous aspects of the biology of Par Pond, a freshwater reactor cooling pond at the Savannah River Plant, South Carolina, have been studied for a number of years by investigators at the Savannah River Ecology Laboratory of the University of Georgia (Gibbons and Sharitz, 1974b). A general assessment of research related to the environmental effects of the operation of power plants is difficult because much of it is contained in reports to Federal agencies concerned with licensing, and is gen erally unavailable for r~view. Zieman (1970) has reported on the early effects of the operation of power plants at Turkey Point on Biscayne Bay, near Miami, Florida. Condi tions of flow rate and ten 1 perature rise of the cooling water were very similar to those at Crystal River. The receiving
PAGE 39
l 9 ecosystem was dominated by a mixture of macroalgae and sea grasses (mostly Thallassia testudinum). By the end of the second summer of operation 50-60 acres of bay bottom adja cent to the mouth of the discharge canal had been denuded of this community and replaced by a blue-green algal mat community. An additional 70-75 acres had some Thallassia, but were still devoid of macrophytic algae, while 160-170 more acres exhibited some stress to the existing macro algae populations. Other available power plant data have dealt with more northern situations involving phytoplankton . -dominated ecosystems. The effects of increased temperature on pri mary production were usually measured by the uptake of carbon-14, often in bottles held in illumin a ted light bo x es. Results have been mixed. Several studies in volving both estuarine and freshw a ter cooling systems have found stimulation of photosynthesis in the cooler months and a depressing effect in the warmest months (Morgan and Stross, 1969; Smith~ -~l-, 1974). Tilly ( l 9 7 4 ) , u s i n g c a r b o n 1 4 rn e a s u r e m e n t s i n c u b a t e d i..!!_ s i t u in Par Pond, South Carolina, found primary production to be somewhat greater in the surface water at the warmer station. This tendency was more pronounced during the warm months of the year. Gurtz and Weiss (1974), also using carbon-14 methods, found inhibition of pho t osynthesis at all times of th e year. A trend to w ard greater inhibition at higher am bient water temp e ratures was suggested by the data.
PAGE 40
20 Only several reports appear to be available on aspects of ecosystems which have been adapting to power plant discharges for a number of years. North (1968) studied the discharge area affected since 1957 at Morro Bay, California. He found abundance and diversity of plants and animals to be reduced in a transitional region over a distance of approximately 200 m from the end of the discharge canal. Recovery to conditions typical of the area occurred in a relatively short hori zontal distance of 10 mat the end of the transitional region. J. R. Adams et .tl_. (1974) could find no differ ence in intertida1 sandy beach populations located near the discharge versus ones further away. Few power plant studies appear to have synthesized the diverse data into an overview of the ecosystem respond ing as an integrated unit to the new set of environmental forcing functions. Emphasis has generally been placed on individual aspects of power plant operation, such as entrainment through the condenser cooling system and entrapment on the screens protecting the cooling water intake pumps (Jensen, 1974c), or on individual species or components of the ecosystem. Typical studies might examine mortality of phytoplankton from passage through the condenser system, diversity and biomass of benthic organisms and fish in the discharge area, or primary producticn of the phytoplankton component of the ecosystem.
PAGE 41
21 Often these studies have been done in the laboratory. Chesapeake Science, volume 10 (1969), and proceedings of symposia edited by Gibbons and Sharitz (1974a) and Esch (in press) contain many papers of this type. Several studies have been published which contain most research results for a particular power plant in one volume (Jensen, 1974a, 1974b; Central Electricity Generat ing Board). Discussion of results, however, is by sub systems with little attempt to synthesize the findings with text, diagrams, or simulation models into a picture of the functioning of the whole ecosystem. DescriRtion of S t udy Area at Crystal River The power plant site in . Citrus County (Figure l) is on the low wave ~nergy portion of the Florida west coast as defined by Tanner (1960). The shallow sloping bottom (46 km to the 5 fathom contour) is part of the drowned karst topography of this portion of west central Florida. The topography of the immediate offshore region is a series of shallow basins separated by oyster reefs (Figure 5). Freshwater sources influencing the area are the Crystal River 4.8 km to the south (mean flow 1500 m 3 /min; 400,000 gpm), and the Withlacoochee River and Cro s s Florida Barge Canal 6.4 and 5.8 km to the north, respectivel y , with a combined flow of 2150 m 3 /min {570,000 gpm).
PAGE 42
Figure 5. Bathymetry of power plant discharge area at Crystal River. Location of inner bay has been circled. Contour interval is l .0 feet. Datum based on mean sea level. (Adapted from Rodgers~~-, 1974)
PAGE 43
INNER _ DISCHARGE BAY ~ ~l*~E: :S . ' -~~ ~-•~"-!.~~-~.~-,. 0 NAUTICAL MILE ... .:-~ ---\;2 .. :'>"' "(~ ...... ..-: .• .... ~,.. . (ADAPTED FR ---.......::...:.:: , ISCHARGi)~~kRODGERS, et QL, 1974) ,'.~-C8~~!\. , : ~ ;:._+:r:t;-.,,( r: -
PAGE 44
24 The power plants are on the landward edge of a tidal saltm a rsh dominated by Juncus roemerianas bordered on the seaw a rd edge by a narrow fringe of Spartina alterniflora. Two units were in operation during this study--unit l since July, 1966, and unit 2 since November, 1969--giving a combined total output of 897 megawatts electrical (MWe). A nuclear powered unit of 885 MWe output was under construction. The two operating units cycle water for once-through cooling at a combined flow of 2430 m 3 /min (640,000 gpm) through canals dredged across the shallow offshore region and saltmarsh. Maximum condenser temperature rise is 6.lC. The powe r plant intake canal extends appro x mately 4.8 km into the Gulf with an average depth of 6-7 m and a width of about 75 m, serving also as the passageway for delivery of fuel oil in barges by large ocean-going tow boats. Cooling water passes down the canal at about 8 cm/sec before being pumped through the power plant condensers, where its temperature rises 5-6 C. The discharge canal is about 1.6 km long with an average depth and width of about 4.5 m and 50 m, respectively. The smaller cross-sectior, Q l area causes th e str e an1 velocity to be about twice th a t in the intake c a nal . The residence time of water mas s es in the canal system is about 20 hour s fo r the inta k e canal and about 3.5 hours for th e discharge canal.
PAGE 45
25 Two types of bay systems are affected by the thermal plume (Figure 6). Imm e diately adjacent to the saltmarsh is the shallow bay of this study averaging about l min depth, composed of a mixture of bottom covered with seagrass, some oyster reef associations, and areas of sand and mud. Seaward of a row of oyster bars is a deeper outer basin of about 2 m average depth in which the plankton and reef ecosystems become impor tant. The "bays" referred to here are actually the immediate landward edge of the Gulf of Mexico. The plume-affected inner bay of this study is a shallow benthic seagrass-dominated system composed almost exclusively of Halodule (Diplanthera) wrightii during the warm months, while in the winter of 1972-73 mixed Ectocarpaceae proliferated and covered much of the bottom area. It did not return during the milder winter of 1973-74. The unequal semi-diurnal tide (see Figure 7) has an average tidal amplitude of about one meter exposing much of the bay bottom on the lowest of the two daily low tides, and draining the entire bay on the lowest spring tides. In addition, strong northerly winds associated with passages of cold fronts in winter occasio n ally push the regional water mass offshore and drain the bay and the nearby coastal area for several days. With normal weather and tides, the heated plume moves back and forth ac~0ss portions of the bay in
PAGE 46
Figure 6. Thermally affected area showing location of the shallo w inner bay system dominated by the seagrass, Halodule wrightii, and the deeper outer bay system. Lettered dots indicate inner bay locations of remote telemetry buoys maintained by Florida Power Corporation for recording water temperatures. Location lettering is as designated by the Florida Power Corporation.
PAGE 47
0 Q 0.5 KILOMETERS 0 0 OUTER BAY .::1 ,. ~ I p 0 '"1:, : : ,; ,. SPOIL 8ft . .AKE 27
PAGE 48
Figure 7 . Typical daily tidal cycle at Crystal River site indicating unequal high and low tides. Ampli tude changes were taken from tide tables (U. S. Department of Commerce, 1972) for June 12, 1973.
PAGE 49
29 2.0.-------r------.--------r-----JUNE 12, 1973 E .,. :c ._ 1.0 a.. w Cl 0 --------~--__._ ___ ...._ __ __ . 0600 1200 1800 TIME OF DAY
PAGE 50
30 response to the tidal cycle. The shallow areas near the power plant which were unaffected by the thermal plume were dominated by a diverse mixture of benthic macroalgae and seagrasses. Areas away from the influence of the power plant discharge at Fort Island, Hodges Island, and in the south intake area (Figure l) were used as comparison areas. The south intake area was located immediately south of the southern intake canal dike. Measurements taken there by others included stocks of fish, benthic inverte brates, benthic macrophytes, zooplankton, sediment organic content, and nutrient concentrations . The benthic macro phytic producers were a diverse mixture of macroalgae and seagrasses. Total metabolism measurements were made at Fort Island and Hodges Island. Most measurements were made in a funnel-shaped bay south of Fort Island. This area, which was somewhat deeper than the inner discharge bay area, was characterized by a benthic flora similar to the south intake area. The extreme clarity of the water influenced by the nearby Crystal River allowed much greater light penetration to the bottom as measured with a submarine photometer than in the power plant discharge area. Hodges Island to the north of the Withlacoochee River (Figure l) was away from freshwater influences. This bay had more turbid water with little growth of benthic macrophytic plants.
PAGE 51
31 Other Studies of the Crystal River Region Little work is available on the Crystal River region prior to power plant construction. Dawson (1955) provided data on oyster populations and hydrography, including measurements at stations now well within the influence of the power plant. After construction and operation of the plants were initiated, many studies were made as part of the larger research program undertaken by Florida Power Corporation. Benthic seagrasses and algae were inven toried by Steidinger and Van Breedveld (1971), while quantitative measurements of biomass were made by Van Tyne (1974). Benthic invertebrates were inventoried by Lyons~ ~l(1971) and measured quantitatively by Evink and Green (1974). Trawl samples of fish were reported by Grimes (1971), Grimes and Mountain (1971), and Mountain (1972). C. A. Adams (1974) analyzed data on fish caught in dropnets from the shallow inshore areas, while Carr and Adams (1973) discussed the food habits of juvenile fish in the beds of benthic seagrasses and macrophytes. Homer (1975) studied seasonal patterns of tidal creek fishes. Trace metal content of oysters from the intake . and discharge canals was reported by Grimes (1971) and
PAGE 52
32 Mountain (1972). Biomass, diversity, and metabolism of oyster bars were measured by Lehman (1974a, 1974b). Blue crab movements in the intake canal area were monitored by Adams, Oesterling, and Snedaker (1974). Nutrients, chlorophyll, and phytoplankton nu m b ers and diversity were measured by Gibson (1975). Zooplankton biomass and diversity were studied by Maturo (1974). Fish and other organisms trapped on the screens protecting the condenser water intake pumps were monitored by Adams, Bilgere, and Snedaker (1974). Entrainment of larval fish and zooplankton through the condenser system was measured by Maturo (1974) and Snedaker and Johnson (1975). Total community metabolism was measured and studied with simulation models for the saltmarsh by Young (1974), for the oyster reefs by Lehman (1974a, 1974b), for the deeper outer bays by McKellar (1974, 1975), and for the power plant canals by Kemp (1974). A larger scale analysis of the energetic costs associated with estuarine cooling compared to technological alternatives was done by Odum (1974b), Odum tl tl(1974), and Kemp et al. (1975). Physical measurements of the hydrography of the aiea were reviewed by Carder (1975). These were used by Klausewitz (1973} for verification of a computer simulation model of the behavior of the thermal discharge
PAGE 53
33 plume. Bedient (1972) simulated the flushing of water from the discharge canal as it related to dispersion of radioactive wastes in the discharge water. Swindler (1973) examined the sedimentology of the region between the Crystal River and Withlacoochee River. Cottrell (1974) studied sedim~nt composition and sedimentation rates in the more immediate plant area. Previous Simulation Models of Marine Ecosystems, Diurnal Oxygen Dynamics, Temperature, and the Effects of Power Plants on Ecosystems Several previous attempts at modeling marine ecosystems have appeared in the literature. Chen and Orlob (1972) developed an extensive simulation of the San Francisco Bay and Delta region incorporating spacial as well as temporal elements. The geographical region was divided into a network of nodes and connecting path ways. Mass balance equations were used to transfer materials between nodes with tidal dynamics as the forcing function. Up to 22 parameters could be con sidered: dissolved oxygen, biochemical oxygen demand, alkalinity, pH, temperature, nitrogen (three forms), phosphorus, suspended sediment, three types of algae, zooplankton, three types of fish, and benthic animals. For conservative elements, only terms for diffusion, advection, input, and output were included in the mass
PAGE 54
34 balance. For biological elements, appropriate terms for rates of growth, respiration, mortality, and chemical transformations were added. Temperature linearly affected respiratory pathways of fish and zooplankton, and affected both photosynthesis and respiration of algae. Growth rate coefficients were based on Michaelis-Mention kinetics. Model calibration to real data was presented for only several parameters with fit being quite good. Subsequent runs evaluated the effect on the bay of proposed regional sewage treatment and water diversion alternatives. Steele (1974) simulated a simple model of the North Sea using storages of nutrients, phytoplankton, zooplankton weight, and zooplankton numbers. Sunlight was considered nonlimiting and was omitted as a forcing function, so that changes in phytoplankton biomass were a function only of nutrients, mixing below the thermo cline, and zooplankton grazing. Nutrient cycling was included as excretion by zooplankton respiration. Equation terms for nutrient uptake and zooplankton grazing were derived from observed experimental data and were given the form of Michaelis-Menton kinetics. Brylinsky (1972) performed a sensitivity analysis on a model of the English channel, which included storages of phytoplankton, zooplankton, benthic fauna, pelagic fish, demersal fish, and bacteria. Photosynthesis was considered a constant external input. Pathways of
PAGE 55
35 exchange between compartments were linear and controlled solely by the donor compartment. Since nutrients were not included as a variable, cycling was not a model fea~ ture. It was stated that the model was not intended to be realistic, but, instead, to illustrate the applica tion and usefulness of the tool of sensitivity analysis. An early attempt to simulate diurnal oxygen dynamics of an ecosystem was made by Odum, Beyers, and Armstrong (1963) using a passive analog circuit. Results supported the theoretical discussion of the effect of a small organic storage capacity in the nannoplankton on the measurement of primary production in tropical seas. Several authors have obtained very good fit for data from microcosms to relatively simple models of their diurnal properties. Sollins (1970), studying a blue-green algal mat, followed oxygen through compart ments of producers, consumers, detritus, dissolved oxy gen, CO 2 (total in solution), atmospheric oxygen, and water. All flows between compartments were controlled by the upstream compartment only (donor control). Using a square-wave regime of light input, the model produced simulated curves of oxygen very similar to measured curves and their rates of change. Kelley (1971) included only storages of carbon dioxide and labile and structural organic matter in his
PAGE 56
simulation of a nutrient-rich freshwater microcosm of mixed plankton. Since his study was partially concerned with the effects of temperature, it was included in a push-pull fashion as an action on every pathway. Rates of flow between compartments were otherwise controlled only by the donor compartments, as in the model by Sollins. Excellent fit was obtained to the measured oxygen data. Nix~n and Odum (1970) considered only storages of organic material and nutrients in a model of hyper saline algal mat community. Transient responses of this very simple model were compatible with those observed in the microcosm. Simulations based on the more variable data gathered from open ecosystems in nature have been carried out. A model of Bissel Cove, Rhode Island (Nixon and Oviatt, 1973) was basically an oxygen balance consisting of a single storage of oxygen with inputs from primary production of plankton, macroalgae, and benthic microflora. Respiratory oxygen losses occurred to producers, sediments, detritus, shrimp, and fish. Diffusion exchange with the atmosphere and tidal exchange with a constant oxygen source were losses o r gains depending on the saturation level of the water and the stage of the tide. Rates of oxygen losses or gains for each pathway were empirically derived from regression
PAGE 57
37 equations calculated from observed data. No feedback or cycling pathways were included. Model response fit reasonably well to observed diurnal curves of oxygen. Boynton (1975) simulated a river-dominated estuary to examine issues of river discharge schedules and potential effects of human development on nearby lands and its relation to an oyster fishery existing in the bay. Using a simplified energy symbol model, diurn a l curves of oxygen very similar to data measured in th e area were obtained. Several simulations have included temperature actions. An early on e emphasizing the effect of temper ature as an exponential function on zooplankton popula tions of the North Sea was done by Riley (1946, 1947). Odum (1975) translated these equations into models using the energy circuit language. Hall (1974) briefly reported on a simulation model of the effect of power plants on the striped bass fishery of the Hudson River. Details of the model were not given. Odum (1974b) discussed some general principles regarding temperature and system responses, including the push-pull effect on both ordering and disordering processes. Examples were given of simulations of equa tions proposed by Eyring and Eyring (1963) and Morowitz (1968) which incorporated the push-pull feature of temperature action.
PAGE 58
, J 38 Nixon and Oviatt (1973) included temperature actions only on respiratory pathways in their simula tion model of Bissel Cove. As a result, a decline in oxygen was predicted as the effect of the action of a hypothetical power plant on the cove. Miller (1974) simulated the effect of maintain ing mangrove vegetation in power plant canals to aid in cooling the water before recirculation through the power plant. Increased, but not severely detrimental, water stress was predicted for the trees. Several simulation models of other ecosystems at Crystal River have been run. Young (1974) observed increased photosynthesis, respiration, and live and dead standing crop in simulations of the effect of elevated water temperatures on the fringing Spartina saltmarshes. Lehman (1974b) simulated the intertidal oyster reefs. Model responses included faster turnover rates for plume-affected conditions. Simulations of effects of adding thermal waters of another power plant suggested reduced seasonal variation of reef standing stocks. Kemp (1974), in a preliminary simulation of the com munity of fish, plankton, and benthos of the power plant intake canal, found fish stocks to be most sensitive to water flow rates and immigration. Plankton was rela tively insensitive to most paramet e rs, being controlled principally by concentrations carried in from outside
PAGE 59
39 the canal. McKellar (1975) simulated the outer bay of the discharge area (see Figure 6) . Raising the water temperature to that measured in the discharge area produced only small increases in total metabolism and some component storages. Water exchanges were shown to be a stabilizing influence by dampening large fluctua tions in zooplankton, phosphorus, and detritus. Simula tion of the conditions expected with future power plants produced no large changes in total community metabolism. Plan of Study The structure and function of the thermally affected inner bay ecosystem at Crystal River and unaffected areas to the north and south were determined from field measurements of biomass of organisms and system metabolism, and from the behavior of ecosystem simulation models evaluated with these and other data. The conceptual model shown in Figure 4 was developed as an overview to show the relation of the main energy exchanges with the outside, and of the main storages of the inner bay ecosystem among themselves. Simpler models which aggregated the main stocks and processes were simulated on an analog computer. Total community metabolism was determined from diurnal changes in free-water oxygen concentrations and was u~ed as an indication of the ability of the
PAGE 60
40 ecosystem to process the energies available to it. Comparison of metabolism of the thermally affected area with areas away from the influence of the power plants indicated the degree to which these processing abilities had been altered. Measurements were taken from June, 1972 through May, 1974 representing all seasons and establishing general seasonal trends of metabolism. Efforts using bottle experiments were made to partition total metabolism between its planktonic and benthic components. Measurements were made of penetra tion of light through the water column. Models were evaluated with data obtained in this study and gathered concurrently by other researchers, with other supporting measurements, information from the literature, and some necessary calculations and assumptions. These models were translated directly into a set of differential equations, which were programmed for analog computer simulation. Simulation runs were . made with coefficients set for conditions with and without the influence of the power plant. Results were compared to the observed data. Sensitivity of the models was examined with respect to changes in water temperature and ratios of discharge canal water to offshore water mixing on the inner bay. Finally, simulations were run with conditions expected when the new power plant begins operation.
PAGE 61
METHODS Metabolic Measurements Community metabolism was measured with diurnal sampling of oxygen following Odum and Hoskins (1958), Odum and Wilson (1962), and Odum (1967), and an abbrevi ated method using dawn dusk-dawn oxygen samples (McConnell, 1962). Oxygen was measured by the azide modification of the Winkler technique (Amer. Publ. Health Assoc., 1971), but adapted for use with smaller sample collection bottles. Mini-Winkler Field Kit and Winkler Method Modific a tion Because of the large number of samples to be processed and the need for compactness, a mini-Winkler field kit developed at the University of Texas Institute of Marine Sciences was used i11 this study . Standard flat-topped 125-ml reagent bottles were used for sample collection in place of 300-ml BOD bottles. Samples were fixed with 0.5 ml of manganous sulfate and azide reage~t carried in dropping bottles in the field kit. After 41
PAGE 62
42 acidification with 0.5 ml concentrated sulfuric acid, 100-ml subsamples were titrated with 0.012 N sodium thiosulfate. This normality allowed direct reading of milliliters of titrant as mg/1 of oxygen. Variability between replicate pairs of oxygen samples could have arisen from many sources; Since the small reagent bottles used were inexpensive, variation in their individual volumes was expected. A test of a 54-bottle subsample of those in use gave an average volume of 122.8 ml with a standard error of 0.22. Because each bottle was filled from a separate sample of bay water taken 30 seconds to one minute apart, vari ations due to water mass differences could also have occurred. Other sources of variation could have included differences in reagent volumes added and differences in sample volumes titrated. Actual differences in titrant volume encountered between replicate pairs of samples were small, however. Based on a subsample of 486 replicate pairs, 72.6 percent differed by 2 drops (0. 1 ml) or less. Since titrant volume was generally in the range of 4-8 ml, this gave an average error of 1 .3-2.5 percent. Loss of accuracy due to increased sources of variability was, therefore, considered minimal, and was far outweighed by convenience in handling in the field. More samples could be processed, permitting better estimates for the whole bay.
PAGE 63
43 Significance of Delay in Fixing Winkler Bottles with Acid A test was made of the effect of an eight-hour delay in adding acid to the sample bottles in the Winkler analysis of oxygen. Thirty bottles were filled with thoroughly mixed salt water from a bucket, and immediately fixed with the manganous sulfate and azide reagents. Ten bottles were picked at random, acidified, and titrated within 30 minutes. The remaining bottles were split into two groups, one group of 10 bottles receiving acid, while the other did not. Both groups were stored in the dark for eight hours. At the end of that time, acid was added to the bottles which had not received it earlier, and both groups were titrated. Table l gives the results of the three treatments. Differences between treatments were significant (95% level), but were considered too small to have any significant effect on the measurements. Complete Diurnal Samplinq of Oxygen The calculation of total community primary pro duction and respiration from free-water measurements of oxygen is based on the model given in Figure 8. As indicated, the oxygen concentration in the water column at any moment and changes in concentration with time are a function primarily of the production of oxygen during photosynthesis, its consumption in respiratory
PAGE 64
44 Table l. Results of a technique test of the Winkler method to determine the effect of the presence or absence of acid in fixed bottles which have been stored for eight hours before titration. Each treatment contained 10 bottles. Results are given in milliliters of titrant. Bottles fixed, Bottles fixed and Bottles fixed acidified, and acidified immediimmediately; titrated ately; titrated acidified and immediately 8 hours later titrated 8 hours later Average 5.45 5.43 5.48 Std. Error 0.02 0.01 0.01
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Figure 8. Model of factors affecting oxygen dynamics in water.
PAGE 66
I 46 SATURATION OXYGEN CONCENTRATION PHOTOSYN ' f IN WATER HESIS~ RESPIRATION ADVECTIVE EXCHANGE
PAGE 67
47 processes, gains or losses because of advective exchange with adjacent water masses, and diffusive exchanges with the atmosphere. The contribution to oxygen dynamics of the nonbiological processes of advection and diffusion may be corrected for if their magnitudes are known or can be estimated. Subtracting their effect allows a calcu lation of changes resulting only from the biological processes of photosynthesis and respiration, and, thus, a calculation of production and respiration. After correcting for diffusion and advection, any gain in oxygen concentration during daylight hours would be a consequence of the greater production of oxygen in photosynthesis than its concurrent use in respiration, thereby providing a measure of net primary production. At night, when there would be no production of oxygen by photosynthesis, the rate of oxygen decline would be an estimate of community respiration. By assuming a similar respiration rate for daylight hours (which would be a conservative assumption), an estimate of the rate of gross primary production may be obtained by adding daytime photosynthe s is and night respiration. Stations were sampled approximately every three hours over a 24-hour period. Two buckets of surface water were collected 30 seconds to one minute apart at each station, and sample bottles were filled from the bottom by siphoning through rubber tubing. Late night
PAGE 68
48 samples were sometimes stored without acidification for titration the following morning (see above for effect on Winkler analysis). Time, temperature, salinity, and depth were noted at each station. Because of the large tidal flushing, advection of water masses from outside areas was at first thought to be important. In order to assess this effect on the diurnal oxygen curve in the study areas, four or five stations were sampled in the early part of the project. Analysis indicated a general similarity in the daily increase and decrease of oxygen at all stations, sug gesting that advection was from areas of similar metabo lism. Thus, errors ir1troduced by advection were thought to be small, and the number of stations was usually re duced to two or three to meet field schedules. Diurnal metabolism graphs were constructed using a standard format (Figure 9) to allow easy visual com parison among all diurnal samples taken at Crystal River as well as with others in the literature (Odum and Hoskins, 1958). The data were analyzed several different ways as the study progressed. At first, a graph for each station was plotted and analyzed sepa1ately. Later, all points from separate stations were plotted on one graph, but only the mean curve was analyzed (Figure 9). Each o x ygen point was the average of duplicate Winkler analyses. Oxygen per square meter (Figure 9c} was
PAGE 69
Figure 9. Example of graphical format for calculation of community metabolism at Fort Island, 24-25 August, 1973, using full diurnal curve of oxy gen. Open circles represent average of measure ments at four stations, each of which are shown as solid points. (See text for detailed dis cussion of [g] and [h].) (a) Oxygen concentration. (b) Depth. (c) Areal oxygen obtained by multiplying (a) and {b). (d) Temperature. (e) Salinity. (f) Percent saturatio n of oxygen calculated using oxygen values in (a). {g) Rate-of-change of oxygen. Dotted line is rate-of-change of (c). Solid line with solid dots is rate-of-change cor rected for depth changes. Solid line with open circles (o---o) is rate-of-change curve corrected for diffusion using coef ficient values given across the top of the diagram . Units of diffusion coefficients are go 2 ;m 2 /hr./1OO % deficit. (h) Rate-of-change of oxygen. Solid line with sol id dots is rate-of-change of (a) multiplied by average depth at each hour. Solid line with open circles (o---o) is curve corrected for diffu sion using same coefficients as in (g).
PAGE 70
... z 0 z ~I(\) X r5 0 0 U z w (_') >X 0 z 0 u ... I In. E w 0 >... (\J 'Z z C\J <( 0 :::) 0 O> ... w a:: :::) !;i a:: u w 0 Cl. w I>... Iz a. a. _J <( (f) Iz 0 z w u a:: 0:: w => Cl. I<( (f) 50 IOr I(a) o----~---~----~---~ 3~(b•) . 2 . .. . I o~-------~--------15 ( C) 5 0 30 ( d) 28 26 16 ( e) 14 12 10 150 100 50 0;300 1200 1800 TIME OF DAY
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51 + l.5r------r-------r------.--------. +1 . 0 (..l---1.o--lo.5510.1 l---1.60---i~~0.55 0.1 0.1 (g) ,---, I I I I I I I I . I I I I DAYTIME NET PHOTOSYNTHESIS I I I I , l "-,-\....::: I I I I I z c,, -0.5 w I -~ l-~-,.. (.9 >x 0 w (.9 z ll.J (.9 >x 0 -1.0 NIGHT RESPIRATION I. 5 ,__ ___ ....__ ___ +l.0,---,------.-----,.--------. +0.5 (h) DAYTIME NET PHOTOSYNTHESIS NIGHT RESPIRATION 0600 1200 TIME OF DAY 1800 Figure 9 continued
PAGE 72
52 obtained by multiplying o x ygen concentraticn (Figure 9a) by depth at that time. Percent saturation (Figure 9f) was calculated for the temperature and salinity at each time using the formula of Truesdale et tl(1955). T he divergence of Truesdale's saturation values from those presented in Standard Methods (Amer. Publ. Health Assoc., 1955) was reviewed by Churchill tl tl(1962), who showed deviations at temperatures less than 25C. Maximum deviations, however, were less than 5 % of the values from Standard Methods, so the errors incurred in this study by using Truesdale 1 s values were considered small. An oxygen rate-of-change curve (Figure 9g) was constructed from the graph of average oxygen per square meter. The amount of change of oxygen during each hour was measured and plotted on the half hour. This raw curve reflected changes in oxygen concentration under one square meter due to changing depth from tidal exchange and diffusive exchange with the atmosphere, as well as photosynthesis and respiration. The effect of changing depth was eliminated by multiplying the incremental depth change for each hour by the average oxygen concentration during that hour. This value was added to the rate curve if the tide was falling or subtracted if the tide was rising. The final adjustment to the rate-of-change curve was for oxygen lost or gained by diffusion between the
PAGE 73
53 water and atmosphere (see more com~lete discussion on page 62) . In general, in the discharge bay only a falling tide from a high high to a low low stage had a sufficient current producing a diffusion rate large enough to make an appreciable correction in the metabolism calculation. Both rising and falling tidal current velocities were greater in the control areas making diffusion corrections more important at all tidal stages. For daytime net photosynthesis the average difference between the area under the curves adjusted and unadjusted for diffusion in the inner bay was 8 percent. At the Fort Island control area it was 24 percent, while at Hodges Island (only two measurements) it was 2 percent. Any diffusion estimate that was incorrect for the discharge bay would have a relativel y small effect on the metabolism calcu lation . At Fort Island the effect would be only somewhat larger. This laborious method was later modified; average oxygen concentration, temperature, depth, salinity, and percent saturation were plotted as before, but the area-based oxygen curve was not calculated. The rate of-change curve (Figure 9h) was obtained by multiplying the hourly rate-of-change of oxy g en concentration by the average depth at that hour giving the rate-of-change on an areal basis. The adjustment for diffusion was made as before.
PAGE 74
54 In all methods the final rate-of-change graph showed the rise of oxygen resulting from net photosyn thesis during the day, and decrease because of respira tion at night. Net daytime photosynthesis was taken as the area under the rate-of-change curve above the zero rate-of-change line. Nighttime respiration was taken as the area under the rate-of-change curve below the zero rate-of-change curve (Figure 9g and 9h). Dawn-Dusk-Dawn Measurements In order to gain more data as a check on day to-day variability of total metabolism and to reduce the amount of field labor involved, the dawn-dusk-dawn method (McConnell, 1962) was used after the first year. The low point of oxygen at dawn, the high point at dusk, arid the low point the following dawn were measured as a short-cut method of approximating the true diurnal curve. Experience in the field showed that the time of the minimum and maximum was not always at dawn or dusk. Clouds in the east at sunrise tended to delay the onset or rising oxygen by an hour or more. Simi larly, afternoon thunderstorms often caused the downturn of oxygen well before dusk. Even on clear days full diurnal curves showed that oxygen concentration often ~ould not increase any more in the last two hours before sunset. The times of dawn and dusk sampling, then, were
PAGE 75
55 often adjusted to the prevailing conditions. Dawn samples were delayed if the morning was cloudy in the east. Dusk samples were generally taken about l-1/2 hours before dusk. Water samples were drawn, fixed, and titrated as described before. Diurnal graphs of averaged data were drawn in the same way as for full diurnals (Figure 10) but, of course, used only three points. Straight lines were used to connect points for oxygen, tempera ture, and percent saturation. Because depth was impor tant to the metabolism calculation, the actual daily patterh was estimated from the observed measurements and the expected tidal amplitudes for the Crystal River area published in the U. S. Department of Commerce tide tables. Because the daily pattern of salinity change was complex, no attempt was made to extrapolate between the measured values. Witt, the three-point dawn-dusk-dawn method, net production and/or night respiration would be under estimated if the minimum and maximum points of oxygen were not sampled when they occurred. The method also used fewer replication3 so that any one unusual measure ment would have a greater effect on the calculation of metabolism. McKellar (1975) gives a more complete discussion of errors associated with the method.
PAGE 76
Figure 10. Graphical format for calculation of community metabolism using dawn-dusk-dawn data. Open circles are the average of measurements at individual stations indicated by solid dots. Numbers across top of the rate-of-change graph are diffusion coefficients.
PAGE 77
0 0 ~ 0 0 N 0 0 co 0 0 OXYGEN RATE-OF-CHANGE, g o 2 /m2hr r + 0 0 9 Ul 0 Ul (Jl _j_ p -r p (Jl t 61 Ul J_ p p I\) ! (.JI PERCENT SATURATION CJ1 8 (JI 0 0 SALINITY, ppt N I\) I\) I\) I\) 0) CD 00 0 TEMPERATURE, oc DEPTH, m (>J (>J (JJ (JJ p :!" ON~O) 000 L l 0 OXYGEN, g 02/m3 (JI 0 <.r1 -....J
PAGE 78
58 An analysis of the difference in metabolism estimates calculated by the dawn-dusk-dawn and full diurnal curve methods is given in Figure 11. Data points were read from a subsample of the graphs of full diurnal curves of oxygen as if that day had been sampled by the dawn-dusk-dawn method, and daytime net photosynthesis and night respiration were calculated. Daytime net photosynthesis would have b e en underestimated by the dawn-dusk-dawn method three times in the inner bay by an average of 33 percent and overestimated twice by a small amount. Agreement was better at Fort Island and Hodges Island but would have been overor underestimated by up to 25 percent. Night respiration by the dawn-dusk-dawn method was only an average of 58 percent of that calculated by the full diurnal curve method in the inner discharge bay. At Fort Island the three-point method was only 75 percent of the full curve method on three occasions, while the full curve value was only 88 percent of the three-point value two times. McKellar (1975) for the outer discharge and control bays at Crystal River found the dawn-dusk-dawn method to underestimate gross production values (daytime net production plus night respiration) usually by less than 10 percent. The average difference between the two methods was not significant at the 0.05 level.
PAGE 79
Figure 11. Comparison of community metabolism estimates obtained from complete diurnal measurements of oxygen versus estimates obtained from dawn-dusk-dawn calculations made using the same data. (a) Daytime net photosynthesis. (b) Night respiration.
PAGE 80
60 8--------------0 'e " 0 6 O> ... (a) DAYTIME NET PHOTOSYNTHESIS El w 0 > 4 0:: => u _J <( 2 z 0:: :::> 0 El 0 INNER DISCHARGE BAY El FORT ISLAND 8. HODGES ISLAND ::1 o 2 4 6 8 er DAWNDUSK-DAWN, g O 2 /m 2 day O> ... 4 a:: => 0 .d 2 z 0:: ::, ( b) NIGHT RESPIRATION 0 0 El 0 INNER DISCHARGE BAY 0 FORT ISLAND A HODGES ISLAND 0 _J O Q 1 2.4 1 6 1 8 DAWN-DUSK-DAWN, g O 2 /m 2 day
PAGE 81
61 Eley (1970) found that dawn-dusk-dawn estimates averaged 91 percent of gross production and 87 percent of total respiration in eight laboratory microcosms and 71 percent of gross production and 52 percent of total respiration in Keystone Reservoir, Oklahoma when compared to the full diurnal curve analysis. In this study 61 percent of the metabolism measurements from the inner bay and 68 percent from the outer bay were made with the dawn-dusk-dawn method. Since the apparent underestimation was largest in the inner bay, these values may be conservative esti mates. Effects of Advection on Calculation of Metabolism If an increase in oxygen occurred at night because of advection, an artifact in the rate-of-change curve was produced which made it appear as if photosynthesis was occ u rring. Net production would be overestimated because the nighttime gain in oxygen would be added to the actual net production occurring during daylight hour s . Night respiration would be underestimated because the area of positive oxygen gain would not be counted in the calculation of re s piration. By measuring this omitted area, night respiration was found to be underestimated by an average of 1.5 g/m2.day on the full diurnal curves from the inner bay.
PAGE 82
62 Light and Dark Bottle M~asurements Light and dark bottle studies were made in the later stages of the project to estimate metabolic com ponents of the water column as apart from the metabolism of the sediments and larger consumer organisms. Bottles (300 ml, BOD) were suspended at about 0.5 m depth by small chains secured to a four-foot length of 3/4-inch PVC pipe floated at each end by a plastic milk carton. Generally, five replicates each of both light and dark bottles were put out as soon as the dawn diurnal run was completed, and picked up at the same time the follow ing day. Fixation and titration were as in American Public Health Association (1971), except that only a 100-ml sub sample was titrated because of the 0.0125 N thiosulfate used. The increase in the light bottle was taken as 24hour net production, the decrease in the dark bottle was taken as 24-hour respiration, and the sum of the oxygen gained plus that used up was taken as gross photosynthesis. Other Field Measurements Diffusion Measurements At Crystal River the rate of diffusion of oxygen into and out of the water column tended to be largely a function of tidal current velocity. Diffusion was measured at various stages of the tidal cycle using a
PAGE 83
63 small nitrogen-filled plastic dome, which floated on the water surface (Hall, 1970, based on original work of Copeland and Duffer, 1964). An oxygen probe measured the return of oxygen into the dome from the water under the normal conditions of underwater circulation. A linear regression was calculated from the raw data. Although the increase in oxygen in the dome is not linear, the early response approximates a straight line. The diffusion rate as g/m 2 /hr/100 percent deficit was calculated from the linear regression, area of water surface covered, volume of the dome, and the observed saturation value of dissolved oxygen in the water. This was the maximum rate of diffusion into oxygen-free water or Oijt of water 200 percent saturated with oxygen. Figure 12 shows a typical diffusion measurement. Because of the small number of measurements taken, assigning diffusion rates to time periods on the graph was a combination of actual measured values and estimates based on field experience with the general magnitudes of tidal currents at different stages of the tidal cycle in the study areas. rhe actual diffusion correction for each hour was calculated by multiplying the maximum rate selected for that hour by the actual saturation deficit during that hour.
PAGE 84
Figure 12. Example of two experiments to determine oxygen diffusion coefficients by measuring the rate of return of oxygen into a nitrogen-filled dome floating on the water's surface. Line through points was obtained by calculating a linear regression. Meter was calibrated to give a reading of 10 in air. Data obtained at Fort Island study area .
PAGE 85
w --'
PAGE 86
66 Light Penetration of the Water Column Light penetration through the water column was measured with a submarine photometer (Tsurumi Precision Instrument Co., S/N 88130) . Light intensity was mea sured at 0. 1-meter depth intervals from the surface to the bottom and compared to a deck cell reading insola tion incident to the water surface. Results were graphed on semi-log paper (Figure 13). The extinction coefficient was calculated was K = where r 1 was light intensity at the shallower depth (Z 1 ) and r 2 was ligh t intensity at the deeper depth -1 (Z 2 ). K was in units of meter .
PAGE 87
Figure 13. Examples of submarine photometer measurements of light penetration through the water column taken at Fort Island away from the influence of the power plant discharge plume and in the inner bay influenced by the plume. Lines through points were fitted by eye. k, extinc tion coefficient.
PAGE 88
E .. . :r: r0... w 0 68 PERCENT OF SURFACE LIGHT INTENSITY 10 50 100 0 ...---------.--......---,,---...,....-,--...,... .......... 1.0 0 0 2.0 El INNER BAY~ k= 1.51/mef er 0 El "-..__FORT ISLAND k= 0 . 9/meter
PAGE 89
DATA ASSEMBLED FROM OTHER PHASES OF THE CRYSTAL RIVER PROJECT AND ELSEWHERE One of the major objectives of the overall research program at Crystal River was to synthesize the knowledge of the forcing functions outside of the system and the storages and process operating within the system. To this end, records of many of these variables from other phases of the project and elsewhere are included here to provide a total view of the estuarine ecosystem. These data are used for obtaining values for the model simulations and in determining if the simula tion results are reasonable. Energy Sources and Inflows Affecting the Inner Bay Seasonal and diurnal patterns of some of the external factors shown in Figure 4 are given below. Sunli9.b_l In Figure 14 is the average daily insolation by month measured at Tampa, Florida, 97 km to the south of Crystal River (Water Information Center, Inc., 1974). 69
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Figure 14. Average daily insolation by month at Tampa, Florida (Water Information Center, Inc., 1974).
PAGE 91
71 8000r------r---r----r----,---,-----r--.--r------c "'O . C\J 6000 C u .. 4000 ti _J 0 Cl) z 2000 et: <( _J 0 en O J . F r v 1 A M J JY A S . 0 N D
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72 Peak insolation months (about 6000 Kcal/m 2 •day) were April and May at the very end of the winter-spring dry season. Daily summer values were lower due to frequent cloudiness from convective storms. Wind Direction and Speed Wind rose diagrams by season are given in Figure 15 (Fla. Power Corp., 1972). Summer winds were pre dominantly westerly and easterly as influenced by the large-scale circulation about the shifting position of the subtropical high-pressure system and by the more local regional land-sea breeze system. With the change in the fall and winter to weather patterns dominated by frontal systems, the predominant wind direction shifted to northerly directions. Average wind speed as given in Table 2 (Fla. Power Corp., 1972) was lowest in the summer and highest in fall and winter due to the strong winds associated with frontal passages. Ambient Air Temperature In Figure 16 are monthly mean, mean maximum, and me a n minimum daily temperatures at Tampa, Florida (Fla. Power Corp., 1972). Diurnal variation was smallest during the summer months when the climate was primarily under the influence of the subtropical high pressure system , and frontal systems usually remained well north
PAGE 93
Figure 15. Wind direction by season at Crystal River site. Bars are percent of readings occurring from each compass bearing (Florida Power Corporation, 1972).
PAGE 94
74 I s DEC. ,,JAN., FEB. MAR. ,APR., MAY N N NE SE s JUN . ,JUL., AUG . SEP. ,OCT., NOV.
PAGE 95
75 Table 2. Seasonal comparison of average wind speed at Crystal River site (Fla. Power Corp., 1972) Season Average wind speed, mph Spring ll. l Summer 9.5 Autumn 12.0 Winter 12.0 Annual average l l. 4
PAGE 96
Figure 16. Monthly mean air temperature at Tampa, Florida (Water Information Center, Inc., 1974).
PAGE 97
LL 0 .. w 0:: :::) <( a: w a.. w I77 80 60 4020 \ \ \ \ ' ' ' ' \ \ --0 r.....__. __ ._____. ______ ....__. ____ _____.____..____..__r J F M A M J JY A s 0 N D
PAGE 98
73 of the area. Minimum temperatures dropped sharply in October as cold fronts began penetrating into Florida, and remained low through the winter when the climate was characterized by cold air advection following frequent frontal passages. Precipitation Monthly mean precipitation at Tampa is presented in Figure 17 (Fla. Power Corp., 1972). About 60 percent of the yearly rainfall occurred from June through Sep tember and was associated with showers and thunderstorms in tropical air masses. During the extensive eight-month dry period extending through May, precipitation was mainly associated with frontal systems. Stocks of the Inner Bay Assembled below are data on stocks of organisms and other quantities important within the inner bay system. Water Temoeratures Weekly average water temperatures at various locations in the discharge canal, discharge study area, and intake area during the course of this study are given in Figure 18. Buoy locations are given in Figure 6. Weekly average electricity generated by units l and 2
PAGE 99
Figure 17. Monthly mean precipitation at Tampa, Florida (Water Information Center, Inc., l 9 7 4 ) .
PAGE 100
tf) Cl) _c (.) C 15 .. IO z 0 <( r5 CL (_) IJJ n: 80 r I a.. Q L I I I ___,_ _ _,_l _ , _L_ I ,..J I J F 1\1 A M J JY A S 0 N D
PAGE 101
81 and temperature rise of cooling water across the condensers for unit l are shown in Figure 19. The average temperature differential across the plant was about 5 to 6C, varying somewhat with power plant operation. The seasonal ambient water temperature cycle was indicated by a monitoring buoy located at the Gulf end of the south intake dike (Figure 18) and by water entering the intake pumps of unit l (Figure 19). For 1973 lowest temperatur~s of 12 to l5C occurred in January and February rising through the spring to a plateau of 28-30C in the summer months of June through September. Rapid cooling began in October. Winter water temperatures were generally higher during the mild 1973-74 winter. These data were very similar to monthly average data for Cedar Key 25 miles to the north. Discharge area temperatures (Figure 18) had the same seasonal pattern as ambient areas, but with a con sistent temperature increase due to the thermal plume. Canal temperatures (buoys F and G) were about 5C higher than ambient, corresponding to the average temperature rise across the power plant condensers. Over the shallow inner bay (buoys GA, GB, GC) the average temperature in crease was only about 3C over ambient, indicating evapora tive and radiative cooling and mixing with some ambient water. Average diurnal temperatures measured during com munity metabolism studies are given in Figure 20.
PAGE 102
Figure 18. Weekly averages of surface water temperatures for the plume-affected inner discharge bay and ambient water of the south intake area. See Figure 6 for buoy locations. Bars super imposed on ambient temperature record are monthly means and extremes measured at Cedar Key 25 miles to the north of Crystal River. Gap in buoy record indicates lack of data for that period at that location.
PAGE 103
(.) 0 83 AMBIENT WATER 30 20 lo CEDAR KEY -(25 YEAR AVERAGE)~ 30 20 10 30 20 10 DISCHARGE CA AL (BUOY F) DISCHARGE CA \ ) 1! 1n72 V 1973 1974
PAGE 104
u 0 30 20 10 30 20 10 84 INNER BAY ( BUOY GA) INNER BAY (BUOY GB) 0 ............... ......-...---...._._..__..__.._.__...._.._. ______ ..._.._.. ___ INNER BAY (BUOY G C) 30 20 I 10 0 .,.,. ___ ... , ..... ,., 1972 1973 1974 Figure 18 continued
PAGE 105
Figure 19. Weekly average of electricity generated by power units at Crystal River, and weekly average intake and discharge water temperature for unit l. (a) Weekly average of electricity generated by units l and 2. {b) Weekly average intake and discharge temperatures of water for cooling pumped through the steam condenser system for unit l . Gap in record indicates unit shut down for repairs during that period.
PAGE 106
o"" . w f-_ <( C 0:: _o 600 W"Zo w (1) 400 (!) "' r-:: 200 uc -:?: 0:: C fOl 0 (_) (1) wE _J w (.) 40 0 .. w et: 30 ::::) I<( 0:: 20 w a.. w 10 l0 ( a} ( b) 86 " /, ,, ,., ,, , \ ,...,,....,, ' ,' V ',J ', I UNIT 2 I I DISCH.~RGE I -INTAKE J F M A M J JY A S O N D J 1973 .._,..,, UNIT DOWN FM AM J JY 1974
PAGE 107
Figure 20. Average diel water temperatures measured during community metabolism studies of the inner discharge bay and the Fort Island and Hodges Island control areas. 0 , Inner discharge bay; [:J , South intake area.
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40-------------------------~------.,._.--oP-'t"-,-""P"-P~ 0 @00 0 8 Oo 0~ u 30 0 0 0 0 (J ~rfJ}D 0) Bl .. 0 0 w 0::: @g :::::, 20 0 co co r ill
PAGE 109
89 Patterns noted were similar to those discussed for Figure 18. Diurnal temperature patterns are given in Figure 21 for four days picked at random in late May, 1974. Ambient daily change was about 3C. Canal temperatures (buoy G) were about 5C above ambient but the pattern was variable. Tidal effects were evident in the record with buoys G and GD exhibiting opposite behavior. In the canal (buoy G) surface temperature decreased at high tide, probably as cooler offshore water flowed in over the warmer but more saline and dense plume. At the north boundary of the discharge bay (buoy GD), a rising tide pushed warm plume water across the bay, which finally reached the buoy sensor at full tide stage. The tempera ture quickly dropped to ambient as cooler water from the north flowed past on the falling tide. The effect of plant load on temperature is ap parent in the data pattern for May 26 and 27 when unit l went offline, while unit 2 continued to operate at a fairly constant load factor (Figure 21). Since both units continued to pump ambient water, the canal temperature dropped several degrees because of dilution of the heat from unit 2. Because of mixing and cooling the tempera ture of the plume reaching buoy GD dropped closer to ambient levels. V2ry little solar heating was evident for May 27 because of the clo11dy conditions for that day.
PAGE 110
Figure 21. Diurnal patterns of electricity generated, water temperatures at three locations, and tidal stage in the discharge area of May 2427, 1974. (a) Electricity generated (MWe) by units l and 2. (b) Water temperatures at three locations near the power plant at Crystal River. Buoys G and GD were in the discharge area. The buoy measuring amient water was in the intake area (see Figure 6). (c) Tidal stage in discharge area. Recorder was located at the end of the bulkheaded portion of the north discharge canal spoil bank.
PAGE 111
.. 0 w I.
PAGE 112
92 Salinity Plotted in Figure 22 are average salinities measured in the study areas during the community metabo lism studies. Salinities were generally 5-15 parts per thousand higher in the discharge area because of the mixing of more saline discharge plume water with lower salinity inshore water. At Fort Island salinities were influenced by the freshwater discharging from the Crystal River nearby. The study area at Hodges Island was away fro m the influence of freshwater sources and had salini ties similar to the discharge bay . Variations in salinity with the tidal cycle may be noted from the graphs drawn as part of the community metabolism studies (Appendix B) . In the discharge bay salinity varied depending on the tidal stage and its influence on the mixture and position on the bay of the more saline discharge plume and less saline ambient water. At Fort Island variations in salinity with the tidal cycle were large. On a falling tide fresher water from the Crystal River flowed over the study area; on a rising tide it was replaced by saltier water from further offshore. At Hodges Island very little variation was encountered.
PAGE 113
Figure 22. Average salinities measured on the inner discharge bay and Fort Island and Hodges Island study areas during the community metabolism studies. 0 , Inner discharge bay; 8 , South intake area.
PAGE 114
.... C. a. 30 .. 20 >Jz _J 6> [!JB ' 0 "---... INNER BAY 0 GJ 0 r.P Q]~ 0:1 (:J 8 \_ SOUTH INTAKE AREA o._ ___ ...__._.__.__J.-.--'......... __,__,,_ ____ ~_._.........i---------------....-.-....---1972 1973 1974
PAGE 115
95 Benthic Macrophytes Seasonal patterns of biomass of benthic macrophytes in the thermally affected inner bay and the in shore portion of the south intake area are given in Figure 23 (Van Tyne, 1974). Each point represents the average 50-150 quarter square meter samples harvested using a hand-held dredge with an attached 1/16-inch mesh nylon bag. Total biomass in the intake area was generally 1.5 to 2.5 times that on the inner bay area. The seasonal pattern in both areas was similar, with highest values in the spring and summer and lower values in the fall and winter. The very low values for fall in the inner bay may be anomalous (see Van Tyne, 1974). Figure 23b, which breaks down the total of Figure 23a into the contributions of seagrasses and macroalgae, indicates that macrophyte biomass in the inner bay was composed almost exclusively of the seagrass liwriqhtii. Macroalgae were dominant in the south intake area composing about 70 to 75 percent of the total biomass at all times of the year. Seasonal biomass of macroalgae by taxon is given in Figure 23c for the south intake area. Seasonal switching of biomass dominance may be evident, with red algae most important in the spring, reds and greens about equally important in the summer, and reds and browns dominating in winter with its lower light intensities.
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Figure 23. Seasonal patterns of benthic macrophytes in the thermally affected inner bay and inshore portion of the south intake area. Sp, spring; S, summer; F, fall; W, winter (data from Van Tyne, 1974). (a) Total macrophyte biomass on the inner bay and south intake areas. (b) Biom a ss of seagrasses and macroalgae in the inner bay and south intake areas. (c) Biomass of red, green, and brown macroalgae in the south intake area.
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C\I E .... 3 I >a "O E Ol .. en Cl) <( 0 m 97 80--------------60 40 20 (a) TOTAL MACROPHYTES ~INTAKE AREA .Q /' \ , ' ,' \ ,,, \ .....--1 N N ER BAY , ,,. a ', \ \ ' .,0 ' ,,. \ .,,, \ ,,.,' \ ,. 0""' 0---------------60------------------(b) 0SEAGRASS A MACROALGAE 40 20 40 (c) MACROPHYTIC ALGAE INTAKE AREA 20 'L ,I 0 -0 0 SP s F w
PAGE 118
98 A map of summ e r standing crop of attached macro phytes for both the discharge-affected areas and the unaffected south intake area is given in Figure 24. Distribution of macrophytes on the inner bay (almost exclusively~wrightii--see above) was confined mostly to the western two-thirds of the bay. The shoreward portion was devoid of attached macrophytes and was the area most immediately affected by the heated effluent from the discharge canal on the rising tide. No con spicuous and widespread bare areas are noted on the south intake area. Diversity of macrophytes was measured by calcu lating an average number of species per sample (Figure 25). Total macrophyte diversity (Figure 25a) was low in the inner bay, with less than two species encoun tered on an average square meter of bottom sampled. Diversity on the south intake area was two to seven times larger with six to eight species per square meter of sampled area. Total diversity has been broken down into its seagrass and macroalgae compon e nts in Fi g ure 25b. The complete dominanc e of th e inner bay by~wriqhtii and the lack of macrop h ytic alga e are emphasized by this plot. Seagrass diversity was larger on the south intdke area (l-2), but m~ch less than the macroalgae diversity (4-6).
PAGE 119
Figure 24. Map of summer standing crop of attached macrophytic plants ~n the region near the Crystal River power plants. Values are g/m and are approximate. Cross hatching indicates areas devoid of macrophytes (adapted from Van Tyne, 1975).
PAGE 120
N 0 0 . 5 ! NAUT ! CAL MILES (ADAPTED FROM VAN TYNE, 1975) I 50 C.:i.!!! > .. ;; I El , !IC~.;!.'? 20 j ,:.: . .. _, 0 0
PAGE 121
Figure 25. Seasonal diversity of benthic macrophytes in the inner discharge bay and the south intake area. See text for diversity calcu lation. Sp, spring; S, summer; F, fall; W, winter (data f rom Van Tyne, 1974). (a) Total macrophyte diversity. (b) Diversity of seagrasses and macroalgae.
PAGE 122
Q) 0.. E 0 en Q) 0 Q) a. en . 0 C .. >..... Cl) 0:: w > Cl 1 02 10 (a) TOTAL MACROPHYTES 1/ 1/ 0 5 INTAKE AREA INNER BAY 0 10 (b) 0 SEAGRASSES AMACROALGAE 5 A ----<:>--r---f/"=----o . -::.-::.-:..-_-_-.::./Jr:_ --0--------.L-...;;.;;:.l~.:.;;..;;:a.;;;.__,_:;:::~....J SP s F w
PAGE 123
103 Benthic Macroinvertebrates Dry weight biomass of benthic macroinvertebrates in the inner discharge bay and south intake area is given in Figure 26 (Evink and Green, 1974). One-square-meter areas were sampled with a Venturi pump arrangement and filtered through a nylon mesh bag. Core samples were also taken for small organisms missed by the Venturi sample, but only several were sorted. These indicated that the Venturi method was sampling only about one-half the actual biomass. Biomass in the inner bay was lower by a factor of four to ten. Seasonal variation in bio mass was small in both areas. The low value measured in the intake area in the November, 1973 samples may have been anomalous. Resident Fishes Seasonal values of fish biomass caught with dropnets in the inner bay and south intake area are plotted in Figure 27. This technique was selective for juvenile life stages and grassand bottom dwelling species, and did not sample the more mobile species such as sharks, mullets, jacks, and rays (Adams, 1974). Season a l biomass was very similar in the two a r eas e xce p t for fall, 1972, which represents a small number of samples. A seasonal pattern was evident in
PAGE 124
Figure 26. Seasonal record of biomass of benthic macro invertebrates in the inner discharge bay and south intake areas (data fron Evink and Green, 1974).
PAGE 125
l 05 NE 15 " (ADAPTED FRO .._ EVINK AND GREEN,1974) I "10 "'C E Ol ... INNER BAY (/) 5 C/)
PAGE 126
Figure 27. Seasonal record of biomass of fish caught with drop nets in the inner discharge bays and south intake areas . F, fall; W, winter, Sp, spring; S, summer (data from Adams, 1974).
PAGE 127
l 07 C\J 3 E "--.. (ADAPTED +FROM 3 ADAMS, 1974) I INTAKE AREA "O 2 Q I I ' E 1 NNER BAY~/ , 0, I I , .. , en I I I ' Cl) PI I <( ' , ... ' I , .... '0 ,I , 0 ,I ,I d al 0 F VJ SP s F w SP s 1972 1973 1974
PAGE 128
108 both areas with the largest biomass in the spring and summer and lower values in the fall and winter. Nutrients Nutrient data measured by Gibson (1975) at a station in the south intake area and at the mouth of the discharge canal are presented in Figure 28. No samples were regularly collected in the inner discharge bay it self. Total organic carbon (Figure 28a) was very simi lar at both stations during the periods studied, values ranging generally from 3 to 8 ppm. No prominent seasonal patterns were evident. Seasonal measurements of P0 4 -P, N0 3 -N, and NH 3 -N are presented in Figures 28b and 28c. Both stations generally had similar levels of nutrients throughout the measurement period except for NH 3 -N during June, July, and August, which was two to nine times more abundant in the south intake area during those months. Seasonal patterns were also similar for both sampling stations. Nitrate and phosphate were less than 50 ppb and usually less than 20 ppb from November through May. Phosphate increased in June, decreased below detectable limits in the July samples, but in creased to very 1arge values during most of August. Nitrate also exhibited an increase to much larger values
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Figure 28. Carbon, nitrogen, and phosphorus measurements at the mouth of the discharge canal and a station in the south intake area (data from Gibson, 1975). ( a ) . Total organic carbon. ( b ) N0 3 N, NH 3 N' and P0 4 P at the mouth of the discharge canal. ( C) N0 3 N, NH~ N, and P0 4 p in the south intak area.
PAGE 130
C 0 E en ..... e 0. C 0 .c !,,. Q) 0. en ..... '0 a. 10 110 (a) TOTAL ORGANIC CARBON (DATA . FROM GIBSON, 1974) o-...__ _____________ _.._ 799S\ T >70516 2 00 1 1 r 1M---' I 100 (b} MOUTH OF DISCHARGE CANAL: i ( DATA FROM GIBSON, 1974) ; I I I J , , I I 0 &::..-.....l-~~~~.:::_.=.~=.1......!=J_~.!.1...J.-.L---I N D J F M A M J JY A S 1973 1974
PAGE 131
C 0 ..0 'Cl) a. Cf) -t,_ 0 a.. 111 500-------------------------(c) SOUTH INTAKE AREA ( DATA FROM GIBSON, 1975) 400 300 200 100 0I I I ,' ! I I I I I . I I I O N D J 1973 F M A M J JY A S 1974 Figure 28 continu ed
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l l 2 during July and August, returning to levels below 20 ppm in late August and September. Ammonia values were similar to nitrate and phos phate at both stations through the fall and winter. In late March or early April both stations exhibited a pulse in abundance with values dropping back to levels somewhat higher than previously through late April, May, and June. The large increase which occurred in phosphate and nitrate in July and August occurred for ammonia only at the south intake station. Levels in both areas declined in late August and September. Chlorophyll-a and Phytoplankton Biomass Data on chlorophyll-~ and phytoplankton biomass are presented in Figure 29 for stations in the south intake area and at the mouth of the discharge canal (Gibson, 1975). Values of biomass and chlorophyll-~ were similar at both stations throughout the sampling period except for early April, when the discharge station was considerably higher than the intake station. Seasonal patterns of biomass and chlorophyll were similar at both stations. The records of . chloro phyll and biomass tracked each other closely from sample to san1ple. Low values were measured during the fall and winter, being lowest in late December and early January. A spring increase occurred during March, April,
PAGE 133
Figure 29. Measurements of live chlorophyll-a and phyto plankton biomass at a station in the south in take area and at the mouth of the discharge canal (data from Gibson, 1975). (a) Live chlorophyll-~. (b) Phytoplankton biomass.
PAGE 134
C: 0 ..0 .. (1) a. (/) .. C 0. E Cl 4.0 3.0 2.0 1.0 1 1 4 ______ 9,5._.9--.--.~---l! I \ (a) LIVE CHLOROPHYLLa (DATA FROM i \ GIBSON, 1975) I : I I MOUTH OF DISCHARGE CANAL\ I I 0 0--0 I \ I I I <;) I \ I' I I \ ,' I \ . I 0 I I ' I 1 I I 9. ?. ,: ,, I I I I I ' I . I I ' I I / I ,' (.j' I I I I "SOUTH INTAKE AREA o-----....._~ __ ___......_ ______ ....... ____ _ 0.6 0.4 0.2 90]'12 I 1~-,--------,--' I I \ ( b) PHYTOPLANKTON BIOMASS , I ( DATA FROM : \ G!BSON,1975) / \ 0 I I I I I I 1 00 \ I I I I I I I AREA I ' I 0 0 ____ ......__ __________________ _ N D J 1973 F M A M J JY A S 1974
PAGE 135
and May, being somewhat larger at the discharge station than a t the intake station. Low values were once again measured during mid-July, but increased again during the rest of the summer.
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RESULTS Given below are measurements and models done as part of this phase of the Crystal River project. Metabolism Measurements All total metabolism measurements obtained by the free water diurnal methods and water column metabo lism as measured by light-dark bottles are given in Tables 3 and 4 for the discharge bay and unaffected bays. Graphs of all individual diurnal measurements are given in Appendix B. Total metabolism measurements are plotted graphically by date of measurement in Figures 30 and 31, and combined and plotted on one 12-month graph in Figures 32 and 33. Seasonal averages are given in Figures 35 and 36. Complete Diurnal Measurements of Oxygen Twelve complete ditirnal measurements of oxygen for estimation of comm11nity metabolism were made in the inner bay between June, 1972 and May, 1974 using one to five sampling stations. Graphs of these data are l l 6
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Table 3. Record of metabolism for the inner discharge bay as measured by diurnal free water oxygen changes and light and dark bottles. Dates marked with an asterisk were complete diurnal measurements. Unmarked dates were dawn dusk-dawn measurements. p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p + R Bottles Bottles tion Insolation Date g O/m 2 -day g O/m 2 .day 2 g 0/m •day g/m 2 g/m 2 g/m 2 Kcal/m 2 day Winter: Dec. 14-15, 1972* 2.3 2.7 5.0 Jan. 22-23, 1973* 1.8 ,. 3 3. l Jan. 31Feb. l , 1973* ,. 2 3.6 4.8 Mean 1.8 2.5 4.3 Std. error O. l 0.5 0.4 Spring: M ay l 011 , 1973 4.8 4.3 9. l May 11-12, 1973 2.9 3.3 6.2 May 24-25, 1974 2.6 l. l 3.7 6500 __, __, -.....:
PAGE 138
Ta b 1e 3 continued p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration P + R Bottles Bottles tion Insolation Date g 0/m 2 day 2 g 0/m -day g 0/m 2 •day g/m 2 a/m 2 g/m2 Kcal/m 2 ,day Spring (cont.): May 25-26, 1974 1. 7 0.7 2.4 6409 May 26-27, 1974 2.3 1. 8 4. l +l. 2 -0.4 1.6 5834 Ju n e 14-15, 1972* 1. 9 2.5 4.4 __, __, Jur.e 29-30, 1972* 2.3 2.6 4.9 co J u ne 17-18, 1973 3.2 2.4 5.6 June 17-18, 1973* 5.4 4.8 1 o. 2 June 18-19, 1973 2. 1 0.9 3.0 June 19-20, 1973 o.o 1. 3 1. 3 JUlll ~ 2 0 -2 l , 197 3 2 .4 1. 9 4.3 +2.5 -2.2 4.7 June 21-22, 1973* 1.0 3.0 4.0 June 22-23, 1973 1.0 1. 2 2.2 Mean 2.4 2.3 4.6 1. 9 l. 3 3.2 Std. error 0. 1 o. 1 0.4 0.4 0.8 2.4
PAGE 139
Table 3 continued p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p _ + R Bottles Bottles tion Insolation Date g 0/m 2 -day 2 g 0/m day g O/m 2 day g/m2 g/m 2 g/m 2 2 Kcal/m -day Su m mer: July 7-8, 1972* 6.3 4.5 l O. 8 July 26-27, 1973 3.5 2.6 6. 1 +0.7 -0.3 1.0 6115 Aug. 2-3, 1972* 4.4 4.5 8.9 __, __, Aug. 2-3, 1973 0.9 l. 3 2 . 2 +0.5 -0. 1 0.6 2889 \.D Aug. 22-23, 1973* l. 1 2.3 3. l Aug. 23-24, 1973 1 . 2 1. 3 2.5 +0.9 -0.4 1. 3 Aug. 24-25, 1973 1.4 1. 5 2.9 Aug. 25-26, 1973 0. 1 2.3 2.4 Aug. 26-27, 1973 0.6 1.8 2.4 Aug. 27-28, 1973 1. 1 2.6 3.7 Mean 2. l 2.5 4.5 0.7 0.3 1 . 0 Std. error 0.4 0. l 0.9 0. 01 0.01 . 0. 04
PAGE 140
Table 3 continued Chage Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p + R Bottles Bottles tion Insolation Date g 0/m 2 ;day g O/m 2 ;day g O/m 2 day g/rn 2 . g/m 2 g/m2 . 2 Kcal/m -day Fall: Oct. 29-30, 1973 l. l l. 6 2.7 +0.5 -0.2 0.7 Oct. 30-31, 1973* 1.6 2.8 4.4 +0.5 -0.2 0.7 Oct. 31N ov. l, 1973 +0.7 -0.2 0.9 3850 __, N 0 Nov. 1-2, 1973 1.3 2.2 3.5 +0.6 -0.4 1.0 4490 Mean l. 3 2.2 3.5 0.6 0.3 0.8 Std. error 0.02 0. l 0.2 0.003 0.003 0.006
PAGE 141
Table 4. Record of metabolism for the Fort Island and Hodges Island areas away from the influ~nce of the power plant discharge as measured by diurnal free water oxygen changes and light and dark bottles. Dates marked with an asterisk were complete diurnal measurements. Unmarked dates were dawn-dusk dawn measurements. p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p + R Bottles Bottles tion Insolation Date g 0/m 2 day g O/m 2 •day g O/m 2 ; day g/m 2 2 g/m . g/m 2 Kcal/m 2 •day \:J inter: Feb. 13-14, 1973* 2.0 1.3 3.3 Feb. 22-23, 1973 1.5 1.7 3.2 Mean l. 8 1.5 3.3 Std. error 0.06 0.8 0.003 sering: M ay 25-26, 1974 5.4 4.5 9.9 +2.7 -0.8 3.5 6409 May 26-27, 1974 4.7 4.3 9. l +2.5 -0.9 3.4 5834 June 25-26, 1973 l. 9 3. l 5.0 -3.2 -5.2 2.0 3037 __, N __,
PAGE 142
Table 4 continued p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p + R Bottles Bottles tion Insolation Date g 0/m 2 day g O/m 2 .day g O/m 2 .day g/m2 g/m2 g/m2 Kea 1/m 2 day Spring (cont.): June 26-27, 1973 5. l 5.4 l O. 5 +l. l -0.7 l. 7 6543 June 26-27, 1973 6.2 5.7 l l. 9 6343 June 27-28, 1973 5 . 2 5.8 11.0 6144 _, N June 28-29, 1973 5.6 5.0 l O. 6 +0.9 -0.3 l. 2 6648 N Mean 4.9 4.8 9.7 0.8 l. 6 2.4 St. error 0.3 O. l 0.7 l. l 0.8 0 ~ 2 Summer: Aug. 02-03, 1972* 4.7 6.5 11. 2 Aug. 16-17, 1972* 1.6 4. l 5.7 Aug. l 0-11 , 1972 2.6 3.4 6 . 0 Aug. 24-25, 1973* 4.0 6.2 10. 2
PAGE 143
Table 4 continued p R Change Change Gross Daytime Net Night in Light in Dark ProducPhotosynthesis Respiration p + R Bottles Bottles tion Insolation Date 2 2 2 2 2 2 2 g 0/m . day g 0/m day g 0/m day g/m g/m g/m Kcal /m day Summer (cont.): Aug. 26-27, 1973 1.6 6.9 8.5 Aug. 27-28, 1973 3.8 7.3 11 . l Mean 3. l 5.7 8.8 N Std. error 0.3 0.4 1.0 w Fa 11 : Nov . 12-13, 1973 2 . 1 3.4 5 . 5 +0.2 -0.3 0.4 3100 Nov. l 314, 1973 4.0 4.4 8.4 +0.3 -0.2 0.4 4140 Nov. 14-15, 1973 4.3 4.2 8.5 +0.2 -0.2 0.4 4280 Nov. 15-16, 1973 3.4 5. l 8.5 +0.3 -0. l 0.4 Mean 3.5 4 . 3 7.7 0.3 0.2 0.4 Std. error 0.2 0. l 0.6 0 .001 0.002 0.0
PAGE 144
Figure 30. Daytime net photosynthesis and night respiration in the inner dis charge bay affected by the thermal plume and the Fort Island and Hodges Island area away from the influence of the power plant. 0, Inner discharge bay; O , Fort Island and Hodges Island areas.
PAGE 145
.. C.f) t-(l) >. + 6 wwo z::C -o rC\j wz E ~G"-+ 4 t-0 C\J >-1-0
PAGE 146
Figure 31. Daytime net photosynthesis plus night respiration as a measure of gross primary production in the inner discharge bay affected by the thermal plume and the Fort Island and Hodges Island areas away from the influence of the thermal plume. [:] , Inner discharge bay; O , Fort Island and Hodges Island areas.
PAGE 147
(j) 0 0 0 0 (/) .. 8' wz 10 0 0 IO 0 1-0 0 z 1-0 >. Oa.. c IU) "'9 OWN :ca:: E 0 0 a.. .............. 0 __, l0 0 0 N I:CON -....J 5 0 0 [] W(.!) 0 :zE 0 0 0 z C, 0 0 w 0 0 0 '%! 0 0 0 0 ....I 0~ 0 a.. 0 0 <( 0 0 0 1972 1973 1974
PAGE 148
Figure 32. All daytime net photosynthesis and night respiration values from Tables 6 and 7 and Figure 30 plotted on 12-month graph.
PAGE 149
.. (/) }-• Cl) 0 +6 0 wwc 0 z::r:-o G 0 OJ ~('~ 0 0 wz [:) 0 >'-.. +4 0 0 CJ) {\J i-Oo 0 0 0 >-i0 , G 0 , 0 -2 0 0 <{ 0 0:) 0 a::~ cP 0 0 0 0 -(\J <%1 0 a.. E 0 G 0 Cl) ............ 0 -4 LL.I (\J dr 0 0 ct:o 0 0 0 0 0 G G ._ ,0 :c c:: B <.!) 0, 6 0 0 z J F M A M J JY AG s 0 N D
PAGE 150
Figure 33. All daytime net photosynthesis plus night respiration values from Tables 6 and 7 and Figure 31 plotted on 12-month graph.
PAGE 151
en ::::> 0 _j -0 El El O..C\J 0 61 en E 10 0 El 0 _......._,___ Cl) (.\J 0 G WO 0 I El [5D IE z 0) >(/) 0 .. r-Z 0 0 0 Oo 0 0 _, D w I:--' a:;5 0 (!)
PAGE 152
132 given in Appendix B. The range of diurnal oxygen change was 2-7 ppm for summer samples (8 measurements) and 2-3 ppm for winter samples (3 measurements). In general, the daily pattern of oxygen changes observed was similar to that found by others elsewhere, with a gain in oxygen in the water du~ing the day from photosynthesis and a loss at night from respiratory activity. The shape of the oxygen curve for individual days, however, was in fluenced by the timing of the tidal cycle. Large rapid increases in oxygen were associated with times of lowest water during daylight hours, while oxygen gains did not occur or were much smaller during daylight periods of highest water. Oxygen increases at night and downturns of oxygen before dusk noted in some measurements were associated with a rising tide and an increase in average water temperature indicating some advection of water from the discharge canal. All graphs of diurnal measurements of oxygen for estimation of community metabolism at Fort Island south of the mouth of the Crystal River (5 measurements representing an average of l to 5 stations) and Hodges Island north of the Withlacoochee River (2 measurements representing an average of 2 or 3 stations) are presented in Appendix B. The range of diurnal oxygen change was about 3 ppm in the summer (5 measurements) and about l ppm in the winter (2 measurements). The tidal cycle did not
PAGE 153
133 appear to be important in determining the shape of the oxygen curve at Fort Island. Nighttime increases in oxygen associated with a rising tide did occur at Hodges Island indicating some advection of more oxygenated water from offshore at that location. To confirm the occurrence of a diurnal curve of oxygen at the study sites, the average oxygen values from all summertime diurnal measurements were plotted together (Figure 34). Each plotted point represents the average of duplicate oxygen determinations at l to 5 stations taken at that time. Diurnal curves were obtained under different tidal regimes and sunlight conditions. The general trend of lowest oxygen near dawn, increasing values during the day, and larger values near dusk was evident. Dawn-Dusk-Dawn Measurements of Oxygen Dawn-dusk-dawn measurements of oxygen in the Fort Island area and the inner discharge bay are included in Appendix B. The general pattern of higher oxygen in the afternoon and lower at dawn was evident in most graphs. Daytime Net Photosynthesis Seasonal averages of daytime net photosynthesis are shown in Figure ~5 for the discharge and control bays.
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Figure 34. Average oxygen values from all summertime diurnal measurements taken in the inner discharge bay and Fort Island control bay .
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(\J E '(\J 0 CJ\ z w . (9 >X 0 l 3 5 10 INNER BAY .. : . 5 0 10 FORT ISLAND e ,::; ..., o----------L--~---1...-------L.-------l 0600 TIME OF 1200 DAY 1800
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136 The only significant season a l variation was the lower winter and higher spring production in the control areas. Comparing the two areas showed that spring, summer, arid fall values of net production in the control bays were generally 1.5 to 2.5 times those in the dis charge area with almost identical values in the winter. Spring and fall values were significantly different between areas while winter and summer values were not. Nighttime Respiration Figure 35 has night respiration by season for the control and discharge areas. A marked seasonal pattern was evident in the control area. The lowest value (l.5 g o 2 ;m 2 -day) occurred in winter, increased to 4.7 g o 2 ;m 2 day in spring, reached its highest value (5.7 g o 2 ;m 2 -day) in summer, and declined again in the fall to 4.3 g o 2 ;m 2 -day. t-tests (95 % level) showed that spring, summer, and fall were not signifi cantly different from each other, while all were significantly different from winter. In the discharge area night respiration values stayed almost constant, varying bet w een only 2.2 g o 2 ;m 2 -day and 2.5 g o 2 ;m 2 -day over the four seasons. t-tests sho w ed no significant difference between any season.
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Figure 35. Seasonal averages of daytime net photosynthe sis and night respiration in the inner discharge bay and control areas. Bars about points represent plus and minus one standard error. Spring is defined as May and June measurements, summer as July and August values. W, winter; Sp, spring; S, summer; F, fall.
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0 -c, N E <'I 0 E 138 +8,-----r----~----..---DAYTIME NET PHOTOSYNTHESIS +6 /"CONTROL AREAS +4 + 2 "-INNER BAY 0 ---------------------O'I 2 -4 -6 CONTROL NIGHT RESPIRATION -8------~---~-------~ 'vV SP S F SEASON
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139 Comparing the two areas in winter showed the controls to be lower than the discharge bay but not significan~ly different (95 % level). During spring, summer, and fall night respiration in the control bays was larger and significantly diffeient from the dis charge bay. Daytime Net Photosynthesis Plus Night Respiration If daytime respiration was assumed to occur at the same rate as nighttime respiration, then the sum of daytime net photosynthesis and night respiration was a measure of gross production. Figure 36 gives daytime net photosynthesis plus night respiration (P + R) plotted by season for the discharge and control bays. Average P + R in the discharge bay showed virtually no variation 2 with season, remaining about 4 g o 2 ;m -day. There was no statistical difference between s e asons (95 % level). The control bays showed a seasonal pattern of average P + R, being lowest in winter (3.3 g o 2 ;m 2 -day), highest in spring {9.7 g o 2 ;m 2 •day), and declining some in summer and fall. There was no significant difference (95 % level) between spring, summer, and fall values, but they were all significantly different from the winter value. Average winter P + R in the control area was slightly lower than that of the discharge bay but the
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Figure 36. Seasonal averages of daytime net photosynthe sis plus night respiration as a measure of gross primary production for plume-affected inner bay discharge area and unaffected con trol area s. Bars about points represent plus and minus one standard error. W, winter; Sp, spring; S, summer; F, fall.
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(\J E " d'J E C1 10 5 141 DAYTIME NET PHOTOSYNTHESIS PLUS NIGHT RESPIRATION CONTROL AREAS~ \__ INNER BAY 0--------------w SP S F SEASON
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142 difference was not significant at the 95 % level. Control area values were significantly larger (95 % level) during spring, summer, and fall than those measured in the dis charge area. Ratio of Net Photosynthesis to Night Respiration Seasonal trends in the ratio calculated as daytime net photosynthesis divided by night respiration (P/R ratio) for the inner discharge bay and control areas at Fort Island and Hodges Island are given in Figure 37. This ratio can indicate to what extent the excess of organic material accumulated above respiratory needs during the day satisfied the nighttime respiratory re quirements. In the discharge b a y the ratio was less than one except in the spring, being lowest in the fall. In the control areas the ratio was considerably greater than one in the winter bijsed on only two measurements, declined to about one in the spring, and fell below one for summer and fall. The ratio was lowest in the summer. Metabolism of the W ater Column Light and dark bottle measurements cif water column m e tabolism excluding larger orgar1isms are given in Tables 3 and 4 for the discharge bay and control bays . In the discharge bay seasonal water col~mn gross
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Figure 37. Seasonal trends of the ratio of daytime net photosynthesis divided by night respiration for plume-affected inner bay area and unaffected Fort Island and Hodges Island areas. W, winter; Sp, spring, S, summer; F, fa 11 .
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en 1.5 . en w :r: fz z 0 >AREAS (/) f0 <( f0:: 0 ::c n. a.. (/) 1.0 ------w f0:: w .z I w <.!) z "-_ INNER BAY f><( 0 0.5 w SP s F SEASON
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145 2 2 production ranged from 3.2 g o 2 ;m -day to 0.8 g o 2 ;m •day, being highest in spring (two measurements), and consider ably lower in summer and fall. In the control areas the average g o 2 ;m 2 -day the fall. 2 value ranted from 2.4 g 0 2 /m day to 0.4 and was also highest in spring and lower in Plankton production was a larger portion of total production in the discharge area than in the con trol areas, ranging from 70 percent of total production in the spring to about 23 percent in the summer and fall. In the control area it was 25 percent in the spring and 5 percent in the fall. Diffusion Measurements Results of diffusion measurements made in the discharge bay and the Fort Island control area are given in Table 5. Values measured in the discharge bay under different current velocities and wind conditions ranged from 0.13 to 0.78 g o 2 ;m 2 /hr/l00 percent deficit. Values averaged 0.44 g o 2 tm 2 /hr/l00 percent deficit when currents were largest (falling tide from high high to low low stage), and were lower at slack tide (0. 13 g o 2 tm 2 /hr/ 100 percent deficit). A measurement during moderate currents but brisk wind gave the largest value of 0.78 g 0~/m 2 /hr/100 percent deficit. L
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Table 5. Diffusion rates measured in the power plant discharge and Fort Island study areas. Diffusion Rate Location Date Tidal Stage Wind 2 g o 2 ;m /hr/100 % deficit Discharge Bay Oct. l O, 1972 Falling Low high Brisk to high low white caps 0.78 Discharge Bay June 28, 1973 Falling High high to low low Brisk 0.53 Discharge Bay July 26, 1973 Falling High high to low low Moderate 0.54 Discharge Bay September 12, 1973 Slack high tide Calm to light 0. 13 Discharge Bay September 12, 1973 Falling High high to low low Calm 0.24 Discharge Bay September 12, 1973 Falling High high to low low Light 0.44 Fort Island June 24, 1973 Rising, low low to low high Light 0.55 Fort Isl and June 25, 1973 Falling High high to low low Light 1.60 ..... +:> O'l
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147 Measurements at Fort Island generally were larger possibly because of the stronger currents there. A strong falling tide gave the high reading of 1.6 g o 2 ;m 2 /hr/ 100 percent deficit, while a more moderate rising tidal current gave a lower value of 0.55 g o 2 ;m 2 /hr/l00 percent deficit. Light Penetration of Water Column Given in Table 6 are light extinction coefficients calculated from submarine photometer readings from the inner discharge bay and the Fort Island and Hodges Island areas away from the power plant. The clearest water occurred at the Fort Island area, possibly as a result of the influence of the nearby discharge of the excep tionally clear Crystal River. The large extinction coefficient at Hodges Island was possibly a result of the discharge of the colored water of the Withlacoochee River about 3 km to the south. Turbidity contributing to the large extinction coefficient in the inner discharge bay was contributed by the water from the power plant discharge canal. On high tides the delineation between the more brownish yellow discharge plume water and somewhat clearer water mass from a previous tide was occasionally quite distinct to the eye .
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148 Table 6. Average extinction coefficients for light penetration of water on the inner discharge bay affected by the power plant discharge plume and unaffected areas to the north and south. Units are meters-1. Area affected by discharge plume Inner discharge baya l.49 Range ( l . 15l . 7) aEight measurements. Fort Area not affected by discharge . plume b C Island Hodges Island 0.90 2.00 Range (l.86-2.28) bTwo measurements. Both were 0.9. cThree measurements
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149 Model Diagrams for Comparing Ecosystems Affected and Unaffected by the Discharge Plume Figures 33 and 39 summarize knowledge gained of the inner bay receiving the thermal discharge from the power plants and the unaffected inshore ecosystem nearby. Values given are only ones actually measured at Crystal River or estimated from measured values. Documentation and calculation of numbers are giver, in Appendix E. A somewhat simpler model, which has been completely evaluated for the inner bay for purposes of computer simulation, is given in Figure 55. The ecosystem that had developed in the inner discharge bay under the influence of the power plant discharge was one of lower diversity, lower summer com munity metabolism, and lower standing stock of some compartments than the adjacent unaffected area. Biomass of benthic producers in the intake area was only about 66 percent of that in the discharge area. Benthic inver tebrate biomass in the discharge area was only 25 per cent of that in the intake area. Total oyster reef bio mass (Lehman, l974a,b) and resident fish biomass was similar in the two areas, although fewer fish were caught in the warm months in a tidal creek adjacent to the inner bay than one adjacent to the intake area (Homer, 1975). Nutrients were very similar between the two areas. Lehman (l974a,b) found diversity of oyster reef
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Figure 38. Summary energy diagram of summer stocks of biomass and material and flows of energy and organic matter for the inner discharge bay. Values given are only ones actually measured at Crystal River or readily estimated from measured values. See Appendix E for documentation or calculation of numbers. Stocks are in g/m2, of organic matter or materia1, flows in g/m2,day of or ganic matter or kcal/m2.ctay of sunlight.
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I PHOS \ .. ' ' ,T RESPIRATORY NUTRIENT REGENERATION f -..---PHOSPHORUS \ ' ', 0 \_L'-----,.:.---7 ',M I ' -. ~ !'LIG ' \ I I I I ., t,_, _________ _ BENTHIC PLANTS AND EPI PHYTES OYSTER REEFS OFFSHORE WA;E?. U1 __,
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Figure 39. Summary energy diagram of summer stocks of biomass or material and flows of energy and organic matter for the south intake area a w ay from the influence of the power plant discharge. Values given are only ones actually measured at Crystal River or readily estimated from measured values. See Appendix E for?documentation or calculation of numbers. Stocks are in g/m of organic matter or material, flows in g/m 2 .day of organic matter or kcal/m2,day of sunlight.
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p,_N ES TU ARY T RESP I RATORY NUTRIENT REGENERATION f ~--L ----sENrH,c PLANTS AND EPI PHYTES I MATTE SEDIMEN OYSTER REEFS OFFSHORE WATER I I I __, u, w
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154 macroorganisms to be lower in the discharge area. Biomass, however, was similar in both areas. Fewer species of fish were caught with drop nets in the discharge bay than in the intake area (Adams, 1974). Simulation Model of Diurnal Properties of the Inner Bay Ecosystem Shown in Figure 40 is a model simplified from Figure 4, which emphasizes the diurnal aspects of the flows and storages of the inner discharge bay. This model was simulated to help in determining the consis tency of the diurnal measurements of oxygen in the presence of advection and to test the effects of power generation operations on the diurnal properties of the inner bay. Table 7 gives the equations derived from the diagram. Calculations of transfer coefficients, scaling, pot settings, and other model functions are given in Appendix C. Photosynthetic production in this model was limited to benthic plant5. Phytoplankton were omitted for simplicity because their contribution to total photosynthesis during the sum m er at Crystal River was small. Light was captured as a function of temperature and phosphorus after being attenuated in proportion to
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Figure 40. Energy diagram for simulation model of inner discharge bay emphasizing the diurnal properties of the system. Switch labeled R is open only on a rising tide; switch marked Fis open only on a falling tide. See Appendix C for calculation of values given on diagram. See Table C-1 and C-4 for for mulae used for radiative and evaporative hea . t losses from water, for heat gain from atmospheric back radiation, and diffusion of oxyge~. Unless ~therwise noted, flows are 9/m day and storages are g/m of organic matter or material.
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er:: -:, BENTHIC DIFFUSION J32 J24 0.00255 ICROBES I 0IMENTS ' ' I ORUS OFFSHOR (J7 O'I
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Table 7. Differential equations for diurnal model of inner bay given in Figure 40. dQ3 cit k (H + C)V l 5 3 u, -...J
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Table 7 continued u, CJ
PAGE 179
159 depth, producing oxygen and labile sugars. The sugars were respired as a funttion of temperature and oxygen, some being fixed into structural biomass, but most being degraded to heat and inorganic nutrients. All consumers were lumped into one compartment because changes in biomass were not believed important on a diurnal basis. Consumers fed on the pool of organic matter in the water column, assimilating some into biomass and returning the rest to the organic pool as feces and pseudofeces. Respiration was modeled as a multiplicative function of temperature and oxygen. A storage of bottom organic matter was omitted from the model because its large quantity precluded any significant change diurnally. However, benthic microbial respiration associated with these sediments was large and was modeled as a function of oxygen and temperature. Within the water on the inner bay are shown storages of heat, total phosphorus, oxygen, and organic matter. All were exchanged tidally with discharge canal and offshore water. For lack of specific data, one-third of the water contributed to the inner bay on a rising tide was assumed to come from the discharge canal and two-thirds from offshore. On a falli~g tide, these flows stopped and water on the inner bay was transported off shore. Water in the model itself had no interaction with anything else other than as a vehicle for transporting
PAGE 180
IOU material. Because of this it was omitted and treated as a forcing function of volume exchange, bringing the phosphorus organic matter, heat, and oxygen carried in the water onto or carrying it off . the bay. Volume ex change was derived from the tide table and programmed on a function generator. The tidal state (rising or falling) operated swit c hes determining whether materials were carried on or off the bay. Phosphorus was taken up in photosynthesis and returned to the water column once again from all respira tory pathways. Oxygen was released into the water column by photosynthesis and removed by all respiratory functions and the dark reactions of photosynthesis. Because of equipment constraints, diffusive oxygen exchange with the atmosphere was programmed as an average daily constant function rather than varying with current velocity. Heat losses through radiation and evaporation were programmed as empirical functions of temperature, obtained by dividing heat storage by depth. The heat cont~nt of the evaporated water and heat lost by convection were omitted because they were small in comparison to the losses from radiation and the heat flux associated with change of state in evaporation (see Table C-4). Sunlight was programmed as part of a sine wave to make a 14-hour day. The tidal cycle was obtained by draw ing a smooth curve through the actual depth measurements
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1 61 obtained during the sampling of diurnil metabolism for June 21-22, 1973. The rate-of-change of this graph was the volume exchange rate for 1 m 2 This function was programmed as closelj as possible on a function generator and the output integrated to obtain the volume of water on the inner bay at any moment. Since this is a model of l m 2 of inner bay, water volume was also depth. The output of the func tion generator and its integrated value along with the a . ctual measured points for June 21 are given in Figure 41. Tidal stage was derived from the volume exchange rate function, which was positive on a rising tide and nega tive on a falling tide. A comparator sensed this polarity and activated the proper switches controlling flows asso ciated with each tidal stage. Since the computer patching using the output of the volume exchange function required positive values only, an absolute value circuit was em ployed to convert the output (Figure 41b). Offshore oxygen concent~ation (McKellar, 1975) was programmed as a sine wave with a low point at 0600 of 6 g/m 3 and a high point at 1800 of 8 g/m 3 (Fi~ure 43d). Offshore (McKellar, 1975) and discharge water temperature were programmed the same way, varying from 27C to 30C for offshore water and 32C to 35C for discharge water (Figure 41c). All other forcing functions were held constant.
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Figure 41. Computer plots of forcing functions of tidal volume exchange, depth, offshore oxygen, and offshore water temperature used in the diurnal simulation model (Figure 40). (a) Output of function generator programmed with volume exchange rate calculated for the tidal cycle in the inner bay on June 21-22, 1973. (b) . Output of function generator with nega tive portions converted to positive with an absolute value circuit. (c) Water depth obtained by integrating the volume exchange rate of (a). Actual data points measured on the inner bay on June 21-22, 1973, are indicated for comparison. (d) Oxygen concentration in offshore water. ( e ) Temperature of offshore water. curve raised 5 C was also used forcing function fer discharge water temperature. This same as the canal
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163 +0.2 ... .c -t0 . I "'0.0 I") E -0.I -0.2 0 . 2 ... .c " 0.1 r<) E 0.0 2 . 0 (c)DEPTH 0 0 E 1.0 0 . 0 .__ __ __._ ___ _._ __ -,..__ __ __, 10 (d)OFFSHORE OXYGEN (X2) E o _ 5 a. 0 -------~-----.... 40 .....----.-,---~,----.-,--( e) OFFSHORE TEMPERATURE (H) ~-----~---------..,u 20 .... 0 0 .__ _ __ __,_, _ _ _ _._, ___ __.__ __ ___, 0600 1200 TIME OF DAY 1800
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164 Model Output with Initial Scaling The diurnal model was run as initially scaled to observe its general behavior and properties (Figure 42). Pot settings are given in Appendix C, Table C-8. The daily course of insolation was a sine wave with a sunrise at 0500 and sunset at 1900, providing a total of 5938 kcal/m 2 for the day, typical of a bright, sunny day at Crystal River. Sunlight actually reaching the benthic plants on the bottom was less because of extinction by the water column. Oxygen in the water column exhibited a typical diurnal pattern, being lowest at dawn, rising rapidly in the morning hours immediately after sunrise to a high point about 1300, and dropping slowly through the afternoon. Fit was reasonable with summer oxygen values actually measured in the inner bay. The rate of gross primary production was limited after about 1000 by the rapid decline in phosphorus as it was taken up in photosynthesis. The area under the production curve was the daily gross primary production and equalled 5.4 g/m 2 , somewhat higher than the summer mean of 4.5 g/m 2 •day, which included measurements on cloudy and clear days. The dual peaks of total respiration resulted from respiration being a function of temperature and total oxygen in the water column. Increasing depth on
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Figure 42. Simulation results of diurnal model of inner bay (Figure 40) with coefficients set as originally scaled. Independent points plotted on the graph of oxygen are all summertime oxygen values measured in the inner bay during complete diufnal metabolism sampling runs. Each point is the average of two to ten individual measurements.
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IOOO (a) SUNLIGHT SURFACE 0::: I C\J_ C: ......... 0 (.) en 0::: w Iw a.. a.. 500 0 2 (b) DEF 1 TH 0 10 (c) OXYGEN 0 '5 (d) GROSS PRIMARY PRODUCTION 1.0 0 . 5 OL-.--....1~--'--------3--I.O (e) TOTAL RESPIRATION .5 QL_. __ 6....J.O_O __ i_J20L0:----:-1~80:::-0:::--.... 166 50 (f)TEMPERATURE 40 30 (.) 0 20 10 0 0 . 10 (g)TOTAL PHOSPHOROUS r
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Figure 44. Solar insolation for June 21, 1973, as recorded by a pyranometer located at the Crystal River power plant site. Total radiation received is indicated.
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.. z '0 ..c: (\J 1000 _J 0 500 (/) 0 (.) z 21 JUNE, 1973 1800 1200 TiME OF DAY 0600 __. -..J N
PAGE 193
Figure 45. Simulation results of diurnal model of inner bay (Figure 40) with original scaling, but sunlight reduced to a daily total similar to June 21-22, 1973. Points ( 0) are ob served data from the inner bay.
PAGE 194
174 1000 (a) SUNLIGHT 50 (f) TEMPERATURE ... 40 .s::. (\J 500 0 0 u 0 0 20 <., 0 10 0 0.10 2 (g)TOTAL PHOSPHORUS I.I) ... E Q) +"'0.05 Q) E c,, 0 0.00 10 (h) ORGANIC MATTER 10 (c) OXYGEN IN WATER rt) -E 5-a. a. c,, 0 0 I I I ( i) BENTHIC PRODUCERS 201.0 (\J ~BIOMASS (d) GROSS PRIMARY PRODUCTION ---0 . 5 10"'-.. LABILE ORGANIC OI MATTER 0.0 0 I I I .... .s::. (\J 10 (j) CONSUMERS 0 (\J c,, E 1.0 "' 5,,.. (e}TOTAL RESPIRATION 0.5 o• 0.0 0 I I I 0600 1200 1800 0600 1200 1800
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The gross primary production of 3.4 g o 2 .m 2 was 2 less than the 4.0 g o 2 -m calculated from the actual data. The total respiration curve still exhibited the same shape as the initial run (Figure 42). Total respiration for this run was 6.1 g o 2 ;m 2 The P/R ratio of 0.56 was larger than the 0.33 calculated from th e diurnal data. Water temperature dropped below the measured values in the afternoon, but still had the same general shape as the observed data. Because of the reduced photosynthesis, phosphorus did not undergo as large a diurnal variation as the initial run. Midday values, however, still limited gross primary production. The labile organic pool within the benthic plants exhibited a small diurnal cycle similar to the initial run. Organic matter in the water column, plant biomass, and consumer biomass had patterns essentially similar to the previous runs. With adjustment of insolation the simulation gave a reasonable overall match to the observed data. Periodic responses were not necessarily expected since the forcing function of volume exchange was not periodic. Also, since the diurnal dynamics of water bodies are generally dependent on forcing functions which are vari able from day to day, the fact that a quantity such as
PAGE 196
176 oxygen does not return to the same value 24 hours later is more the rule than the exception. The nonperiodici ties observed were all well within variations known to occur at Crystal River. Output of Model with Various Ratios of Canal Water to Offshore Water on a Rising Tide Since the relative contributions of water from the discharge canal and offshore to the inner bay on a rising tide was only an ~ stimate, the model was rerun with different proportional contributions of water from these sources. Coefficients were set for the following ratios on a rising tide: equal amounts of canal and offshore water, a 2:1 ratio of canal to offshore water, and canal water only. Graphs of simulation results are given in Figures 46-48. Differences in response of the model to the different conditions were small. For oxygen, the minimum value at dawn was lowered slightly and the magnitude of the maximum value and time of its occurrence reduced somewhat because of the increasing contribution of canal water with its lower oxygen content on the rising tides. The temperature curve rose as the proportion of canal water increase~ matching best when canal water made up all of the flow into the inner bay on a rising tide {Figure 48). All other parameters were essentially
PAGE 197
Figure 46. Simulation results of diurnal model of the inner bay (Figure 40) with equal amounts of canal and offshore water contributed to the inner bay on a rising tide. Points ( 0) are observed data from the inner bay for June 21-22, 1973 .
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178 1000 (o) SUNLIGHT 50 (f) TEMPERATURE .. 40 .c:: N 5 0 u 30 0 0 c., 20 ::ac:: 0 10 0 QIO (g) TOTAL PHOSPHORUS (b} DEPTH Ill ... cu +cu UI E 0 0.00 10 10 .{h} ORGANIC MATTER . (c} OXYGEN IN WATER ro __,. E E ' 5"""" 0. 0. c:,, 0 0 I I I (i) BENTHlC PRODUCERS 20 N y--BIOMASS 1.0 (d) GROSS PRIMARY E PRODUCTION " 10 'LABILE ORGANIC 0.5 t,I MATTER 0,0 0 ~.L::. C\I E lO (j}CONSUMERS 0 C\I c::,, E 1.0 (e) TOTAL RESPIRA~ ............ 5 .... 0.5 C1' ____ ___,.,.... I 0.0 0 . 0600 12CO . 1800 0600 1200 1800
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Figure 47. Simulation results of diurnal model of the inner bay (Figure 40) with two parts canal water to one part offshore water contributed to the inner bay on a rising tide. Points ( 0) are observed data from the inner bay for June 21-22, 1973.
PAGE 200
180 1000 (a) SUNLIGHT ... s::. . N 500 0 0 :i,c U) ... C) C) E E a. a. ... .s::. 0 (b) DEPTH 0 0 0 IO (c) OXYGEN 0 o.___._ _ ___.____--'---..__J I.O[ (d) GROSS PRIMARY 0 . PRODUCTION . 51 0,0 LOI {e}TOTAL RESPIRATION I 0.5~ ~_J Q.Q ---;----;I 0600 1200 I 800 0 0 Q 50 (f) TEMPERATURE 40 30 20 10 0 0.10 (g) TOTAL PHOSPHORUS 000 10 (h) ORGANIC MATTER IN WATER o.__ _ ___. ________ _ ( i) BE NTH IC PRODUCERS "1E ~BIOMASS ' ~::::::::==:=:::::==::::::::::::=:=--~=i OI IO ~LABILE ORGANIC MATTER 0 IO (j) CONSUMERS 0 .__ _ _.._, ___ , ___ ...._,_--I 0600 1200 1800
PAGE 201
Figure 48 . Simulation results of diurnal model of inner bay (Figure 40) with canal water alone being contributed to the inner bay on a rising tide. Points ( 0) are observed data from the inner bay for June 21-22, 1973.
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182 (a) SUNLIGHT 50 (f) TEMPERATURE 40 .c: . C\I 5 30 u 0 0 20 0 :ii: 0 10 0 0.10 (g) TOTAL PHOSPHORUS (b) DEPTH "' 0 ... QJ GJ E 0 0 0.00 10 10 -(h) ORGANIC MATTER (c) OXYGEN IN WATER ,n E C. 5~ Q. QI 0 0 I I I (i) BENTHIC PRODUCERS 201.0 (d) GROSS PRIMARY (\I ~BIOM~SS '{ PRODUCTION -0.5 10"---LABILE ORGANIC 01 MATTER ... 0.0 0 I I I .c: N '~ 10 N (j) CONSUMERS 0 N 01> '{ 1.0 5(e)TOTAL RESPIRATION j 0, 0 . 5 -----------~ I I 0.0 0 0600 1200 1800 0600 1200 1800
PAGE 203
183 unchanged from previous runs. The best overall fit of temperature and oxygen was with a mixing ratio of 2 parts canal water to l part offshore water (Figure 47). Responses of Model to Increased Temperature of Disch arg e Canal Water The addition of the third power plant at Crystal River was expected to raise the temperature of the dis charge canal l to 2C and increase discharge velocity by about a factor of two, so that an increased tempera ture and different rising tide mixing ratio might be expected on the inner bay. The diurnal model was rerun using the same series of rising tide mixing ratios as in the previous set but with canal water temperature raised to 7C over ambient inst e ad of 5C {Figures 49-51 ). The only discernible effect on model output was to increase water temperature on the inner bay about lC. All other model output was essentially unchanged from previous runs. Model Response with No Discharge from Power Plant One cooling alternative at Crystal River was the construction of closed cycle cooling towers. To test this possibility, which would eliminate the flow of any heated effluent from the discharge canal, the model was run with only offshore water flowing onto the
PAGE 204
Figure 49. Simulation results of diurnal model of the inner bay (Figure 40) wit~ a 7C differential of discharge canal water over ambient water and a mixing ratio on a rising tide of one part canal water to one part offshore water.
PAGE 205
1000 (a) SUNLIGHT 50 (f) TEMPERATURE .. 40 .c . N 50() 0 30 0 0 20 0 0 10 0 0 . 10 (g) TOTAL PHOSPHORUS (b) DEPTH Cl) ... Cl> CIJ E Cl 0 0 . 00 10 ... (h) ORGANIC MATTER 10 (c) OXYGEN IN WATER ft) --E 5 5...-a. 0. CJI 0 0 I I I (i) BENTHIC PRODUCERS 20-"' FBIOMASS 1.0 (d) GROSS PRIMARY PRODUCTION r----.:......_ 10 ... ~LABILE ORGANIC 0 . 5 Cl MATTER 0.0 0 ' . . ... .c . "J,. 10 N (j) CONSUMERS 0 "' 0, 1.0 ( e) TOTAL RESPIRATION 5 ... 0 . 5 er, 0 . 0 0 . . . 0600 1200 1800 0600 1200 1800
PAGE 206
Figure 50. Simulation results of diurnal model of the inner bay (Figure 40) with a 7C differential of discharge canal water over ambient water and a mixing ratio of 2 parts canal water to 1 part offshore water on a rising tide.
PAGE 207
100 ._ .c N 500 C u 1,/) ... OJ Q.) E 0 187 (a) SUNLIGHT (b) DEPTH 0'------'------'----'-------' 10 (c) OXYGEN E a. a. 0 1.0 (d) GROSS PRIMARY 0.5 PRODUCTION 0,0 .. .c . N C\I 0 CJII 1.0 0 . 5 (e)TOTAL RESPIRATION 0.0 0600 1200 1800 50 (f) TEMPERATURE 40 0 30 0 20 10 0 0.10 (g) TOTAL PHOSPHORUS c,, 0 . 00 ........ _ __._ __ ___._ __ __._ __ -+ 10 (h) ORGANIC MATTER IN WATER re> 5 CJII 0 (i) BENTHIC PRODUCERS 20 ,N A,:-BIOMASS " 10 ~LABILE ORGANIC c,, MATTER 0 I I I IO (J) CONSUMERS N 5,D' 0 I I I . 0600 1200 1800
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Figure 51. Simulation results of diurnal model of the inner bay (Figure 40) with a 7C differential of discharge canal wat e r over ambient water and with canal water alone flowing onto the inner bay on a rising tide.
PAGE 209
189 100 (a) SUNLIGHT 50 (f) TEMPERATURE ... 40 .c 500 30 0 u 0 0 20 i! 0 10 0 0.10 (g) TOTAL PHOSPHORUS (b) DEPTH Ul ... C> Q) E c,I 0 0.00 10 ... (h) ORGANIC MATTER 10 (c) OXYGEN IN WATER It) ---E Q. 5i==Q. Ot 0 0 I I I ( i) BENTHIC PRODUCERS 201.0 '" ;,:--BIOMASS (d) GROSS PRIMARY E PRODUCTION ", 10 -0.5 c,, -,:_LABILE ORGANIC MATTER 0.0 0 I I I .. .c: Cl.I 10 C\I {j) CONSUMERS 0 C\I c,, 1.0 5(e) TOTAL RESP: RATION 0.5 C/1 --0.0 0 I I I 0600 1200 1800 0600 1200 1800
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190 inner bay on a rising tide (Figures 52 and 53). Oxygen levels increased and temperature levels decreased some what over previous runs because canal water with its lower oxygen content and higher temperature was no longer being contributed to the inner bay. Other model output did not change discernibly from previous runs over the 24-hour period of the simulation. Model Response to Timing of the Tidal Cycle Because the time of occurrence during the day of high and low tide on the inner bay was believed to be important in determining the shape of the oxygen curve, the model was rescaled and rerun with the tidal cycle reversed from the previous runs. Simulation results are given in Figure 54. The oxygen curve with this tidal regime was m o r e II c l a s s i c a l II i n s h a p e \'I i t h a r a p i d r i s e a f t e r d a w n , tapering off to a high point near dusk. Gross primary production was limited by low phosphorus and light during the midday period . . Total respiration exhibited the same dependence on total oxygen as in previous runs. Total phorphorus underwent a diurnal cycle in fluenced by respiratory recycling, advection, and uptake in photosynthesis. The large peak at dawn was a result of respiratory regeneration into the smaller volume of water present on the bay with the low tide at that time.
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Figure 52. Simulation results of diurnal model of the inner bay (Figure 40) with no discharge of cooling water from the power plant discharge canal and original scaling of insolation.
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192 1000 50 ( a) SUNLIGHT (t) TEMPERATURE ... 40 .c N 500 u 30 0 0 u 20 0 10 0 0.10 (o) TOTAL PHOSPHORUS (b) DEPTH Ul L. 11> -11> E c,, 0 0.0 10 10 .-(h) ORGANIC MATTER (c) OXYGEN IN WATER __,. E 5 5a. a. c,, 0 0 I I I ( i) BENTHIC . PRODUCERS 20 { d) GROSS PRIMARY N 1 . 0 'Z PRODUCTION 0 . 5 c,, 10 LABILE ORGANIC _A MATTER L. 0,0 0 .c (\j IO (j) CONSUMERS N 0 N c,, I.O~TO~ 5,c,, 0.5 . ~ 0 I I . I 0.0 I 0600 1200 1800 0600 1200 1800
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Figure 53. Simulation results of diurnal model of the in ner bay (Figure 40) with no discharge from the power plant discharge canal and insolation re duced to one-half original scaling .
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194 1000 50 (a) SUNLIGHT (f) TEMPERATURE ... 40 .c: . N 500 'Z . u 300 0 20 u 0 10 0 0.10 (g) TOTAL PHOSPHORUS (b) DEPTH IJI rt) ... E 11> "Zo . os 11> E 01 0 0 . 00 10 (h) ORGANIC MATTER (c) OXYGEN IN WATER rt) E 5 a. 5 Q. O'I 0 0 ( i) BENTHIC PRODUCERS 20 1.0 N BIOMASS (d) GROSS PRIMARY 'Z PROOUCTION 0 . 5 Cl ~LABILE ORGANIC MATTER 0 . 0 0 ... .c: N 10 (j) CONSUMERS 0 N O'I . ~ 1.0 5,(e) TOTAL RESPIRATION 0.5 c,, 0 . 0 0 I I I 0600 1200 1800 0600 1200 1800
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Figure 54. Simulation results of diurnal model (Figure 40) with timing of occurrence of high and low tide reversed from previous runs.
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196 IOOO L. ( a ) SUNLIGHT (f ) TEMPERATURE .c 40 (\j E "'-500 u a 0 20 u 0 10 2.0 (b)DEPTH 0 0.10 (g) TOTAL PHOSPHORUS V) L. (l) 1.0 +Q) E 0.51 o> 0 . 0 0.00 15 (c) OXYGEN (h) ORGANIC MATTER 8 IN WATER 10 r<) E E n. "' C\. 4 o> 0 0 LO (d) GROSS PR ! MARY ( i } BENTHIC PRODUCERS PRODUCTION 20C\l y--BIOMASS 0 . 5 E L. "' 10 (\J MATTER 0 . 0 0 I (\J 0 (e} TOTAL R E SPIRATION Ol 04 10 ( j} CONSUMERS C\I -:---.___/~~ E 02 "' 5 o> 0 . 00 I I I 0600 1200 1800 0600 1200 1800
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Figure 55. Energy diagram of simulated model of inner discharge bay empha sizing seasonal properties of the ecosystem and flows in g/m2, day. Unless otherwise noted, storages are i n g/m2 of organic matter or material. See Appendix D for calculation of values given. Pathways indicating the effect of temperature on system properties have been omitted to simplify the diagram. The path way enter i n g a w o r k gate marked w i th a II T 11 is assumed to come from the symbol T T
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BENTHI INVERT \ I ......, ._::;; co
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Figure 56. Seasonal patterns of insolation and tempera ture used as forcing functions in the seasonal model of the inner bay ecosystem (Figure 55). (a) Seasonal course of sunlight simulated with a function generator. Solid line is response of function generator. Inde pendent points are average daily insola tion by month at Tampa, Florida, from Figure 14. (b) Simulated seasonal cycle of water tempera ture for the inner bay. Solid line is sine wave approximation of seasonal cycle. Unconnected points are monthly mean water temperatures at Cedar Key, Florida, from Figure 18.
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>. 0 "'O (\J E ' 0 u 200 8000,-...,...-.--.---.--,--~-.--.---.r-r--.---. (a)INSOLATION 6000 4000 2000 o .____,___.....___....____.____.___.____,_____,_____.____.____.____. 40..-----.--,--.--.---.---.----.-----.--,--.----.--{b)TEMPERATURE 30 o 20 0 10 o.___.____.____._ __ 1__ .__..__..___.__L..._...___. J F M t \ M J JY A S O N D
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201 Depletion during the day from uptake in photosynthesis limited the rate of primary production. Temperature dropped during the day because back radiation from the atmosphere was not included as an input in this run. The general insensitivity of previous runs to temperature, however, indicated that correction of this inaccuracy would not alter the model response very much. Simulation Model of Seasonal Properties of the Inner Bay Ecosystem Given in Figure 55 is an energy diagram of the model of the inner bay simulated for study of its seasonal properties. The equations following from the diagram are given in Table 8. Calculations and documentation of various other model parameters are given in Appendix D. All forcing functions were considered constant except temperature and sunlight because of the lack of adequate data to program them with any seasonal patterns. Sunlight (Figure 56a) was programmed on a function gen erator to match the pattern of average daily insolation by month at Tampa, Florida. Seasonal temperature was simulated as a sine wave function with a low of l5C on January 1st and a peak of 33C on July 1st (Figure 56b). Large deep bodies of water often have a tempera ture cycle which lags insolation by several months.
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Table 8. Differential equations for seasonal model of inner bay system given in Figure 55. N 0 N
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Table 8 continued N 0 w
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204 However, in the shallow coastal area of west central Florida water temperature was usually closely in phase with insolation. The model itself contained storages of benthic macrophytes (Q 1 ), phytoplankton (Q 7 ), total phosphorus (Q 2 ), organic matter in the water column (Q 3 ), and sediments (Q 4 ), benthic invertebrates (Q 5 ), and fish (Q 6 ). Oyster reef biomass (R) was considered a consta n t forcing function outside of the model, but its filtering action on organic matter in the water column was included as a function of temperature (Galtsoff, 1928; Nelson, 1935; Loosanoff, 1958; all quoted in Lehman, 1974). Gross primary production (J 2 ) is shown as the product of the action of sunlight, temperature, phos phorus, and plant biomass. Incident solar radiation is shown as a constant flow source (J 0 ) from which some is drawn for use in photosynthesis (J 1 ), the remainder (JR) being used in other physical processes. If all other factors are nonlimiting, primary production may increase by capturing more and more sunlight previously unused in photosynthesis {JR). At some level of produc tion all incident solar radiation (J 0 ) is being used in photosynthesis (J 1 now equals J 0 ) so that sunlight becomes a liniiting factor. The storage of benthic plant biomass produced in photosynthesis {Q 1 ) is not grazed directly, but is
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205 lost to respiration (J 3 ) and storages of organic matter in the sediments (J 6 ) and water column (J 5 ). Phyto plankton are lost by grazing of filter-feeding benthic invertebrates (J 39 ) and oysters (J 38 ), and by exchanges with offshore and discharge canal populations (J 43 , J 44 ). Storages in the water column of organic matter (0 3 J and phosphorus (0 2 ) exchange tidally with concen trations in the discharge and offshore water (J 8 , J 9 , J 16 , J 17 ). Inflows from the saltmarsh (J 7 , J 15 ) are constant. Loss of organic matter by respiration (J 14 ) occurs as a product of temperature and the quantity stored. Organic matter is gained by the sediments (0 4 ) through pathways of settling of plant matter (J 6 ), sedi mentation from the water column (J 13 ), feces and pseudo feces from oyster reef organisms (J 23 ), death of benthic invertebrates and fish (J 21 , J 22 J, and feces of benthic invertebrates (J 20 ). Losses from the sediments are from microbial respiratirin (J 18 ) and deposit feeding of benthic invertebrates (J 19 ). Oyster reef biomass (R) is modeled as constant and outside of the model boundaries because more detailed simulations are av a ilable in Lehman (1974). Reef organisms filter organic material from the water column (J 11 ) as the product of the qua11tity of organic material {0 3 ), temperature (T), and reef bio~ass (R).
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206 Unassimilated material is released to the sediments as feces and pseudofeces (J 23 ). All benthic invertebrates are lumped into one compartment (Q 5 ). Feeding inputs are shown as filter feeding on organic matter and phytoplankton in the water column (J 12 ) and deposit feeding on organic matter in the sediments (J 19 ). Ingested food is assimilated (J 24 ) at an assumed efficiency of 50 % , the rest being returned to the sediment organic storage (J 20 ). The rate of these processes is modeled as the product of temperature (T), the stored quantities of organic matter (Q 3 + Q 4 ), and invertebrate biomass (Q 5 ). Losses of invertebrate biomass are by respiration (J 25 ) and predation of fish (J 26 ). Respiration is considered to be the product of temperature and the square of invertebrate biomass. The fish compartment includes only resident species, since the storage value was obtained from the dropnet measurements. Both carnivorous (J 10 ) and detritus feeding (J 26 ) pathways are indicated. Since the propor tion of intake by each pathway is unknown, the calculated assimilation is merely divided between the two pathways. Losses of fish biomass are fro ~ death (J 22 ), modeled as a linear density-dependent drain , and respiration (J 28 ), m odeled as the product of the square of biomass storage and te m perature.
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207 Phosphorus is recycled to the water column pool by all respiratory activity (J 29 , J 30 , J 31 , J32' J34' J42l The amount of phosphorus released was taken as a percentage of the organic matter respired. The effect of temperature is included in the model as a multiplicative function on all biologically mediated pathways. An exponential or other function was not used for several reasons. Because of acclimation, respiration may not actually follow an exponential relationship be tween winter and summer temperatures, the rate observed being lower in warmer temperatures than would be predicted from an exponential extrapolation of rates during cold temperatures. A linear multiplicative relationship gives an output approximating this reasoning. Mechanisms in addition to predation are thought to operate regulating population size at high population levels. In this model a square term interaction on drain ing respiratory pathways of benthic invertebrates and fish has been used to include this factor in model behavior. Initial Simulation and Adjustments When the seasonal model ~as simulated with co efficients set for the original scaled values, the stor ages of fisl1 and benthic plants deviated somewhat from the observed data. To correct the excursion of fish
PAGE 228
20 8 biomass, which was increasing to about twice the initial condition value, pathway J 22 representing death and losses to higher trophic levels was increased to make inflows to the storage equal outflows. Loss pathways J 5 and J 6 from benthic plants were reduced somewhat to maintain the original summer biomass level of 40 g/m 2 . After adjustment of the parameters described above, model behavior (Figure 57) was more in line with available field data and trends of the storages. Benthic plant biomass follows the observed pattern of low values in fall and winter, increasing through the spring to the largest values during summer. The observed summer value was not quite reached because the 40 g/m 2 used in the original scaling was chosen before the e x act value from field measurements was available. The trend of the simulation for the fall and winter was realistic, but was somewhat off from the data points. Biomass was probably variable during the cold months, being reduced drastically when strong cold fronts would drain the inner bay for several days, as seen in the fall sample, and recovering to somewhat higher levels afterwards, as seen in the winter sample. Deviations from measured values for phytoplankton biomass may result from several reasons. The observed values were measured at the mouth of the discharge canal
PAGE 229
Figure 57. Simulation results with initial scaling of season a l model of the inner bay (Figure 55). Measur e d data for benthic plants, resident fish, benthic invertebrates, gross photo synthesis, and total respiration have also been plotted by quarter for comparison.
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"' 210 8000r----r-----,----.-----..-----r---~40 Cl) Iz 20~ a: w 0. w I( C} N NE 1L-.-..J.-----------------__.:::,5 0 . 05 ~100 0> 0, 0 >. 0 -0 PHOSPHORUS ( a ) o._ __ ....._ __ _._ __ _._ ___ ._ __ _._ __ ~o 6 4 BENTHIC INVERTEBRATES I:] [:J TOTAL GROSS PRODUCTION ( 0) BENTHIC PLANT PRODUCTION (ll) PHYTOPLANKTON PRODUCTION (.t) 0 (3 YEARS
PAGE 231
211 and are, thus, only roughly representative of conditions for the inner bay. Also, the large flushing exchange with a constant offshore source of biomass, an assumption which was not entirely correct, tended to dampen any seasonal variations produced by the model. Fish biomass simulated in the model matched fairly well with the 1.5 year's data measured for the inner bay. Simulated values for benthic invertebrates was higher than the measured values. However, the sampling technique used probably was measuring only about half the actual biomass. When doubled, they fall fairly close to the simulated values. The initial gain in biomass at the start of the simulation was well within variations in the data. Because of the large size of the storage, organic matter in the sediments underwent only a small seasonal change, being lowest in spring and highest in late summer. Large changes in the storages of phosphorus and organic matter in the water column were prevented by the large exchange with the constant offshore source. No adjustments of coefficients could produce simulation patterns of respiration and photosynthesis similar to the observed values. However, the pattern of a peak in phytoplankton production in the spring followed by benthic plant production in the summer, and a P/R ratio of one in the spring were similar to observed patterns, although the magnitudes were incorrect.
PAGE 232
Response of Simulation Model to Increased Temperature An expected consequence of the operation of the power plant under construction at Crystal River was a small increase in the temperature of the discharge canal water. Coupled with possible modified flushing patterns in the discharge area because of increased canal veloci ties, the average temperature of the inner bay could increase from lC to 3C. The maximum case was chosen, and the model was simulated with a seasonal temperature pattern of 18-36 C. All other parameters were left un changed. Simulation results are given in Figure 58. Increased temperature was somewhat stimulatory to gross photosynthesis of benthic plants but not phyto plankton. Total respiration was also stimulated. The increased photosynthesis of benthic plants increased the standing stock somewhat. Resident fish biomass increased, while benthic invertebrate biomass remained about the same, possibly in response to increased predation losses to the larger fish stock. The observed reduction in the storage of organic matter in the sedi ments may indicate that this source was being drawh upon to satisfy the increased consumer demands. Any changes in the storage of organic matter in the water column from increased filtering by consumers was obscured by the exchange with offshore concentrations.
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Figure 58. Simulation results of seasonal model of the inner bay (Figure 55) with seasonal pattern of temperature increased 3C.
PAGE 234
z c, Q"O 8000 ti~ _J E 4000 O' C/) z8 -~ 214 40u 0 w er: ::) 20 ffi CL w Io._ __ _._ _____ _._ ______ _._ _ __.o C/) Iz
PAGE 235
21 5 Response of Simulation Model to Increased Temperature and Turbidity Another possible consequence of the operation of unit three at Crystal River was an increase in turbidity accompanying the increase in temperature. This possi bility was tested by simulating the model with seasonal temper~tures of l8-36C as in the previous run, but with the flow of sunlight utilized in photosynthesis (J 1 ) reduced from 50 percent to 30 percent. Simulation results are given in Figure 59. Benthic plant photosynthesis was reduced consider ably despite the previously demonstrated stimulatory effect of increased temperature alone. Phytoplankton photosynthesis was largely unaffected, making it a larger percentage of total gross production. Total respiration also declined because of the reduction of several storage compartments. Biomass of benthic plants decreased considerably, while phytoplankton biomass was reduced somewhat except during its spring peak. The higher trophic levels of invertebrates and fish declined because of the reduced primary production. Re s__p_o n s e o f S i rn u l a t i o n Mod e l t o D e c r e a s e d Tu r b i d i t y The previous simulation indicated the importance of turbidity in . controlling primary production in the
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Figure 59. Response of seasonal simulation model of the inner bay (Figure 55) to increased temperature and turbidity. The seasonal pattern of tem perature was increased 3 C, and the flow of sunlight utilized in photosynthesis reduced from 50 % to 30 %.
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z~ Q"O 217 TEMPERATURE w Cl'.'. :::> r" c:tC\I _J E 4000 o, 20 Cl'.'. w n. C/) z8 -~ Q._ __ _._ _____ __._ ______ .,_ _ __.Q C/) z ct _J n. C\I u E ' 40 I o, 20 r(\J z w CD (a) 0.10 E ,0.05 0, BENTHIC PLANTS PHYTOPLANKTON SEDIMENT ORGANIC MATTER ( b) WATER ORGANIC MATTER ( c) PHOSPHORUS ( a) O 0:::=====::::============::::============:::=====:::::0 (\J 5 E ' 0, BENTHIC INVERTEBRATES RESIDENT FISH o~=====:!===-=========-:!=-=-=========="!:=-=-=-==---. >0 6 "O 4 (\J 0, 2 TOTAL RESPIRATION TOTAL GROSS PRODUCTION BENTHIC PLANT PRODUCTION PHYTOPLANKTON PRODUCTION w r
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218 inner discharge bay. To test the effect of a reduction in turbidity in the discharge water, the model was simu lated with . light available for use in photosynthesis (J 1 ) increased from 50 percent to 70 percent. Two seasonal temperature ranges were used to bracket the temperature increase expected from operation of unit three. Simulation results with seasonal temperatures of 15-33C are given in Figure 60, while those for a range l8-36C are given in Figure 61. For both temperature conditions (Figures 60 and 61), total gross photosynthesis increased considerably over the previous runs with the same temperature but less light (Figures 57 and 58), resulting entirely from increased benthic plant photosynthesis. Benthic plant photosynthesis also appeared to be resp on ding more to the seasonal light pattern than previously, with an upturn and peak earlier in the year. The same pattern was reflected in benthic plant biomass with a larger standing crop at all times of the year and peak biomass occurring somewhat earlier; Phytoplankton biomass was unchanged. Large storages of organic matter in the sediments and biomass of fish and invertebrates could also be supported by the larger rate of primary produc tion: Many of the same trends were noted between the two simulations at the higher light but different temperature levels (Figures 60 and 61) as between the previous runs at lower light but different temperatures (Figures 57 and 58).
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Figure 60. Response of seasonal simulation model of the inner bay (Figure 55) to decreased turbidity and a seasonal temperature range as originally scaled. The flow of sunlight utilized in photosynthesis was increased to 70 %.
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220 8000 40 J-> z ~ w Q "O 0: ~"':::::, 6-!: 4000 20 0: Cl) 0 w Z 0 0.. -~ INSOLATION w I0 (/) 0 Iz z 1.0 o PHOSPHORUS(a) 0 0 0 INVERTEBRATES "' 5 E '0, 0 TOTAL RESPIRATION TOTAL GROSS PRODUCTION 6 BENTHIC PLANT PRODUCTION PHYTOPLANKTON PRODUCTION >, 0 "O "' E 'Ol
PAGE 241
Figure 61. Response of seasonal simulation model of inner bay (Figure 55) to decreased turbidity and a seasonal temperature range of 18 C 36C. The flow of sunlight utilized in photosynthe sis was increased to 70 % .
PAGE 242
C\I 222 aooo.----""T"""""-------.----~---.-----.40 z >, 0C -"C I. 20 c::: w a.. w I0'---J._____ __. ______ _,_ ____ 0 (/) Iz :r: a.. WATER ORGANIC MATTER ( c) ( c J-------------------~5 Cl .!: 0 . 05 Cl PHOSPHORUS(a) 0 0 0 (BENTHIC INVERTEBRATES RESIDENT FISH (\J E ' en 0 'TOTAL RESPIRATION BENTHIC TOTAL GROSS PRODUCTION PHYTOPLANKTON PRODUCTION PLANT 6 PRODUCTION >, C -0 4 (\I E ' en 2
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DISCUSSION Presented in this section are summary data of the ecosystems at Crystal River, comparisons with other estuaries, and discussion of temperature, turbidity, and ecosystem responses as observed and simulated. Seasonal Patterns of the Ecosystems at Crystal River A dominant feature of temperate ecosystems is the seasonal variation of many of the external energy sources such as sunlight and air temperature. In estuaries many of the behavioral patterns of the cre a tures and the processes of metabolism are coupled to the pulsing of the environmental variables. Seasonal Patterns of Metabolism The re m arkably con s tant seasonal pattern of met a b o lism found for the inner ba y was very unusual, wh i le that observ e d at the Fort Island and Hodges Island ar e as away fro m the power plant was typical of patterns found in other Gul f coast estuarie s in Te xas (Odum, 1967) 223
PAGE 244
224 and Louisiana (Day tl tl-, 1973). Further north; shallow estuarjne systems had similar summer values but lower winter values (Nixon and Oviatt, 1973; Cory, 1974). Summer metabolism measurements made during this study are compared in Table 9 with measurements taken else where in Florida, at other Gulf Coast locations, and more temperate estuaries of the United States. In 2 general, summer metabolism values of 3-12 g o 2 /m day in the areas at Crystal River unaffected by the power plant plume were similar to those measured in other coastal areas. The generally higher turbidities in the discharge area may have been responsible for the lower levels of metabolism there during the warmer months. That the inner bay was actually capable of high rates of photosynthesis when conditions were right could be seen from the rapid oxygen production when shallower water of a low tide occurred during the midto late afternoon. Other shallow estuaries in which tlwrightii was prominent or dominant had summer productivities similar to or higher than the the control areas of this study (Hellier, 1962; Odum, 1967). The failure of productivity to drop in the winter in the inner bay as it did in the areas away from the plant may indicate a stimulatory effect of the warmer water temperatures. Respiratory processes may have been
PAGE 245
Table 9. Comparison of gross primary production and total respiration measured at Crystal River with some values from other areas in Florida and similar systems elsewhere. Location System Type Inner Bay, Crystal Marine mea dov ; s River, Fla. with consumer reefs Inner bay control M arine meadows areas, Crystal with consumer River, Fla. reefs Outer bay areas, Marine meadows, Crystal River, consumer reefs, Fl a. plankton important Apalachicola Bay> Mid salinity Fla. plankton Apalachicola Bay, Oligohaline Fla. areas Apalachicola Bay, High salinity grass Fla. flats Summer metabolism Gross Production 3-4a 3-9a 4-lOa 3-12a 3-Sa 7-12a Total Respiration 3-4b 3-12b 4-8b 3-lOb 2-lOb 6-lOb Reference This study This study McKel la r, 1975 Boynton, 1975 Boynton, 1975 Boynton, 1975 N N U'1
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Table 9 continued Summer Metabolism Gross Total Location System Type Production Respiration Reference Whitefish Bay, Bottom dominated; 7C Tabb et al. , Fla . Plankton unimportant gC 1962Coot Bay, Fla. Turbid plankton 7C 14c Tabb~ .tl_., 1962 Long Key, Fla. Grass bed 34C Odum, 1957 N Redfish Bay, N m Port Laguna, 5-26c 5-33c Tex . Marine meadows Odum, 1967 Copano, Lavaca, Bays \\Ii th l-14C 2-22c N ueces Bays, Tex. consumer reefs Odum, 1967 Upper Laguna Madre, Hypersaline thin 8-25c 4-22c Tex. grass Odum, 1967 Corpus Christi, Mid salinity 6-27c ll-27c Arkansas Bays, Tex. plankton Odum, 1967
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Table 9 continued Summer Metabolism Gross Total Location System Type Production Resp i ration Airplane Lake, La. 4_7C 3-4c Bisse l Cove, 4-7C R. I. Mid salinity 4-lOc aDaytime net production plus night respiration. bNight respiration doubled. cAs defined by Odum and Hoskins (1958). Reference Day et _tl. , 1973 Nixon and Oviatt, 1973 N N . ......,
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228 affected more than photosynthesis because of limited light. In the seasonal simulation model total respira tion in the winter was stimulated more than photosynthesis by a 3C increase in temperature. A P/R ratio less than one in the inner bay when it was greater than one at Fort Island may support this idea. No combination of reasonable coefficient adjust. ments of the seasonal simulation model produced a pattern of increased winter metabolism as observed for the inner bay. Although the magnitude of metabolism was incorrect, model behavior suggested that phytoplankton may have been dominant in the winter. No light and dark bottle data are available to test this idea, but if winter plankton metabolism were of the order of that in the spring, total metabolis m similar to summer values would result. Net Production and the "Spring Dinner" The seasonal patterns of several parameters at Crystal River provided evidence for a spring pulse of productivity in the phytoplankton. Chlorophyll-~ and phytoplankton biomass increased in April and May with some increase in ammonia. Net community production in the control areas and phytoplankton production as measured by the light and dark bottle experi~ents was much larger in the spring. McK e llar (1975) also found much higher p h y toplankton productivity in the spring (one measurement)
PAGE 249
229 in the outer discharge and control bay areas. Saville (1966) found highest phytoplankton production as measured by the uptake of carbon-14 in May and June in the Waccasassa estuary, a coastal area 20 kilometers to the north, which is very similar to the Crystal River region. Net accumulation of organic matter in a population such as phytoplankton with rapid turnover may be possible during periods such as the spring, when insolation is increasing rapidly and nutrient storages are larger, but the increase in water temperature is lagging behind. Under these conditions, processes of organic primary production stimulated by light and nutrients may outstrip respiratory processes degrading organic structure, result ing in a net accumulation of biomass. A simulation of a producer module was run to test this idea (Figures 62 and 63). When temperature and light were varied out of phase the model exhibited properties of springtime accumulation similar to that observed in north-temperate oceans (Raymont, 1963) . Simulation of the seasonal model with phytoplankton embedded within the whole system produced similar results. In shallow coastal waters such as the Crystal River area water temperature does not lag light as much as in the open sea, allowing producer respiration to track photo synthesis more closely, so that the response observed was not as large.
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Figure 62. Energy diagram and analog computer patching diagram of simulation model of producer module with temperature affecting both photosynthetic and respiratory pathways. ( a ) ( b) Energy diagram. Flows are in g/m2.day of organic matter, energy, or material. Storages are in g/m2 of organic matter or material. Analog computer patching diagram. Equations following from the energy diagram were Pot settings were Pot setting Pot setting kl 0.240 k5 0.023 k2 0.165 k6 0.035 k3 0.244 ICQ 1 0.333 k4 0.318 ICQ 2 0.500
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(a) 231 0.024 1------x X 5500 kca1/m2.day)i ( b) +REF---t 2.9 \ ' ' ' I I I , -----,"" FROM SINE WAVE GENERATOR FOR LIGHT FROM SINE WAVE GENERATOR FOR TEMPERATURE ...__ __________ , _____ -------------
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Figure 63. Simulation results of model of producer module in Figure 62 with seasonally varying light and temperature. Note scale difference for pri mary production and respiration.
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i 4000 ....... 8 2000 (\J E ....... OI >, 0 "O (a} 0 . 03 0.02 0.01 0 233 u 20 ( b} 50 0 (b) I. 5 >, 0 "O 1.0.
PAGE 254
234 This seasonal pulse of net production may serve as a "spring dinner" for juveniles and young-of-the-year of many species, which have adapted to take advantage of it by linking their periods of migration, reproduction, or rapid growth to the time of net accumulation. Odum (1967) summarized several years of work by many investi gators on the community metabolism and animal stocks of two Texas bay systems , documenting seasonal trends in productivity, respiration, and movements of animals. Seasonal migrations into the estuaries in the late winter and spring when productivity was rising rapidly was a dominant feature of these systems. Some data suggest that stocks at Crystal River were responding to the spring bloom of phytoplankton since the P/R ratio for the system was near one. Maturo (1974) found rapidly rising biomass and numbers of zooplankton in the spring in the inshore regions around the power plant, while fish larvae were most numerous and decapod larvae were increasing rapidly in number. The calculated production rate for zooplankton was also largest in the spring, while biomass and predation rates of zoo plankton predators were still low. Resident fish biomass increased in the warmer months from winter lows (Figure 27), and oyster spat set increased markedly in June (Lehman, 1974a,b).
PAGE 255
235 Seasonal Migrations and System Stability Systems with prominent seasonal pulses, such as temperate estuaries, may be exploited by populations which move in during the period of olenty, experiencing rapid exponential growth, and then move away. A system of this kind may be stable even though it has no controls on growth internal to its populations. To test this theory, the seasonal model was modi fied to add the feature of offshore migration of fish in the fall months and onshore migration of larvae and juveniles in the spring. The square term drain of respiration representing internal controls on population size was removed. With the migration pathways turned off, the fish storage was unstable, dying off in several years . . With some migration the stock could maintain itself in an oscillating yearly pattern (Figure 64), suggesting that the estuary may have established a stable pattern through exchange with the open sea. Seasonal Substitution of Species Seasonal patterns in the benthic primary pro ducers similar to ones observed in other estuaries seem to be important at Crystal River. In the south intake area the prominence of red and brown algae in the winter and spring with greens assuming more importance in the
PAGE 256
Figure 64. Simulation response of seasonal model of the inner discharge bay to the addition of path ways of exchange of fish and fish larvae with offshore waters. See text for details of changes made in original model for this simu lation.
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(\J z 0 -0 ......... IC\I , a "O 4 C\I E ......... CJ') 2 FISH r BENTHIC INVERTEBRATES YEARS
PAGE 258
238 summer may be a response to changing insolation and temperatures. Species of the family Ectocarpaceae (a brown algae) were dominant in the inner bay during the winter of 1972-1973, almost completely covering the areas of tl wrightii (Van Tyne, 1973). Its failure to return the following year was possibly attributable to the excep tionally mild weather that winter. This family was also reported as an important winter species for some systems in Texas (Conover, 1964), Louisiana (Day~ tl-, 1973), and North Carolina (Dillon , 1971). Changing the relative dominance of species or substituting entire new ones may be a more effective way of utilizing a varying energy regime. Maintaining genetic adaptations within one or several organisms so that it may function efficiently over the entire range of condi tions prevalent may be energetically more expensive than having several more specialized organisms each adapted to conditions existing only part of the time. Species substitutions may be the most effective way to make maximum use of available energies at all times of the year as expected from the Lotka power principle. The existence of a pool of species adapted to various environmental conditions could have been impor tant at Crystal River in facilitating adaptation of com pone n ts of the ecosystem to the added stress of tempera ture. By eliminating some species and replacing them with
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239 others, an ecosystem optimally adapted to the new condi tions may be maintained. Seasonal variation of species dominance may be a mechanism for maximizing photosynthesis under all condi tions. In a simulation model with all photosynthetic species lumped into one or two compartments, a changing photosynthetic efficiency would require a time-varying coefficient. A rough attempt at simulating this feature was made by using switches and comparators to switch from the original scaled coefficient to a larger one during the winter months. Simulation results are given in Figure 65. Increasing the coefficient in winter increased total photosynthesis during that period, although the action was sharp and abrupt because of the method of sim ulation. If the coefficient adjustment had been smooth and gradual with time the simulation result for total photosynthesis may have been along the dotted pathway, which would have given a larger winter value than pre vious simulations, but still not as large as the measured value. Comparisons of the Ecosystems at Crystal River and Adaptation to the Thermal Discharae After construction of the power plant at Crystal River the inner bay became an interface system between the energy flows of the economic systems of man and the
PAGE 260
Figure 65. Simulation results of seasonal model of inner bay as modified in Figure 64 with larger photosynthetic coefficient added in winter. Dotted line in total photosynthesis graph is estimate of curve if coefficient adjustment was gradual rather than abrupt as in the simulation.
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C\J E ' z >, 0 0 241 SOOOr---~-------r-------~----.40 /TEMPERATURE (_) 0 . ..
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242 4.------.-----------------BENTHIC PLANT PRODUCTION 2 O'----~------_,,__ ______ ..J._ __ -J 2 PHYTOPLANKTON PRODUCTION 4 TOTAL PHOTOSYNTHESIS >, 0 -0 ' C\J 2 CJl 0 6 TOTAL RESPIRATION 4 2 0 ._ ___ _._ _________ _,,__ ______ __ ......, YEARS Figure 65 continued
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243 estuarine patterns and processes of nature. Previously, the inner bay had been adapted to its own set of energy constraints, but with plant operation a new set of energy forces derived from both sistems was at work, requiring the malleable and adaptable ecosystem components to be regrouped and adjusted into a new combination, which once again maximized the power flow according to the new energy regime. Temperature and Primary Production at Crystal River One of the issues considered of major importance by many regulatory agencies grappling with the problem of power plant discharges has been the effect of temper ature on primary production. Will higher temperatures stimulate chemical pathways so that primary production increases, or will the producer organisms be stressed by the heat, lowering their photosynthetic ability? Evidence from the models and studies by others suggest that higher temperature alone was not the primary cause of the lower levels of metabolism found for the inner bay at Crystal River. The push-pull model of temperature action as used in this dissertation predicts that production will either increase or remain the same depending on input energies. If they are not limiting, temperature should stimulate production. Kelley (1971), studying freshwater
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244 microcosms started with a rich nutrient medium, observed highest rates of primary production in the ones with the higher mean temperature. However, if input energies are limiting the same rate should be maintained because in creased respiration would lower the standing stock of biomass to a steady-state level capable of being supported by the original rate. Primary production could only be decreased in this model if input energies were also re duced. In the seasonal model, raising the temperature inc~eased primary production and total respiration, indi cating heat was an energy subsidy to the system. Large flushing rates and increased respiratory cycling may have allowed the phosphorus storage to be maintained at its original level so as to support the increased uptake demand. Other studies indicate that temperature by itself may not be a stress on ecosystem productivity. Redfish Bay, Texas, a shallow seagrass system with naturally occur ring summertime temperatures similar to those measured on the inner discharge bay (Hellier, 1962) had a seasonal range and pattern of metabolism ~uch like the control areas at Crystal River (Odum, 1967). Duke (1967) found production values similar to su1nmer values at Fort Island in a thermal hot spring with an average temperature of 56C. Brock (1970), reviewing the work of others, reported
PAGE 265
245 values from other hot springs similar to and higher than those of Duke. As seen in the diurnal curves, the inner discharge bay at Crystal River was capable of high rates of photosynthesis when conditions were right. Turbidity and Production at Crystal River Turbidity contributed by the discharge plume from the power plant may have been primarily responsible for the reduced primary production during the warmer months in the inner discharge bay--a fact which became increas ingly important in discussions of the interagency review committee concerned with licensing of Crystal River Unit Three. Support for this conclusion comes from the models and some field data. Odum (1963) found reduced community metabolism under turbid conditions from dredging in Redfish Bay, Texas, a shallow system dominated by Thallassia and H. wrightii. Zieman (1970) noted high turbidities associ ated with the discharge area for generating units locate d at Turkey Point on Biscayne Bay, Florida. As mentioned previously, reducing input energies, in this case sunlight reaching the benthic producers, is the only way primary production can be reduced in the push-pull model of temperature action. In the simulatio n of the seasonal model, gross production increased
PAGE 266
246 considerably when turbidity was reduced, and was much more sensitive to changes in this parameter than to the temperature changes expected with the operation of unit three. Diversity and Biomass at Crystal River The generally lower diversity of many components and the lower toial biomass of larger consumers in the inner bay may be adaptations to the combination of high summertime water temperatures eliminating some intolerant species and reduced rates of primary production being unable to support levels of biomass characteristic of adjacent areas without thermal loading. That li• wrightii is adapted to naturally occurring higher temperatures or conditions of stress may account for the overwhelming dominance of this benthic plant in the inner discharge bay. Phillips (1960) reported li wrightii to be found in Florida most frequently on the shallower bottoms adjacent to shore where water temperatures reach higher dayti~e levels in the summer . . Zieman (1970) found the seagrasses such as Thalassia and tlwrightii were tolerant of higher temperatures in the di sc harge area of the Turkey Point power plants on Biscayne Bay, Florida than were the attached macroalgae. In Texas tlwrightii was found adjacent to shore in Redfish Bay and as the dominant
PAGE 267
247 benthic plant in the shallow hypersaline Upper Laguna Madre estuary. This species may be only a minor component of a more mixed system because the energetic costs of maintaining genetic adaptations necessary to survive under occasionally harsher conditions reduces its competi tive ability. Temperature and turbidity conditions of the inner discharge bay, however, may eliminate compe tition from other species allowing tiwrightii to become dominant. The reduction in total biomass of larger consumers may be a consequence of the lower rate of primary produc tion; the inner bay with about one-half the rate of gross primary production of the south intake area had about one-half the standing stock of higher trophic levels. The relatively small temperature increase (3C average) found in this study together with the likelihocid of meta bolic acclimation responses reducing its effect suggest that temperature was less important in reducing consumer biomass levels. Reduction in diversity of consumers may have resulted from several factors. The smaller energy flow in the inner bay may not have provided enough support for the maintenance of the more specialized organisms of more diverse communities, while the problems of adapt ing to higher and often abruptly changing temperatures depending on the location of the thermal plume may have
PAGE 268
248 eliminated many species. Kelly (1971) found lower species diversity in freshwater microcosms subjected to fluctuat ing temperatures than in those experiencing constant high or low temperatures. The Inner Bay as an Ecosystem Adapted to the Thermal Plume The widely held belief that systems receiving thermal discharges are stressed may be true only for several years after the onset of power plant operation. Adjustments in the structure and function of an ecosystem as obs~rved in the inner bay may allow for the relief of the stresses imposed by the thermal plume through selection of a combination adapted to the new conditions. Allen and Brock (1968), using microcosms seeded from a wide variety of sources and kept at temperatures from 2C to 75C, found each one to develop and maintain its own characteristic combination of organisms despite extensive cross-mixing of systems. Brock (1970) stated that opti mum temperatures of many hot spring organisms as deter mined in laboratory experiments was near that of the environment from which they were collected, indicating that these systen1s were adapted communities, not stressed ones. Behavior of the seasonal model also suggested tf1at the inner bay system was quite different from the
PAGE 269
249 unaffected areas. Model responses similar to patterns measured in the control areas could not be obtained by adjusting only temperature, sunlight, and initial biomass storages to conditions found in the control areas, sug gesting that pathway coefficients and, thus, the basic nature of the two systems were different. Because of the period of adjustment and reorgani zation within the ecosystem which may occur in response to thermal alteration, any assessment . of environmental impact during the period of transition may provide a false picture of the long-term consequences of a thermal addition. A truer assessment of impact would be the structure and function of the ecosystem resulting only after adaptation to the new environmental conditions has taken place. Temperature and Selection for Faster Turnover A major adaptation of the inner discharge bay to increased temperatures may have been a shift of meta bolic activity away from the benthic compartments towards the phytoplankton component in the water column. McKellar (1975) found a similar trend for the deeper outer bay areas, and discussed how the push-pull effect of tempera. ture action on system pathways might lead to selection for smaller bio1nass with rapid turnover in order to main tain the same rate of energy flow within the system.
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250 In the inner discharge bay, benthic producer biomass and primary production were lower than in the unaffected areas, while the much-reduced respiration of the bottom muds suggested possible selection for a much lower biomass. The very low biomass of benthic invertebrates in the inner bay accounted for virtually all the difference in the total biomass of larger consumers between the two areas. Plankton primary production, on the other hand, was much larger in terms of both percentage of total community production and actual magnitude in the inner discharge bay than in the unaffected intake area. Similar standing stocks of phytoplankton, resident fish, and oyster reef biomass between the two areas may have indicated that the increased phytoplankton primary production was available for consumption by higher trophic levels. For producer organisms such as phytoplankton, which generally produce more organic material in photo synthesis than is required to satisfy their individual respiratory demands, the push-pull temperature model would predict an increase in standing stock with in creases in the rate of photosynthesis if no compensatory increase in grazing also took place. This occurred for benthic plants in the seasonal simulation, which were not grazed directly in that model. Phytoplankton biomass remained the same, while its productivity increased slightly, indicating that the increased biomass produced was being r em oved through grazing and flushing.
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251 For all organisms the model predicts lower stand ing stock levels with temperature increases unless input energy sources are nonlimiting. That increased primary production was supplying higher trophic levels in the seasonal simulation was indicated by the increased fish biomass and lack of decline in the invertebrate stocks from the increased predation. Organic matter in the sediments declined, while that in the water remained the same suggesting that they were helping supply the increased ingestion demand of these consumer populations. McKellar (1975) found a similar response in a computer simulation model of the outer bay system at Crystal River. In the inner discharge bay, phytoplankton may have been able to capture more sunlight to support the increased photosynthesis stimulated by higher temperatures. This additional production may have been grazed back by consumers, keeping phytoplankton standing stock at its former level and allowing the increased consumer respira tory demands to be matched by ingestion so as to maintain their previous standing stock levels. Shifting of rela tive reef composition to a larger total oyster biomass but smaller quantities of other reef organisms may further indicate the emphasis on a grazing food chain. A shift to a detritus diet in middle juvenile stages of pinfish (Lagod~n rhomboides_) in the inner discharge bay
PAGE 272
from an epiphyte diet in the south intake areas (Adams, 1972) suggested a different food web within the fishes also. Predictions of the Effect of the Operation of Unit Three at Crystal River The response of the simulation models to condi tions expected for the operation of Unit Three at Crystal River may be used as possible predictors of the effect of this plant when it comes on line. Because validation of some aspects of the seasonal model was not good, in ferences drawn from its responses must be used with caution. Nevertheless, results of these simulation models may still be better vehicles for predicting future impact than the mental models often used by decision makers. Both simulation models were relatively insensi tive to the small increase in temperature expected from the operation of Unit Three. In fact, if a temperature rise was the only expected effect the models predicted that metabolism would be stimulated somewhat. However, the d a ta suggested and behavior of the seasonal simulation supported the idea that turbidity may have been the major factor controlling productivity in the inner bay. If this is true, the effect of Unit Three could be large. Since the water velocity in the discharge was expected
PAGE 273
253 to double, the sediment load of the plume water could increase because of increased scouring. Couple~ with an increase in the mixing ratio of canal water to off shore water contributed to the inner bay on a rising tide, average turbidities as well as temperature could increase. In the simulation run using these conditions, the stimulation of metabolism by increased temperature was more than offset by the reduction of photosynthesis from increased turbidity. Energy Costs of Alternatives to Estuarine Cooling of the Thermal Discharge at Crystal River Regulatory agencies concerned with licensing of Unit Three at Crystal River have suggested closed-cycle cooling towers as one means of alleviating the reduction in energy flows in the estuarine environment resulting from the use of once-through cooling. The dollar cost of technological alternatives, however, represents an energy expenditure and effect on the environment which must be accounted for somewhere else in the economy. On this basis any man-made substitute for the use of the natural environment for cooling must pass the test of returning more energetic benefits than the energy costs incurred in its construction and alteration and displacement of natural ecosystems.
PAGE 274
254 Such an energy evaluation may be calculated by examining the total energy costs associated with the alter natives at Crystal River of cooling towers or a once-through cooling system. By using energy instead of money, the con tributions and costs to natural systems with which no direct money payments are associated are included in the calculation. In man's economy the magnitude of the money flows circulating in the opposite direction as energy may be an index of the quantity of energy flowing (Odum, 1971). In natural systems energy flows may often be measured directly in energy units. After conversion of all the different types of ener~y to the same concentration or quality level (often fossil fuel equivalents are chosen), all flows may be added together and the total energy involvement calculated for both cooling alternatives. The difference between the yearly total gross primary production of the control areas and the inner bay (difference in the area under the curves in Figure 36) may be taken as one of the energy costs of once-through cooling at Crystal River. After converting to a common denominator of fossil fuel equivalents (FFE) using factors from Odum tl .tl_. (1974), the energy cost to the region is calculated as 0. 17 x 10 9 FFE kcal/yr. Converting the money cost of construction and maintenance of mechanical draft cooling towers to its energy equivalent gives an energy cost
PAGE 275
255 9 of 276 x 10 FFE kcal/yr (Kemp et .tl_., 1975). much larger than the energy cost of once-through cooling. Expanding the calculation for the once-through option to include all other environmental impacts, such as loss of larvae and juveniles of many species and impingement losses of fish at the cooling water intake, still found cooling towers to be much more energy expensive. As fossil fuels became scarcer, the system that uses these fuels for jobs which can be done at a cheaper energy cost by the natural environment may not remain economically competitive with systems that utilize the free services of nature in concert with their ~conomy. At Crystal River. the construction of cooling towers would appear to be energetical ly wasteful.
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APPENDICES
PAGE 277
APPENDIX A EXPLANATION OF THE ENERGY SYMBOLS USED IN THIS STUDY
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258 Given below are brief explanations of the symbols of the energy circuit language used in the model diagrams in this dissertation. More complete discussions of these and other symbols may be found in H. T. Odum (1971, 1972, 1973). N Q kQ Energy Source Module. A source of energy or material external to the boundaries of the system of inter est. The driving force may be con stant or time varying and is inde pendent of behavior of the system within the boundary. Storage Module. Storage of energy or material within a system. The quantity in storage fluctuates with time as a function of the inflows and outflows (dQ/dt = J1 J2), where depreciation losses are in cluded in the outflow pathway. Self-Maintaining Consumer Module. An aggregated module representing a consumer unit. Included inside are at least one storage module and one . work gate interacting to do work on input energy to that unit, providing a logistic response. When used only as a visual symbol for organizing model components no path ways are implied beyond those ac tually shown.
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1 I .. 259 Production and Regeneration Module. An aggregated module representing the combination of the capture of pure energy such as light feeding a self-maintaining module, and a work feedback loop controlling inflow processes. Usually used to depict green plants. When used as a visual s~nbol only, it may repre sent the production and consumption of entire ecosystems. Heat Sink . . Energy conversion to heat with each work process. Pathway of Energy Exchange. Flow of energy or materials. Barb indi cates a one-way flow; no barb indi cates back forces acting along the pathway. Heat sink represents frictional and back force losses. Adding Junction. Adding of two flows, where J3 = J1 + J2. Work Gate. An interaction in which the resultant flow is some specific function of the interacting forces. Often the function is considered multiplicati~e. giving J = kN1N2. N1 and N2 may be external driving forces, internal storages, or forces caused by flows.
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J J 260 Two Way Work Gate. Flow along path way driven by N 2 may be in either direction depending on conditions determined by N1, N2, and N3: J = kN2(N1 N3). N1 and N3 may be sources or sinks external to the system . or storages within the system. N2 may be a flow, internal storage or external source. Force Uelivered from a Flow. An interaction in which a flow of energy along one pathway (J1) de livers a force for driving an energy fl ow a 1 ong a second pathway (J2)The delivered force is pro portional to the flow from which it is derived (J 1 ). J2 = kNJ1 An example is transport of sus pended material by a water flow. Draq Action Work Gate. Special type of work gate in which an in crease in one flow, internal stor age, or external source (N 1 ) has a retarding effect on the output flow (J) of another source or stor age (N2). Sensor symbol indicates that there is no appreciable loss from N1 in this interaction.
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X N 261 Flow-Limited Interaction. An inter action in which the resultant flow (J 2 ) is a function of a constant flow (J 0 ). J2 may be limited by J 0 because as X increases, J2 may . increase only to the point at which all of J 0 is being utilized. Since J 0 is an independently fixed quantity of flow, J 2 cannot draw more energy from the source (SJ than is flowing per unit of time. Logic Switch. Flow J is turned on or off by logic processes within S, controlled by processes of N.
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APPENDIX B GRAPHICAL ANALYSES OF DIURNAL STUDIES OF COMMUNITY METABOLISM IN THE INNER BAY AFFECTED BY THE THERMAL DISCHARGE PLUME AND IN THE FORT ISLAND AND HODGES ISLAND AREAS AWAY FROM THE INFLUENCE OF THE THERMAL DISCHARGE. DOTTED RATE-OF-CHANGE CURVE IS PLOT OF RAW CURVE OF OXYGEN PER SQUARE METER. RATE-OF-CHANGE CURVE WITH OPEN CIRCLES IS CORRECTED FOR TIDAL CHANGES. REMAINING RATE-OF-CHANG E CURVE IS ALSO CORRECTED FOR OXYGEN DIFFUSION.
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::3o I 2.DO I I L .. I I I l :.: . 'L-.l 01ooo ' I I l . .. I \ . I !_ I 1 . : t -~~ \ ~ I . . . I . . I . .. , .. -l : I ' . I . . I I . / . . ' ' ' ' , . ' ,,...J 1800 -t 1.0 ~o.s a..o -C>,S" 6 . c, -o.s i 0 I" t T ... 0 rv t .J 1
PAGE 284
o,J r.:: LiJ I264 10 Inner Discharge Bay 21-22 June 1972 .___ . ~--. i --~ : :__, , . j.:.. :. , ; ; __ _ __ _ t. . :.. . ! . . ': .. ... ~ . : . : ~ ; ~;-.: _ _ _ _ _ 3'f : -.+ , _ ,_..:: _ . -__ j _ _ _ 32 I o0 -..,-c,L _ __:__1. ___ _.1._ ___ ..__ __ __, l200 I \ .. ... . . I . \ . . . -~-r . 1 . . t t ;E -f j \ : . : . t: : . -__ . _ _ __ _ .1_ ___ ~ If . ~--l / : J _ , __ . .. . L-1 t I ' I , . .. I t I ' , ' , I T + I I I I 1,._J 'o.si 0 C,,6 p .......___ ::> -f-/ , () ~o.,;'i rP 0.() 3"' . -a.s
PAGE 285
r'l E --d-.1 -r: $f (). i 0 So Inner 2 9-30 Discharge June 1972 :: . . . -~. . .. . . . . ... . 265 Bay -.. :_ . . ----L ~-: : _ : ~ ~f t-' _ r . . , -:.Ja....o -------~ ----. r ::r . ...,
PAGE 286
266 Inner Discharge Bay 7-8 July 1972 :r 2. !;:: <'. ) 4r-, . . ---. . . ~. ; . . . . -: . . .. .. . . . . . . IO _ _ L __ '--.. --: ~ -',.:.. .. + . . :_: .. : . . . !: ~. L~ .. ; . ~ :: ;E;:• 7~3j~ --. . i : : . 1 . -. . -:----,~ -~ ---.:..-.:.._ ~-;'" _ __ _ ; :. 3 '-1. ' . : ~ .: -: ; j:'. ~_[~ .i I I::: -z:. J <( \/l J,4 . . 1.,_;_ ~-tJ--7"~ . . . ! I I ; ., 1• 1 8 ~~ . . .. . --_ t-~! -+ :. -, -. _ _ -------O(c<'.t) n .. o o +l. 0 o.c -o.s i :... . _~ ; ----: : -t-----'----..L--_;___,_ ___ ...: . . ---:. . . ~ ~~ .l -~ . : . '.--: : 1 -\ ~~-~ . . . I ll .. '. ; _ . ;. : .... . I I . . ,. . .. . . . I . , , . , . : . . .. \ . 0 ----o.o 'l--------.. . J t_;, . . : : : r . :.. : . . . ! r . ; . . -1.0 -----..: 1,., -;I' '\
PAGE 287
267 Inner Discharge Bay 2-3 August 1972 0 -..-t--+-t-i -----~~---__J :r' k:~2 . o zl5 /,o . IS /C) s . . : . -. : ---~-.:.. . . ..; ---.: -~ -. . ... . . . .. . ---.; -=-~-+ . : . . -. -:--~ ~ ___ '..._ _ _ . . .. . . . . --~ . : . -. ; : . . . . : : ; . --_ _ : _ .. . : ~ ~= ~:-:~~~ ~~~~-:~:~ ~-~ : _ _ __ _ . . -:: : . -. . \ .. .. .. ..: . .. :.:.~ ~~ ~-: _:_ _ _: __ _ __ _ _ _ _:_ _ _ ::_ . : __::_ ---. . --: . : _ : .:. ; . .\ : .. ; . '. . -:. . .. :t 3<; . ~ : ! ;; .. -:~~ : ~~~-:~---. _ __ _ r---'---:-:-'--....:.....--L.. __ -J __ . ~ .., -o.o Zb i; Z'fZfi . . -. . _ ._ ..; :. ~ -'~ : :.. . . --.. -:: _ ; . ~ : sn: rnr_?; ? i : \ tj : : : :f T\.Q ' . . . ; . -:. -22 .1 4. flZo V) I.S-6 10 ~( Ill~ i~ 100 /1-~ So . , . . \. ---:;~ -~_; __ __ L __ ; _ __ _ _ ____ ._ -~ _ _ _ _ _ _ ;__ 1 . -~~----------~o~-~~---• -~ ~~J ~ 1=_ _ -_ --~-_:_~ --;L = -'fZ _ : ~: :\2:~L \:)\ ~. ~7 , 0.0 •~~: .. I . . ___ ._ __ _jL_ __ i__ _ __,.i: 1.0 1 2.oo /8 00 12. 00
PAGE 288
IO ,,,f "' 0 s C ff ~o Ill l.o ,Q b.o Inner Discharge Bay 14-15 Dec e mber 1972 -------. ' . . . -.. -----~ -268 ; -~ : -... , •o.si o , o rP -31,-i ;r -'..:: '. .. _ :: 1-'..---...._ ___ -'-___ .l._.._--,-,,SIS .. ' ,J IO -_:__-_::. : ~ : . >. : '::~ :::: '.-. o ~~ -~ L~ ~ ~-~~ ?\ 5" ~/.. --~ :_. _ : ~ -: . ,.:~~-=__ _ .. .. :.. . . .. :~ :-: -. . __ _ _ __ ;.. ....,.:_ . -----. . : . --'....-._ . 2.8 ~-----~ 2 ,., I . . . . . : . :: . _ , __ ,. . . ' .. . . ..:. ...: . ..:: . . a .:..:.~ . r :---~, 2-'f _ _ J... _ ____ __ _ __ _ _ ___ _ ___ -_ _ _ f -.. : ; . .. : ~ -~ --~_ . ~ -~ _ _ :_ . -1. ... , .. . . . : ; ; : . _ : : . . . . -. . : ... .: . . --: . _ : . : ; . : :.: . :.. .. .. I I __ ;__ . _ . _ _ _'. '' 'j . : ' J : j "' •. I ! ~ j : . . ::; :~ :~ ; ~. I . ' ' . _ ; 21... . . . . . . . ' ' . . J._ ___ ...1.. ___ _,__~___,__;..._ __ ____ -. . . . D "'r\.o 1 0 ['l ---0,() E rJ r '
PAGE 289
rJ ' F ---o"J t 269 I(; Inner Discharge Bay 22-23 January 1973 --------. , . . l . . ---~----.--: IS , , . ' -. -----j :: : _ : = . . . . . . < : . . j_ :. .i _ __ ~~ -~-::~ :.:~~ ---_ _ . : . . -: ... 0 ~ ~ ~ . .. : . .. ~ -: ~ r= r, ___ , ; ~-~~ ~'f I _; . -----------!-~-~i -r. , . _ __ ;..,,. o.o +z.o :,_ ;_ , L i. Tt :__:c_,~ ~-:n " 1 ' .L...-, . . ,. -1 . . . , . . ~ ~ .-1._h ~ _: 0,C> . ' ; .. . \ , ~: ' . \ I . . 1 -::-f< . r-\ I '\ . \ I . \._j . . . \ .. T\ . t . I 1 -1.0 I .. \ . . I ~-4 s,--.L.~ __ ...__..:.....__,_ ___ _._ ___ L_ __ _j_ ___ _,_ ___ ..._ __ ....... -2 . 0 1200 l~ l2..oo \Boo
PAGE 290
270 Inner Di s char ge Bay 31 January and 1 February 1973 s ---:1 ; --. . .o --: I . c, 0 r,, -;r -,
PAGE 291
rl f rJ 0 So OU z i1J J271 0 2,o ,, , o Crystal River Plant May 10-11, 1973 . L 1 0 t-' 6,o-~---->-------<-----+----,~ ! ; : ! . . O,o 3 r /C, s , :t.. ..... ..J : .. ~~ -: _ _ _ _ : ~ . ~ T l ~ : + ... ' . ' . ' . . .. . i_ _ __ i _ _ . . ~-:. I . : . :. ISol-------,..--~--...-----~ ------:1 ~,..., /o o .ro'------L-----'-------'--\<...00 \eoo . ~ :r : ; =. : _~.-_. ~(_ _ . -, . _-: . . :,... :; .: . -k :: : : . : : ~. i ; ~ _} 1 .l ~ =i ;: . . . : ,.::i:L'.c.l ~l-J_ . :~->i'.J_ l/J.]J; -1,0 -~ i : _i :! ::: ~ --_ r +\; : < : (~_r /ttr :-, . : . . : . . . . . : :::-: . . lc_oo :r: J:J
PAGE 292
272 Crystal River Plant May 11-12, 1973 . +":_. : !. _ _ _L_ . . :i--: :: : . _ . -i . :1 . . : :i :-i . :.r-: . {Tf r ~ :i:: : : l .. ; t _ : ~ ~ t . . ; .: . . ~ : r : 0 >-----, -, .,.. >. . ---. l l _ c,o _ _ ----, ,. .,. c . , -----f If 2.0 ;b \.o ,Q ,s z ,~ 0 ~i J d/D O 1~ so -+ _ !~ -'"--: ~ r;_~'.J I " l =~ .. : . : . _ : ; : .. : ; .. .' ; -: ;-: ; r : : f -~: --~ ...; . . :.. ; : -; . . : ~•;_i~X.~ l ~ ~~. -: . _. --. . .. . : .. : ; . = : : ; .. : . : . \-\.D 1 0 r,J --(),() 1,, :i: fJ -,.o OG,00 1000
PAGE 293
ID i -----01'1) -:r:" 2. ~f I ,-,) 0 5a " 0 r. /ll 'L ,J rt '.) (L Vl . Inner 17-18 D ischarge 73 June 19 273 Bay :_ _ __ _ __ . . ~ ~= -~ __ :_. , . . . . . . . . A =~~'---=-:._-----\----~ : f--"'c;:=2 _ . . . .. . . . \--.:_ _ ' '-.. (J(ooQ 1800 . :~ ~. . . . -. . . -. -/ --_ . . . . ... 0(.,0Q
PAGE 294
Inner Discharge Bay 17-18 June 1973 .. . . 274 r~ oi--.---------------1 1:z.o /.l,( [[JI/,() (J. o.o.,..._ __ _ /0 .s 1 -~ -. . .. . I 0 . ~ . : .. : . _.. . . _ _ +z.o 1800
PAGE 295
I CJ ,.,,E "' 0 a :r2.o tf tJJ I, 0 fl 3~ 0:_j'f z LU oU 3'L }-Jo' 32 too 275 Inner Discharge Bay June 18-19, 1973 i . " .\_, , : .. !, . . : : .. ; _ : . ... . . . : ---: . . : . ... . _ ; JC) }=a ___ _._.,;._ ----'-----'--"------[ , . d C,, :~ . cc: .:_::. ;c , .,._:. , . cs :.:C:. . y, -t-o.s ., ;,, 2.11 K c. F: 1 o.o -o.s . : ,, , _ _ ,, _ __ '------''-------...L.---06oc 1"2..0o )Boo
PAGE 296
0 0 to do 276 Inner Discharge Bay June 19-20 7 1973 ::-. -;-. -: . _; -. :-'. -. . _ : . : _ :-..:... f _:~::-: ~ . :. ; _ . :..; : . .. .. . . : : . : ... . . .. -. . . . . . . .. ___ .. ----i 6 t: :::: l . _ \~ L:7 ) . :-~[,: : . : ; . TJ __ : . ) _ _ \ __ _ . : ,~ ~ ~ I 1,---. . . . .. L :. . . ~ .. : 2.4 .... . , /sol-_: ___ J.____ _..._ ____ _. ____ --1 f. /oo '-------~...,..--=--------... .... .... --: . . . . : . _ . _ . ...52:Jl....~ ~~~ ~ ..J --= ~~=~ ~ '~ = =~=' ,.Jib..~~--:--1 ___ _ ___ _ L_ _ ___ _ _ ___ -l--------''-------Otoo<:> le.Do 1soo
PAGE 297
: ffi t (J /1.~ 2 u w 0 />-" t ,2 0. :J 4'. CL 1/) 0 2..,D /.o 0 ,C, 3 'f 32. 3o 32. 28 d9 277 Inner Discharge Bay June 20-21 1 1973 '' I . _ _ : _ _ _ ; . , : . .. : _ . : ' . --a: -;. _ : i -: : .. . : : -: = _ ; . --~ . : ! " -.. : . . i : : . ; i ,! . ! . . . -! : :: 1 -~ _! __ _ ' .. ~ ) , -i : ~ -; -: ~ . ~ ..... .. . ' . ' . . . /~ c, ~-------'=---'-----'-'------"'------, /oo -10.s _ .., , C,,.. ... : ' ,,.,.. o . a --.... .. . . J _ ______ _ L _ ___ -1, ___ _ orooo \BO O
PAGE 298
278 Inner Discharge Bay June 22-23 1 1973 10~------------------J_i.l.:.-3'f 32. 3o 32. 28 k _ ~ : ~=: ~-'\ _ . . . _ . . _. _ _ _ :: -~ -•-2. y. 0 . . . . . . . . /~-o-----,--~--,,--------------1 /oo I . ' : : : . --;;I ./ h~•I I i ' ~ (.). . . f:: ,, 17 . I _ __ __ _ _ ..i ____ __ __,_ ____ ___.. ____ 0(d:)O I 2-0 D \BOO
PAGE 299
10 (If ,,J s 0 &o A r ffi~ (:) z 00 '? t /Cl-j (l.. 1/) -;c I-9 .z ~/1'. ()[. J: 0 2,0 I.O 0,0 3(:, 31.f32 3o 2.8 2b 2-.y Z.2 I 00 S() -I 0,5 o.o -0,5 i i 279 Inner Discharge Bay July 26-:-27, 1973 " j .t . I .. f . __ _ _ _ _: _ _ r -' . . . i . ' I . i . . . . . . . . t . : I r . : -_ _ _ ___ _ _ _-1. __ _ _ _ _ J __ _ _ _ _ _ __ _ _l,_ _ _____ _ OloOo 1200
PAGE 300
280 Inner Discharge Bay Aug 2-3 1 1973 10 ~ -----------------. 1: ....._ + + .; . ,...J 0 l: .. --~ _ _ _ : -<--s~..:....,....-'---~~-_;___:_~-.:--""~~7 0 Z,o l.o 2.8 100 . ! . i .. . !. . -: . : -------:. . ,. , :.,-; , [__ f+Ir: 1 ,, : ' k ::: ( :: : ~ _ ; ___ ! . > l. .. i. ! . : ! : s-o l== ==== -.1.-o-------=~-==-=====1 0,0 ! I .: . . . . .. . i _ : _ _ '. .. : ... 1 . .. . -~ L _ J ___ :.._.,! __ _ . .. L __ _ _ . t 4 -rF: i. : 41 J ~. :r -:>I .t i,-:.. .t -'--,f ., j,-0 ,.:i -,f ., . . . . : , . . . : i . . : . : ' : . : : . . . , Lo. ~z: . _ ~ >, 1 . z _ s L I ' . -J Oboo i. . . . l ' .. .. . . , 1200
PAGE 301
>t ~t _J p.(h I D Inner Discharge Bay 22-23 Au g ust 1973 j " i : ;-:_i-. . -: . .. •i ; _ . _ _. . '-; -. .. . ------. 281 ' -I . I ' . , . 01--.....:.. __ ...._ ____ ________ --1 _ _ !...-, J . C .z . o 1 0 ----------. --------. I ""'" ----':---~-' -. _:_\ J ......,_-=4 \...._ =-.J . . . . l I . . L I I ----'--: . . . i. : . -~ _ . . . _ _ _ -------. -. : _ _ .. . \ l . 1 : : . . .. /S -. ... . _ .. ~; ~ -'. I , . -~ ' ~-_ _ __ : . : . : _ : . _ _ : --~. --: .. _ _ _ _ :--.s 2.e 2. lo .2'-l / 5"{) J I• -, , : ;... _ _ . -t . ,' _ :, .. : '. -~: . .. .. : . : : _ -_ :_ _ --. _ . . .-__ _ _ _ __ . .. :, _ _ _ _ __ : _ _ ;. : . : i-:: : _ ___ . .. _ _ _ , ,-: ... . . i---~ . . .. . :--:: _ :~ : ;_ . . . i . -------1 ---: __ _ ____ _ .so 1-___ _.. ___ _ _L ___ --..JL-------' / 200 /80 0 O,Cl -1.0
PAGE 302
-r ().." i UJ ff v D 0 2.0 I , D o,o 30 -to.s o . c . .. 282 Inner Disch a rge Bay Aug 23-24, 1973 .. . i . . ! i I . . ! \"2..00 i \ 'oOO ( ~ () .
PAGE 303
/o r
PAGE 304
,.,~ rJ 0 :r:" t= t tJ.l 0 " r' ,--ZI--CJ-. _I fl4. \I) 'tIg v fl. ill J fJI/} /Q s 0 2..,0 l,o o.o 3o 28 2~ 2.2:z. /0() 0,0 284 Inn er D i sch a rge Bay Au g 25-26, 1973 ... : j .. ; .;. 1 -. . : _ _ _ ' _ _ _ . _ _ _ ' . ' . ---; --: :-+'. .. !. . . . . : -::: ------~----~-r -<-.:-+ . ___ ; _.-_ __ !__ ' . : . : : --: -: . .. ' -.
PAGE 305
,J 0 So ti1. ,if N 0 28 5 Inner Discharge Bay Aug 26~27, 1973 ,o.-----~-,----,---...,....~---, s 0 2,o -r i . . -! . i - •: > . --: . i . i : .. : . 2 ::iI}i:1!1 1 J f !:: :; : : :; ; u :. z 2. : t ,. i. / i , .. . " : r L -------I ,Si /oo so -to,..s O,o -o . s :~J _ Lf f 1 : ) . : ~r _ -! I I . 1 I /Boo
PAGE 306
rt1 ,-J 0 s 0 2, 0 /,0 Lnner Disch arge Bay Aug. 27,28 1 1973 0.0~---------,--------='-'-----' : , l -.. T : ; : z_. : --r : ; _. :~~+ ~i : +, :_;;( : : . ~ -~r~ lf" ~ ~~ : :s ~ ~-: ~~r ~r .( :_;t.l I ! . ! . .. I. l -o.s l1.0o
PAGE 307
"'E rJ 0 " -:r: ~t CJ r" 1-(.lj_{)i/) 1 0 s a 2., o l.o 0,0 2'2. 2..o llo 28 2.G:, 2'-f 22. ls-o 287 Inner Di s ch a r g e B a y O c t. 29-30 1 1973 .. . i :-----:-= -, .;..-~--~_, i : -T t ; T -'. -:. . i . . :!_ ,_ , ,_ .. _._ . 1 . .. -' ' T ! -: ... .. rr '. f' : : 1 -: i : ; ! :: 7 .7 i -T ! S61--' -----+---..--'-...... --'___ .:_.;.......:.......:....:........!..:.....:...J ot ::r: o.o i .... , i
PAGE 308
f Jl t Ji i b~ t/. t!l 'J fl.-~ l/) ID 3o So 288 Inner Discharge Bay 30-31 October 1973 >----~ ~--. ____ ,__ ___ _, ---'. -----. ---•' '.. . -.. . . --. :-. ------: 0(,,00 \Bco -: ; . ; . _ ro.s; I -. ' ' . -_. . ... :! . . . -:. ; . ; :. . . : -: . -~ : [ : -: . .. -i ... t ~ ~~: : . : -'. ~ 4 . -; . _ _ _ i . : . ; -, ' i .. t i I . -,.o I J ... _ r :.__I r:..""? . .~---<
PAGE 309
v.T 4 ,J 0 '?.'( t.l LLf ,t., 0 i ,-. 30 : ! . i ; .. -~ ;. ~ 7~ . -~ :_~~-: ~ : : -~~ : :i:f ~: r.~ __ _.: Dr.coo l '2oo 289 .P'. l . 1'1 _ K• 2 . ,.1 ~ -t >i~ -_.~~ _,.;~ :: i
PAGE 310
>2, o ~k :it12..8 < If) 2. f, 1\.\ 0 7. ~9 JJJ v rJ lo c, rf:? t !i 1/) G,o 290 Inner Disch a rge Bay May 24-25, 1974 i . ; ; '. : : ; ~ i f : . ; \ :-:~ , -:~:_ : _ __ : . . -----. . -~ ----------. -. -. . _ : _ : _ _ ! : ! _ _ _ _ ; .. _ ;_. '" i _'._ --. _ .. . -----. : --___ : -_ ._ .. -: . .. . . :! : _; . , .. . ; -. .. : --: .. ;-: '. .. -i--:-.'. . . . . . ---. ->-o,sL------'-------J'-----'----1aco /
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(") "' 0 (t IO s 0 2,0 /,0 3'-f 3 2. 30 3o 2.B IO CJ 6 c 291 Inner Dicsharge Bay 25-26 H ay, 197L1 . . . . . . -1< ; . _ -:. . ;-: -~ : : . . : ' ' ' -! : _i .+~ -t . . : i~ . . ;. : ... : .; . . __ ;.., _ .; ~ . ___ : _ _ _ , _ _ : : : : .. ; . .. . . .. : : .. ! . ' . -~ . -: . ' . . +o.s.~---------C------~ --: --rJ 0 o. o 0 (.,00 1 200 \8 00
PAGE 312
"'E rJ 0 > ~f ;!1 " t /0 s0 Z,o l,o 0,0 31-f 32 30 3o 2-8 2.i:,, IY.O Inner Discharge Bay 26-27 Nay , 1974 I I I ' , .; ~ u: re,: ~ , ~.1. 1, . ' . ' -_ _ _ i __ . : _ _ : L. -! : -'.. . 1 . ;_: T . . ::....~ . : _ ~ :_:,• ~-:--~ ~ --. .. . . . . -.-. -,, . . . : 'f-.. -: . . ' ( _ :' ----.. ~; -= ;. .. . ! ! : . _ . . ; =. : ~-:. ; . ; _ _-~ -_. .: ; -; : : .< ; ~ ; : .. . '_ .-: _ . o "_ .: --, : c . : .. _ .. --. . c. Q ' .. i ... ; .. --------. , N o . o ~....,___.__~----'--c'i---'-~:--......,\~--''---1 0 -' ----....l.----....l.------' O
PAGE 313
,,j 0 S-, t ?: t 2 0 f-2~ ~a Ct'.) t~ 10 lo 0 Fort Island Aug 2-3, 1972 -:---: .:..;;. _ -: . . 4"'!: -;:: -. ! :..~:• -:. -:,: c , _. _ _ :. : _r/ . -i-~.:) . . -t ~ --" ---~ = -. -: 3o t---e--.,--:-_ 2B I lo l'f /2 l ! f'I"" ' I ' 293 ioole,_,~ I 0~ So 1'2. oo 1900 OG::.oo \.00 r, = r r; . . . : -180C
PAGE 314
294 Fort Island 10-11 Au g ust 1972 ,a-----,-.-.:...._--.----...------1r---, .. .,. I. :----: ----:~------. ~----=-. i -.. : . . . . . . -. _ : . . I St oi _ L.. ___ ....L. ___ __. ____ .,_ ___ _,I 12.DO I. . , I I I ~ -, . I ~ 1 '. _:_ __ : : ,0 -\.o 0,() \ . o l-. ___ ...l..._.!.,_ _ _i ___ •_~_ L ____ I --~ 2 . () o ~co 1 8 00 i 0 I" { ::, ,
PAGE 315
('1 cf t " ffi (-l ,., () b ,., D,. z ov I!} I>1-~
PAGE 316
Hodges Island 22-23 F ebr uary 1973 /0 ,.. t .. , --. ' , . -... . . ' : . . . : ... . . . ' . -=I I J ' I ' . / s ,-, --I--' '-'--~ -:.: ; . i _ __ i _ _ _ -: . ... -";--~... :... /c, s l"f(J.." /Z. !! UJ lo 1 22. >2-c. t -~1: 18 ~/lI~ l,J t:: /,YQ 0 ffi [ /oo ,J (L i~ t;o 1?... 00 296 . ~~7 ~ . :~ ___ , ~ \ __ ~;~: _ _ ..;.,._ "•.. I . --r-t OG,00 ;l . I I I ' . J •~j +os '1 0 ,., 00? ,, o,o ,... i G fJ --3,., r
PAGE 317
1 -----rJ C) So I,... __t ,.i~ ----iJ 0 297 Fort Island 25-26 Jun e 1973 10---------------------, s C> 2 ,o r----..;__-..:_;::.~ /,c, ..3.2.. ' 'i12 B /iro ro,so,o ----~ ----:. . ; : ... . . .. . . . .. : ... ! . ; .:: + : ;:: . . l : : . .. ; . . . -i . . . . ; .. ; I : ! , : _ __ _ ---• -.. .. _. -------.---.: -. i: ; l . . . -. . ... ... . . . .... . . . .. . .. --. . . . . ... , . .. -.. . : --: i ; -o.s _ _ _ _ _ , _ ____ L__ ____ _j_ ____ -< OCco o /2.oo
PAGE 318
;'Q (fl~ -cf s $a 0 r F 2.o /,0 A uJ 32. IX '.) .3o 1: iliJ Z-8 ll,I) 2~ -~ Z4 lb 298 Fort Island 26-27 Jun e 1973 I 2-o r:, / 8C>C>
PAGE 319
1'0 s Fort Island 26-27 June 1973 299 . .. .. , . . . ---. .. --.. ' : ... , ' ' ' ' .. ~. : I .. . ' ----. ---L-t------~-----'----i\---'-'------l 8,0Q::i .3,o Z. , Qt ~--'---.:::...:...::. ,;,.c---<>-""'-c / , O \ ------' ' _ : /'~--\~ ' _ : ...:... IS 10 s v 30 0 'i' 2-B uJ U , f-)It,, , _ 2 JI 'f i1i. (l. I 2. 1 /1 ID z ,,, ,, t;? JLJ /{J(J v ui D-!. I[) sc, _ ____ _ _:__ : : . : __ _ ___ _ \ _ . -J~ . ' . . . . . ------..------..... --. . \ ---. . . ~ -; •. C .. . ! . . , __ s_ _ . . . 1 _-_: __ , . : . . ' . , .. . -. . . . . : :: - •. . :r _ _ _ : _ _ __ . .: . . . . : . , . : ' .. _: : -: -~ -\/~ -t: . . : .... ;;, _ _ _ i t :. --:-~ . . --.. ----:-~ -:-c-:i,----...:.----.i...~===!=-=:oc=::t-1.0 : '. >i .f .. :: :-1 -~ ~: ~:~~ :.. ----. . . . : . . . . . . -. i . --: ~ . . : .. : : ! -. . -: : . 0(o0<'., . --i . I \ I \Boo ::r ...,
PAGE 320
-f kt UJ f-.+ uJ :J ill J 0 i IJJ }-')-1--J-?: ().. .J fJ.4. ./) ~K :z:. .,.,. J ti dg~ I I/) /0 0 2,o .:L.o 32. 3o 2.9 2"' <-'-/ /~ l'-f /2._ /cJ 8 /Yo loo G,() 300 Fort Island 27-28 June 1973 -) . . i. I .. : : . '. .. . . --• . .. . . . . ----: . :. . -:-! ---; : : : . . :_, -:: . --: _ _ i _ _ _ ----. ---: ; ! .. . .. ; . . . . . : -~ = : i ; . --: ; : j. : . : ::.-: : > .-; _;. 7. -:+ ,.. . -=--",,-:,," --j ! :=-;. + . . . l 2.(.) ( ;, \800
PAGE 321
r'1~ ,,J 0 r ~f A /CJ .!) 0 2,o I, o 3 2._ 3 o 8 o ,o 301 Fort I s land 28-29 Jun e 197 3 _ : _____ : __ _ _ : _ : _ _ !" . . ' I .. . ! . . .. . -. : : j _ :: ~: : ;_ ( . : :-!-~~ . I [ I _ :-! -. -: _ __ . . _ _ . : . ! .. ----. ; : : . . : : : : , '" . ' : ' i . ... . . : . .. : . : . . i' . : r-; ( .. : ; ; -~ : ---:. -, 1 2.. oc.:,
PAGE 322
.,, E" ---cf r~f 00 r:{' z uJ }302 Fort Island 16-17 Au g ust 1973 /C> s 0 2. I 0
PAGE 323
303 Fort Island 26-27 Au g ust 1973 /( j -------------------------1 . i. . . : lb >I/ c; II). I z_ ..J (.1. ..{_ /D v'l 8 z /~ 0 I:; 9 &g .J d pl_ '.) ti \fl C,C) l,. _.. -to . s ' . : 1 ----,J o . o 0 -o, S" ..,_ _____ _ , _ ____ _ _ ...... _____ ---'-------' O 0 " -0( .>
PAGE 324
304 Fort Island 27-28 August 1973 .. : 1 . j : 1 i -' 1 . ! 0 /(o [, l'7' ~/2__ -A:i_f!/o VI 8 I -z /'l o -0 d rt /oo lV k fl'J. V) .::,0 ~. \. -fO,S,.,E I ' ! ' O, o ON J ---$ = -o,s J
PAGE 325
L _c Fort Island 12-13 Nove mb e r 1 9 73 /0 2. c, : : ' i . --: .. : .. ~T . ----. -:. : . : .. t.. : -=: L . . .... . . . : . i i . : . . , . : . . : _ _ _ : ---/ 91-----'-+----,-------:--+--:----. : , l b .2o i . ; __ _ ! _ :_ . .. , . _ .. ' , , . . ' . . ; _ _ _ _ _ . . :_~:_ ---. --: -. . . . ---.. . . . . : . . _ .. _ : -: : :-; --: . . i -: --: -.-'. . . . . . . . . . . . . . _ . . . '.---'.. -; : . : . . ! . . : . _ . . _. _ _ _ , . ! . loo . : : . : __ . _ _ .. _ _ . _ _ . ___ . _ _ ; ' j ' " : : ' i'-' '----"""" .i. L ~ "---~ oi;, _ oo 12. u o 1800
PAGE 326
.s \... __c -t-o .s o . JUb Fort Island 13-14 Novem ber 1973 i . i i . : . .. i = i : ' ... ; . , _ ___ _ : . __ . _ . , _ : _ : _ : j "'' . i : _ _ _ _ :~~ : : l _ _ _ : __ ; : ___ _ _ _ I. . . / .. . .: ! . { t,00 ' r ' -----....... ~--------1 ------L---------'---------' o i::, oo 1 200 / BOO
PAGE 327
307 Fort Island 14-15 Nov em b e r 1973 10 1 N s 0 i0 -:i }iF 2 . IJJ f-l 2:2 : ---: !-:. : . . ; -! _ _ _ : ; :..;_:. . . . . . . : . : . : =: G,Q 0, 0 ---------C: ! : ,oo ,u : o 1 e,oo
PAGE 328
308 Fort Island 15-16 November 1973 IC I s I . -! . ' ------2.o I ,B -: . -< . __ . : -;.-: . --;---. __ . . >-i . : -. -.. :: i . :(=t . ... i :-. . i . : . ( -. :r : : . ! .. ; i : : . i : : : ' . : . . . . : -1 + :. 2.. "I t i2. . :i 2-o I-1 4I(, ~(.J., /7' ' _: _ _ j_ ; _! _ _ _ _L_ . : . ... . . .. •. :: 1 . . , . .. . ... . -i-~~~+ :: . . ... . . t .. ... : : . _i_ . .. i .:'. '. ~ --z /';
PAGE 329
f; Z, ::J 4:. v'l lo 309 Fort Island 26-27 Nay 1974 2.8~ -c..b . -----. . . .. . . . --. ---=-C:Co c.o
PAGE 330
LU f)-I:: z'. l vl z 0 tif 1 .JJ J'. ,J ()! '11~ }f !:i 1/) 310 For t Is l and 2 52 6 May 1 9 7 4 / or-----:-""'""'"-------------. . , 2.8 2'3 --1 2..o \ 00 So ..:i O
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APPENDIX C INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, HEAT BUDGET CALCULATIONS, CALCULATION OF TRANSFER COEFFICIENTS, SCALED EQUATIONS, POTENTIOMETER SETTINGS, FUNCTION GEN ERATOR SET-UP, AND ANALOG COMPUTER PATCHING DIAGRAM FOR DIURNAL SIMULATION MODEL OF INNER BAY (Figure 40).
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Table C-1. Documentation of values used for forcing functions, standing stocks, and exchange rates in the diurnal simulation model of the inner bay (Figure 40). 1.1 m was used as average depth. Storage Description Total phosphorus in water column Heat content of bay water Oxygen concentration in bay water Total organic carbon in bay water Biomass of seagrass in bay Calculation Aver. cone. = 0.045 g P/m 3 (0.045 g P/m 3 ) (1.1 m) = 0.05 g/m 2 Summer diurnal range: 5-7 mg/1 Assume midnight value half way between high at dusk and low at dawn= 6 mg/1 (6 g/m 3 ) (1 . 1 m) = 6.6 g/m 2 (5 g/m 3 ) (1.1 m) = 5 . 5 g/m 2 Summertime standing stock= 25 g/m 2 Assume 50% refractory material (25 g/m 2 ) (0.5) = 12 g/m 2 Reference Mc Ke 11 a r, 19 7 5 Appendix B Figure 28 w N
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Tab l e C-1 continued Storage Description Flow Biomass of labile organic material in seagrasses Biomass of consumers Description Averaqe hourly i n so l ation reaching \ v a ter surface Unused solar insolation Solar insolation utilized in photosyn thesis Calculation Assume 50 % of seagrass standing stock is labile (25 g/m 2 ) (0.5) = 12 g/m 2 Calculation Average daily insolation in June = 5610 kcal/m 2 /day 2 (5610 kcal/m /day)= 400 k l/ 2/hr 14 hrs daylight ca m Assume 50 % of sunlight unused in photosynthesis (400 kcal/m 2 /hr) (0.5) = 200 kcal/m 2 /hr Assume 50 % of sunlight used in photosynthesis (400 kcal/m 2 /hr)(0.5) = 200 kcal/m 2 /hr Reference Figures 26, 27 Reference Figure 13 w w
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Table C-1 continued Flow Description Gross production of labile organic matter Gross oxygen production Average hourly respiration Calculation Summertime daily average gross photosyn thesis = 3.8 g o 2 ;m 2 /day Assume l g organic matter produced for each g o 2 . 3.8 g/m2/day = 0.271 g/m2/hr 14 hrs sunlight Assume rate is 0.3 g/m 2 /hr@ 2 pm. Assume daytime net photosynthesis plus night respiration= gross photosynthesis. Assume rate is 0.3 g/m 2 /hr@ 2 pm. Assume steady state conditions so that all labile material produced during daylight is utilized over 24 hours. 2 3 8 g/m /day = 0.158 q/m 2 /hr 24 hrs Reference Table 6 w
PAGE 335
Table C-1 continued Flow OP.script ion Maintenance respiration degrad ing organic matter into heat Labile organic material stored as standing crop Loss of benthic producer standing stock to organic detritus poo 1 Calculation Assume maintenance respiration is 30% of gross production. Jones (1968) found Thalassia respiration to be about 10 % of gross production. In steady state J 2 = J 4 over 24 hrs. (0.158 g/m 2 /hr) (0.3) = 0.048 g/m 2 /hr Difference between gross respiration (J 4 ) and maintenance respiration (J 5 ). (0.1580 g/m 2 -hr 0.0474 g/m 2 -hr = 0. 1106 g/m 2 . hr Assume steady state. Therefore, J6 = J 7 Reference Day et al.; 1973 Jones":1968 w u,
PAGE 336
Table C-l continued Flow Description Respiration of consumers Assimilation of ingested organics by consumers Feces production of consumers Total intake by producers Calculation Assume respiration rate of 0.085 g dry wt respired/g dry body wt/day (6 g/m 2 ) (0 . 085 g respired/g body wt/ day) (l day/24 hrs)= 0.021 g/m 2 -hr Assume steady state so that assimilation (Jg) equals respiration (J 8 ) Assume 50 % assimilation efficiency. There fore, assimilation (J 9 ) = feces production ( J, 0) Total intake (J 11 ) = assimilation (Jg) + feces (J 10 ) 0.021 g/m 2 -day + 0.021 g/m 2 -day = 0.042 g/m 2 -hr Reference Day et _tl., 1973 w 0-,
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Table C-l continued Flow Description Utilization of oxygen by plant res pi ration Utilization of phos phorus in photo synthesis Advective addition of total phosphorus from po1A1er plant cooling water Calculation Assume l g o 2 used for each gram of organic matter respired. Therefore, J 12 = J 5 . Assume organic matter produced is 0.9% phosphorus. (0.3 g/m 2 hr) (0.009) = 0.0027 g/m 2 hr@ 2 pm Assume addition from this source only on rising tide. Assume power plant cooling water 1/3 of total flow on rising tide. (P 1 ) (V rising) (1/3) = J 14 (0.045 g/m 3 ) (0.10 m 3 /hr) (1/3) = 0.0015 g/hr at midnight (0.045 g/m 3 ) (0.12 m 3 /hr) (10 hrs) (l/3) = d .OTB g/m 2 day Reference Van Breedveld, 1966 quoted in Jones, 1968 w __, --..J
PAGE 338
Table C-l continued Flow Description Advective addition of hea t from power plant cooling water Advective addition of oxygen from power plant cooling water Calculation Assume addition from this source only on rising tide. Assume power plant cooling water l/3 of total flow on rising tide. Heat content= CPT = (1000 kcal/m 3 : 0 c) (33 . 5C) = 33500 kcal/m 3 (H + C) (V rising) (l/3) = J 15 (33500 kcal/m 3 ) (0.12 ~?/hr) (10 hr) (1/3) = 13400 kcal/day (33500 kcal/m 3 ) (O. l m3/hr) (1/3) = 1117 kcalihr at midnight Assume addition from this source only on rising tide. Assume power plant cooling water 1/3 of total flow on rising tide. (x 1 ) (V rising) (1/3) = J 16 Reference w 00
PAGE 339
Table C-1 continued Flow Jl6 (cont.) Description Advective addition of organic matter from power plant cooling v,a ter Utilization of oxygen . by consumer respir ation Calculation (5.1 g/m 3 ) (0.12 m 3 /hr) (10 hr) (l/3) = 2.04 g/day (5.1 g/m 3 ) (0.1 m 3 /hr) (l/3) = 0.17 g/hr at midnight Assume addition from this source only on rising tide. Assume power plant cooling water 1/3 of totaT flow on rising tide. (t~ 1 ) (V rising) (l/3) = J 17 (5 g/m 3 ) (0.12 m 3 /hr) (10 hr) (l/3) 2 g/day at midnight Assume l g o 2 utilized for each g organic matter respired. Therefore, J 18 = J 8 Reference w __,
PAGE 340
Table C-1 continued Flow Description Advective exchance of organic matter with offshore area Calculation Reference Rising tide: addition from offshore 2/3 of total addition. (5 g/m 3 ) (0.12 m 3 /hr) (10 hr) (2/3) = 4 g/day = 0.333 g/hr at midnight Falling tide: entire exchange through this pathway. (5.0 g/m 3 ) (0.108 m 3 /hr) (12 hr)= 6.48 g/day (5 g/m 3 ) (0.19 m 3 /hr) = 0.95 g/hr@ 2 _ pm w N 0
PAGE 341
Table C-1 continued Flow Description Advective exchange of oxygen with off shore area Calculation Reference Rising tide: addition from offshore 2/3 of total addition. (7 g/m 3 ) (0. 1 m 3 /hr) (2/3) = 0.465 g/hr at midnight (7 g/m 3 ) (0.12 m 3 /hr) (10 hr)(2/3) = 5.6 g/day Falling tide: entire exchange through this pathway. 3 3 (6 g/m) (0.19 m /hr)= 1 .14 g/hr@ 2 pm (6 g/m 3 ) (0.108 m 3 /hr) (12 hrs)= 7.78 g/day w N --'
PAGE 342
Table C-1 continued Flow Description Advective exhcange of heat with offshore area Calculation Rising tide: addition from offshore 2/3 of total addition. Heat content CPT = (1000 kcal/m 3 0 c) (28.5C) = 28500 kcal/m 3 (H) (V rising) (2/3) = J 21 R (28500 kcal/m 3 ) (0.12 m 3 /hr) (10 hrs) (2/3) = 22800 kcal/day (28500 kcal/m 3 ) (0.l m 3 /hr) (2/3) = 1900 kcal/hr at midnight Falling tide: . entire exchange through this pathway. (28500 kcal/m 3 ) (0.108 m 3 /hr) (12 hrs) (2/3) = 24624 kcal/day Reference w N N
PAGE 343
Table C 1 continued Flow J21F (cont.) Description Advecti~e exchange of total phos phorus with off shore area Calculation (28500 kcal/m 3 ) (0.19 m 3 /hr) = 5415 kcal/hr @ 2 pm Rising tide: Addition from offshore 2/3 of total addition. (0.045 g/m 3 ) (0.1 m 3 /hr) (2/3) = 0.003 g/hr at midnight (0.045 g/m 3 ) (0.12 m 3 /hr) (10 hrs) (2/3) = 0.036 g/day Falling tide: entire exchange through this pathway. Reference w N w
PAGE 344
Table C-l continued Flow J22F (cont.) Description Phosphorus re generated by respiration of benthic producers Phosphorus re generated by respiration of consumers Radiative heat loss to atmosphere Calculation (0.045 g/m 3 ) (0.108 m 3 /hr) (12 hrs) = 0.058 g/day (0.045 g/m 3 ) (0.19 m 3 /hr) = 0.0086 g/hr @ 2 pm Assume organic matter is 0.9 % phosphorus. Phosphorus comes from maintenance respiration. (1.14 g/m 2 ;day) (0.009) = 2 24 hrs/day 0.000428 g/m 'hr Assume organic matter 0.5 % phosphorus. . (0.51 g/m2•day) (0.005) = 0.000106 g/m2'hr 24 hrs/day Reference Van Breedveld, 1966, quoted in Jones, 1968
PAGE 345
Table C-1 continued Flow J25 (cont.) Description Sediment respir ation Phosphorus re generated by sediment respiration Calculation = 9829 kcal/m 2 ; day = 410 kcal/m 2 hr r Assume P/R ratio of l; gross production (J 2 ) = total respiration. Sediment respiration = total respiration plant respiration consumer respiration. Reference J 26 = 3.8 g/m 2 day 1.14 g/m 2 ;day 0.51 g/m 2 •day = 2.66 g/m 2 •day = 0.1108 g/hr Assume organic matter 0.5 % phosphorus. w N u,
PAGE 346
Table C-1 continued Flow J27 (cont.) Description Oxygen utilized in sediment respiration Heat from evaporation Heating of water by solar radiation Calculation J 27 = (2.66 g/day) (0.005) = 0.0133 g/day = 5.54 x ,o4 g/hr Assume l gram oxygen required for each gram organic matter respired. Assume everything constant except Ts (water temperature). Ignore heat carried away by evaporated water . 2 e = 11365 kcal/m day cpe = 474 kcal/m 2 .-hr at midnight Assume all solar input absorbed by water. Reference Huber and Harleman, 1968 Table C-4 w N '
PAGE 347
Table C-l continued Fl 01'1 J30 (cont. ) Description Back radiation from atmosphere Diffusion of oxygen between atmosphere and water Calculation Assume average 24 hour air temperature of 20C. J 31 = 0.970 T 4 J 31 = (0.97) (l.171 x kcal/m 2 :day:K 4 ) (293K) 4 J31 8832 . 2 368 kcal/m 2 .-hr = kcal/m day= Q3 R (Cs ) (_Q) D cs C = s oxygen value at 100 % saturation Reference w N -...J
PAGE 348
Tab1e C-1 continued Flow J32 (cont.) Description Calculation Q 3 = quantity of ox.rn'=n in water column D = depth R 0 = average diffusion coefficient Evaluated at midnight: (6.25 -1:1) (~:~~) = 0.01 g/m 2 hr Reference w N (X)
PAGE 349
329 Table C-2. Initial and maximum values of storages for diurnal simulation model of inner bay (Figure 40). Initial values are for conditions at midnight. Initial value Maximum value Storage Water column Volumetric Water column Ql 0.023 g 0.045 g/m 3 0. 15 g Q2 16640 kcal 32 c 60000 kcal G3 3.12 g 6 ppm 18 g G4 2.6 g 5 g/m 3 15 g G5 12 g 20 g Q6 12 g 20 g G7 6 g 10 g
PAGE 350
330 Table C-3. Initial and maximum values of forcing func tions for simulation model of inner bay (Figure 40). Initial values are for mid night. Forcing function Initial value Maximum value pl ' p2 0.045 g/m 3 0.10 g/m 3 H 28500 kcal/m 3 35000 kcal/m 3 H + C 33500 kcal/m 3 40000 kcal/m 3 Xl . 5. l g/m 3 8.0 g/m 3 X2 7.0 g/m 3 12.0 g/m 3 Ml, M2 5.0 g/m 3 10.0 g/m 3 J 0 840 kcal/hr 0 V 0. l 3 m /hr 0.2 m 3 /hr D 0.52 m 2 m
PAGE 351
331 Table C-4. Calculation of radioactive, evaporative, and convective heat losses for use in diurnal simulation model of inner bay (Figure 40). Formulae are from Huber and Harleman (1968) . Radiative heat loss: = 0.97 0 T 4 r s a= Stefan-Boltzman constant= 4.877 x 10-B kcal/m 2 -hr-K Ts= water te m per a ture (K) = 305 K 0.97 = emissivity of water = (0.97)(1.171 106 kcal/m 2 -dayK 4 )(305 K) 4 = 9829 kcal/day r Evaporation: e = p (a + bw)(e ~e )L s a p = density of water= l g/cm 3 = 10 6 g/m 3 empirical constant -4 a = = 3.08 x 10 m/day-mm Hg b empirical constant -4 = = 1 . 85 x 10 /sec/day mm Hg w = wind speed = 8 mph = 3.5 8 m/sec es = saturation vapor pressure of water ea = saturation vapor pressure of water l/J = relative humidity= 0.7 L = latent heat of v a poriz a t i on 595.9 0.54 T s (32 c) (24 C) 595.9 (0 . 54)(32 C) = 57 8 .6 ca l/g = "' 36 mm Hg = "' 22.5 mm Hg e = (10 3 kg/m 3 )[3.0 8 x l04 m/daymm Hg+ (l .85 x 104 sec/d a y m rn Hg)( 3. 5 8 m /s ec )J[(36 mm Hg) (0 . 7) (22.5 mm H g )](57 8 .6 k c a l/ kg )
PAGE 352
332 Table C-4 continued Evaporation (continued) Cp = specific heat of water= l kcal/kgC v = (10 3 kg/m 3 )(9.7 x 104 m/daymm Hg)(20.25 mm Hg) (l kcal/kg-C)(32C) v = 629 kcal/m 2 -day Convective heat loss: c = Np(a + b w )(Ts Ta) N = proportionality constant= 269.l kcalmm Hg/kgC Ts= witer temperature (surface)= 32 C Ta= air temperature (daily average)= 26.7C = C (269.l kcal-mm Hg/kgC)(l0 3 kg/m 3 )(9.07 x 104 m/day-mm Hg)(5.3C)
PAGE 353
333 Table C-5. Calculation of transfer coefficients for diurnal simulation model of inner bay (Figure 40). All evaluations calculated for conditions at midnight except those associated with photosynthesis or falling tide, which were evaluated at 2 pm. Coefficient Calculation k 1 J 0 = k 0 S(l-D) = k 0 (780)(0.6) = 429 kcal/hr@ 2 pm 429 ko = (780)(0.6) = l 215 kl = (468)(0.023)(32) = 0.6241 = (1)(0.3) = k2 (439)(0.023)(32) -4 9.501 X 10 J 4 = k 4 Q 6 TQ 3 = 0.158 g/hr 0.158 4 k 4 = TT2)( 3 2 )(J~J = 1.32 x 10
PAGE 354
334 Table C-5 continued Coefficient Calculation J 5 = not needed in patching 0.1108 -5 k6 = (12)(32)(3.12) = g,25 x 10 k = 0.1106 = g_22 x 10-3 7 12 . 0. 021 k8 = (6)(32)(3 . 12) = 3.51 X 105 kg Jg= k 9 Q 4 Q 7 = 0.021 g/hr 0.021 kg = ( 2. 6 )( 6) = 1. 35 X 103 k,o J 10 = Jg; therefore k 10 = kg= 1.35 x 10 -3 0.042 -3 kll = ( 2 _ 6 )( 6 ) = 2.69 x 10
PAGE 355
335 Table C-5 continued Coefficient Calculation 0.0474 -5 k12 = (3.12)(12)(32) = 3 96 x lO Q T J = k J l = 0.0024 g/hr@ 2 pm 13 13 o kR+k 1 Q 1 T k _ (0.0015 (3) _ l 14 0.1 (0 . 045T J 15 = k 15 HV(l/3) = 1117 kcal/hr _ 1117 3) kl5 33500)(0.1 = l _ (0. 17)(3) _ Jl6-kl6(5.l)(O.l) -l k (3 )( O . 1 6 7) l 17 (5)(0.19) =
PAGE 356
336 Table C-5 continued Coefficient Calculation 0.021 5 kl8 = (32)(3.12)(6) = 3 .51 x 10_ (3)(0.333) kl9R (2)(5)(.1) = l _ (l.0)(0.95) kl9F (5.0)(0.19) = l k = (_lL(Q_._ 465) = l 20R \2JT7)(0.l) k = ( l. 0 ( l. 79) = l 20F 5 0.19 J21R = k21R(H + C)(V)(2/3) = 1900 kcal/hr _ (3)(1900) k21R (2)(28500)(0.1) = l
PAGE 357
337 Table C-5 continued Coefficient Ca lcul ati on _ l. 0) 5700) k21F (30000) 0. 19 = l _ 3 )( 0. 003) k22R (2 (0.045)(0.l) = l k _ (l.0) 0.0095) = l 22F 0.05) 0.19 0.000428 -7 k23 = (12)(32)(3.12) = 3 . 57 X lO 0.000106 -7 k24 = T6JT32)(3.l2) = l.77 x 10 4 2 J 25 = k 25 (0.97)(a)(T) = 410 kcal/m /hr 410 k25 = (0.97)(4.879 X l0-8)(8.6537 X 109) = 1.0
PAGE 358
338 Table C-5 continued Coefficient Calculation Not needed for patching 0.00054 6 k27 = (32)(3.12) = 5.55 X 100.lll 3 k28 = (32)(3. l2T . = 1.11 X 10k 29 = 11365 = l 11365 4 2 J 31 = k 31 a0.97 T = 368 kcal/m -hr 368 k3l = 368 = l k = _Q.:_9_1 = l 32 0. 01
PAGE 359
Table C-6. Equations of Table 7 scaled for simulation of diurnal model of the inner bay given in Figure 40. ( 0. 1 ) ( 0. 2) kl 4 kPl (0.15)(3) (0.15)(0.2) k 22 F (0.15)(2) (10)(18) (40)k 24 + ----,,---,,-,=---0. 15 [ V ] ( (2) (0.1 )(0.2) k 22 RkP 2 0.2 + (3)(0.15) (20)(40)(18)k 23 + ----=-~--0 .15 [Q ] [Q ] [ ] (18) (40)k 27 16 1 do + 0 15 ( Ql T ) k J 13 o kR + k Q T l l * w w I..O
PAGE 360
Table C-6 continued + (0.0343) (40000)(0.2)1< 15 (60000)(3) (0.0084) [ H 5000] 40000 + . 40000 840 + 60000 [ J30] 840 (continued)
PAGE 361
Table C-6 continued ( (2)(40000)(0.2)k 2 lR + (60000)(3) \ [ H2 7 [ V] (60000)(0.2)k 2 lF 40000j 0.2 (60000)(2) 9 -8 (9.5979 x 10 )(0.97)(4.879 X 10 L k 25 595.9 k 29 60000 60000 ( 595.9 _ (40)(0.54) 595.9 595.9 ( 40 [fa-] 313 4 + 273) 313
PAGE 362
Table C-6 continued d (0.0444) [~!~] + ( (0.0889) (0 . 1000) [ 60 ~~ 0 ] [ 0 \j ) (0.0076) ( (0.1278) [ Jo] + o.8727) 4 (0.0081)(1 0.0362 [; 0 ] ) + (o.oos8) [ 2 ~ 3 ] 4 [ ~] [-v-J _ . ( (2)(12)(0.2)k 20 ~ 8 0.2 (3)(18) continued
PAGE 363
Table C-6 continued (l8)(0.2)k 2 0F (18)(2) ( 18 )( lO) ( 40) k 1 8 + 18 (l8)(40)k 28 18 (20)(40)(l8)k 12 + 18 d 1~] . (o . 0189 i [xi] [/ 2 ] ( (o. 0889) [ ~fl [ 0 \] (0.1000) [{fl [ 0 \] ) + (0.0316) [~fl [I 0 ] [{i] + (0 . 0140) continued w .i:,. w
PAGE 364
Table C-6 continued + (0.0444) [{~] [Jo] (10)(0.2) k1lM1 (15)(3) (10)(15) k 10 15 (20) k 7 15 (15)(0.2) klgF (15)(2) (10)(15) k 11 15
PAGE 365
Table C-6 continued (0.0222) [~b] [ 0 ~J [Q2057 1. 333 ( 0. 0092) ij [ 047 [ v l ) [Q7] 1 04] _ (o.,ooo) TsJ 0 _ 2 J (o.o,35) 10 L 15 + (0.0269) e~J L ;:J d [~] (20)(40)(18) k 6 dt 20 = (0.0665) + + (0.0097) [~g] (20) k 7 20 w +'> (.Jl
PAGE 366
Table C-6 continued d [07'j 10 dt ( 15 )( l O) kg 10 d [~ (0.0202) dt (20)(40)(18) k 4 + 20 + (0.0951) (10)(18)(40) k 8 10 [ Ql 4 5 ] [Ql 0 7] [ 07] [Q3] [ T ] + (0.0252) To T8 40 *See Table C-7 for scaling. w O"I
PAGE 367
347 Table C-7. Scaling of terms associated with photosynthesis in equations in Table 10 for diurnal simula tion model of the inner bay (Figure 40). = = (840) k 13 0.15 ( 840) ( 6) kl 3 (0.15)(5.0) [ ~] ( (0.15)(40) [itsl _[Zo_d_) 840 Q kR + ( o. i 5) l 40) k1 lo.~~ [ lal [ Jol ( [ili] [-Jo] ) s40J +[6k 1 7 ~l [r ~J 5 . o 5.oJ Lo. 15J 4o (0.0511) fJol( [i+J[iJ ) LB40J o, T . (o.1000)+(0.5349) ~,J [ 40 ] (840) k 3 18
PAGE 368
Table C-7 continued d l~] = dt (840) k 2 20 348 = [ J 0 J-( [ofs][k] . (0.0479) 840 Ql T (o.1000)+(0.5349) [o.1sj [40]
PAGE 369
349 Table C-8. Potentiometer settings for initial run (Figure 43) of diurnal simulation model of inner bay (Figure 40). Potentiometer Setting Potentiometer Setting kl 0.5337 kl 4 kp l 0.0200 l Ok 2 0.4789 kl 5 0.0444 k3 0.0532 kl6kxl 0.0189 l0k4 0.9510 k1lm1 0.0022 lO lOk 5 0.2760 10kl8 0.1400 lOk 6 0.6650 kl9Rkm2 0.0044 k7 0.0092 10 kl9F o. 1000 lOk 8 0. l 040 k20R 0.0089 kg 0.0084 ----ro klO 0. 0135 k20F 0.1000 kll 0.0269 k2l R 0.0089 ----ro l Ok 12 0.3160 k2l F O. l 000 k13 0. 0511 k22Rkp2 0.0040 10
PAGE 370
350 Table C-8 continued Potentiometer Setting Potentiometer Setting k22F 0. 1000 ICQ 7 0.6000 10k 23 0.343 IC depth 0.2600 k24 0.0084 wl 0.4486 lOOk 25 0.7600 W2 0.2617 lOk 27 0.2670 l lOkr 1.0000 10k 28 0.4440 RD 0.0014 k29 0.0081 l 0 k30 0.0014 RD 0.0208 7o c; k31 0. 1390 A 0.5000 ICQ 1 0. 1500 B 0.5000 ICQ 2 0.2667 C 0.1000 ICQ 3 0. 1667 D 0.1251 ICQ 4 0.1667 E 0.5833 ICQ 5 0.6000 F 0.0428 ICQ 6 0.6000 G 0.8143
PAGE 371
3 51 Table C-8 continued Potentiometer Setting H 0.0834 l 0 I 0.3625 J 0. 1333 K 0.2083 L 0.7917 M 0. 1278 N 0.0872
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352 Table C-9. Potentiometer settings for the EAI 580 variable diode function generator used to produce the tidal volume exchange func tion given in Figure 42 for the diurnal model of the inner bay (Figure 40). The special 12-segment set-up was used. X f ( X) 0.000 +0.5000 0.0208 +0.5000 0.0675 0.0000 o. 1459 -0.4500 o. 1875 -0.4500 0.3962 +0.8000 0.4375 +0.6000 0.6042 -0.9500 0.7292 -0.8500 0.8959 +0.8000 0.9875 +l.0000 l . 0000 +l .0000
PAGE 373
Figure C-1. Analog computer patching diagram of scaled equations given in Tables C-6 and C-7 for the diurnal simulation model of the inner bay (Figure 40).
PAGE 374
354
PAGE 375
APPENDIX D INITIAL AND MAXIMUM VALUES OF STOCKS AND FLOWS, CALCULA TION OF TRANSFER COEFFICIENTS, SCALED EQUATIONS, POTEN TIOMETRIC SETTINGS, FUNCTION GENERATOR SET-UP, AND ANALOG COMPUTER PATCHING DIAGRAM FOR SEASONAL SIMULATION MODEL OF THE INNER BAY (Figure 55).
PAGE 376
Table 0-1. Documentation of values used for standing stocks and exchange rates in the seasonal model of the inner bay (Figure 55). Storage Description o, R Standing stock of benthic plants Total phosphorus in water column Organic matter in water column Organic matter in sediments Biomass of benthic invertebrates Biomass of fish Oyster biomass Calculation Reference Van Tyne, 1974 Assumed same as outer bay Mc Ke 11 a r , l 9 7 5 Measured at Crystal River Gibson, 1975 Measured at Crystal River Cottrell, 1974 Measured at Crystal River. Venturi pump Evink and Green, samples plus core samples. Core samples 1974 never worked up. Assumed same order as Venturi samples. Total biomass= 2 x Venturi samples. Measured at Crystal River with drop nets. Adams, 1974 Assume dry weight 25% of wet weight. Measured at Crystal River Lehman, 1975 w (Jl '
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Table D-1 continued Flow Description Sunlight reaching water surface Sunlight used in photosynthesis Sunlight unused in photosynthesis Gross photosynthesis of bottom plants Calculation Average insolation at Tampa, Fla. in June (1961-72) = 5800 kcal/m 2 ;day x 30 days= 174000 kcal/m 2 ;mo. Assume one-half sunlight utilized in photosynthesis. (174000 kcal/m 2 -mo) (l/2) = 87000 kcal/m 2 •mo. J J = 174000 87000 = 87000 kcal/m 2 -mo . o l Total production as measured with the free water diurnal method minus phytoplankton production as measured with light-dark bottles. 2 . 2 2 4.12 g/m •day 0.93 g/m •day= 3.19 g/m •day 2 2 (3.19 g/m day) (30 days) = 95. 7 g/m mo Reference Water Information Center, Inc. (1974) w u, -....J
PAGE 378
T a ble 0-l continued Flow Description Respiration of bottom plants Uptake of phosphorus in photosyn t hesis Benthic plant bio m ass lost to organic matter pool in w ater column Calculation Assume respiration 30 % of gross photo synthesis (3.19 g/m 2 •day) (0.3) = 0.96 g/m 2 -day (0.96 g/m 2 day) (30 days)= 28.8 g/m 2 mo Assu m e benthic plant matter produced (J 2 ) is 0.9 % phosphorus. (3.l9g/m 2 day) (0.009) = 0.0287 g/m 2 day (0.0287 g/m 2 day) (30 days)= 0.8613 g/m 2 mo Assume benthic plant storage (Q 1 ) in steady state. Therefore, J 2 = J 3 + J 5 + J 6 J 5 + J 6 = 3 . 19 g/m 2 day 0.96 g/m 2 •day = 2.23 g/m 2 •day Reference Day et tl ; 1973 Van Breedveld, 1966, quoted in Jones, 1968 w tT1 CX>
PAGE 379
Table D-1 continued Fl OV,' JS (cont.) Description Benthic plant biomass lost to organic matter pool in sedi ments Import of detritus from salt ma rs h Tidal import of organic matter to inner bay from discharge canal and offshore Calculation Therefore, JS = 2.23 g!m 2 : day 2 = 1.12 g/m 2 -day (1.12 g/m 2 ;day) (30 days)= 33.6 g/m 2 mo See calculation for JS. Detrital export from marsh about 1.0 g/m 2 of marsh area/ day. Assume marsh area draining to inner bay about same area as inner bay. Therefore, input to inner bay= 1.0 g/m 2 -day = 30 g/m~ mo Since concentration of organic matter in discharge water and offshore is similar, total import to bay is total volume exchange times concentration. Reference Young, 1974 w u, I.O
PAGE 380
Table D-1 continued Flow JS (cont.) Description Ti da 1 export of organic matter from inner bay Ingestion by fish of organic matter by fish Calculation (l ,030,50 _ Q _ _ ~1 3 /day) (5 g/m 3 ) = 7 _ 5 g/m2•day 687,000 m 2 (7.5 g/m 2 day) (30 days)= 225 g/m 2 -mo Total daily volume exchange= 1,030,500 m 3 (1,030,500 m 3 /day) (5 g/m 3 ) __ 2 7.5 g/m -day 687,000 m 2 (7.5 g/m 2 -ctay) (30 days)= JlO = J27 J26 2 225 g/m mo 2 2 J 10 = 0.25 g/m day= 0.1 g/m day = 0. 15 g/m 2 . day ( 0. 15 g/m 2 . day) ( 30 days) 2 = 4. 5 g/m mo Reference w O'\ 0
PAGE 381
Table 0-l continued Flow Description Ingestion of organic matter by oyster reef organisms Ingestion of water column organic matter by benthic invertebrates Sedimentation of organic matter from water column to sediments Calculation Assume steady state population. 2 J 11 = 0.6 + 0.6 = 1 .2 g/m day (1.2 g/m 2 -day) (30 days)= 36 g/m 2 -mo Assume 10 % of ingestion by benthic inver tebrates is by suspension feeding. Sedimentation rate in inner bay= 5.26 g/m 2 ~day. Organic matter content of sediment= 5 % (5.26 g/m 2 day) (0.05) = 0.263 g/m 2 day (0.2~3 g/m 2 -day) (30 days)= 7.89 g/m 2 -mo Reference Cottrell, 1974 Cottrell, personal communication w ' __,
PAGE 382
Table 0-1 continued Fiow Description Bacteria 1 respiration in water column Phosphorus input from sa 1 t marsh to inner bay Calculation Water column respiration as measured with dark bottles= 0.24 g/m 2 ~day Water column gross production= 0.93 g/m 2 -day Assume phytoplankton respiration is 30% of gross production. Bacterial respiration= total water column respiration minus phytoplankton respiration. 2 J 14 = 0.93 0.28 = 0.65 g/m day 2 2 (0.65 g/m •day) (30 days)= 19.5 g/m •mo Detrital input from marsh= 1 g/m 2 -day (see calculation for J 7 ). Assume 1 g of detritus came from 1 g of live plant. Assume 90% of phosphorus leached from plant upon death. Juncus roemerianus is 0.15% phosphorus. Reference Table 6 Table 6 Day et _tl., 1973 de la Cruz, 1973 w O"l N
PAGE 383
Table 0-1 cont1nued Flow Description Input of phosphorus from discharge canal and offshore to inner bay Tidal exchange of phosphorus off shore Calculation Concentration of phosphorus in canal and offshore water is the same. Therefore, J 16 = total volume exchange x concentration (1,030,500 m 3 /day) (0.05 q/m 3 ) J 16 = 687,000 m 2 = 0.075 g/m 2 -day (0.075 g/m 2 -day) (30 days)= 2.25 g/m 2 mo J 17 = total volume exchange x concentration (1,030,500 m 3 /day) (0.05 g/m 3 ) J 17 = 687,000 m 2 = 0.075 g/m 3 -day (0.075 g/m 2 day) (30 days) = 2.25 g/m 2 , mo Reference w ' w
PAGE 384
Table D-l continued Fl ov-1 Description Sediment respiration Ingestion of sediment organics by benthic invertebrates Calculation By difference after subtracting all other respiration from total system respiration as measured by the free-water diurnal oxygen change method. Assume total respiration is twice night respiration. J 18 = total respiration J 3 J 14 J 25 J 18 = 4.34 0.96 0.65 0.30 0.09 0.6 = 1.74 g/m 2 ctay (l.74 g/m 2 day) (30 days)= 52.2 g/m 2 -mo Assume 90 % of ingestion to benthic inverte brates is by deposit feeding. Jl9 = (J20 + J24) (0.9) Jl9 (0.53 + 0.53) (0.9) 2 = = 0.954 g/m day = 28.62 g/m 2 •mo Reference
PAGE 385
Table D-1 continued Flow Description Feces production by benthic in vertebrates Mortal ity of benthic inverte brates Mortality of fishes Oyster feces, pseudofeces and mortality Calculation Assume 50 % assimilation of organic intake. 2 Therefore, J 20 = J 24 = 0.53 g/m day = 15.9 g/m 2 -mo Assume to be 2.5% of standing stock per day. 2 2 (3.5 g/m) (0.025/day) = 0.09 g/m ;day (0.09 g/m 2 -day) (30 days)= 2.7 g/m 2 •mo Assume to be 2.5 % of standing stock per day. (2.5 g/m 2 -day) (0.025/day) = 0.063 g/m 2 day (0.06 g/m 2 •day) (30 days) = 1.89 g/m 2 •mo Assume 50 % assimilation efficiency. Assume steady state population so that 2 2 J23 = J 35 = 0.6 g/m •day= 18.05 g/m •mo Reference w " (J1
PAGE 386
Table D-l continued Flow Description Gross ass i mil ti on by benthic invertebrates Respriation of benthi c i nverte brates Predation on benthic inverte brates by fish Gross assimilation by fish Calculation Assume gross assimilation is 15 % of standing stock per day. (3.5 g/m 2 ) (0.15) = 0.53 g/m 2 •day (0.53 g/m 2 day) (30 days)= 15.9 g/m 2 •mo Assume respiration rate of 0.085 g dry wt . respired/g dry body wt/day. (3.5 g/m 2 ) (0.085/day) = 0.30 g/m 2 .day (0.3 g/m 2 -day) (30 days)= 9 g/m 2 '. mo Assume to be 4 % of standing stock per day. (2.5 g/m 2 day) (0.04/day) = 0.1 g/m 2 •day (O.l g/m 2 •day) (30 days)= 3/gm 2 ;mo Assume to be 10 % of standing stock per day. Reference Day tl _tl., 1973 w O'\ '
PAGE 387
Table D-1 continued Flow J27 (cont.) Description Respiration of fish Regeneration of phosphorus by fish respiration Calculation . 2 2 (2.5 g/m ) (0.1 / day) = 0.25 g/m •day (0.25 g/m 2 day) (30 days)= 7.5 g/m 2 mo Assume to be 3.6 % of dry body weight per day . (2.5 g/m 2 ) (0.036/day) = 0.09 g/m 2 •day (0.09 g/m 2 -day) (30 days)= 2.7 g/m 2 mo Assume organic matter is 0.5 % phosphorus by weight. J29 = (J28) (0.005) J 29 = (O.o9 g;m 2 -day) (0.005) = 0.00045 g/m 2 •day (0.00045 g/m 2 day) (30 days)= 0.0135 g/m 2 :mo Reference Prosser and Brown, 1961 w 0-, --.J
PAGE 388
Table D-1 continued Flow Description Regeneration of phosphorus by respiration of benthi c i nverte brates Re genera ti on of phosphorus by respiration of microbes in sediment Regeneration of phosphorus by res pi ration of benthic macrophytes Calculation Assume organic matter is 0.5 % phosphorus by weight. J 30 = (0.3 g/m 2 day) (0.005) = 0.0015 g/m 2 -day (0.0015 g/m 2 day) (30 days)= 0.045 g/m 2 •mo Assume organic matter is 0.5 % phosphorus by weight. J 31 = (l .74 g/m 2 day) (0.005) = 0.0087 g/m 2 day (0.0087 g/m 2 day) (30 days)= 0.26 g/m 2 ;mo Assume organic matter is 0.9% phosphorus by weight. Reference Van Breedveld, 1966, quoted in Jones 1968 w O'\ 0:,
PAGE 389
Tabie D-1 continued Flow J32 (cont.) Description Regeneration of phosphorus by respiration of oyster reefs Regeneration of phosphorus by respiration of microbes in water column Calculation J 32 = (0.96 g/m 2 -day) (0.009) . 2 = 0.00864 g/m •day (0 . 00864 g/m 2 -day) (30 days) = 0. 26 g/m 2 , mo Assume organic matter is 0.5 % phosphorus by weight. J 33 = (0.6 g/m 2 -day) (0.005) = 0.003 g/m 2 ,day (0.003 g/m 2 -day) (30 days) = 0.09 g/m 2 -mo Assume organic matter is 0.5% phosphorus by weight. Reference
PAGE 390
Tab l e Dl cont i nu e d Flow J34 (cont.) Description Oyster reef respiration Calculation 2 J 34 = (0.65 g/m ,day) (0.005) = 0.00325 g/m 2 •day (0.00325 g/m 2 day) (30 days) = 0.0975 g/m 2 -mo Biomass of oyster reef organisms= 290 g/m 2 of reef area. . Assume reef areas is 5 % of total bay area. Reef respiration= 0.083 g o 2 ;g dry wt/day Assume reef submerged 12 hours a day. Assume l g o 2 consumed equals l g organic matter respired. 2 (290) dry wt/m) (0.083 g o 2 ;g dry wt/day) = 24.07 g o 2 consumed/m 2 ,day (24.07 g o 2 ;m 2 •day) (0.05) (0.5) = 0.6 g/m 2 -day (0.6 g/m 2 -day) (30 days)= 18.05 g/m 2 •mo Reference Lehman, l974a,b w -...J 0
PAGE 391
Table D-1 continued Flow Description Gross photo synthesis of phytoplankton Respiration of phytoplankton Grazing of phytoplankton by oyster reef organisms Calculation As measured with light and dark bottle experiments= l .O g/m 2 ;day 2 2 (l .O g/m day) (30 days)= 30 g/m mo Assume respiration 30 % of gross photo synthesis (l . 0 g/m 2 -day) (0.3) = 0.3 g/m 2 -day (0.3 g/m 2 -day) (30 days)= 9.0 g/m 2 ,mo Assume biomass in steady state in summer, so that J38 + J39 = 1.0 0.3 0.45 + 0.45 = 0.7 g/m 2 .day Reference Tab 1 e 6 Day et tl, 1973
PAGE 392
Table D-1 continued Flow , u38 (cont.) Description Grazing of phyto plankton by benthic invertebrate filter feeders Uptake of phosphorus in photosynthesis Calculation Assume 90 % of grazing is by oyster reef organisms (0.7 g/m 2 ;day) (0.9) = 0.63 g/m 2 day 2 2 (0.63 g/m day) (30 days} = 18.9 g/m mo Assume 10 % of grazing is by benthic invertebrate filter feeders (see calculation for J 38 ). (0. 7 g/m 2 day) (0.1) = 0.07 g/rn 2 day (0.07 g/m 2 day) (30 days)= 2.1 g/m 2 mo Assume phytoplankton biomass is 0.5 % phosphorus . (l . O g/m 2 day) (0.005) = 0.005 g/m 2 day (0.005 g/m 2 -day) (30 days)= 0.15 g/m 2 -mo Reference w --.J N
PAGE 393
Table D-1 continued Fl O\
PAGE 394
Table D-1 continued Flow Description Input of phyto plankton from discharge canal and offshore Tidal exchange of phytoplankton biomass offshore Calculation Biomass of phytoplankton in discharge canal water and offshore water identical. Therefore, J 44 = total volume exchange x concentration (l ,030,500 m 3 ) (0.3 g/m 3 ) J 43 = 687,000 m 2 = 0.45 g/m 2 •day (0.45 g/m 2 -day) (30 days)= 2 13. 5 g/m -mo J 44 = total volume exchange x concentration (l ,030,500 m 3 /day) (0.3 g/m 3 ) J 44 = 687,000 m 2 = 0.45 g/m2day (0.45 g/m 3 -day) (30 days)= 2 13.5 g/m •mo Reference Figure 29 w -....J .&,,,
PAGE 395
Table D-l continued Flow Description Feces production by oysters of unassimilated phytoplan k ton Assimilation of phytoplankton ingested by benthic inverte brates Unassimilated phytoplankton ingested by benthic inverte brates Calculation Assume assimilation efficiency for oysters of 50 % 2 2 (0.63 g/m -day) (0.5) = 0.32 g/m -day (0.32 g/m 2 : day) (30 days) = 9.6 g/m 2 •mo Assumed assimilation efficiency for invertebrates of 50 % . 2 2 (0.07 g/m ; day) (0.5) = 0 . 035 g/m •day (0.035 g/m 2 •day) (30 days)= 1.05 g/m~ mo Assume assimilation efficiency for in vertebrates of 50 % . (0.07 g/m 2 day) (0.5) = 0.035 g/m 2 day (0.035 g/m 2 day) (30 days)= 1.05 g/m 2 •mo Reference w .......i u,
PAGE 396
376 Table 0-2. Initial and maximum values of forcing functions and storages for seasonal simulation model of inner bay (Figure 55) . Forcing functions Initial value Maximum value J 174000 kcal/m 2 -mo 240000 kcal/m 2 -mo 0 J7 2 30 g/m -mo 30 g/m 2 -mo J8 225 g/m 2 -mo 2 225 g/m mo Jl5 2 0.0405 g/m -mo 0.0405 g/m 2 -mo Jl6 2.25 g/m 2 -mo 2 . 25 g/m 2 -mo T 33c 40c Storage Initial value Maximum value Ql 40 g/m 2 75 g/m 2 Q2 0.05 g/m 2 0.15 g/m 2 Q3 5 g/m 2 10 g/m 2 Q4 160 g/m 2 250 g/m 2 Q5 3.5 g/m 2 l 0 g/m 2 Q6 2.5 g/m 2 10 g/m 2 Q7 0.3 g/m 2 1.5 g/m 2 R 14.5 g/m 2 20 g/m 2
PAGE 397
Table D-3. Coefficient 377 Calculation of transfer coefficients for seasonal simulation model of inner bay (Figure 55). All evaluations were made for summer conditions. Calculation J = k S = 174000 kcal/m 2 -mo 0 0 k = 174000 = l o 174000 87000 kR = 174000 = o. 5 = JoTQ 2 Q 1 = 8700 kcal/m 2 -mo Jl kl kR+k 1 TQ 2 Q 1 = (1)(87000) kl (174000)(33)(0.05)(40) = 0.00 7576 k = (l)( 95 . 7 ) = 8.3333 x 106 2 (174000)(33)(0.05)(40)
PAGE 398
378 Table 0-3 continued Coefficient Calculation k = (1)(0.8613) = 7 _ 5 x 10 -8 4 (174000)(33)(0.05)(40) k = 33 6 = 1.344 5 40 k = 33 6 = 1.344 6 40 J 7 is a constant flow J 8 is a constant flow
PAGE 399
379 Table D-3 continued Coefficient Calculation klO = (5)(i]~( 2 . 5 ) = 0.01091 36 kll = (5)(33)(14.5) = 0.01505 k = 7 89 = 1.578 13 5
PAGE 400
380 Table D-3 continued Coefficient Calculation J 15 is a constant flow J 16 is a constant flow k 2.25 45 17 = 0.05 = 28.62 kl9 = (160)(33)(3.5) = O.OOl 548
PAGE 401
381 Table D 3 continued Coefficient Calculation k 21 = = 0.7714 k 22 = 1 2 ~~ = 0.756 18.05 k23 = (5)(33)(14.5) = 0.007545 k 15. 9 24 = [(160)(33)(3 . 5)+(5)(33){3.5)] = 8.3331 X 104 k = g = 0.0223 25 (3 . 5) 2 (33)
PAGE 402
382 Table D-3 continued Coefficient Calculation 3 k26 = (3.5)(33)(2.5) = 0.0104 k 7.5 27 = [(5)(33)(2.5)+(3.5)(33)(2.5)] = 0.0107 k 2 7 = 0.01309 28 = (2.5) 2 (33) O.Ol 35 = 6.5455 X 10-S k 29 = (2.5) 2 (33) k30 = 0.045 = l. 1132 x 10-4 (3.5) 2 (33)
PAGE 403
383 Table D-3 continued Coefficient Calculation k = 0 26 = 4.9243 X 105 31 (160)(33) 0.26 -4 k 32 = ( 4 0)( 33 ) = 1.9698 x 10 0.09 -5 k33 = (5){33)(14.5f = 3.7617 x lO 0.0975 -4 k 34 = ( 5 )( 33 , = 5.9091 x 10 18.05 k35 = (5)(33)(14.5) = 0.00754
PAGE 404
384 Table 0-3 continued Co e ff i c i en t . Calculation (1)(30) _ -4 k36 = (174000)(33)(0.05)(0.3) 3 483 X lO 9 k37 = To.31TTIT = 0.9091 (l)(0.15) k40 = (174000)(33)(0.05)(0.3) = 1.7416 X 10-fi
PAGE 405
385 Table D-3 continued Coefficient Calculation _ (1)(87000) k41 (174000)(33)(0.05)(0.3) = l.OlOl 87000 k41R = 174000 = o. 5 k o.o 45 = 0.004545 42 = (0.3)(33) J 43 is a constant flow k 13. 5 45 44 = 7[3 =
PAGE 406
386 Table D-3 continued Coefficient Calculation
PAGE 407
Table D-4. Equations of Table 8 scaled for simulation of seasonal model of the inner bay given in Figure 55. + ( 75) ( k 5 ) 75 + (0.0840) [ Q7 5 1 ] * ( 7 5) ( k 6 ) + 75 + (0.0872) + 3.33 (0.0252) [ Q75 1 ] w co ....._,
PAGE 408
Table D-4 continued I Q2 l d l 0.15 J = dt + + + 0.0405 0. l 5 [ J l 5 l 0.0405 . (100) (40) (k 30 ) 0. l 5 ( 7 5 ) ( 4 0 ) (k 3 2 ) 0. l 5 (l.5) (40) k 42 )0 . 15) + 2.25 0. l 5 2 [46] + + + (100) (40) (k 29 ) + ----------'0. l 5 (250) (40) (k 31 ) 0. 15 (10) (40) (20) (k 33 ) o. 15 (10) (40) (k 34 ) 0. 1 5 [4~] w co c:i
PAGE 409
Table D-4 continued d [ifs] 10 dt = (0.0270) [ J 15 l 0.0405 .J 2 + (0. 2 9 6 9} + (0.2006) * + 10(0.1500) [ J 16 ] 2.25 [ 46] + (0.3283) [2~] + (0.1818) * . 2 + (0.1745) [;~] [/ 0 ] + (0.3940) [4ro] w co <.O
PAGE 410
Table 0-4 continued + (0 . 1576) d [ Ql 3 oJ ( 7 5 ) ( k 5 ) dt 10 + (10) (40) (20) (k 11 ) 1 0 10(0.4500) * 30 ra 225 7o w \ .o 0
PAGE 411
Table 0-4 continued + + (10) (40) (10) (k 10 ) 1 0 -7.3(0.0840) (0.3000) . + 10(0.1204) [~6] [41;] [2~] [ J38 7 ] 10(0.2250) [2~~] + 10(0.4500) [~~] + (0.2200) [;6] [46] [{~] + 25(0.0063) [;6] . w \.0 __,
PAGE 412
Table D-4 continued d [il 2 50J dt (250)(40)(10)(k 19 ) + 250 ( 1 5 ) ( 4 0 ) ( 2 0 ) k 4 5 [Q 7 7 [ T 7 [ R ] . 250 1.5J wJ 20 ( o. o 2 5 2) [~ 0 ] (0.0063) (10)(40)(20)(k 23 ) 250 (250) (40) (k 19 ) 250 (10)(40)(1.5)k 47 250 (0.0241) continued
PAGE 413
Table D-4 continued = (0.0030) [ Ql 6 0] (30) (4000) k 24 l 0 (10) (40) (1.5) k 46 + ---~, o-------'-(0.0031) [;~] (0.0344) [2~'6] (0.0073) [i: 0 ] [; 0 ] [, 0 .\] (100) (40) (k 25 ) l 0 continued w <.O w
PAGE 414
Table D-4 continued (10) (40) (10) (k 26 ) l 0 25(0.0031) [~6] w \.0 .i:::,
PAGE 415
Table 0-4 continued rQ6] a Lnr 2(4000) k 27 = cit 10 = (0.8560) ( (0.5000) [; 6] [4TO] [;~] + { 0 5000) 2 (0.5236) [~~] [/ 0 ] 2s (0.0030) [~i] (...,; \.C . (J1
PAGE 416
Table D-4 continued d 10 dt + l 3. 5 -,--:--s + (0.9000) ( 1. 5 ) 4 0 ) k 3 7 [ ~] [_r_l l . 5 l . 5 . 40J (10) {40) (1.5) k 39 1. 5 10(0.3636) continued w I.O a,
PAGE 417
Table D-4 continued l O ( 0 . 7 6 3 9 ) [ lQ .\] [ ; O] [ 2 \] 10(0.4500) *See Table 0-5 for scaling. l 0 ( 0 . 2 4 2 4 ) [ ~] [ ; o ] [ lQ .\] w I.O -....J
PAGE 418
Table 0-5. Scaling of terms associated with photosynthesis in equations in Table 8 for seasonal simulation model of the inner bay (Figure 55). d [~] (24oooo)(40)(0.15)(75)(k 2 J [ J ] / [Zo~ [o:f5] [;~] l 0d t -= ( l O )( 7 5) 24g000 \ -kR_+_(~4-0 )~(-0-. 1-5~)(=7-5 )~(-k~l )_I _T _]_I_Q_]_[_Q_]_ l 4o Lo . f 5 7 ) d [~] [ J ] ( [ Jo] [a:~s] [;~] = (0.2667) o lOdt 24 0000 (0.1111) + (0.7575) [i] [~] 40 0.15 w "-0 co
PAGE 419
Table D-5 continued l0dt ct[o+s] l0dt (240000)(40)(0.15)(75)(k 4 ) (10)(0.15) . [ T 7 [ Q2 7 [Q1J . [ J ] ( ifoj o.l5j 75 24 0~00 k + (40)(0.15)(75)(k 1 ) 1.l_] R . L40 (240000)(40)(0.15)(1.5)(k 40 ) [ J ] ( (10)(0.15) 240~00 (7.2xl0 7 )(k 4 ) 4.5 6 (l.44xl0 )(k 40 ) lO w I.O I.O
PAGE 420
Table D-5 continued d [~] [ T] [~] [~] 40 0. 15 1. 5 l Odt k41R + (40)(o.15)(1.5)k41 [fa]
PAGE 421
Table D-5 continued ) d [; = 10 ( 0.5016) lO d t [ J 7 ( [lo] [ifs] [2s] 240 ~ 00 J (o.os) + (0.9091) [i] [~] . 40 0.15
PAGE 422
402 Table 0-6. Potentiometer settings for initial run (Figure 57) of simulation of the seasonal model of the inner bay (Figure 5 5). Potentiometer Setting Potentiometer Setting l /10 kR 0.9000 k23 0.0241 kl 0.7575 k24 l .000 k2 0.2667 k25 0.8920 k3 0.0872 k26 0.4156 k4 0. 1200 k27 0.8560 k 5 0.0840 k28 0.5236 k6 0.0252 k29 0.1745 J7 0.3000 k30 0.2969 JS 0.2250 k31 0.3283 kg 0.4500 k32 0.3940 klO 0.4364 k33 0.2006 k 11 0. 1204 k34 0. 1576 kl2 0.2200 k36 0.5016 kl3 0.0063 k37 0.3636 kl4 0.4728 k38 0. 1054 Jl5 0.0270 k39 0.2424 Jl6 0. 1500 k40 0.2508 kl7 0.4500 k41 0~9091 kl8 0.412 1/100 k 4 lR 0.2000 . kl9 0.0619 k42 0.1818 k20 0.0344 J43 0.9000 k21 0.0031 k44 0.4500 k 22 0.0030 k45 0.0321
PAGE 423
403 Table D-6 continued Potentiometer Setting Potentiometer Setting k46 0. 1818 B 0.2250 k47 0.0073 C 0.7500 ICQ 1 0.5333 D 0.2500 ICQ 2 0.3333 E 0.0333 ICQ 3 0.5000 F 0.8333 ICQ 4 0.6400 G 0.2500 ICQ 5 0.3500 H 0.5000 0CQ 6 0.2500 I 0.5000 . ICQ 7 0.2000 L 0.2500 w 0.0523 M 0.3333 w 0.0523 R 0.7250 A 0.6000
PAGE 424
404 Table D-7. Potentiometer setting s for EAi 580 variable diode function generator used to produce the seasonal cycle of sunlight given in Figure 56 for the simulation of the seasonal model of the inner bay (Figure 55). The function was pro grammed to begin on July 1st. X f ( X ) 0.0000 0.6875 0.0417 0.6650 0. 1250 0.6138 0.2083 0.5525 0.2917 0.5050 0.4583 0 . 3688 0.5417 0.3888 0.6250 0 . 4738 0.7917 0.7000 0 . 8750 0.7488 l. 000 0 . 6875
PAGE 425
Figure D-1. Analog computer diagram of scaled equations given in Tables D-4 and 0-5 for the seasonal simulation model of the inner bay (Figure 55) .
PAGE 426
i t bffiYI~ 0 0)
PAGE 427
APPENDIX E DOCUMENTATION OF DATA USED IN SUMMARY DIAGRAMS OF SUMMER STOCKS AND FLOWS FOR THE INNER DISCHARGE BAY (Figure 38) AND SOUTH INTAKE AREA (Figure 39)
PAGE 428
Table E-1. Documentation of numbers appearing on Figure 38 of the inner discharge bay ecosystem affected by the thermal discharge of the power plant. Storage R Description Total phosphorus in water colu m n Biomass of p h ytoplankton B i omass of benthic macrophytic plants O r ganic matter in water column Biomass of resident fish Biomass of benthic m acro invertebrates Organic matter in sediments Biomass of oyster Calculation Assumed similar to outer discharge bay. Measured at Crystal R iver. Measured at Crystal River. Measured at Crystal River as total organic carbon. Measured at Crystal River. Dry weight assumed 25 % of fresh weight. Measured at Crystal River. Measured at Crystal River. Value is content of top centimeter of sediment. Measured at Crystal River. Reefs assumed to be 5 % of bay area. {270 g/m 2 of reef)(0.05) = ~14 g/m 2 Reference McKellar, 1975 Figure 29; Gibson, 1 975 Figure 25; Van Tyne, 1974 Figure 28; Gibson, 1975 Figure 27; Adams, 1974 Figure 26; Evink and Green, 1974 Cottrell, 1974 Lehman, l974a,b 0 0:,
PAGE 429
Table Flow Jl , u2 J3 J4 E-1 continued Description Sunlight at water surface Gross production of phytoplankton Phytoplankton respiration Gross production of benthic plants Respiration of benthic plants Respiration of mic r obes in the sediments Calculation Eleven year average at Tampa, Fla. Measured at Crystal River with light and dark bottles. Assumed to be 30 % of gross production. . 2 2 (l.O g/m •day)(0.3) = 0.3 g/m •day Total community gross primary production minus phytoplankton primary production. 4.5 g/m 2 •day 1.0 g/m 2 •day = 3.5 g/m 2 •day Assumed to be 30 % of gross production . (3.5 g/m 2 •day)(0.3) = l .05 g/m 2 •day Assigned by difference after all other respiratory pathways evaluated. J 6 = Total respiration J 3 J 5 J7 J 8 Jg JlO J6 = 5 0.3 1.05 0.34 0.07 0.1 0.58 = 2.56 g/m 2 •day Reference Figure 13 Table 3. Day et~-, 1973 Day et ~-, 1973
PAGE 430
Table E-1 continued Flow Description Respiration of benthic macro invertebrates Respiration of resident fish Respiration of microbes in water column Respiration of oyster reef organisms Calculation Assume respiration rate of 0.085 g dry wt respired/g dry body wt/day. (4 g/m 2 )(0.085) = 0.34 g/m 2 •day Assume to be 3.6 % of dry body weight per day. (2 g/m 2 )(0.36) = 0.72 g/m 2 •day Water column respiration from dark bottle measure ments minus phytoplankton respiration. 0.3 g/m 2 •day -0.3 g/m 2 •day = <0. l g/m 2 •day Respiratory rate of reefs measured at Crystal River. (14 g/m 2 )(0.083 g/m 2 •day) = l .16 g/m 2 •day Assume reefs submerged 12 hours per day. (1.16 g/m 2 •day)(0.5) = 0.58 g/m 2 •day Reference Day et~-, 1973 Prosser and Brown , 1961 Lehman, 1974a,b ....., 0
PAGE 431
Table E-2. Documentation of numbers appearing on Figure 38 of the south intake area ecosystem unaffected by the thermal plume of the power plant. Storage o, R Description Total phosphorus in water column Biomass of phytoplankton Biomass of benthic macrophytic plants Organic matter in water column Biomass of resident fish Biomass of benthic macroinvertebrates Organic matter in sediments Biomass of oyster reef organisms Calculation Assumed similar to outer control bay. Measured at Crystal River. Measured at Crystal River. Measured at Crystal River as total organic carbon. Measured at Crystal River. Dry weight assumed 25% of wet weight. Measured at Crystal River. Measured at Crystal River. Value is content of top centimeter of sediment. Measured at Crystal River. Reef assumed to be 5% of bay area. (290 g/ml•day)(0.05) = 'vl5 g/m2 Reference McKellar, 1975 Figure 29; Gibson, 1975 Figure 25; Van Tyne, 1974 Figure 28; Gibson, 1975 Figure 27; Adams, 1974 Figure 26; Evink and Green, 1974 Cottrell, 1974 Lehman, 1974a, b
PAGE 432
Table Flow Jl J 2 J3 J4 E-2 continued Description Su n light at w ater surface Gross production of phytoplankton Phytoplankton respiration Gross production of benthic plants Respiration of benthic plants Respiration of microbes in the sediments Calculation Eleven year average at Tampa, Fla. Measured at Crystal River with light and dark bottles. Assumed same percentage of total gross production as for fall. Assumed 30 % of gross production. 2 2 (0.46 g/m •day)(0.3) = 0 . 14 g/m •day Total community primary production minus phyto plankton primary production . 2 2 2 8.8 g/m •day 0.46 g/m •day= 8.34 g/m •day Assume 30 % of gross production. 2 2 8.34 g/m •day)(0.3) = 2.50 g/m •day Assigned by difference after all other respiratory pathways evaluated. J 6 = Total respiration J 3 J 5 J 7 J 8 J 9 JlO J6 = 11.4 0 . 14 2.50 1 . 7 0.07 0.09 0.75 = 6.15 g/m 2 •day Reference Figure 13 Table 4. N
PAGE 433
Table E-2 continued Flow Description Respiration of benthic macro invertebrates Respiration of resident fish Respiration of microbes in 1 1Ja ter co 1 umn Respiration of oyster reef organisms Calculation Reference Assumed respiration rate of 0.085 g dry wt. respired/g Day et al., 1973 dry body wt/day. (20 g/m 2 )(0.085) = 1.7 g/m 2 •day Assumed to be 3.6 % of dry body weight per day . (2 g/m 2 )(0.036) = 0.072 g/m 2 •day Water column respiration from dark bottle measurements minus phytoplankton respiration. 0.23 g/m 2 •day 0.14 g/m 2 •day = 0.09 g/m 2 •day Assume 5 % of dry body weight per day. (15 g/m 2 )(0 . 05) = 0.75 g/m 2 •day Prosser and Brown, 1961 Day et tl•, 1973 w
PAGE 434
LITERATURE CITED Adams, C. A. 1972. Food habits of juvenile pinfish (Lagodon rhomboides), silver perch (Bairdiella chrysura), and spotted seatrout (Cynoscion nebulosus) of the estuarine zone near Crystal River, Florida. M. S. thesis, University of Florida, Gainesville. Adams, C. A. 1974. Comparison of selected vertebrate populations in two estuaries adjacent to the Crystal River power generation facility, pp. III-87 to 111-105 . In Crystal River Power Plant. Environmental Considerations. Final Report to the Interagency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Adams, C. A., C. J. Bilgere, and S. C. Snedaker. 1974. Impingement data record, pp. III-165 to III-314. In Crystal River Power Plant. Environmental Con sfderations. Final Report to the lnteragency Research Advisory Committee. Florida Power Cor poration, St. Petersburg. Adams, C. A., M. J. Oesterling, and S. C. Snedaker. 1974. Effects of impingement and entrapment on the Crys tal River blue crab, Callinectes sapidus Rathban, population, pp. 111-107 to III-146. In Crystal River Power Plant. Environmental ConsTderations. Final Report to the lnteragency Research Advisory Committee. Florida Power Corporation, St. Peters burg. Adams, J. R., D. G. Price, and F. L. Cloqston. 1974. An evaluation of the effect of Morro Bay power plant cooling water discharge on the intertidal macroinvertebrate community. Pacific Gas and Electric Company, San Ramon, California. Allen, S. D. and T. D . Brock. 1968. The adaptation of heterotrophic microcosms to different temperatures. Ecology 49:343-346. 414
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415 American Public Health Association. 1955. Standard Methods for the Examination of Water, Sewage, and Industrial Wastes, 10th ed. N. Y. American Public Health Association. 1971. Standard Methods for the Examination of Water and Wastewater, 13th ed. N. y. Antia, N. J., C. D. McAllister, T. R . Parsons, K. Stephens, and J. D. H. Strickland. 1963. Further . measurements of primary production using a large-volume plastic sphere. Limnol. Oceanogr. 8:166-183. Bedient, P. B. 1972. A two-dimensional transient numerical model for radionuclide transport in tidal waters. M. S. thesis, University of Florida~ Gainesville. Beyers, R. J. 1962. The metabolism of twelve aquatic labora tory microecosystems. Ph. D. dissertation, Univer sity of Texas, Austin. Boynton, W. R. 1975 . Energy basis of a coastal region: Franklin County and Apalachicola Bay, Florida. Ph. D. dissertation, University of Florida, Gaines ville. Brock, T. D. 1967a . Life at high temperatures. Science 158:1012-1019. Brock, T. D. 1967b. Relationship between standing crop and primary productivity along a hot spring thermal gradient. Ecology 48:566-571. Brock, T. D. 1969. Vertical zonation in hot spring algal mats. Phycologia 8:201-205. Brock, T. D. 1970 . High temperature systems. Ann. Rev. Ecol. Sys. 1:191-220. Brock, T. D. and M. L. Brock . 1969. Recovery of a hot spring community from a catastrophe. J. Phycol. 5:75-77. Brylinsky, M. 1972. Steady-state sensitivity analysis of energy flow in a marine ecosystem, pp. 81-101. In Systems Analysis and Simulation in Ecology, Vol.-!!. B. C. Patten (ed.). Academic Press, Inc., N. Y. Bullock, T. H. 1955. Compensation for temperature in the metabolism and activity of poikilotherms. Biol. Rev. 39:311-342.
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416 Carder, K. L. 1975. Attachment no. 5. In Summary Analy sis and Supplementary Data Reportto the Inter agency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Carr, vi. E. S. and C. A. Adams. 1973. Food habits of juvenile marine fishes occupying seagrass beds in the estuarine zone near Crystal River, Florida. Trans. Amer. Fisheries Soc. 102:511-540. Central Electricity Generating Board. Hydrobiological studies in the River Blackwater in relation to the Bradwell Nuclear Power Station. A joint re port of the studies undertaken during 1959-1965 by the Central Electricity Generating Board and Ministry of Agriculture, Fisheries and Food . Publ. by Central Electricity Generating Board, Great Britain. 65 p. (undated). Chen, C. W. and G. T. 0rlob. 1972. Ecologic simulation for aquatic environments. Final report to Office of Water Resources Research, U. S. Dept. of Inter ior. Accession no. ~03-07164. Nat. Tech. Info. Ser., Springfield, Virginia. Churchhil l, M. A., R. A. Buckingham, and H. L. Elmore. 1962. The prediction of stream reaeration rates. Tennessee Valley Authority, Division of Health and Safety, Environmental Hygiene Branch, Chatta nooga, Tennessee. Conover, J. T. 1964 . The ecology, seasonal periodicity and distribution of benthic plants in some Texas lagoons. Botanica Mar. 7:4-41. Copeland, B. J. and W. R. Duffer. 1964. The use of a clear plastic dome to measure gaseous diffusion rates in natural waters. Limnol. 0ceanogr. 9: 494-499 . Cottrell, D. J. 1974. Sediment composition and distribu tion at Crystal River power plant, pp. II-309 to II-377. In Crystal River Power Plant. Environ mental Considerations. Final Report to the Inter age n cy Research Advisory Committee. Florida Power Corporation, St. Petersburg. Davis, H. L. III. 1971. Evaluation and use of the par tial pressure of carbon dio x ide in studying metabo lism in heated experimental ecosystems. Ph. D. dissertation, North Carolina State University, Raleigh.
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417 Dawson, S. E. 1955. A study of the oyster biology and hydrography at Crystal River, Florida. Publ. Inst. Mar. Sci. Univ. Tex. 4:279-302. D a y , J . W . , W . G . Sm i t h , P . W . W a g n e r , a n d ~J . C . S tow e . 1973. Community structure and carbon budget qf a salt marsh and shallow bay estuarine syst~m in Louisiana. Publication no. LSU-SG-72-04, Center for Wetland Resources, Louisiana State University, Baton Rouge. de la Cruz, A. A. 1973. The role of tidal marshes in the productivity of coastal waters. Assoc. Southeast ern Biol. Bull. 20:147-156. Dillon, C. R. 1971~ A comparative study of the primary productivity of estuarine phytoplankton and macro benthic plants. Ph. D. dissertation, University of North Carolina, Chapel Hill. Duke, M. E. L. 1967. A production study of a thermal spring. Ph. D. dissertation, University of Texas, Austin. Eley, R. L. 1970. Physicochemical limnology and community metabolism of Keystone Reservoir, Oklahoma. Ph. D. dissertation, Oklahoma State University, Still water. Esch, G. W. Thermal Ecology, II. AEC Symposium Series (in press). Evink, G. and B. Green. 1974. Benthic invertebrate comparisons in two estuaries adjacent to the Crys tal River power generation facility, pp. III-1 to III-87. In Crystal River Power Plant. Environ mental Considerations. Final Report to the Inter agency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Eyring, H. and E. M. Eyring. 1963. Modern and Chemical Kinetics. Van Nostrand Reinhold Co., N. Y. Florida Power Corporation. 1972. Crystal River Unit 3. Applicant's Environmental Report, Vol. l. Gibbons ,, J. W. and R. R. Sharitz (eds.). 1974a. Thermal Ecology. AEC Symposium Series (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia.
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418 Gibbons, J. W. and R. R. Sharitz. 1974b. Thermal altera tion of aquatic ecosystems. JI.mer. Sci. 62:660-670. Gibson, R. 1975. Attachments no. 2 and 8. In Summary Analysis and Data Report to the Interagency Re search Advisory Committee. Florida Power Corpora tion, St. Petersburg. Grimes, C. B. 1971. Thermal addition studies of the Crystal River steam electric station. Prof. Paper Ser. no. 11. Florida Department of Natural Re sources, Marine Research Laboratory, St. Petersburg. Grimes, C. B. and J. A. Mountain. 1971. Effects of ther mal effluent upon marine fishes near the Crystal River steam electric station. Prof. Paper Ser. no. 17. Florida Department of Natural Resources, Marine Research Laboratory, St. Petersburg. Gurtz, M. E. and C. M. Weiss. 1974. Effect of thermal stress on phytoplankton productivity in condenser cooling water, pp. 490-507. In Thermal Ecology. J. W. Gibbons and R. R. Sharitz (eds.). AEC Symp. Ser. (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia. Hall, C. A. S. 1970. Migration and metabolism in a stream ecosystem. Ph. 0. dissertation, Univer sity of North Carolina, Chapel Hill, Hall, C. A. S. 1974. Models and the decision making process: The Hudson River power plant case, pp. 203-218. In Ecosystem Analysis and Prediction. S. A. Levin{ed.). Proceedings of a conference, Alta, Utah. Soc. Ind. Appl. Math., Philadelphia. Hellier, T. R., Jr. 1962 . . Fish production and biomass studies in relation to photosynthesis in the Laguna Madre of Texas. Publ. Inst. Mar. Sci. Univ. Tex. 8:1-22. Homer, M. L. 1975. Seasonal abundance, biomass, diver sity and trophic structure of fish in a salt marsh tidal creek affected by a coastal power plant. In Thermal Ecology, II. G. W. Esch (ed.). AEC Symposium Series (in press). Huber, W. C. and D. R. F. Harleman. 1968. Laboratory and analytical studies of the thermal stratifica tion of reservoirs. Rept. No. 112. Hydrodynamics Laboratory. Massachusetts Institute of Technology, Cambridge.
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419 Jensen, L. D. (ed.). 1974a. Environmental responses to thermal discharges from the Indian River Station, Indian River, Delaware. Electric Power Research Institute, Palo Alto, California. Jensen, L : D. (ed.). 1974b. Environmental responses to thermal discharges from the Chesterfield Station, James River, Virginia. Electric Power Research Institute, Palo Alto, California. Jensen, L. D. (ed.) . . 1974c. Entrainment and intake screen ing. Proceedings of the Second Entrainment and Intake Screening Workshop. Electric Power Research Institute, Palo Alto, California. Jones, J. A. 1968. Primary productivity of the tropical marine turtle grass, Thalassia testidinum Koenig, and its epiphytes. Ph. D. dissertation, Univer sity of Miami (Flnrida). Kelley, R. A. 1971. The effects of fluctuating tempera ture on the metabolism of laboratory freshwater microcosms. Ph. D. dissertation, University of North Carolina, Chapel Hill. Kemp, W. M. 1974. Ecosystems of the intake and discharge canal, pp. I-36 to I-337. In Crystal River Power Plan t . Environmental Considerations. Final Report to the Interagency Research Advisory Com mittee. Florida Power Corporation, St. Petersburg. Kemp, W. M., W. H.B. Smith, H. N. McKellar, M. E. Lehman, M. Homer, D. L. Young, and H. T. Odum. 1975. Energy cost-benefit analysis applied to power plants near Crystal River, Florida. In Models as Ecological Tools: Theory and CaseHistories. C. Hall and J. Day {eds.). John Wiley and Sons, N. Y. (in press). Klausewitz, R. H. 1973. Diffusion model for a shallow, barricaded estuary. M. S. thesis, University of South Florida, St. Petersburg. Kull berg, R. G., 1966. The distribution of algae in six thermal spring effluents of Western Montana. Ph . D. dissertation, Michigan State University, East Lansing.
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420 Lehman, M. E. 1974a. Oyster reefs at Crystal River and their adaptation to thermal plumes, pp. 1-269 to 1-361. In Crystal River Power Plant. Environ mental Considerations. Final Report to the Inter agency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Lehman, M. E. 1974b. Oyster reefs at Crystal River, Florida and their adaptation to thermal plumes. M. S. thesis, University of Florida, Gainesville. Lyons, W. G., S. P. Cobb, D. K. Camp, J. A. Mountain, T. Savage, L. Lyons, and E. A. Joyce, Jr. 1971. Preliminary inventory of marine invertebrates collected near the electrical generating plant, Crystal River, Florida, in 1969. Prof. Paper Ser. no. 14. Florida Department of Natural Re sources, Marine Research Laboratory, St. Peters burg. Mature, F. J. 1974. Zooplankton research, pp. IV-1 to IV-392. In Crystal River Power Plant. Environ mental Considerations. Final Report to the Inter agency Research Committee. Florida Power Corpora tion, St. Petersburg. McConnell, W. J. 1962. Productivity relations in carboy microcosms. Limnol. Oceanogr. 7:335-343. McKellar, H. N. 1974. Metabolism and models of outer bay plankton ecosystems affected by power plant, pp. 1-519 to 1-269. In Crystal River Power Plant. Environmental ResearchAdvisory Committee. Flor ida Power Corporation, St. Petersburg. McKellar, H. N. 1975. Metabolism and models of estuarine bay ecosystems affected by a coastal power plant. Ph. D. dissertation, University of Florida, Gainesville. Miller, P. C. 1974. Potential use of vegetation to en hance cooling in holding ponds, pp. 610-628. l!!_ Thermal Ecology. J. vJ. Gibbons and R.R. Sharitz (eds.). AEC Symp. Ser. (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia. Morgan, R. P. and R. G. Stross. 1969. Destruction of phytoplankton in the cooling water supply of a steam electric station. Ches. Sci. 10:165-171.
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421 Morowitz, H. J. 1968. Energy Flow in Biology. Academic Press, N. Y. Mountain, , J. A. 1972. Further thermal addition studies at Crystal River, Florida with an annotated check list of marine fishes collected 1969-1971. Prof. Paper Ser. no. 20. Florida Department of Natural Resources, Marine Research Laboratory, St. Petersburg. Nixon, S . . and H. T. Odum. 1970. A model for photore generation in brines. ESE Notes, Vol. 7, Dept. Envr. Sci. Eng., University of North Carolina, Chapel Hill. Nixon, S. W. and C. A. Oviatt. 1973. Ecology of a New England salt marsh. Ecol. Mon. 43:463-498. North, W. F. 1968. Biological effects of a heated water discharge at Morro Bay, California. Paper pre sented at the VI International Seaweed Symposium, Madrid, Spain. Odum, H. T. 1957. Primary production measurements in eleven Florida springs and a marine turtle-grass community. Limnol. Oceanogr. 2:85-97. Odum, H. T. 1963. Productivity measurements in Texas turtle grass and the effects of dredging an intracoastal channel. Publ. Inst. Mar. Sci. Univ. Tex. 9:48-58. Odum, H. T. 1967. Biological circuits and the marine ecosystems of Texas, pp. 99-157. In Pollution and Marine Ecology. T. A. Olson and F. J. Burgess {eds.). Interscience Publ., N. Y. Odum, H. T. 1971. Environment, Power, and Society. Wiley-Interscience, N. Y. Odum, H. T. 1972. An energy circuit language for eco logical and social systems: Its physical basis, pp. 139-211. In Systems Analysis and Simulation . in Ecology, Vol. II, B. C. Patten {ed.). Academic Press, Inc., N. Y. Odum, H. T. 1973. Chemical cycles with energy circuit models, pp. 224-259. In The Changing Chemistry of the Oceans. D. Dyrssen and D. Jagner (eds.). Wiley-Interscience, N. Y.
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422 Odum, H. T. 1974a. Energy: Crisis to Steady State. 3rd draft to be revised. Storter Printing Co., Gainesville, Florida. Odum, H. T. 1974b. Energy cost-benefit models for evaluating thermal plumes, pp. 628-648. In Thermal Ecology. J. W. Gibbons and R. R.Sharitz (eds.). AEC Symp. Ser. (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia. Odum, H. T. 1975. Marine ecosystems with energy circuit diagrams, pp. 127-151. In Modelling of Marine Systems. J. C. J. Nihou-1-(ed.). Elsevier Sci. Publ. Co., N. Y. Odum, H. T., R. J. Beyers, and N. Armstrong. 1963. Consequences of small storage capacity in nanno plankton pertinent to measurement of primary production in tropical waters. J. Mar. Res. 21: 191-198. Odum, H. T. and C. M. Hoskins. 1958. Comparative studies on the metabolism of marine waters. Publ. Inst. Mar. Sci. Un-iv. Tex. 5:16-46. Odum, H. T., W. M. Kemp, H. H. B. Smith, H. N. McKellar, D. L. Young, M. E. Lehman, M. L. Homer, L . . H. Gunderson, and A. D. Merriam. 1974. An energy evaluation and alternatives for management, pp. 1-13 to II-255. In Crystal River Power Plant. Environmental Consfderations. Final Report to the Interagency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Odum, H. T. and R. F. Wilson. 1962. Further studies on reaeration and metabolism of Texas bays, 1958-1960. Publ. Inst. Mar. Sci. Univ. Tex. 8:23-55. Phillips, R. C. 1960. Observations on the ecology and distribution of the Florida seagrasses. Fla. St. Bd. Conser., St. Petersburg. Prof. Paper Ser. no. 2. Phinney, H. K. and C. D. McIntire . 1965. Effects of temperature on metabolism of periphyton communi ties developed in laboratory streams. Limnol. Oceanogr. 10:341-344. Prosser, C. L. and F. A. Brown. 1961. Comparative Animal Physiology. W. B. Saunders Co., Phila delphia.
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423 Raymont, J. E. G. 1963. Plankton and Productivity in the Oceans. Pergamon Press, Oxford. Riley, G. A. 1946. Factors controlling phytoplankton populations of Georges Bank. J. Mar. Res. 6: 54-73. Riley, G. A. 1947. A theoretical analysis of the zoo plankton population of Georges Bank. J. Mar. Res. 6:104-113. Rodgers, B. A., R. H. Klausewitz, and R. J. Keller. 1974. Results of bathymetry and bottom type analysis of the Crystal River power plant discharge basin. Independent Environmental Study of Thermal Effects of Power Plant Discharge, Tech. Report no. 5. Dept. Mar. Sci., University of South Florida, Tampa. Saville, T. 1966. A study of estuarine pollution prob lems on a small unpolluted estuary and a small polluted estuary in Florida. Bull. Ser. no. 125. Vol. 20. Eng. Progress at the University of Florida, Gainesville. Smith, W. H. B., H. McKellear, D. L. Young, and M. E. Lehman. 1974. Total metabolism of thermally affected coastal systems on the west coast of Florida, pp. 475-489. In Thermal Ecology. J . i.J. G i b b on s and R . R . S h a r i t z ( eds . ) . A EC Symp. Ser. (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia. Snedaker, S. C. and J. Johnson. 1975. Attachment no . ll. In Summary Analysis and Supplemental Data Reportto the Interagency Research /1.dvisory Committee. Florida Power Corporation, St. Peters burg. Sollins, P. 1970. Measurement and simulation of oxygen flows and storages in a laboratory blue-green algal mat ecosystem. M . . S. thesis, University of North Carolina, Chapel Hill. Steele, J. H . 1974. The Structure of Marine Ecosystems. Harvard University Press, Cambridge, Massachu setts.
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424 Steidinger, K. A. and J. F. Van Breedveld. 1971. Ben thic marine algae from waters adjacent to the Crystal River electric power plant (1969 and 1970). Prof. Paper Ser. no. 16. Florida Depart m~nt of Natural Resources, Marine Research Laboratory, St. Petersburg. Stockner, J. G. 1967. Observations of thermophilic algal communities in Mount Rainier and Yellowstone National Parks. Limnol. Oceanogr. 12:13-17. Stockner, J. G. 1968. Algal growth and primary produc tivity in a thermal stream. J. Fish. Res. Bd. Can. 25:2037-2058. Swindler, J. P. 1973. Sedimentology of the low-energy coastal region between the Crystal River and With lacoochee Rivers, Florida west coast. M. S. thesis, University of Florida, Gainesville. Tabb, D. C., D. L. Dubrow, and R. B. Manning. 1962. The ecology of northern Florida bay and adjacent estuaries. Tech. Ser. no. 39. St. Fla. Bd. Conser., St. Petersburg. Tanner, W . F. 1960. Florida coastal classification. Gulf Coast Assoc. Geol. Soc. Trans. 10:259-266. Tilly, L. J. 1974. Respiration and net productivity of the plankton community in a reactor cooling reservoir, pp. 462-474. In Thermal Ecology. J. ~J. Gibbons and R.R. Sharitz (eds.). AEC Symp. Ser. (CONF-730505). Nat. Tech. Info. Ser., Springfield, Virginia. Truesdale, G. A., A. L. Downing, and G. E. Lowden. 1955. The solubility of oxygen in pure water and sea water. J. Appl. Chem. 5:53-62. U. S. Department of Commerce. 1972. Tide Tables 1973. East Coast of North and South America including Greenland. U. S. Government Printing Office, Washington, D. C. Van Tyne, R. F. Florida Systems ville. 1973. Fall Quarter Progress Report to Power Corporation. Resource Management Program, University of Florida, Gaines
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425 Van Tyne, R. F. 1974. Comparisons of the benthic flora in estuaries adjacent to the Crystal River power generation facility, pp. 11-377 to 11-390. In C r y s t a l R i v e r P o \v e r P l a n t . E n v i r o n m e n t a l C on"=" siderations. Final Report to the Interagency Research Advisory Committee. Florida Power Cor poration, St. Petersburg. Van Tyne, R. F. 1975. Attachment no. 10. In Summary Analysis and Supplemental Data Reportto the lnteragency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Water Information Center, Inc. 1974. Climates of the States, Vol. l Eastern States. Port Washington, N . y . Wiegert, R. G. and P. C. Fraleigh. 1972. Ecology of Yellowstone thermal effluent systems: Net primary production and species diversity of a successional blue-green algal mat. Limnol. Oceangr. 17:215-228. Young, D. L. 1974. Salt marsh and the effect of ther mal plume, pp. 11-l to 11-93. In Crystal River Power Plant. Environmental ConsTderations. Final Report to the Interagency Research Advisory Committee. Florida Power Corporation, St. Petersburg. Zieman, J. C., Jr. 1970. The effects of a thermal effluent stress on the sea-grasses and macro algae in the vicinity of Turkey Point, Biscayne Bay, Florida. Ph. D. dissertation, University of Miami (Florida).
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BIOGRAPHICAL SKETCH Wade Hampton Barnes Smith was b~rn on July 3, 1944 at Louisville, Kentucky. He received his Bachelor of Arts degree from Emory University in August, 1966. He was awarded the Master of Arts in zoology from the University of North Carolina at Chapel Hill in August, 1971. This program was interrupted from January, 1969 through December, 1970 for employment with the E. I. DuPont Company. He entered the Systems Ecology program, Department of Environmental Engineering Sciences, Uni versity of Florida in March, 1971, and began employment with the Mitre Corporation, McLean, Virginia in Sep tember, 1975. 426
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I certify that I have read this study and that in my opinion it conforms to acceptable . standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. H. T. Odum, Chairman Graduate Research Professor of Environmental Engineering Sciences I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Associate Professor of Environmental Engineering Sciences I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. L E. Bullock Professor of Electrical Engineering
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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. / .,j , , ,,/ /.: / _, r J: J. Ewe l Assistant Professor of Botany I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. S. C. Snedaker Associate Professor of Biology and Living Resources, Rosenstiel School of Marine and Atmospheric Sciences, University of Miami (Florida) This dissertation was submitted to the Graduate Faculty of the College of Engineerin~J and to the Graduate Council, and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. August, 1976 Dean, Graduate School
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