C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor

Slough

Levee 31W

Road

Park Main

1

Old Ingraham Highway

Card Sound Road

Road

Park

Main

1

C-111

Barnes Sound

FLORIDA BAY

Levee 31W

McCormick Creek

Trout Creek

Taylor Creek

West

Highway

Creek

Card Sound Road

U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the

U.S. Geological Survey Priority

Ecosystem Science Program

and the

National Park Service Critical

Ecosystem Studies Initiative

WaterResources

Investigations

Report 03-4287

Two-Dimensional Hydrodynamic Simulation of

Surface-Water Flow and Transport to Florida Bay

Through the Southern Inland and Coastal Systems (SICS)
Two-Dimensional Hydrodynamic Simulation of 

Surface-Water Flow and Transport to Florida 

Bay through the Southern Inland and Coastal 

Systems (SICS)

By Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and

Carl R. Goodwin

U.S. Geological Survey

Water-Resources Investigations Report 03-4287

Prepared as part of the 

U.S. Geological Survey Priority Ecosystem Science Program and the

National Park Service Critical Ecosystem Studies Initiative

Tallahassee, Florida

2004
U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

Use of trade, product, or firm names in this publication is for descriptive purposes only 

and does not imply endorsement by the U.S. Geological Survey.

For additional information 

write to: 

U.S. Geological Survey

2010 Levy Avenue

Tallahassee, FL 32310

Copies of this report can be 

purchased from:

U.S. Geological Survey

Branch of Information Services

Box 25286

Denver, CO 80225-0286

888-ASK-USGS

Additional information about water resources in Florida is available on the internet 

at http://fl.water.usgs.gov
Contents III

CONTENTS

Abstract...................................................................................................................................................................................... 1

Introduction................................................................................................................................................................................ 2

Purpose and Scope ........................................................................................................................................................... 2

Description of Study Area................................................................................................................................................ 4

Previous Studies ............................................................................................................................................................... 6

Approach.................................................................................................................................................................................... 8

Model Selection and Required Enhancements................................................................................................................. 8

Data .................................................................................................................................................................................. 9

Topography .......................................................................................................................................................... 10

Vegetation ............................................................................................................................................................ 10

Water Level, Currents, and Discharge ................................................................................................................. 11

Salinity ................................................................................................................................................................. 11

Rainfall, Wind and Solar Radiation ..................................................................................................................... 11

Process Studies in Support of Model Development....................................................................................................... 15

Model Construction, Calibration, Testing, and Application .......................................................................................... 16

Description of Model Structure ............................................................................................................................................... 16

Governing Equations...................................................................................................................................................... 17

Numerical Solution Technique....................................................................................................................................... 18

Model Input Requirements............................................................................................................................................. 18

Enhancements for Everglades Application .................................................................................................................... 20

Rainfall as a Time-Varying Point Source ............................................................................................................ 20

Spatially Detailed Evapotranspiration Calculations............................................................................................. 20

Wind-Sheltering Coefficient ................................................................................................................................ 21

Computational Cells Adjacent to Flow Barriers .................................................................................................. 21

Other Code Modifications.................................................................................................................................... 21

Construction, Calibration, Testing, and Application of Flow and Transport Model ............................................................... 22

Computational Model Domain....................................................................................................................................... 22

Boundary Conditions ..................................................................................................................................................... 22

Water-Surface Boundary...................................................................................................................................... 22

Lateral Boundaries ............................................................................................................................................... 25

Model Parameters........................................................................................................................................................... 28

Computational Control Parameters ...................................................................................................................... 28

Wind Coefficients ................................................................................................................................................ 29

Evapotranspiration ............................................................................................................................................... 29

Frictional Resistance — Vegetation..................................................................................................................... 30

Flow Coefficient — Coastal Creeks .................................................................................................................... 30

Dispersion Coefficient ......................................................................................................................................... 33

Calibration...................................................................................................................................................................... 33

Testing............................................................................................................................................................................ 36

Verification .......................................................................................................................................................... 36

Sensitivity Analysis.............................................................................................................................................. 40

Model Application Examples......................................................................................................................................... 44

Flow Estimates at Unmeasured Locations ........................................................................................................... 44

Water Ponding and Salinity Distribution for Different Inflow and Wind Conditions......................................... 47

Using SICS Model for Restoration Testing ......................................................................................................... 48

Conclusions.............................................................................................................................................................................. 50

References Cited ...................................................................................................................................................................... 50

Appendix I—SWIFT2D Subroutines Modified for Southern Inland and Coastal Systems (SICS)....................................... 55

Appendix II—Excerpt from Input File Highlighting Areal Gains and Losses........................................................................ 56
IV Contents

PLATES [in back pocket]

1. Maps showing water levels and unit discharges for verification simulation

2. Plots showing water-level time series at field stations for verification simulation

3. Map of wetland flow velocities for verification simulation, July 29-31, 1997

4. Maps showing salinity distribution in verification simulation

5. Maps showing effects of wind and Taylor Slough bridge flows on water levels

6. Maps showing effects of wind and Taylor Slough bridge flows on salinity

FIGURES

1-6. Maps showing:

1. Southern Inland and Coastal Systems (SICS) study area and selected data-collection sites....................................3

2. Discharge, conductivity, and water-level data-collection sites within the study area...............................................5

3. Apparent resistivity in the Southern Inland and Coastal Systems (SICS) study area at 5-meter depth below 

land surface ...............................................................................................................................................................7

4. Vegetation features in the Southern Inland and Coastal Systems (SICS) study area..............................................12

5. Location of acoustic Doppler velocimeter measurements in the Southern Inland and Coastal Systems (SICS) 

study area ................................................................................................................................................................14

6. Map showing rainfall data-collection sites .............................................................................................................15

7. Space-staggered grid used in SWIFT2D.......................................................................................................................19

8-10. Maps showing:

8. Model grid, location of embankment barriers, and location of creeks in the study area........................................23

9. Land-surface elevation in grid cells ........................................................................................................................24

10. Model boundaries and data-collection sites used to determine discharge, conductivity, and 

water-level boundary conditions.............................................................................................................................26

11-13. Graphs showing spectral function of stage:

11. Downstream of structure S-21 ................................................................................................................................27

12. At McCormick Creek..............................................................................................................................................28

13. At Trout Creek ........................................................................................................................................................28

14. Map showing Manning’s n values used in the model ...................................................................................................31

15. Time-series plots showing measured and computed salinities at coastal creeks for calibration simulation in 

September 1997.............................................................................................................................................................34

16. Maps showing salinity distributions from the calibration simulation ...........................................................................35

17. Time-series plots showing measured and computed flows at coastal creeks for calibration simulation in 

September 1997.............................................................................................................................................................37

18. Map of wetland flow velocities for calibration simulation, September 22, 24, and 25, 1997 ......................................38

19-21. Graphs showing:

19. Measured and computed creek flows for verification simulation, August 1996 to July 1997 ...............................39

20. Model-computed flows at each section for verification simulation and map showing flow cross sections 

for Joe Bay .............................................................................................................................................................45

21. Model-computed flows at selected coastal creeks for verification simulation, August 1996 to July 1997............46

22. Hydrograph showing differences in computed flow at Trout Creek with and without wind effects for 

verification simulation...................................................................................................................................................47

23. Hydrographs showing measured and estimated daily mean flows for Taylor Slough bridge, 1989-99........................49

TABLES

1. Hydrologic and meteorological data-collection sites for the Southern Inland and Coastal Systems (SICS) study.............13

2. Summary of studies and research investigations used to develop the Southern Inland and Coastal Systems 

(SICS) model.......................................................................................................................................................................16

3. Stream friction terms and lengths and Manning’s n.............................................................................................................32

4. Results of sensitivity analysis...............................................................................................................................................42

5. Summary of sensitivity tests for coastal creeks....................................................................................................................44
Contents V

CONVERSION FACTORS, DATUMS, ABBREVIATIONS, AND ACRONYMS

Multiply By To obtain

meter (m) 3.281 foot

meter per second (m/s) 3.281 foot per second

meter squared per day (m2/d) 10.76 foot squared per day

meter squared per second (m2/s) 10.76 foot squared per second

cubic meter per second (m3/s) 35.31 cubic foot per second

kilometer (km) 0.6214 mile

square kilometer (km2) 0.3861 square mile

centimeter (cm) 3.281 x 10-2 foot

centimeter per second (cm/s) 3.281 x 10-2 foot per second

Vertical coordinate information is referenced to the National 

Geodetic Vertical Datum of 1929 (NGVD 29) and the North 

American Vertical Datum of 1988 (NAVD 88); horizontal 

coordinate information is referenced to the North American 

Datum of 1983 (NAD 83).

Acronyms

ADI Alternating-direction implicit

ATLSS Across Tropic Level Systems Simulation

CERP Comprehensive Everglades Restoration Plan

CESI Critical Ecosystem Studies Initiative

ENP Everglades National Park

GIS Geographic information system

GPS Global positioning system

HSE Hydrologic Simulation Engine

MAD Mean absolute difference

MD Mean difference

NOAA National Oceanic and Atmospheric Administration

NPS National Park Service

PES Priority Ecosystem Science

RMSD Root mean square difference

SFRSM South Florida Region Simulation Model

SFWMD South Florida Water Management District

SFWMM South Florida Water Management Model

SICS Southern Inland and Coastal Systems

SWIFT2D Surface-water integrated flow and transport in two dimensions

TBA Turning bands algorithm

USGS U.S. Geological Survey

Other Units of Abbreviations

g/L gram per liter

ppt part per thousand

s/m1/3 second per meter cube root

W/m2 watt per square meter

Abstract 1

Two-Dimensional Hydrodynamic Simulation of 

Surface-Water Flow and Transport to Florida Bay 

through the Southern Inland and Coastal 

Systems (SICS)

By Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

ABSTRACT 

Successful restoration of the southern Florida 

ecosystem requires extensive knowledge of the physical characteristics and hydrologic processes controlling 

water flow and transport of constituents through 

extremely low-gradient freshwater marshes, shallow 

mangrove-fringed coastal creeks and tidal embayments, and near-shore marine waters. A sound, physically based numerical model can provide simulations 

of the differing hydrologic conditions that might result 

from various ecosystem restoration scenarios. Because 

hydrology and ecology are closely linked in southern 

Florida, hydrologic model results also can be used by 

ecologists to evaluate the degree of ecosystem restoration that could be achieved for various hydrologic 

conditions.

A robust proven model, SWIFT2D, (SurfaceWater Integrated Flow and Transport in Two Dimensions), was modified to simulate Southern Inland and 

Coastal Systems (SICS) hydrodynamics and transport 

conditions. Modifications include improvements to 

evapotranspiration and rainfall calculation and to the 

algorithms that describe flow through coastal creeks. 

Techniques used in this model should be applicable to 

other similar low-gradient marsh settings in southern 

Florida and elsewhere.

Numerous investigations were conducted within 

the SICS area of southeastern Everglades National Park 

and northeastern Florida Bay to provide data and 

parameter values for model development and testing. 

The U.S. Geological Survey and the National Park 

Service supported investigations for quantification of 

evapotranspiration, vegetative resistance to flow, windinduced flow, land elevations, vegetation classifications, salinity conditions, exchange of ground and 

surface waters, and flow and transport in coastal creeks 

and embayments.

The good agreement that was achieved between 

measured and simulated water levels, flows, and salinities through minimal adjustment of empirical coefficients indicates that hydrologic processes within the 

SICS area are represented properly in the SWIFT2D 

model, and that the spatial and temporal resolution of 

these processes in the model is adequate. Sensitivity 

analyses were conducted to determine the effect of 

changes in boundary conditions and parameter values 

on simulation results, which aided in identifying areas 

of greatest uncertainty in the model. The parameter 

having the most uncertainty (most in need of further 

field study) was the flow coefficient for coastal creeks. 

Smaller uncertainties existed for wetlands frictional 

resistance and wind. Evapotranspiration and boundary 
2 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

inflows indicated the least uncertainty as determined 

by varying parameters used in their formulation and 

definition. 

Model results indicated that wind was important 

in reversing coastal creek flows. At Trout Creek (the 

major tributary connecting Taylor Slough wetlands 

with Florida Bay), flow in the landward direction was 

not simulated properly unless wind forcing was 

included in the simulation. Simulations also provided 

insight into the major influence that wind has on salinity mixing along the coast, the varying distribution of 

wetland flows at differing water levels, and the importance of topography in controlling flows to the coast. 

Slight topographic variations were shown to highly 

influence the routing of water.

A multiple regression analysis was performed to 

relate inflows at the northern boundary of Taylor 

Slough bridge to a major pump station (S-332) north of 

the SICS model area. This analysis allows Taylor 

Slough bridge boundary conditions to be defined for 

the model from operating scenarios at S-332, which 

should facilitate use of the SICS model as an operational tool.

INTRODUCTION 

The National Park Service (NPS) is charged with 

the task of conserving and protecting Everglades 

National Park (ENP), which includes the Southern 

Inland and Coastal Systems (SICS) that connect the 

Taylor Slough and C-111 wetlands with Florida Bay 

(fig. 1). Preservation of this ecosystem requires a 

hydrologic regime that approximates natural hydrologic conditions. At stake are thousands of acres of 

invaluable wilderness habitat and wildlife that the habitat supports (U.S. Army Corps of Engineers, 1992). 

Recent studies suggest that the SICS area is under great 

ecological stress with dwindling populations of many 

freshwater and saltwater animal species (Van Lent and 

others, 1998). Fifteen species found in the area are 

either threatened or endangered with extinction 

(Beccue, 1999). Gradual reductions over time in freshwater flow from north to south in the SICS area are 

thought to have contributed to the northward encroachment of salt-tolerant mangrove vegetation into the 

former domain of freshwater marsh vegetation (Smith, 

1998). These reductions in freshwater are the result of 

modifications to the natural flow regime that divert 

water for other uses.

Physical characteristics and hydrologic processes 

within canals, wetlands, and subtidal embayments of 

the southern Florida ecosystem are being defined and 

investigated by the U.S. Geological Survey (USGS) in 

projects supported through the Priority Ecosystem 

Science (PES) Program and through the NPS Critical 

Ecosystem Studies Initiative (CESI). Investigations 

have been undertaken to better understand important 

wetland processes such as vegetative resistance to flow, 

evapotranspiration, ground-water/surface-water 

exchanges, quantity and distribution of flow in creeks 

and marshes, canal/wetland interactions, saltwater 

intrusion, and wind-induced flow (Schaffranek and 

others, 1999). Considerable effort has also been 

expanded to precisely measure land-surface elevations 

in the wetlands and along the mangrove fringe and 

coastal embankment to determine the bathymetry of 

subtidal embayments and tidal creeks in northeastern 

Florida Bay. Additional data have been collected on 

coastal creek discharges, flow velocities in Taylor 

Slough, and water levels throughout the system.

Most of these investigations focused on individual topics and, in many cases, results were limited to a 

finite number of points at limited locations and for a 

short time. To better describe SICS area hydrology on 

larger temporal and spatial scales, results of these studies needed to be integrated. Moreover, current understanding of the SICS area needs to be used to evaluate 

changes that might occur in response to various watermanagement scenarios. In 1996, the USGS initiated a 

study to determine the effects of relevant physical characteristics and hydrologic processes on the flow regime 

in the SICS area. The USGS surface-water integrated 

flow and transport in two dimensions (SWIFT2D) 

hydrodynamic/transport model was adapted to this 

mixed sheetflow, stream, and tidal regime using findings from the PES and CESI investigations (Swain, 

1999). The model has the capability to simulate both 

current conditions (throughout the SICS area) as well 

as possible future conditions.

Purpose and Scope

The purpose of this report is to describe the 

development, testing, and application of a flow and 

transport simulation model for the SICS area, a critically important and threatened ecosystem of southeastern ENP. The report summarizes the extensive research 

efforts that resulted in better definition and understanding of major physical features and processes in the
Introduction 3

Joe Bay

Weather

Station

Old Ingraham

Highway ET site

P-33

ET Site

S21

0

0 40 MILES

40 KILOMETERS

80°45 ́

25°30 ́

25°15 ́

80°  ́ 30 80°15 ́

25°  ́ 30

25°00 ́

24°30 ́

26°00 ́

26°30 ́

81°30 ́ 81°00 ́ 80°  ́ 30 80°00 ́

0 5 10 MILES

0 5 10 KILOMETERS

EVERGLADES

NATIONAL

PARK

Levee 31N

C-111

ATLANTIC OCEAN

Joe Bay

BISCAYNE BAY

Barnes Sound

FLORIDA BAY FLORIDA KEYS

West Lake

Card Sound

Taylor Slough

Levee 31W

Road

Park

Main

OCEAN

Florida

Bay ATLANTIC

Taylor

Slough

Bridge S-332

1

1

997

Royal Palm

Ranger

Station

MIAMI-DADE

BROWARD

COLLIER

MONROE

PALM BEACH HENDRY

LEE

Florida Keys

GULF

OF

MEXICO

Old Ingraham Highway

Area

shown

above

ROC KY GLADES

EXPLANATION

EVERGLADES NATIONAL PARK

APPROXIMATE AREA OF TAYLOR SLOUGH

BOUNDARY OF SOUTHERN INLAND AND

COASTAL SYSTEMS (SICS) STUDY AREA

BUTTONWOOD EMBANKMENT

STAGE MEASUREMENT SITE (USGS)

RAINFALL, WIND AND SOLAR RADIATION

MEASUREMENT SITE (USGS)

RAINFALL MEASUREMENT SITE (NPS)

PUMP STATION

ET EVAPOTRANSPIRATION

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 1. Southern Inland and Coastal Systems (SICS) study area and selected data-collection sites. (USGS, 

U.S. Geological Survey; NPS is National Park Service)
4 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

SICS area and that were used in the development of the 

model. Studies were conducted to better describe and 

document topography, distribution of vegetation, vegetative resistance to water flow, water levels, currents, 

flow, salinity, meteorology, ground- and surface-water 

interactions, and evapotranspiration. The report also 

describes the structure, characteristics, capabilities, 

requirements, and limitations of the SWIFT2D numerical flow and transport simulation model and also 

discusses several enhancements made to the code to 

improve simulations for the SICS area.

The construction, calibration, testing, and application of the SWIFT2D model to the SICS study area 

are documented. This report describes incorporation of 

physical and hydrologic data into the model, the reliability of the hydrologic simulations, results of some 

model applications, and some general ways the model 

might be used to help evaluate hydrologic responses to 

proposed Everglades restoration alternatives.

The model was adapted to the study area using 

information on land-surface elevations, topographic 

features, vegetation characteristics, and bathymetry. 

The model was then calibrated and verified using data 

on flow rates and salinity measured at key outflow 

points along the mangrove fringe. Additionally, 

concurrent set measurements that defined mass fluxes 

at strategic transect locations within the wetlands and 

continuously measured water levels in the wetlands 

were used for comparison and verification of model 

results. The model was calibrated using data from 

September 1-30, 1997, and was verified using data 

from August 1, 1996, to July 31, 1997. The sensitivity 

of model results to changes in critical model parameters and boundary data was evaluated, both to establish 

error bounds for simulation results and to identify critical factors controlling flow dynamics and transport 

properties throughout the SICS study area. Numerical 

simulations that represent past and current hydrologic 

conditions were made using available data or estimated 

values, where no data existed, to establish baseline 

conditions. Through further application of the calibrated model, these baseline conditions can be used to 

evaluate the effects of future hydrologic changes within 

the SICS ecosystem. The SICS model version 1.2, 

described in this report, simulates time-varying information on surface-water level, flow velocity, salinity, 

and conservative material transport at a relatively 

detailed spatial scale.

Description of Study Area

The study area, referred to hereafter as the SICS 

area, encompasses about 900 km2. Within the study 

area are the Taylor Slough drainage basin of southeastern ENP, wetlands southwest of the C-111 Canal, part 

of northeastern Florida Bay, and several natural drainage features, including Alligator Creek, McCormick 

Creek, Taylor River, East Creek, Mud Creek, Trout 

Creek, Shell Creek, and West Highway Creek. Also 

included in the area are shallow coastal embayments, 

such as Joe Bay and Little Madeira Bay (fig. 2). A cluster 

of inland lakes are present in the southwestern corner 

of the study area, including West Lake, Cuthbert Lake, 

Seven Palm Lake, Monroe Lake and several smaller 

lakes (fig. 2). The study area boundary follows the ENP 

Main Park Road and then Old Ingraham Highway to 

the bridge over Taylor Slough and finally southeastward along part of the C-111 Canal. Flows from the 

very flat study area through the creeks and into Florida 

Bay have a large controlling influence on salinity 

concentrations and distribution in the bay (Nuttle, 

1995).

The SICS area is a small but prominent ecosystem that is somewhat hydraulically isolated south of a 

northeasterly trending topographic high of several 

centimeters called the Rocky Glades (fig. 1). Natural 

water flow to the SICS area occurs during times of high 

water level through a north-south trending depression 

known as Taylor Slough. As water has been drained 

from the Everglades over the last 60 years for urban 

and agricultural development, flows to Taylor Slough 

have diminished. This natural source of freshwater to 

the SICS area has been supplemented with water deliveries from the extensively managed canal system in 

southern Florida—through pump station S-332 to 

Taylor Slough, through Levee 31W Canal (Rose and 

others, 1981), and through C-111 Canal (fig. 1). The 

Levee 31W Canal lies northeast of Taylor Slough and 

brings water from the north, terminating just southeast 

of Taylor Slough bridge. Farther to the east, the C-111 

Canal forms the northeastern boundary of the SICS 

area; farther south, the canal crosses US-1 and 

discharges into Barnes Sound.

Old Ingraham Highway is a substantial obstruction to flow along the northwestern and western parts 

of the study area. However, the road does not 

completely block flow, especially during high-water 

periods (Craighead and Holden, 1965). Although overtopping of Old Ingraham Highway has been observed 

during high-water events, volumes of water moving
Introduction 5

AlligatorCreek

McCormick

Creek

Taylor

River

East

Creek

Mud

Creek

TroutCreek Shell Creek

West

Highway

Creek

East

Highway

Creek

Oregon

Creek

Stillwater

Creek

S175

S18CuS18C

R127

P67

TSH

P37

E146

CP

EVER4

EVER7

EVER5A

EVER6

EPGW/SW

EP12R

TSB

Supplemental

Taylor

River

80°  ́ 45

25°25 ́25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Long Lake

Little Madeira Bay

Cuthbert

Lake

Monroe

Lake

Taylor Slough

Levee 31W

Road

Park Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

Degraded

section

EXPLANATION

0 1 5 MILES0 1 2 3 4 5 KILOMETERS

2 3 4

EVERGLADES NATIONAL PARK

APPROXIMATE AREA OF TAYLOR SLOUGH

BOUNDARY OF SOUTHERN INLAND ANDCOASTAL SYSTEMS (SICS) STUDY AREABUTTONWOOD EMBANKMENT

STAGE MEASUREMENTS SITE (USGS)STAGE, CONDUCTIVITY, AND DISCHARGEMEASUREMENT SITE (USGS)COASTAL CREEK LOCATIONSTAGE MEASUREMENT SITE (NPS)STAGE AND CONDUCTIVITY MEASUREMENTSITE (NPS)DISCHARGE MEASUREMENT SITE (SFWMD)

Base from U.S. Geological Survey digital data, 1972Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 2. Discharge, conductivity, and water-level data-collection sites within the study area (USGS, U.S. Geological Survey; NPS, National Park Service; SFWMD South Florida Water Management District). 
6 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

over the road have not been measured. About 5.5 km of 

the 14-km east-west section of Old Ingraham Highway 

(fig. 2) have been degraded, and this segment is where 

overland flow most often occurs. 

The NPS has studied hydrologic conditions 

within the SICS area for quite some time. Continuous 

measurements of stage or stage and conductivity were 

made at 10 sites within the SICS domain (fig. 2) by the 

NPS. These sites contain shallow wells so that stage 

measurements can continue, in conjunction with 

several sites operated by the USGS, when levels are 

below land surface.

Ground-water inflow into the SICS area was 

investigated by Fitterman (1996), who described the 

location of the ground-water interface between saltwater and freshwater in the SICS study area. During the 

investigation, a helicopter-based instrument pod was 

used for measuring the electromagnetic response of the 

ground at differing frequencies to determine the apparent resistivity of the underlying formation (Fitterman 

and Deszcz-Pan, 1999). The resistivity is highly 

inversely correlated to the salinity of the shallow ground 

water. The apparent resistivity map (fig. 3), for a depth 

of 5 m (meters) below land surface, indicates a relatively sharp transition between more resistive (lower 

salinity) ground water on the north side of western Old 

Ingraham Highway to higher salinity on the south side 

of the highway. To the east, the transition zone is closer 

to Florida Bay in the vicinity of Taylor Slough, but the 

transition zone then trends northeasterly toward US-1 

(Fitterman and Deszcz-Pan, 1998). The general southsoutheast direction of fresh ground-water flow (Swain 

and others, 1996) is forced by buoyancy to move 

upward as the freshwater approaches the saltwater interface. The region where upwelling of fresh ground water 

into the surface-water regime should occur is just landward of the saltwater-freshwater interface shown in 

figure 3. Evidence also suggests that saltwater has 

apparently intruded eastward adjacent to the degraded 

section along Old Ingraham Highway.

Additional evidence of ground-water flow into the 

study area is from geochemical tracer measurements 

conducted to determine the locations of ground-water 

discharge to surface water in wetland areas (Harvey and 

others, 2000a; 2000b). The area just south of the central 

bend at Old Ingraham Highway near site P67 (fig. 2) has 

been identified as a primary source of ground-water 

seepage to surface waters of the SICS area. Overland 

flow is most likely to occur west of this area, which 

includes the degraded section of Old Ingraham Highway.

The southern boundary of the SICS study area is 

well south of the Florida Bay shoreline. Florida Bay is 

a shallow saline water body semi-enclosed from the 

Atlantic Ocean by the Florida Keys archipelago (fig. 1). 

The northeastern part of Florida Bay has negligible 

diurnal or semidiurnal tidal forcing, but water levels 

can fluctuate 10 to 30 cm during sustained frontal type 

wind events (Smith, 2001).

One of the most hydrologically significant 

features of the SICS area is a higher elevation feature 

along the coast called the Buttonwood Embankment 

(fig. 1). This ridge is estimated to be on the order of 15 

cm higher than the surrounding marsh (Holmes and 

others, 2000). The existence of the Buttonwood 

Embankment is thought to be related to either build-up 

of organic matter from the overlying mangrove forest 

or deposition of sediment near the shore that is eroded 

from Florida Bay during periodic hurricanes and tropical storms (Holmes and others, 2000). Several creek 

channels cut through this ridge and drain into northeastern Florida Bay. The ridge itself forms a partial 

low-head dam to overland flow from the SICS wetlands 

into Florida Bay, and the incised channels concentrate 

the flow into a small number of creeks. The ridge itself 

rarely is overtopped (Hittle, 2000).

Previous Studies

Numerous studies of Everglades hydrology have 

been conducted in recent years, and several models of 

the southern Florida region have been developed. Few 

models have been applied to the coastal Everglades 

(none focusing on the SICS area). This section summarizes some of the previous modeling efforts in the Everglades.

To implement the Comprehensive Everglades 

Restoration Plan (CERP) (U.S. Army Corps of Engineers, 1999), numerous natural resource management 

decisions must be made with less than complete information on the probable impacts of the decisions on 

hydrology, habitat, wildlife, and millions of southern 

Florida residents. Because numerical simulation 

models are capable of reasonably integrating many 

complex and interacting processes, models are finding 

greater use in southern Florida for evaluation of the 

effects of possible future management scenarios. It is 

increasingly important, therefore, that all such models 

be as reliable as possible.
Introduction 7

Road

Park

Main

Taylor

Slough

Bridge

80°  ́ 45

25°25 ́25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80

0 1 5 MILES0 1 5 KILOMETERS 234

234

Old Ingraham Highway

C-111

Joe Bay Barnes S

FLORIDA BAY

West Lake

Taylor Slough

Levee 31WRoyal Palm Ranger Station 1

EXPLANATION

80°35 ́

RESISTIVITY, IN OHM METERS

GREATER THAN 12550 TO 40 15 TO 1075 TO 50125 TO 75

20 TO 1530 TO 2040 TO 30

5.0 TO 2.07.5 TO 5.010 TO 7.5LESS THAN 2.0

BOUNDARY OF SOUTHERN INLAND AND COASTAL SYSTEMS (SICS) STUDY AREA.

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 3. Apparent resistivity in the Southern Inland and Coastal Systems (SICS) study area at 5-meter depth below land 

surface (from Fitterman and Deszcz-Pan, 1998).
8 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

One key model now being applied to the SICS 

and other southern Florida areas is the Across Trophic 

Level Systems Simulation (ATLSS) model (Deangelis, 

2000). The ATLSS model is used to compare the relative effects of differences between alternative hydrologic scenarios on several key indicator species 

(alligator, snail kite, Florida panther, white-tailed deer, 

and Cape Sable seaside sparrow) within the ecosystem 

using linked species models. The ATLSS model 

requires very detailed and accurate water-level, flow, 

and salinity information from a hydrologic model in 

order to simulate realistic population changes for these 

species in response to restoration options (DeAngelis, 

2000). Improved hydrologic input to ATLSS should 

result in better ecological simulations.

Southern Florida hydrologic conditions have 

been simulated by the South Florida Water Management Model (SFWMM) for more than 15 years 

(MacVicar and others, 1984). This model has undergone numerous improvements since its inception and is 

relied upon to provide regional information at coarse 

spatial resolution. The Hydrologic Simulation Engine 

(HSE) for the next generation SFWMM, called the 

South Florida Region Simulation Model (SFRSM), has 

been tested in the Everglades region (Brion and others, 

2000). The overland flow algorithm in the HSE, as in 

the SFWMM, neglects inertial forces, and analysis 

indicates that these models are more reasonable in their 

representation of water level than flow volumes (Bales 

and others, 1997). The SFWMM has been used to 

simulate coastal flows into Florida Bay as part of a 

hydrodynamic modeling effort (McAdory and Kim, 

1998). In this application, simulated coastal flows were 

much greater than field measurements (Hittle, 2000), 

resulting in simulated Florida Bay salinities that were 

much lower than measured values. Another large 

regional model was attempted with the 

FEMWATER123 code (Lin and others, 2000). This 

included one-dimensional canal flow, two-dimensional 

overland flow, and three-dimensional finite-element 

ground-water flow. The combined model was very 

computationally intensive which restricted its usage.

The need for greater accuracy and finer spatial 

resolution of hydrologic model input to ecological 

models as well as the need for better information on 

freshwater flows that can be used in Florida Bay 

models highlight the importance of an improved flow 

model of the SICS coastal region. Such a model should 

substantially improve the reliability of information 

available for resource management decision making in 

support of Everglades restoration.

APPROACH 

The approach for this study included selection, 

enhancement, and application of a numerical model 

capable of simulating flow and solute transport within 

the SICS area and into Florida Bay. Data were obtained 

from several sources to apply, calibrate, and test the 

model. Additionally, results from ongoing or recently 

completed process studies were used to develop the 

model. The approach used for model selection and 

enhancement, model development, application of 

process studies in support of model development, and 

model calibration, testing, and application are 

described in this section.

Model Selection and Required 

Enhancements

A numerical model was needed to accurately 

simulate water movement and solute transport through 

the SICS area to Florida Bay for a range of existing and 

possible future conditions, given natural or imposed 

changes in inflows. Selection of the model for the study 

was governed by the anticipated application of the 

model and by the controlling physical characteristics 

and governing hydrologic/hydraulic processes in the 

SICS area.

Numerous physical characteristics and processes 

affect flow in the SICS area. Hydraulic gradients are 

very small—less than 2 cm per kilometer (Lee and 

others, 2000a; 2000b). Water movement into Florida 

Bay from the SICS area is strongly affected by the 

coastal Buttonwood Embankment as well as the coastal 

creeks that breach the embankment, water levels in 

Florida Bay and the Everglades, wind conditions, 

evapotranspiration, and the frictional resistance to flow 

by vegetation. With such low hydraulic gradients, rainfall and exchanges with ground water are also important factors in the total water budget. The transition 

from freshwater in the Everglades to saltwater in Florida Bay and the location and size of this transition zone 

also affect water movement and solute transport. 

Although some parts of the SICS area are continuously 

inundated, other parts vary between inundated and 

dry (water level at or below land surface) conditions. 
Approach 9

Small creeks also are present throughout the SICS area, 

particularly in the southeastern part of the study area 

(fig. 2), and these creeks play a major role in the movement of water and solutes into Florida Bay.

Given these characteristics, the model selected 

for this study needed the capability to simulate: 

(1) time-varying, two-dimensional, depth-averaged 

overland flow through spatially varying topography; 

(2) the effects of wind on flow; (3) drying and rewetting within the study area; (4) dynamic transport of 

salt including the coupling between density and flow; 

(5) one-dimensional flow through creeks at a smaller 

spatial scale than for overland flow; and (6) the effects 

of rainfall and evapotranspiration on water balance and 

flow.

The SWIFT2D model (Leendertse, 1987), 

described in some detail later, was selected for this 

study because the model: (1) includes many of the 

capabilities required for the SICS application, (2) is 

easily modified, (3) is a nonproprietary and freely 

obtained code, (4) runs on a personal computer, and 

(5) has been successfully applied to other systems in 

Florida and elsewhere. The model solves the hydrodynamic equations of mass continuity and momentum 

conservation in two horizontal dimensions. Drying and 

rewetting of the land surface are simulated. The model 

also includes algorithms that describe flow at various 

types of structures; this feature was particularly important for the simulation of flow in tidal creeks and 

through the Buttonwood Embankment. The creeks are 

much smaller than the size of the computational grid 

cell, and thus, are represented in SWIFT2D as notches 

in a barrier. Time-varying transport of constituents is 

simulated, and the transport equation is coupled to the 

flow equations through density effects.

Many previous applications of the SWIFT2D 

model were for tidally driven systems with hydraulic 

gradients generally greater than those of the SICS area. 

Many of these applications, however, included selected 

areas having lower hydraulic gradients, such as in tidal 

flats, similar to the SICS area. Slight modifications to 

the SWIFT2D model were sometimes needed in previous applications. For instance, the SWIFT2D model 

was used to design the Dutch Delta Works (Leendertse 

and others, 1981), and modifications to the model 

subsequently were made to evaluate mixing and 

chaotic stirring in the Dutch Wadden Sea (Ridderinkhof and Zimmerman, 1992). In a report on a model 

of the Eastern Scheldt estuary in the Netherlands 

(Leendertse, 1988), an evaluation of the effects of the 

advection terms on tidal propagation was conducted. 

These experiments illustrated the importance of the 

timestep size, grid size, roughness estimation, depth 

measurement accuracy, turbulence closure, and horizontal momentum exchange in obtaining accurate 

simulations. Lee and others (1989; 1994) demonstrated 

the effects of highway crossings and embankments on 

the circulation and flow within an estuarine system that 

consisted of narrow channels and extensive tidal flats 

that became exposed at low tide. Using a nested 

computational grid, Schaffranek and Baltzer (1988) 

used SWIFT2D to evaluate hydraulic effects of modifications to wetlands in the Port Royal Sound area of 

South Carolina. Bales and Robbins (1995) and Robbins 

and Bales (1995) characterized flow, circulation, and 

solute transport in the Pamlico and Neuse River estuaries in North Carolina using the SWIFT2D model. 

Those studies included detailed field measurement 

programs and calibration and testing of the SWIFT2D 

model. 

Other studies have simulated the effects of 

dredging and alternative spoil placement options on 

tidal flow, circulation, and flushing within several estuaries in Florida, including Tampa Bay (Goodwin, 1987) 

and Hillsborough Bay (Goodwin, 1977; 1991). Application of SWIFT2D to Charlotte Harbor (Goodwin, 

1996) and the Loxahatchee River (Russell and Goodwin, 1987) provided insight into tidal flow and mixing 

characteristics and how they might change with 

proposed future alterations to causeways and bridges. 

Schaffranek (1986) and Schaffranek and Baltzer (1990) 

illustrated horizontal density-gradient effects on estuarine flushing and circulation in the upper Potomac estuary and the effect of bathymetric grid density on model 

results using the SWIFT2D model.

The SWIFT2D model, in its standard form, satisfies the hydrodynamic requirements for the SICS application. Several enhancements were required, however, 

to represent hydrologic processes such as evapotranspiration and rainfall. The computational algorithms for 

wind and flow at barriers also were enhanced.

Data

Data served the following distinct purposes in 

the study: (1) to characterize the model area, (2) to 

provide model boundary conditions, (3) to assist in 

model performance testing, and (4) to estimate model 

parameters. Most data used to characterize the model 

area were developed by field studies associated with 
10 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

this modeling effort. Boundary conditions and data for 

model performance testing were derived from numerous projects conducted by the USGS, South Florida 

Water Management District (SFWMD), and ENP. Data 

from all of these sources are available on a database 

that can be accessed at http://sofia.usgs.gov.

Results from field studies were used to estimate 

model parameters. Most parameters are constrained to 

values close to field measurements, and confidence in 

these parameter values is high. This approach for determining parameters is in contrast to the typical approach 

for parameter determination in model studies. Typically, during model calibration, parameters are set to 

nominal values obtained from the literature and 

adjusted over a wide range until model simulation 

results are in reasonable agreement with available data. 

In contrast, the SICS model parameters are largely 

derived from process studies and are physically based. 

Hence, the chance of nonunique solutions, in which 

similar simulation results are obtained with different 

combinations of parameter values, is less likely to 

occur than with a model calibrated using the typical 

approach. In some cases, values measured in the field 

at a few points may not always be the best representation for a parameter in a model due to scale effects; the 

model represents an effective value as applying over an 

entire grid cell, whereas measurements sometimes 

apply to a point. Nonetheless, field measured values 

typically define model parameters more accurately than 

values obtained from other indirect sources including 

the literature and model tuning. Methods used for 

obtaining data for this study are described in the 

following sections.

Topography

Topographic data included land-surface elevations, embayment bathymetry, Buttonwood Embankment elevations, and the widths and bottom elevations 

of tidal creeks. The USGS used a helicopter-mounted 

global positioning system (GPS) unit and weighted line 

to measure land-surface elevations (Desmond and 

others, 2000) in the Everglades wetlands. Land-surface 

elevations were measured on a grid with about 400-m 

spacing (Henkle, 1996). 

The bathymetries of Joe Bay and Florida Bay 

were measured by the USGS (Hansen and DeWitt, 

1998), using a boat with a depth finder and a GPS unit. 

More than 30,000 individual depth measurements 

along boat track lines were made in Joe Bay (fig. 2). 

The bathymetries of other subembayments and Florida 

Bay were determined from nautical charts developed 

from National Oceanic and Atmospheric Administration (NOAA) data. The USGS Florida Bay data coincided well with the nautical charts, while providing a 

much more refined representation of the embayment 

bathymetry than was previously available. The 

bathymetries of West Lake and associated lakes were 

estimated from depth measurements made by USGS 

personnel in September 1999. All bathymetric and 

topographic elevations were referenced to the North 

American Vertical Datum of 1988 (NAVD 88).

The location of the Buttonwood Embankment 

was derived from 1:24,000 scale USGS topographic 

maps. Based on observations by USGS personnel, 

the bottom elevations of tidal creeks at the location 

where the creeks cut through the embankment are 

all at an elevation of about 1.5 m below NAVD 88. 

The creek widths are as follows: (Eduardo Patino, U.S. 

Geological Survey written commun., 1998):

Channels connecting the lakes in the southwestern part 

of the study area (West Lake area) were estimated to be 

about 24 m wide.

Vegetation

Aerial- and land-based vegetation surveys 

(Carter and others, 1999; Jones, 1999) were conducted, 

and results were compiled into a geographic information system (GIS) database (Stewart, 1997). The aerial 

surveys were conducted to determine regional vegetation types by using spectral reflectivity and visual 

onsite observations for ground truthing. These data 

were compared with data previously collected for the 

area, such as the 68-class 1993-94 Landsat vegetation 

map and a 20-class Landsat thematic mapper image 

(February 2000). The vegetation in the study area was 

categorized into eight classes at a horizontal resolution 

Creek name Width 

(meters)

McCormick Creek 16.8

Taylor River 6.7

East Creek 12.2

Mud Creek 12.2

Trout Creek 36.6

Shell Creek 12.2

Stillwater Creek 9.1

Oregon Creek 4.6

East Highway Creek 15.2

West Highway Creek 21.3
Approach 11

of 30 m (fig. 4). Although vegetative density is not 

indicated by this classification system, the system does 

identify areal distribution of vegetation types for correlation to hydrologic parameters, and the information is 

adequate for hydrodynamic modeling.

Water Level, Currents, and Discharge

Water-level, current, and discharge data were 

collected at 23 sites in the study area and 1 site (P33) 

north of the study area (fig. 2 and table 1). Data used 

for this study were collected by the SFWMD, USGS, 

and NPS through existing monitoring networks and 

research projects.

Gage datums at the continuous water-level 

recording stations were established relative to the 

National Geodetic Vertical Datum of 1929 (NGVD 

29). The model was developed, however, using topographic data referenced to NAVD 88. Therefore, gage 

datum adjustments were made at all water-level 

stations. The CORPSCON datum adjustment routine 

(North Carolina Geographic Information Coordinating 

Council, 1999) was used to adjust datums from 

NGVD 29 to NAVD 88 at all stations except R127, 

TSH, P37, E146, and CP. At these stations, reference 

marks relative to NAVD 88 were established during 

land-surface elevation surveys (Gordon Shupe, U.S. 

Geological Survey, written commun., 1999). Subsequent surveys determined the differences between the 

NAVD 88 reference marks and previously established 

NGVD 29 datums. Adjustments to correct NGVD 29 

gage datums to NAVD 88 elevations are as follows:

A unique aspect of this study involved the 

measurement of flow velocities (currents) in the 

wetlands (Tillis, 2001). This type of data is seldom 

available, but is invaluable for testing model performance. Flow velocity, depth, and water-quality constituents (water temperature, dissolved-oxygen 

concentration, specific conductance, and pH) were 

measured within the study area at 137 locations (fig. 5), 

including along three approximately east-west 

Station

Datum

adjustment 

(meters)

R127 -0.5200

TSH - .4916

P37 - .4801

E146 - .3734

CP - .5288

transects in the wetlands (Schaffranek and others, 

1999). Acoustic Doppler velocimeters were used to 

make point velocity measurements at various depths in 

the water column, and depth-averaged velocities were 

calculated at each measurement location for use in 

model evaluation. The data were collected between 

July 1997 and July 1998. Data from the first two 

measurement sessions were used in this study.

Salinity

Salinity measurement stations in the study area 

are shown in figure 2 (as conductivity locations) and 

presented in table 1. These stations are located at the 

mouths of coastal creeks. Specific conductance sensors 

were deployed at multiple vertical positions in the 

water column to detect any vertical stratification. Little 

vertical variation in salinity occurred except at brief 

intervals during flow reversals (Hittle, 2000). The 

specific conductance measured at these locations was 

converted to salinity by the following relation (Riley 

and Skirrow, 1975):

, (1)

where s is salinity, in parts per thousand; and Cs is 

specific conductance, in microsiemens per centimeter at 

25 °C. The standard USGS method for converting 

specific conductance to salinity was given by Miller and 

others (1988, p. 14). The maximum specific conductance measured at Trout Creek in 1996 was 42.238 

microsiemens per centimeter, which converts to a salinity of 27.08 ppt using equation 1 and to a salinity of 

27.11 ppt using the equation by Miller and others 

(1988). The differences are very small (0.1 percent) 

compared to potential measurement error in the field. In 

addition to the data from the coastal creek stations, 

salinity from NPS-operated stations in Florida Bay were 

used to define the southern salinity boundary. 

Rainfall, Wind, and Solar Radiation

Initial applications of the SICS model (version 

1.1) used rainfall data collected at the Old Ingraham 

evapotranspiration site and the Joe Bay weather station 

(fig. 1). Data for the model domain were interpolated 

from these two sites. This approach proved to be 

unsatisfactory, considering the large spatial variations 

in southern Florida rainfall. For example, from July 

1996 to February 1997, rainfall was 107.2 cm at 

the Old Ingraham site and 68.1 cm at the Joe Bay site. 

s 0.4081Cs

1.121 =
12 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Levee 31W

Road

Park Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

EXPLANATION

SAWGRASS

Old Ingraham Highway

EVERGREEN

0 1 5 MILES0 1 5 KILOMETERS 234

234

80°  ́ 45

25°25 ́25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°35 ́ 80°2

RUSH/OTHERSAWGRASS/RUSHSAWGRASS/BUNCHGRASS

BOUNDARY OF SOUTHERN INLAND ANCOASTAL SYSTEMS (SICS) STUDY AREOPEN WATERMANGROVE/WATERMANGROVE/EVERGREEN

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 4. Vegetation features in the Southern Inland and Coastal Systems (SICS) study area.
Approach 13

Table 1. Hydrologic and meteorological data-collection sites for the Southern Inland and Coastal Systems (SICS) study 

[The P-33, Old Ingraham Highway, and Joe Bay sites are shown in figure 1; the sites used for rainfall data are shown in figure 6; the sites used 

for boundary conditiona are shown in figure 10. All remaining sites are shown in figure 2. Data: C, conductance; D, discharge; ET, 

evapotranspiration; S, stage; R, rainfall; WL, water level. Agency: NPS, National Park Service; SFWMD, South Florida Water Management 

District; USGS, U.S. Geological Survey. Purpose: BC, boundary condition; MF, model formulation; MPT, model performance testing]

Site name Map identifier Latitude Longitude Data Reporting 

interval

Period of

record Agency Purpose

Sites shown in figure 1

Joe Bay weather station Joe Bay weather station 25o13′28′′ 80o32′24′′ R Daily 1991-Present NPS BC

Old Ingraham Highway Old Ingraham Highway 

ET site

25o21′12′′ 80o38′07′′ ET,WL,R,W 15 minutes 1995-Present USGS BC,MF

P-33 P-33 25o36′55′′ 80o42′11′′ ET Hourly 1995-Present USGS MF

Sites shown in figure 2

Craighead Pond CP 25o13′44′′ 80o42′15′′ WL Daily 1978-Present NPS MPT

E-146 E146 25o15′18′′ 80o40′01′′ WL Daily 1994-Present NPS MPT

Everglades 4 EVER4 25o20′43′′ 80o32′44′′ WL Daily 1985-Present USGS MPT

Everglades 5A EVER5A 25o17′16′′ 80o34′21′′ WL Daily 1985-Present USGS MPT

Everglades 6 EVER6 25o17′54′′ 80o30′43′′ WL Daily 1991-Present NPS MPT

Everglades 7 EVER7 25o18′35′′ 80o32′34′′ WL Daily 1991-Present NPS MPT

Everglades Park 12R EP12R 25o16′26′′ 80o26′43′′ WL Daily 1988-Present NPS MPT

Everglades Park groundwater/surface-water stationEPGW/SW 25o16′49′′ 80o30′12′′ WL Daily 1986-Present NPS MPT

P-37 P37 25o17′08′′ 80o41′19′′ WL Daily 1953-Present NPS MPT

P-67 P67 25o19′50′′ 80o39′02′′ WL Daily 1962-Present NPS MPT

R-127 R127 25o21′15′′ 80o36′24′′ WL Daily 1984-Present NPS MPT

Taylor Slough Hilton TSH 25o18′44′′ 80o37′52′′ WL Daily 1994-Present NPS MPT

Sites shown in figure 6

Everglades 8 NP-EV8 25o20′46′′ 80o28′44′′ R 15 minutes 1992-Present NPS BC

Flamingo NP-FLA 25o08′29′′ 80o54′53′′ R 15 minutes 1962-Present NPS BC

Little Madeira Little Madeira 25o10′31′′ 80o37′56′′ R 15 minutes 1993-Present NPS BC

P-38 NP-P38 25o22′14′′ 80o50′01′′ R 15 minutes 1983-Present NPS BC

Terrapin Bay Terrapin Bay 25o09′24′′ 80o43′30′′ R 15 minutes 1993-Present NPS BC

Trout Cove Trout Cove 25o12′39′′ 80o31′60′′ R 15 minutes 1993-Present NPS BC

Upstream Taylor River Upstream Taylor River 25o13′28′′ 80o39′11′′ R 15 minutes 1993-Present NPS BC

Sites shown in figure 10

Buoy Key Buoy Key 25o07′15′′ 80o50′02′′ WL,C 15 minutes 1993-Present NPS BC

Butternut Key Butternut Key 25o05′17′′ 80o31′08′′ WL,C 15 minutes 1993-Present NPS BC

CY2 CY2 25o19′45′′ 80o40′58′′ WL 15 minutes 1996-Present NPS BC

CY3 CY3 25o19′46′′ 80o45′03′′ WL 15 minutes 1996-Present NPS BC

East Highway Creek East Highway Creek 25o14′40′′ 80o26′28′′ WL,C 15 minutes 1996-Present USGS BC

Long Sound Long Sound 25o14′05′′ 80o27′27′′ WL,C,R 15 minutes 1993-Present NPS BC

McCormick Creek McCormick Creek 25o10′03′′ 80o43′55′′ WL,D,C 15 minutes 1995-Present USGS MPT

Mud Creek Mud Creek 25o12′09′′ 80o35′01′′ WL,D,C 15 minutes 1995-Present USGS MPT

Nine Mile Pond NMP 25o15′15′′ 80o47′54′′ WL 15 minutes 1996-Present NPS BC

P-46 P46 25o19′11′′ 80o47′45′′ WL 15 minutes 1966-Present NPS BC

P-67 P67 25o19′50′′ 80o39′02′′ WL Daily 1962-Present NPS BC

S-175 at L31-W canal S175 25o25′04′′ 80o34′25′′ D Daily 1970-Present SFWMD BC

S-18C at C-111 Canal S18C 25o19′50′′ 80o31′30′′ WL,D,C Daily 1968-Present USGS BC

Supplemental Taylor River Supplemental Taylor River 25o12′41′′ 80o38′53′′ WL,D,C 15 minutes 1998-Present USGS MPT

Taylor River Taylor River 25o11′27′′ 80o38′21′′ WL,D,C 15 minutes 1995-Present USGS MPT

Taylor Slough Bridge TSB 25o24′06′′′′ 80o36′24′′ D Daily 1960-Present SFWMD BC

Trout Creek Trout Creek 25o12′53′′ 80o32′01′′ WL,D,C 15 minutes 1996-Present USGS MPT

Upstream of S-18C a C-111 

Canal

S18Cu 25o19′50′′ 80o31′30′′ WL Daily 1985-Present USGS BC

West Highway Creek West Highway Creek 25o14′33′′ 80o26′50′′ WL,D,C 15 minutes 1996-Present USGS MPT

Whipray Basin Whipray Basin 25o04′41′′ 80o43′39′′ WL,C,R 15 minutes 1993-Present NPS BC
14 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

C-111

Joe Bay

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

EXPLANATION

EVERGLADES NATIONAL PARK

0 1 5 MILES T10 1 5 KILOMETERS 234

234 T4

LOCATION OF ACOUSTIC DOPP

VELOCIMETER MEASUREMEN

ALONG TRANSECTS

80°  ́ 45

25°25 ́25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°35 ́ 

AIRBOAT TRAIL

BOUNDARY OF SOUTHERN INLAND ANDCOASTAL SYSTEMS (SICS) STUDY AREA

APPROXIMATE AREA OF TAYLOR SLOUGH

T3T2 CENTERLI

Base from U.S. Geological Survey digital data, 1972Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 5. Location of acoustic Doppler velocimeter measurements in the Southern Inland and Coastal Systems (SICS) study area.
Approach 15

The maximum difference in monthly rainfall at the two 

sites was 17.5 cm in August 1996. In order to improve 

the spatial representation of rainfall, 15-minute data 

were collected at a network of 14 rainfall stations 

(fig. 6), and a kriging algorithm was used to determine 

rainfall amounts for each cell.

Wind speed and direction were recorded at 15-

minute intervals at the Old Ingraham Highway site and 

at the P33 site, which is located about 29 km north of 

the Old Ingraham Highway site (fig. 1 and table 1). 

Winds at these sites are highly correlated (H.L. Jenter, 

U.S. Geological Survey, oral commun., 1998). As a 

result, spatially uniform wind speed and direction were 

used for the study area using measurements at the Old 

Ingraham Highway site. 

Solar radiation data also were collected by a 

pyranometer at the Old Ingraham Highway and P33 

sites (fig. 1 and table 1). Solar radiation can be used 

as an indicator of evapotranspiration (discussed later). 

A comparison of solar radiation between the two sites 

showed a mean absolute difference (MAD) in hourly 

solar radiation values of 48.5 W/m2 in 1997, which is 

14 percent of the daily mean solar radiation at the Old 

Ingraham Highway site. Because the Old Ingraham 

Highway site borders the study area, the pyranometer 

data from this site are used to represent solar radiation 

over the entire model domain.

Process Studies in Support of Model 

Development

A number of investigations and research projects 

had been (or were) conducted in the SICS area over the 

course of this study. The investigations ranged from 

data collection (for example, measurement of ground 

elevations and flows in tidal creeks) to process studies 

(for example, studying the relations of wetland vegetation and resistance to flow). Results of many of these 

investigations were used to construct and test the SICS 

model and greatly reduced the uncertainty in model 

parameters (discussed later). The relevant studies are 

summarized in table 2.

Whipray

Basin

Upstream

Taylor River

Trout

Cove

Terrapin

Bay

Long

Sound

Little

Madeira

CP

Old Ingraham

Highway

NP-P38

P37

R -127

NP-FLA

NP-EV8

S18C

80°50 ́ 80°30 ́

25°20 ́

25°10 ́

FLORIDA BAY ATLANTIC OCEAN

0 3 6 KILOMETERS

0 3 6 MILES

RAINFALL STATION

BOUNDARY OF SOUTHERN INLAND AND

COASTAL SYSTEMS (SICS) STUDY AREA

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27 EXPLANATION

Figure 6. Rainfall data-collection sites.
16 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Model Construction, Calibration, Testing, 

and Application

The modeling approach consisted of: (1) computational grid development; (2) assembly of data for 

model boundary conditions and model testing; 

(3) selection of initial values of model parameters 

based on results of field and laboratory process studies; 

(4) model calibration using data from the period 

September 1-30, 1997; (5) performance testing in 

which simulation results were compared with data 

collected from August 1996 to July 1997; (6) sensitivity analysis in which the effects on simulation results of 

small changes in model parameters and boundary data 

were evaluated; and (7) model application. Sensitivity 

analysis included evaluation of the effects of changes in 

the flow coefficient for coastal creeks, wind-friction 

coefficient, evapotranspiration rate, wetlands frictional 

resistance, boundary water levels, tidal function, 

boundary discharge, salinity, and land elevation on 

simulation results. The model was applied to quantify 

the effects of wind and of varying discharges at the 

Taylor Slough boundary on flows in Taylor Slough and 

to Florida Bay.

DESCRIPTION OF MODEL STRUCTURE 

The two-dimensional, vertically integrated, 

unsteady flow and transport model SWIFT2D 

(Leendertse, 1987) was applied to the study area. 

The model was first developed for applications in 

Jamaica Bay, N.Y. (Leendertse and Gritton, 1971). 

Since that time, the model has undergone numerous 

revisions and updates, including enhancements 

described in this report for the SICS area application.

The SWIFT2D model was originally designed to 

simulate flow and transport in vertically well-mixed 

estuaries, coastal embayments, lakes, rivers, and inland 

waterways. Westerink and Gray (1991) describe the 

model as “a very comprehensive modeling package 

which is based on a staggered alternating-direction 

implicit solution.” SWIFT2D also includes many 

features such as time-stepping options, advective term 

discretization options, transport of passive tracers, 

coupled salinity transport, flooding and drying, the 

ability to include hydraulic structures, two alternative 

bottom friction terms including a form based on the 

subgrid scale energy level, a parametric expression for 

turbulence effects, various formulations for horizontal 

dispersion, and reactions and local inputs for transport. 

Table 2. Summary of studies and research investigations used to develop the Southern Inland and Coastal Systems (SICS) model

Reference Description Data use in SICS model

Fitterman (1996) Determination of freshwater-saltwater interface in ground water through airborne 

electromagnetic methods

Parameter estimation

German (1995) Two field sites collecting energy-budget information, including rainfall and wind, 

for computation of evapotranspiration

Hydrologic input to model and model formulation

Halley and Prager (1996) Mobile salinity measurements in Florida Bay Model boundary construction

Hansen and DeWitt (1998) Bathymetry of off-shore areas collected with depth-finder and global positioning 

system

Model area characterization

Henkle (1996) Helicopter-based land-elevation measurement for study area at 400-meter spacing Model area characterization

Jenter (1999) Determination of wind-friction sheltering term for highly vegetated areas Model formulation

Jones (1999) Aerial- and land-based vegetation surveys used to categorize vegetation types Model area characterization

Lee and Carter (1996) Laboratory and field studies to relate vegetation type to frictional resistance to flow Model area characterization

Patino (1996) Continuous measurement of stage, streamflow, and salinity in five tidal creeks 

along the southern boundary of the SICS area

Model boundary conditions and model 

performance testing

Schaffranek and others (1999) Measurement of wetland flow velocity with mobile acoustic meters Model performance testing
Description of Model Structure 17

This section describes the governing equations, the 

numerical procedures to solve the model equations, 

model input requirements, and enhancements made to 

the model for this study.

Governing Equations

Relatively complete mathematical descriptions 

of the SWIFT2D governing equations are provided in 

Leendertse (1987), Goodwin (1987), and Bales and 

Robbins (1995). Those descriptions are not repeated 

here, but the relevant features of the equations are 

described for the SICS model.

 The basic equations of unsteady, nonuniform, 

variable density, turbulent fluid motion are formulations of the law of conservation of mass and Newton's 

second law of motion (conservation of momentum). 

Conservation of fluid mass is given by the equation of 

continuity, and conservation of solute mass is 

expressed by a transport equation. The law of conservation of momentum is given by the Navier-Stokes 

equation, which is the basic relation expressing 

Newton's second law for a viscous fluid. These equations apply to a infinitesimal parcel of fluid at an 

instant in time, but can be simplified by decomposing 

velocity, pressure, and mass into temporal mean values 

and turbulent fluctuations and then averaging over a 

time interval that is long relative to the time scale of the 

turbulent fluctuations. These three-dimensional equations of motion and transport are further reduced to a 

set of two-dimensional equations by assuming that 

vertical accelerations are negligibly small and by integrating the equations over the depth of flow. The resulting equations are nonlinear, time dependent, and retain 

coupling of motion and transport so that time-varying 

horizontal density gradients are included in the equations of motion. Because the nonlinear advective and 

bottom stress terms are retained in the governing equations, the presence of eddies can be simulated and 

residual circulation can be computed. 

The momentum equation describes the balance 

between fluid acceleration and applied forces. Total 

acceleration is the sum of local acceleration (temporal), 

advection of momentum (advective terms), and Coriolis acceleration. Forces acting on the fluid include the 

horizontal pressure gradient and shear stresses (bottom, 

surface, and internal). The horizontal pressure gradient 

consists of the water-surface gradient and the vertically 

integrated density gradient, which result from horizontal 

variations in density. Because of this dependence of the 

momentum balance on salinity (through density), the 

horizontal density gradient terms couple the momentum 

equations to the transport equation. The horizontal 

gradient of atmospheric pressure is assumed to be 

negligible for the SICS area, and is not included in the 

model.

Stresses applied at the channel bottom are calculated from a formulation that includes the square of the 

velocity and a resistance coefficient. This quadratic 

formulation is essentially a depth-dependent friction 

relation based on the assumption of a vertical logarithmic profile of horizontal velocity in a steady flow. The 

equivalent drag coefficient increases with decreasing 

depth, and the correct vorticity is produced at land 

boundaries if the shoreline is adequately resolved by 

the computational grid (Signell and Butman, 1992). 

Shear stress exerted by wind at the water surface 

is typically described as a function of the square of the 

wind speed. For example, Thomas and others (1990) 

listed six formulations for computing shear stress at the 

water surface, five of which are functions of the square 

of the wind speed. The uncertainty in all of the relations, including the one used in the SICS model, must 

be considered when determining the value of the 

empirical coefficient relating stress to wind speed.

Internal stresses are computed from horizontal 

diffusion terms—one for each coordinate direction 

(Leendertse, 1987); that is, the product of a horizontal 

mixing coefficient and the sum of the second derivative 

of the x- and y-direction velocity gradients. This term 

includes the effects of viscous stresses, turbulent 

stresses, subgrid scale momentum transfer, and the 

horizontal gradient of the cross product of vertical 

deviations from the vertical mean (a term resulting 

from the vertical integration of the three-dimensional 

transport equation). Viscous stresses oppose relative 

movement between adjacent fluid particles, but are 

small relative to turbulent stresses. Turbulent stresses 

represent a momentum flux and are a result of the 

decomposition of the nonlinear Navier-Stokes equations. Momentum transfer that occurs at horizontal 

scales greater than the computational grid length is 

resolved by the model through the velocity field, but 

momentum transfer that occurs at the subgrid scale 

must be described empirically. This subgrid scale 

momentum transfer, which becomes less important as 

the computational cell size decreases, is also included 

in the horizontal diffusion term. 
18 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

SWIFT2D uses a formulation for the horizontal 

mixing coefficients that is a function of the kinematic 

viscosity (used to compute viscous stress), horizontal 

gradient of the vertical vorticity, and an unadjusted 

horizontal mixing coefficient (Leendertse, 1987). The 

kinematic viscosity is spatially and temporally invariant for the model domain, as are the unadjusted horizontal mixing coefficients (one for each coordinate 

direction). Vorticity is computed from the velocity 

field.

The vertically integrated transport equation 

includes terms for advection, dispersion, sources, and 

sinks. The dispersion coefficient in each horizontal 

direction is assumed to equal the sum of a dispersion 

in the direction of flow and an isotropic dispersion. 

The dispersion coefficient in the direction of flow is 

computed from a relation (Elder, 1959) that includes 

the depth of flow, velocity, the Manning coefficient, 

and a coefficient relating dispersion to flow properties, 

which is a user-defined value. The isotropic dispersion 

coefficient also is specified by the user and includes the 

effects of wind, waves, molecular diffusion, subgridscale effects, and vertical integration of the transport 

equation.

The final equation required by the model is 

an equation of state relating water density to water 

temperature and salinity. Because water density varies 

only slightly with temperature, temperature is assumed 

to be uniform and constant throughout the model 

domain.

In summary, the governing equations are as 

follows: (1) a vertically integrated continuity equation, 

(2) a vertically integrated longitudinal momentum 

equation, (3) a vertically integrated lateral momentum 

equation, (4) a vertically integrated transport equation, 

and (5) an equation of state relating salinity and 

density of water. These five equations are solved 

simultaneously at each timestep for the five unknowns: 

(1) water level, (2) vertically integrated longitudinal 

velocity, (3) vertically integrated lateral velocity, 

(4) vertically integrated salinity, and (5) vertically 

integrated density.

Numerical Solution Technique

The governing differential equations cannot be 

solved analytically. Instead, the equations are solved 

using a procedure that replaces the continuous differentials in the equations by finite-difference expressions. 

The finite-difference equations are applied at specified, 

equally spaced, computational points in the model 

domain and are solved at successive timesteps to provide 

a close approximation of the time history of water level, 

flow velocity, and salinity within the model domain. 

The finite-difference equations are solved on a 

space-staggered grid (fig. 7). This grid results in an 

efficient solution because velocity points are located 

between water-level points for solution of the continuity equation (Leendertse, 1987). A complete description of the finite-difference formulations for each of the 

four governing conservation equations is given by 

Leendertse (1987).

The alternating-direction implicit (ADI) method 

is used to solve the governing equations. This method 

uses a splitting of the timestep to obtain a multidimensional implicit solution which provides second-order 

accuracy. The advantage of the ADI method over other 

implicit schemes is that solution of each set of algebraic finite-difference equations requires only the 

inversion of a tridiagonal matrix (Roache, 1982). The 

stability and convergence characteristics of the ADI 

technique as applied to the SWIFT2D governing equations are presented by Leendertse (1987). Although the 

method is unconditionally stable, there are some practical limitations to the magnitude of the timestep 

(Roache, 1982), particularly for model domains having 

irregular boundaries (Weare, 1979) or complex 

bathymetries (Benque and others, 1982).

Model Input Requirements

Six types of input information are required 

to execute the SICS model: (1) initial conditions, 

(2) boundary conditions, (3) physical properties of the 

system, (4) model parameter values, (5) orientation of 

the coordinate system, and (6) model options. Initial 

conditions are required to define the water level, velocity, and salinity in each computational cell prior to initiation of a simulation. Except as noted below, initial 

water surface must be level, and the initial velocities 

are usually set to zero. Initial salinity values can be 

uniform or can vary from computational cell to computational cell. Better results are obtained more quickly 

when initial conditions specified in the model closely 

match prototype conditions. The model also can be 

restarted using results saved from a previous simulation 

as initial conditions, but this option was not used in the 

SICS application. When the model is restarted using 

results from a previous simulation as initial conditions, 

the initial water surface need not be level.
Description of Model Structure 19

Information on boundary conditions is required 

at each computational timestep throughout the simulation period. Lateral boundaries can be open (flow 

passes through the boundary in either direction) or 

closed (no flow through the boundary). Time-varying 

boundary conditions for flow or water level and salinity 

must be established at the open boundaries to describe 

inflows and outflows to the model domain. 

Physical properties of the system are described at 

land surface and water surface. The bottom conditions 

are described by the land-surface elevation, a resistance 

coefficient, and ground-water inflow in each computational cell. The land-surface elevation and the resistance coefficient remain constant during a simulation 

period, but ground-water inflow is time varying. The 

water-surface boundary condition consists of the 

spatial and time-varying wind field, evapotranspiration, 

and rainfall inputs. A spatially uniform wind field was 

used for the SICS model application, whereas evapotranspiration and rainfall varied throughout the model 

domain, as subsequently described.

Several regional model parameters must be 

specified prior to each simulation. These parameters 

include air density, latitude of the study area (a single 

value for the entire area), kinematic viscosity of water, 

wind-stress coefficient, the unadjusted horizontal 

mixing coefficients, the isotropic mass dispersion coefficient, a coefficient that relates mass dispersion to flow 

properties, a resistance coefficient for each computational cell and for tidal creeks, and marginal depth. The 

first three parameters (air density, latitude, and kinematic viscosity) are easily specified for the SICS area, 

assuming that the air and water temperature do not vary 

substantially during the simulation period. The other 

parameters are known with less certainty, but results 

from process studies were used to establish these 

parameters as subsequently described. 

A marginal depth, which is used to identify when 

a computational cell is “wet” and when the cell is 

“dry,” must be specified. When the water depth is less 

than one-half the marginal value, the computational 

cell is assumed to be dry and is removed from the flow 

and transport computations. The marginal depth effectively represents the fact that vegetation and microtopography completely impede flow for very shallow 

water. Likewise, in the evapotranspiration computations, as the water depth goes to zero, the volume of 

water available for evapotranspiration reaches zero 

when the water depth reaches one-half the marginal 

value (the same depth at which the computational cell 

is removed from the flow calculations).

The orientation of the coordinate system must 

be specified. At long open boundaries, the governing 

equations are solved by assuming: (1) the velocity that 

is parallel and adjacent to the boundary is zero; and 

(2) the gradient of velocity perpendicular to the boundary is zero. Consequently, to improve model performance near open boundaries, the x-axis is ideally, if 

feasible, aligned with the predominant longitudinal 

axis of the study area so that the y-axis is parallel to 

the upstream and downstream boundaries.

There are three primary user-controlled model 

options. Two options permit the user to specify the type 

and frequency of model output. The form of the numerical scheme used for solution of the advective terms in 

momentum equations also can be selected. Choices 

for the numerical scheme include: (1) omitting the 

advective terms; (2) the Arakawa (1966) method, 

which results in the conservation of vorticity and 

vorticity squared in the simulation; and (3) the Leendertse (1987) method, which is computationally 

ENCLOSES ALL ELEMENTS OF A SINGLE CELL

WATER-LEVEL GRID POINT

DEPTH GRID POINT

V-VELOCITY GRID POINT

U-VELOCITY GRID POINT

m-2 m-1 m m+1 m+2

n-2

n-1

n

n+1

n+2

EXPLANATION

Figure 7. Space-staggered grid used in SWIFT2D.
20 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

simpler than the Arakawa method but does not 

conserve vorticity. The second (Arakawa method) 

option was used for the SICS model. 

Enhancements for Everglades Application

Several enhancements to the SWIFT2D model 

were made to adequately simulate key hydrologic 

processes for the SICS application. The following 

features were added to the model: (1) time-varying 

areal gains (rainfall or ground-water discharge) and 

losses (ground-water recharge), (2) spatially detailed 

computation of evapotranspiration, (3) spatially varying wind-sheltering coefficient, and (4) flexibility for 

computational cells adjacent to flow barriers. These 

and other minor code modifications are discussed in 

this section. A list of the original SWIFT2D routines 

that were modified to create the computer code used for 

the SICS application is given in appendix I.

Rainfall as a Time-Varying Point Source

The original SWIFT2D “rainfall” code has the 

option of designating time-varying point sources and 

sinks in specific computational cells. The computational algorithm simply adds or subtracts the volume 

per timestep from the appropriate cell. For the SICS 

application, it is desirable to have such a specified input 

applicable to all cells in the computational domain to 

represent the effects of rainfall. A subroutine created 

for SWIFT2D reads in rainfall information at the same 

time interval specified for the tidal input data. For each 

time interval, a flag specifies whether rainfall occurs 

during the time interval. If rainfall does occur, a grid of 

rainfall values is read in and applied to every active cell 

(wet cell within the computational domain). 

The concentration of all constituents in rainfall 

inflow to each cell is assumed to be zero. Following the 

addition of water to a cell from rainfall, the constituent 

concentration within each cell is recalculated based on 

the ratio of added volume from the input to total cell 

volume. Some limitations to this approach for treating 

rainfall inputs are described as follows:

• There are no inputs to dry cells, which conceptually 

is equivalent to assuming that rainfall to dry 

areas infiltrates and does not run off to wet cells. 

This assumption has not been tested, but seems 

reasonable for the flat terrain of the SICS area. 

However, ground-water discharge to the study 

area is likely affected by the infiltration.

• Rainfall with nonzero constituent concentration are 

not represented. For the SICS application, 

however, the only constituent included in the 

simulations is salinity, and the salinity of rainfall 

is generally negligible.

Spatially Detailed Evapotranspiration 

Calculations

Evapotranspiration is the primary mechanism by 

which water leaves the Everglades (Duever and others, 

1994). Evapotranspiration rates depend on vegetation 

characteristics (rainfall interception and leaf area), net 

solar radiation, wind (advection and turbulent transport), relative humidity, and plant-available water 

capacity which is a function of rooting depth, soil 

hydraulic properties, and water depth (Zhang and 

others, 2000). The SICS model represents the spatial 

variation in vegetation and water depth at the computational grid scale (305 × 305 m), and data do not exist on 

smaller scales to represent evapotranspiration, which 

can depend strongly on water depth and vegetation at 

the same scale. Enhancements were made to SWIFT2D 

to include evapotranspiration in the calculations and to 

include this process at the scale of the computational 

grid.

Evapotranspiration at a particular location in the 

Everglades can be reasonably represented by a formulation that is a function of water depth and solar radiation (German, 1999). Research is continuing to 

improve evapotranspiration predictions by including 

vegetation type as variable in the formulation (German, 

2000b). The formulation developed by German (1999), 

described later, was used to calculate evapotranspiration for the SICS model. 

The evapotranspiration volume is determined for 

each computational cell during each computational 

timestep, and this volume is removed from the model 

domain. Constituent concentrations in the computational cell are adjusted for the change in water volume. 

In reality, evapotranspiration continues even when the 

water level is below land surface, with water extracted 

from the unsaturated zone and shallow ground-water 

system. However, the SICS model represents surface 

water only, so evapotranspiration that withdraws water 

from below land surface is not represented in the 

model. When the water depth is less than the userdefined marginal depth, the evapotranspiration rate is 

multiplied by a factor of:

(2 × depth − marginal depth)/marginal depth.
Description of Model Structure 21

With this equation, the evapotranspiration rate reaches 

zero when the depth reaches one-half the marginal 

depth (the same depth at which the dry computational 

cell is removed from the flow calculations).

There are three limitations to the evapotranspiration calculation used in the SICS model. First, water 

lost from below the ground surface through evapotranspiration is not included in the calculations, so the 

surface water required to resaturate the soil is not 

accounted for in the simulations. Second, the evapotranspiration rate is actually a function of the available 

energy in the water rather than solar radiation. The 

pyranometer measurement of solar radiation is a useful 

areal indicator of local solar radiation and available 

energy. However, because solar radiation becomes zero 

at sunset when significant heat energy remains in the 

water, there is a tendency in the model to underestimate 

evapotranspiration at sunset. Likewise, evapotranspiration is generally overestimated near sunrise when solar 

radiation is heating the water. However, over a daily 

cycle, the total evapotranspiration volume, which is on 

the order of 0.3 cm, generally is accurately predicted. 

Finally, the evapotranspiration algorithm in the SICS 

model was based on measurements in the study area 

and may not be applicable to other areas.

Wind-Sheltering Coefficient

Because SWIFT2D was originally developed for 

open-water applications, a spatially uniform surface 

wind stress was applied to the entire model domain. 

However, highly vegetated areas, such as the wetlands 

in the SICS area, shelter the water surface from the 

wind (Reid and Whitaker, 1976), effectively reducing 

the wind stress at the water surface. The work of Jenter 

(1999) supports this idea that emergent vegetation has a 

substantial sheltering effect on water-surface wind 

forcing. This reduction of wind stress at the water 

surface was simulated in this study by using a windsheltering coefficient, which is a simple linear multiplier of wind speed. Wind-sheltering coefficients have 

been successfully used in other hydrodynamic models 

to account for the effects of seasonal variation in vegetation along the shoreline of a reservoir (Cole and 

Buchak, 1995).

Preliminary results from research on the effects 

of wetland vegetation on wind stress at the water 

surface (Jenter, 1999) suggest that a spatially uniform 

sheltering coefficient can be applied to areas with 

emergent vegetation. The SWIFT2D model was modified 

by adding a simple algorithm for efficiently applying 

the wind-sheltering coefficient. This sheltering coefficient is applied to all computational cells having a 

Manning’s coefficient greater than 0.1, which is based 

on the assumption that the high Manning’s coefficient 

indicates the presence of emergent vegetation, which is 

true for the SICS application. This approach simplifies 

model input by avoiding the need to define a separate 

array of cell-by-cell wind-sheltering coefficients. For 

cells with no emergent vegetation, the wind-sheltering 

coefficient was 1.0.

Computational Cells Adjacent to Flow Barriers

In the original version of SWIFT2D, computations ceased if a computational cell adjacent to a flow 

barrier in the direction of flow became dry. When the 

adjacent computational cells are wet, the flow barrier 

acts as a levee or weir. However, barriers are used in the 

SICS model to represent the coastal embankment 

which, in the natural system, has adjacent high ground 

that is dry under some conditions. Hence, an enhancement was required to allow computations to continue 

even if computational cells adjacent to barriers were 

dry. The code was modified to provide the constraint 

that there was no flow over or through a barrier at locations where computational cells on either side of the 

barrier were dry. Flow is allowed to enter a cell adjacent to a barrier from other directions. There is no storage of constituents at the barrier when the cell adjacent 

to the barrier is dry. This modification resulted in a 

reasonable representation of the coastal embankment.

This enhancement does not, however, cover all 

possible conditions that can occur at a barrier. For 

example, consider the condition in which cells on both 

sides of a barrier are initially dry and one cell becomes 

wetted as a result of inflow. Because of the previously 

described algorithm, no flow can occur across or 

through the barrier. The dry cell remains artificially dry 

and can only be rewetted from another cell on the same 

side of the barrier as the dry cell. This situation does 

not occur in the application of the SICS model, but 

users should be aware of such a limitation in other 

SWIFT2D applications.

Other Code Modifications

Several other minor modifications were made 

to the original SWIFT2D code for the SICS area 

application:
22 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

• The code was modified to set the wind friction to 

zero in computational cells adjacent to a waterlevel boundary. This modification helps prevent 

numerical oscillations at the boundary: a situation observed in other model applications (R.W. 

Schaffranek, U.S. Geological Survey, oral 

commun., 1999).

• Print routines were modified so that: (1) simulated 

constituent concentrations at selected locations 

can be printed at the same time interval as water 

levels and discharges, and (2) simulated water 

levels and velocities are printed to a different file 

than the remainder of the simulation output. The 

output units for the simulated velocities also 

were given increased precision to accommodate 

the low velocities in the SICS area.

• The original version of SWIFT2D would not operate 

properly if more than one barrier was present in 

a column of computational cells. The code was 

modified to allow multiple barriers to be specified per column. 

CONSTRUCTION, CALIBRATION, TESTING, AND APPLICATION OF FLOW AND 

TRANSPORT MODEL 

Implementation of the SWIFT2D model for the 

SICS study area required: (1) development of the 

computational grid, (2) specification of boundary 

conditions, and (3) identification of values for model 

parameters. Each of these steps is described in the 

subsequent sections along with model calibration, testing, and application results.

Computational Model Domain

The model domain is irregularly shaped and 

contains 9,738 computational cells (fig. 8). The computational cells are 305 m square, so the total area of the 

model domain is 905.8 km2. The maximum north-south 

extent of the domain is 29.90 km (98 computational 

cells), and the maximum east-west extent is 45.14 km 

(148 computational cells). The 305-m square grid cells 

provide good resolution of the study area, and do not 

require unreasonable computer resources to perform 

simulations. The Florida Bay open boundary of the 

model was positioned a sufficient distance from the 

freshwater-saltwater mixing zone to minimize the 

problems associated with gradient type boundary 

conditions.

As previously described, land-surface elevations 

were measured at about 400-m spacings (Desmond and 

others, 2000). A linear distance-weighted four-point 

interpolation of the 400-m (1,312 ft) spaced data was 

used to assign land-surface elevations to each computational cell of the 305-m SICS grid (fig. 9).

 The spatial characteristics of the Buttonwood 

Embankment (fig. 8) vary at a scale that is much 

smaller than the computational cell size. Rather than 

attempting to assign relatively high land-surface elevations to computational cells along the embankment, 

which would result in poor resolution of the embankment, flow barriers were used to represent the embankment (fig. 8). In cells where the embankment is 

diagonal to the cell, the embankment is represented by 

a series of north-south and east-west flow barriers 

within the cell. The location of the embankment was 

derived from field observations aided by USGS 

1:24,000 scale topographic maps. All creeks flowing 

through the embankment are defined as cuts in the flow 

barriers (fig. 8). Elsewhere, creeks are defined as solitary flow barriers with the sill elevations at the creek 

bottom. (Creek dimensions were presented earlier in 

the topography section.)

Boundary Conditions

Boundary conditions are supplied at the water 

surface and at lateral boundaries. These boundary 

conditions are described in this section. 

Water-Surface Boundary

The “rigid lid” assumption, in which the water 

surface in each computational cell moves vertically, but 

no deformation of the level water surface in the cell 

occurs, is used at the water-surface boundary. This 

implies that high-frequency wind waves are not 

included in the simulations. As previously described, 

evapotranspiration and rainfall volumes are computed 

for each computational cell during each timestep, and 

these volumes are removed (evapotranspiration) or 

added (rainfall) to the computational cells. 

Wind conditions are represented as spatially 

uniform over the model domain, and data from the Old 

Ingraham Highway site (fig. 1 and table 1) were used to 

define the wind field. Measured fluctuations in wind 

conditions at less than an hourly timescale typically do 

not reflect regional patterns. Therefore, a moving average wind speed was used for the boundary. For each
Construction, Calibration, Testing, and Application of Flow and Transport Model 23 0 1 5 MILES 0 1 5 KILOMETERS 234 234

C-111

Joe Bay

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

McCormick Creek Taylor River East Creek Mud Creek Trout Creek

Shell Cree

Stillwater

Creek

Ore

Cr

West

Highway

Creek

Ea

High

Cre

Alligator Creek 1

1

10 20 30 50 40 60 70 80 90 100 110 120 130

140

14

1020

30

40

5060

70

80

90

98

Long Lake

EXPLANATION

80°  ́ 45

25°25 ́25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°35 ́ 

BOUNDARY OF SOUTHERNINLAND AND COASTAL SYSTEMS(SICS) STUDY AREAAPPROXIMATE AREA OFTAYLOR SLOUGH

EVERGLADES NATIONAL PARK

LOCATION OF HYDRAULIC BARRWITH CUTS TO REPRESENT CREBUTTONWOOD EMBANKMENT

Base from U.S. Geological Survey digital data, 1972Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road

Figure 8. Model grid, location of embankment barriers, and location of creeks in the study area.
24 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Figure 9. Land-surface elevation in grid cells.
Construction, Calibration, Testing, and Application of Flow and Transport Model 25

computational timestep, the east and north components 

of the wind speed were averaged over a 5-hour period 

centered on the timestep. This temporal smoothing 

yields a realistic regional wind field (H.L. Jenter, U.S. 

Geological Survey, oral commun., 1999).

Wind measurements were made 2.4 m above 

land surface, but the wind drag coefficient, Cd, is applicable to wind speeds measured at a height of 10 m 

above land surface. Wind speeds measured at 2.4 m 

were converted to speeds at 10 m by the equation 

(Chadwick, 1996):

, (2)

where W is the wind speed at the desired height, Wm is 

the wind speed at measured height, z is the desired 

height above the land surface of 10 m, zm is the 

measured height of 2.4 m, and zo is the roughness 

height. Assuming that zo = 1 m, then equation 2 

reduces to W = 2.5Wm.

Lateral Boundaries

Lateral boundaries are defined as open (having 

free exchange of water and salt across the boundary) or 

closed (having no flow across the boundary). Open 

boundaries can be described by a time series of 

discharge or water level, with discharge boundary 

conditions generally providing more realistic simulation results. The SICS model lateral boundaries are 

identified in figure 10.

Inflow at Taylor Slough bridge is computed with 

a stage-discharge relation (Everglades National Park, 

written commun., 1999) from the Taylor Slough bridge 

site. Discharge entering from the north into L-31W, 

released from hydraulic gate structure S-175, is 

provided by the SFWMD using a stage-discharge 

rating at S-175. 

Dynamics of the flows entering the wetlands 

from the section of C-111 Canal between hydraulic 

control structures S-18C and S-197 (fig. 10) are of 

great interest and are under investigation (Schaffranek, 

1996; Schaffranek and Ball, 2000). The S-18C 

discharge is provided by the USGS, and S-197 is 

usually closed. When S-197 is occasionally opened, 

flow is provided by the SFWMD. The levee on the 

southern side of the section of C-111 has been removed 

W

Wm

--------

z

zo

---- ⎝ ⎠ ⎛ ⎞ ln

zm

zo

-----

⎝ ⎠ ⎜ ⎟ ⎛ ⎞

ln

= -----------------

to promote delivery of additional water to the easternmost area of the ENP wetlands (fig. 1) (Ball and 

Schaffranek, 2000a). The discharge entering the 

wetlands along C-111 is assumed to be the difference 

in flows at S-18C and S-197. Field observations by the 

USGS and ENP indicate that the northerly flows 

through several culverts that line this section of the 

canal are minimal due to the higher topography on the 

northern side of the canal. Within the model, the canal 

discharge to the model domain is placed in an artificial 

topographic low along the boundary of the SICS area 

adjacent to C-111 (fig. 9) to allow uniform flow distribution along the entire section of C-111 between S-18C 

and the US-1 boundary of the SICS flow model just 

upstream of S-197. Evapotranspiration losses from this 

boundary are simulated in the same manner as for the 

rest of the model domain.

The lateral boundary along C-111 Canal in the 

northeastern part of the model domain actually represents ground-water interaction through the levee with 

C-111 Canal. The ground-water interaction between 

the L-31W and C-111 Canals north of S-18C (fig. 10) 

is considered important. Specifically, when water levels 

in the C-111 Canal are higher than the land elevation 

west of the levee, leakage through and under the levee 

supplies water to the wetlands west of the levee, 

supplementing the wetland ponding. Although 

SWIFT2D is a surface-water model, the ground-water 

interaction of the wetlands with the C-111 Canal can be 

approximated. Water levels at the boundary cells north 

of S-18C and east of the levee are assigned measured 

S-18C water levels for boundary condition treatment. 

The frictional coefficient for the model cells within the 

boundary is set to represent flow resistance equivalent 

to the hydraulic conductivity through and under the 

levee. In this way, leakage though and under the levee 

is represented as flow through these boundary cells. 

At lower water levels in the C-111 Canal, the simulated 

leakage would tend to dry the boundary cells. Under 

these conditions, the model would represent no 

exchange through and under the levee.

The boundary along Old Ingraham Highway and 

southward along part of Main Park Road (fig. 10) experiences overtopping and occasional culvert flow. Flow 

measurements have been made by ENP at the culverts 

along Main Park Road (fig. 10), which includes the 

western Old Ingraham Highway boundary, but none 

have been made on the rest of Old Ingraham Highway 

nor have overtopping flows been measured. Due to the 
26 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

scarcity of these flow data, the model boundary was 

constructed using water-level data from five ENP field 

sites (NMP, NP46, CY2, CY3, and NP67) shown in 

figure 10. These sites provide data on stage along the 

south and east side of Old Ingraham Highway (fig. 10). 

Because Old Ingraham Highway is just outside the 

model domain defined by these stage sites, it was not 

necessary to simulate flow in the culverts under the 

highway. 

The Old Ingraham Highway and Main Park Road 

boundary is designed in three segments. Boundary cell 

water levels were linearly interpolated between each 

pair of adjacent sites. Segments are from: NMP to 

NP46, NP46 to CY3, and CY3 to NP67. This approach 

is justified by the fact that station CY2 had water-level 

values very close to those obtained by a linear interpolation from CY3 to NP67. Water levels along this 

boundary were set to zero when field sites measured 

water levels below the land surface. 

Figure 10. Model boundaries and data-collection sites used to determine discharge, conductivity, and water-level 

boundary conditions.
Construction, Calibration, Testing, and Application of Flow and Transport Model 27

Field measurements indicate that the culverts on 

Old Ingraham Highway south of NMP carry negligible 

flow (Stewart and others, 2000), which is also true for 

the section of Old Ingraham Highway northeast of 

NP67. Hence, these boundaries were established as 

no-flow boundaries. Flows are not available for the 

culverts under US-1. Therefore, this boundary was 

specified with a measured water level at nearby West 

Highway Creek (fig. 10).

The open boundary along the southern part of the 

model has a specified water-level condition designed to 

closely match measured water levels in Florida Bay 

and at coastal creeks. In order to determine if there is a 

significant diurnal tide signature at the coastal waterlevel stations (fig. 2), a spectral analysis was performed 

on the water-level data from selected sites. The spectrum is the Fourier transform of the autocovariance 

function ατ, which is computed from the field data by:

, (3)

where t

max is the total time of the data set, zt

 is the water 

level at time t, z is the mean water level, and zt+τ is the 

water level at a later time (t + τ). The spectrum Γω is 

then calculated from the autocovariance function by the 

equation (Lumley and Panofsky, 1964):

, (4)

ατ

zt ( ) – z zt + τ ( ) – z

t = 1

t

max

∑

t

max – 1 = ----------------------------------------------------

Γω

1

2π

------

( )α ωτ τ cos

τ = 1

τ

max

∑

τmax

= --------------------------------------

where ω is the frequency. At frequencies (ω) that have 

more significant autocovariance values, the value of the 

spectrum is higher. Thus, the spectrum shows dominant 

frequencies of fluctuations. A spectrum calculated for 

downstream water levels at structure S-21 along the 

shore of Biscayne Bay (fig. 1) shows a strong lunar tidal 

signature (fig. 11). The sharp peak in the spectrum at 

one-half day (12 hours) indicates the lunar tidal cycle. 

In comparison, the spectra at McCormick Creek (fig. 12) 

and Trout Creek (fig. 13) do not show this lunar tide 

signature. The water-level fluctuations at these coastal 

creek outlets to Florida Bay are not subject to a standard 

lunar tide and instead are probably influenced more by 

wind.

The southern SICS model boundary lies 

between the water-level data collected at the coastal 

flow stations at McCormick Creek, Taylor Creek, and 

Trout Creek and offshore ENP stations BK, WB, and 

BN (fig. 10). An average of these water levels from 

these seven stations was used to define the boundary. 

The average is used for the entire boundary to avoid 

numerical oscillations that can occur when small lateral 

water-level differences are forced along long open 

boundaries (R.W. Schaffranek, U.S. Geological Survey, 

oral commun., 2000).

Salinity must be defined at all open boundaries. 

All the discharge open boundaries are located inland 

and were assigned a salinity value of zero. Flow 

through the culverts beneath US-1 is assumed to have 

the salinity recorded at East Highway Creek (fig. 10). 

Salinity data measured at offshore ENP stations BK, 

WB and BN (fig. 10) were used for the southern 

boundary. Salinity was linearly interpolated between 

sites BK and WB and between sites WB and BN. 

0

4

3

2

1 X 10

0

X 10

X 10

X 10

2

2

2

2

2 4 6 8 10 12 14 16 18 20

PERIOD LENGTH, IN DAYS

SPECTRUM

Figure 11. Spectral function of stage downstream of structure S-21.
28 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Salinity west of site BK was assumed to be equal to site 

BK values. Likewise, salinity east of site BN was 

assumed to be equal to values measured at site BN. All 

of the salinity values were then translated north and 

applied at the model boundary.

Model Parameters

Implementation of the SWIFT2D model for the 

SICS study area required specification of values for 

critical model parameters. This section describes the 

various model parameters including computational 

control parameters, wind coefficients, evapotranspiration, frictional resistance both in vegetated marshes and 

coastal creeks, and the dispersion coefficient for the 

transport equation.

Computational Control Parameters

Control of the computational simulations 

requires specification of an integration timestep, selection of a frequency for reevaluation of depth-dependent 

Chezy coefficients, and assignment of parameters for 

the wetting and drying algorithm. A 7.5-minute 

computational timestep of one-half the data-collection 

interval, was used. The Courant number was less than 4 

for this timestep size.

The numerical solution in the SICS model does 

not allow the computation of depth-dependent Chezy 

friction factors from the specified Manning coefficients 

at times when the grid nodes are checked for drying 

and flooding. For this application, new Chezy values 

are computed every 45 minutes, and drying and flooding 

are checked every 30 minutes; therefore, the resultant 

Chezy computations are delayed one timestep only 

every 90 minutes. 

PERIOD LENGTH, IN DAYS

0

4

3

2

1 X 10

0

X 10

X 10

X 10

2

2

2

2

2 4 6 8 10 12 14 16 18 20

SPECTRUM

Figure 12. Spectral function of stage at McCormick Creek.

PERIOD LENGTH, IN DAYS

0

4

3

2

1 X 10

0

X 10

X 10

X 10

2

2

2

2

2 4 6 8 10 12 14 16 18 20

SPECTRUM

Figure 13. Spectral function of stage at Trout Creek.
Construction, Calibration, Testing, and Application of Flow and Transport Model 29

A Chezy value cannot be computed from the 

assigned Manning coefficient when the water depth in 

a cell is less than the marginal value, so the Chezy 

value must be assigned in those cases. As previously 

discussed, the user-supplied value for marginal depths 

in dry cells was set to 0.10 m. The residual depth 

values for dry cells, at which higher Chezy resistance 

values are assigned, is intended both to approximate 

the naturally occurring drop in flow velocities to zero 

at the bottom and to suppress the potential growth of 

local numerical instabilities that can develop in 

complex shallow water bodies. If a wetland cell has a 

Manning’s n of about 0.4, and the water depth is at the 

marginal value of 0.10 m, the Chezy value is about 3. 

However, in areas of the model which are open water 

and have a Manning’s n of 0.02, the Chezy value is 60 

at the marginal depth. Because virtually all flooding 

and drying occurs in the wetlands, an average Chezy 

value of 5 is specified for cells with depths less than the 

marginal depth.

Wind Coefficients

The coefficient for the wind-friction term, Cd, in 

the momentum equation has historically ranged from 

1.5 × 10-3 for light winds to 2.6 × 10-3 for heavy 

winds (Wilson, 1960). A research project is underway 

to better define this coefficient and the effects of emergent vegetation (Jenter, 1999). A slightly lower value 

(1.2 × 10-3), identified for winds less than 36 m/s 

(Large and Pond, 1981), was found to work well in the 

model. The wind-sheltering coefficient, Sw, for emergent vegetation (as previously discussed) is described 

by Reid and Whitaker (1976). Best estimates of Sw

range from 0.1 to 0.5; a value of 0.33 is used in the 

model. Jenter and Duff (1999) suggest that the Reid 

and Whitaker (1976) values are reasonable for the 

SICS area wetlands.

Evapotranspiration

Results of research to parameterize evapotranspiration in southern Florida wetlands were used 

to compute evapotranspiration in the SICS model 

(German, 1995). The Priestly-Taylor equation relates 

evapotranspiration to available energy (Linsley and 

others, 1982, p. 162-163):

ET α , (5)

δ R[ ] n – G – M

HL( ) δ γ + = -----------------------------------

where ET is evapotranspiration, α is the site coefficient, 

δ is the slope of the saturation-vapor-pressure curve, Rn 

is the net radiation exchange, G is the soil heat flux, M 

is the rate of heat storage above the soil and below the 

point where Rn is observed, HL is the latent heat of evaporation, and γ is the Bowen ratio coefficient.

Substantial site-specific information is needed to 

use equation 5. Comparison of a number of sites near 

the model area indicates that the coefficient α can be 

expressed as a function of solar radiation, χ, in watts 

per square meter and water depth, d, in meters 

(German, 1999):

α = 1.036 – 0.000388χ + 0.4564d – 03.3342d2 . (6)

No strong correlation between α and vegetation type 

was found by German (2000a; 2000b) in the sets of data 

available from nine evapotranspiration sites, suggesting 

that a general formulation is valid for all vegetation 

types in the model domain.

Whereas most of the parameters in equation 5 

are site specific and difficult to measure, χ in equation 

6 is assumed to be spatially uniform at the scale of the 

model. Therefore, regression analysis was used to estimated ET from α and χ. Hourly data from 1996 at the 

Old Ingraham Highway site and the P-33 site (fig. 1) 

were used in the analysis; data were used only when 

measured water levels were above land surface. 

Although located north of the study area, the P-33 site 

has vegetation and hydrology similar to the SICS area. 

Two forms of the regression were used: (1) ET as a 

function of αχ and χ, (equation 5 suggests a multiplicative relation between α and available energy), and 

(2) ET as a function of α and χ. The two prediction 

equations are: 

ET = – 1.32 × 10-5αχ + 2.73 × 10-5χ + 2.56 × 10-3 (7)

and

ET = – 2.30 × 10-3α + 1.70 × 10-5χ + 1.79 × 10-4 . (8)

Both equations had a correlation coefficient ρ of 0.79 

and were statistically significant at p < 0.01.

Given that neither equation has a stronger correlation, the multiplicative relation of α and χ in equation 

7 was used. A time series of pyranometer readings χ

are input from the evapotranspiration data set to the 

model to compute an effective cell-by-cell evapotranspiration value. The coefficient α is computed for each 

cell by equation 6, and the evapotranspiration rate 

computed by equation 7 is applied to the cell for the 

timestep as described in the evapotranspiration computation section.
30 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Frictional Resistance — Vegetation

One of the most important flow-controlling 

terms in virtually all hydraulic models is the resistance 

to flow or frictional resistance. Unfortunately, very 

little information exists in the literature to guide selection of appropriate values for friction coefficients in 

vegetated wetlands, such as in the SICS study area. 

Because of the importance of this term, field and laboratory research was performed to determine the effective frictional resistance to water flow through differing 

Everglades vegetation types (Lee and others, 1999). 

Extensive hydraulic measurements (velocity, depth, 

hydraulic gradient, and so forth) were made in a laboratory flume containing transplanted marsh vegetation. 

Field measurements of velocity, depth, and vegetation 

type and density were also made in conjunction with 

point measurements of the hydraulic gradient using a 

portable pipe manometer at many locations in the study 

area (Lee and others, 2000a). The results indicated that 

flow regimes in the study area are not fully turbulent 

flow and are normally within the transition region 

between laminar and turbulent flow (Lee and others, 

2000b). Because the Manning equation was formulated 

for fully turbulent flow and the SICS flow is transitional, an effective Manning’s n was calculated for use 

in the equations developed for SWIFT2D.

Preliminary results show high values for 

Manning’s n with little variation among vegetation 

types. For sawgrass, 14 measurements gave an 

average Manning’s n of 0.43 s/m1/3 with a range from 

0.23 s/m1/3 to 0.60 s/m1/3. For rush, four measurements 

gave an average Manning’s n of 0.46 s/m1/3 with a 

range from 0.36 to 0.57 s/m1/3. For mixed rush/ 

sawgrass, six measurements gave an average Manning’s 

n of 0.38 s/m1/3 with a range from 0.26 to 0.61 s/m1/3. 

The range of average values for different vegetation 

types is 0.08 s/m1/3 (J.K. Lee, U.S. Geological Survey, 

written commun., 1998). According to Schaffranek and 

others (1999), the average values of Manning’s n for 

different sawgrass densities are 0.42 to 0.48 s/m1/3; a 

range for different densities of 0.06 s/m1/3. The range of 

variation within each type is larger than both the average range between vegetation types as well as the range 

between densities within the same type. Acknowledging that measurement variation exceeded type variation, average values for each type were used: 0.43 

s/m1/3 for sawgrass, 0.46 s/m1/3 for rush, and 

0.38 s/m1/3 for mixed rush/sawgrass. These values 

were used as a guide for the model based on vegetation 

types identified in figure 4. Many areas that did not 

clearly fall into one of these vegetation types were 

assigned a Manning’s n of 0.4. Open-water areas were 

given a nominal value of 0.02. This areal distribution of 

Manning’s n coefficients is shown in figure 14.

Due to microtopography and vegetation, the 

effective flow resistance factor for a model cell varies 

with the flow depth. Research is underway to identify 

the hydraulic factors that affect the frictional resistance 

and to determine resistance as a function of flow depth 

and velocity (Jenter, 1999). No final conclusions have 

been drawn as to the most suitable form of the resistance factor variation. However, when upscaling frictional resistance from point measurements at the field 

scale to represent resistance of an entire model grid, 

microtopography has the capability of increasing the 

effective frictional resistance at lower water depths. 

The variation in topography creates sinuosity in flow, 

increasing the flow resistance experienced at shallow 

depths. Based on this functionality, a form is proposed 

and used in the SICS model to represent the variation 

of Manning’s n with depth:

neff = nref(dref /d)power, (9)

where

The parameter dref would theoretically be the 

water depth at which the previously mentioned field 

value nref was measured. Numerical experiments with 

the SICS model indicated that best results were 

obtained with dref = 0.6 m and power = 2. The values of 

these coefficients would logically depend on the topographic and vegetative features of the application 

region.

Flow Coefficient — Coastal Creeks

Resistance coefficients are also needed for the 

coastal creeks that convey water to Florida Bay. The 

approach used to establish reasonable resistance coefficient values for the SICS model included numerical 

experiments to adjust coefficients to closely match 

computed and measured creek flow in five creeks. 

Field confirmation of these values was then obtained 

neff is the effective Manning’s n, 

nref is the reference Manning’s n from preliminary 

field estimates, 

dref is the reference water depth,

d is water depth, and

power is the exponent that represents nonlinear 

characteristics of the relationship. 
Construction, Calibration, Testing, and Application of Flow and Transport Model 31Figure 14. Manning’s 

n values used in the model.
32 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

in one creek by measuring sufficient information to 

compute Manning’s n for 1 year. The values were also 

compared to those available in the literature.

The regions where coastal creeks cross the 

Buttonwood Embankment (fig. 2) are represented in 

the SICS model as cuts in barrier cells. The flow 

condition that occurs almost exclusively in the cuts 

is submerged weir flow. The hydraulic barrier equation 

defining this flow condition in the model is 

(Leendertse, 1987, p. 34):

, (10)

where Q is discharge in the stream, Cr is a flow coefficient term of the stream segment, B is stream width, d is 

depth, g is gravitational acceleration, and ∆h is head 

drop across the embankment. Equation 10 is similar to 

a weir flow equation. The Manning equation for this 

assumed rectangular cross section is:

, (11)

where λ is 1 in metric units and 1.49 in English units, 

and L is the stream length.

Combining equations 10 and 11 gives:

. (12)

Equation 12 can then be used to estimate 

Manning’s n from the model calibrated Cr value. 

Values of Cr were calibrated to match measured flows 

for the five creeks where discharge data were available. 

Results are presented in table 3 along with the stream 

lengths, L, estimated from USGS topographic quadrangle maps. Values of L were not allowed to exceed 610 

m (the width of two cells) because the section of the 

stream crossing the embankment is represented in the 

model as occurring between the cell immediately 

upstream of the barrier and the cell immediately downstream. Effective Manning’s n values are computed 

from equation 12 using an average creek depth of 1.5 

m. West Highway Creek has a substantially lower n

than the others creeks, and field observations indicate 

this creek has the least vegetation. The range of n

values for the creeks, other than West Highway Creek, 

is generally considered to be valid for heavily vegetated 

reaches (French, 1985, p. 129).

Q Cr = Bd 2g∆h

Q λ

n

--Bd5 3/ ∆h

L = ------

n

λd2 3/

Cr 2gL = --------------------

Manning’s n for a coastal creek can be inferred 

from the measured creeks to be about 0.1 (table 3). For 

the creeks where discharge was not measured, values of 

Cr were estimated using equation 12. These values 

assume that the Manning approximation is valid, and 

the frictional resistance is similar to the average of the 

measured creeks.

As a further investigation of the flow coefficients 

for the coastal creeks, a supplemental continuous 

water-level and discharge monitoring station was 

installed 3.22 km upstream from the original coastal 

station on Taylor River (fig. 2). The measured 

discharge and water-level differences between the original station and the upstream station were used to determine n from Manning’s equation for daily average data 

from July 31, 1999 to August 1, 2000. The computed 

Manning’s n for each day was averaged for the period 

and yielded a mean value of Manning’s n of 

0.121 s/m1/3 with a standard deviation of 0.078 s/m1/3. 

The value of n determined by using equation 12 

and calibrating the model to measured flows was 

0.152 s/m1/3 at Taylor River. Thus, the difference 

between the Manning’s n value obtained by calibrating 

the model to measured flows and that obtained directly 

from field measurements is less than the standard deviation of the field measurements.

Although the Manning equation for surface 

water applies for turbulent flow and Darcy’s law for 

ground water applies for laminar flow, Merritt (1996) 

found it useful to approximate overland flow with 

Darcy’s law in a ground-water model. In this study, an 

Table 3. Stream friction terms and lengths and Manning’s n

[Cr, friction term of the stream segment; n, Manning’s coefficient]

Site name Cr

Length

(meters) Effective n

McCormick Creek 0.10 610 0.121

Taylor River .08 610 .152

Mud Creek .07 488 .194

Trout Creek .25 146 .099

West Highway Creek .35 219 .058

Alligator Creek .08 610 .1*

East Creek .10 390 .1*

Shell Creek .08 610 .1*

Stillwater Creek .08 610 .1*

Oregon Creek .08 610 .1*

East Highway Creek .08 610 .1*

* Estimated vlue.
Construction, Calibration, Testing, and Application of Flow and Transport Model 33

analogous technique is used to represent the groundwater interactions with the C-111 Canal in a surfacewater model. Fish and Stewart (1991) indicate a 

hydraulic transmissivity in the area between the 

L-31W and C-111 Canals of about 56,000 m2/d. 

Equating the Manning equation with Darcy’s law 

yields the following:

, (13)

where λ is Manning’s constant (1.49 in English units, 

1 in metric units), d is overland flow depth adjacent to 

the canal, Sf

 is surface-water slope, and T is aquifer 

transmissivity.

Solving equation 13 with an average flow depth 

of 0.1 m, a water slope of 0.0005, and a transmissivity 

of 56,000 m2/d = 0.648 m2/s yields a Manning’s n of 

1.5. Raising the flow depth to 0.3 m raises Manning’s n

to 9.3, and a flow depth of 0.6 m yields a Manning’s n

of 29.5. With this level of uncertainty and unusually 

high values of n, an order of magnitude value for n of 

10 was assigned to cells that represent ground-water 

flow between the C-111 Canal and the model domain.

Dispersion Coefficient

The transport of salt and other constituents in 

the model is affected by the dispersion coefficient in the 

transport equation. The magnitude of the dispersion 

coefficient is scale dependent; the larger the water body, 

the larger the coefficient. The effective dispersion coefficient is on the order of meters squared per second in 

open channels, whereas its magnitude is hundreds of 

meters squared per second in estuaries (Fischer and 

others, 1979). In application of the dispersion coefficient 

in a numerical model, the length scale of significance is 

the cell size. Additionally, numerical diffusion can result 

from solution approximations in numerical models. This 

creates an additional dispersion component because 

concentrations at the end of a timestep must be assigned 

to the two closest computational nodes rather than at an 

exact physical location (Fischer and others, 1979). The 

horizontal dispersion coefficient, D, is calculated as:

, (14)

where σ2 is the variance of the constituent concentration 

distribution. In the case of the SICS model, if the mean 

velocity u ≈ 0.05 m/s, which would be an unusually high 

value considering the field measurements (Tillis, 2001), 

λ

n

-- d

5

3

--

Sf TSf =

D

0.5 σi + 1

2

σi

2 ( ) –

∆t = -------------------------------------

then the ratio of the distance traveled in one timestep 

u∆t to the grid size ∆x is about 0.07. This means that at 

the end of the timestep, mass originating at the edge of 

the cell has moved to an average location x = 0.07∆x. 

The mass must be reassigned to node locations: 0.93 

fraction to x = 0 and 0.07 fraction to x = ∆x. Thus, at the 

end of the timestep, 0.93 fraction of the mass is at a 

distance 0.07∆x from x, and 0.07 fraction of the mass is 

at a distance 0.93∆x from x. The increase in variance 

that is solely due to this numerical process is:

σ2 = 0.93(0.07∆x)2 + 0.07(0.93∆x)2 = 0.065∆x2. (15)

This yields a numerical dispersion of D = (1/2)0.065 

(305 m)2/450s = 6.7 m2/s. With a lower mean velocity 

of u = 0.01 m/s typically found in the wetlands, numerical dispersion is reduced to 1.5 m2/s. Numerical dispersion is much smaller than the physical dispersion 

described in the next section.

Calibration

The model was calibrated by adjusting computational control parameters over reasonable ranges to 

produce the best match between computed and 

measured values of velocity flow and salinity for the 

calibration period. The calibrated model was subsequently applied to a different time period to verify or 

assure that the determined parameter values apply for 

conditions other than those used for calibration.

The calibration period was chosen to coincide 

with a time of intensive measurement of flow velocities 

in the wetlands. The 1-month simulation period was 

September 1-30, 1997. Results from September 22 to 

25 were used for comparison with field velocity data, 

which corresponds to one of four field measurement 

efforts conducted from July 1997 to July 1998. A 17-

day warm-up period (August 15-31, 1997) was used to 

allow effects of errors in the initial conditions to dissipate from the model.

Extensive field research in the study area has 

reduced the uncertainty in values to use for a number of 

parameters in the SICS model. The parameters with 

greatest uncertainty are the flow coefficients of the 

coastal creeks and the field-scale dispersion coefficients. The flow coefficients of the coastal creeks were 

calibrated to the values as presented in table 3 by 

matching measured and simulated flow at the coastal 

creeks, flow velocities and water velocities in the 

wetlands, and coastal salinities.
34 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Salinity dispersion is most noticeable near the 

coast. The dispersion coefficient that produced the best 

match between measured and simulated salinities was 

10 m2/s (fig. 15). This result indicates that the numerical dispersion is a smaller part of the effective dispersion. The calibrated model dispersion coefficient is not 

as large as documented in field-scale estuary studies 

because the coefficient in the model applies to individual computational cells.

The coastal creek outlets where the point field 

conductivity measurements were taken had large 

spatial gradients in salinity. Salinity distributions from 

the calibration simulation are shown in figure 16; some 

salinity intrusion into the subembayments is apparent. 

This spatial variability in salinity presents difficulties in 

comparing point measurements and computed mean 

cell salinities as shown in figure 15. Nonetheless, 

considering these difficulties, measured and computed

McCORMICK CREEK

SALINITY, IN GRAMS PER LITER

SEPTEMBER

1997

20

16

12

8

4

0

TAYLOR RIVER

20

16

12

8

4

0

MUD CREEK

20

16

12

8

4

0

TROUT CREEK

20

16

12

8

4

0

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Figure 15. Measured and computed salinities at coastal creeks for calibration simulation in September 1997.
Construction, Calibration, Testing, and Application of Flow and Transport Model 35Figure 16. Salinity distributions from the calibration simulation.
36 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

salinities shown in figure 15 are in reasonable agreement. The average errors in salinity for this 1-month 

period for these five creeks in figure 15 are: -3.32 ppt for 

McCormick Creek, 1.40 ppt for Taylor River, 2.25 ppt 

for Mud Creek, 2.56 ppt for Trout Creek, and 1.62 ppt 

for West Highway Creek. 

Measured and computed flows at the coastal 

creeks are shown in figure 17. Positive flow is toward 

Florida Bay. The measured creek flows were well 

reproduced by the model as shown in figure 17. The 

largest observed flows, both positive and negative, 

occurred at Trout Creek (fig. 17). The statistical agreement between measured and computed flows is 

discussed later in this report.

Although the general direction and magnitudes 

are similar, substantial differences exist between 

measured and computed wetland flow velocities as 

shown in figure 18. It should be noted that the measured 

values are point values measured over a 2- to 5-minute 

period, whereas the computed values are presented as 

daily averages for the cell area. Short-timescale variations in flow direction are created by wind fluctuations, 

causing instantaneous measurements to differ from daily 

averages. The high, multidirectional flows near Old 

Ingraham Highway (fig. 18, September 22, 1997) are a 

boundary effect, but are indicative of higher velocities in 

shallower depths. Further examination of computed and 

measured wetland flow velocities is made in the next 

section. Additional data collection is underway using 

continuous measuring field sites. 

The USGS crews measured flows along Main 

Park Road, which enters the study area along Old 

Ingraham Highway (fig. 1), during September 22-26, 

1997, and obtained an average of 4.53 m3/s (excluding 

Taylor Slough bridge). The total volume rate produced 

by the SICS model was 5.29 m3/s inflow along the 

entire Old Ingraham Highway model boundary on 

September 24, 1997 (Tillis, 2001), which represents a 

good match of flow magnitude and direction.

Testing

This section describes results of model testing. 

First, model verification is described in which the calibrated model is applied with a different set of boundary 

input than used for calibration, and with no adjustment 

of model input parameters. The extent of agreement 

between computed and measured results serves as an 

indicator of model accuracy and the degree of confidence to place in subsequent simulations. Results of 

sensitivity testing also are described in which several 

input variables are systematically varied one at a time. 

The differences between computed output (water level, 

flow, velocity, and salinity) before and after input variation are a measure of model sensitivity to the parameter 

being changed. It is desirable that output be minimally 

sensitive to parameter variations. In cases where this is 

not so, additional effort is needed to increase accuracy 

of input as much as possible. 

The verification simulation run encompasses the 

period from August 1996 to July 1997. This time 

period also was used by the U.S. Army Corps of Engineers in the development of boundary conditions for 

inland and Florida Bay models. Including a 16-day 

warm-up period, the model run starts on July 15, 1996, 

and finishes July 31, 1997.

Verification

 The model parameters developed for the calibration simulation were used in the verification simulation 

to represent the flow regime in the wetlands and along 

the coast. Results of the 1-year verification simulation 

are shown at monthly intervals on plate 1. The higher 

land-surface elevations are most apparent as dry areas at 

intermediate water levels, such as on August 1, 1996. 

At high water levels, such as on September 1, 1996, 

the Joe Bay area receives water from Taylor Slough, the 

L-31W Canal, and the C-111 Canal. However, at lowwater levels, such as on February 1, 1997, simulations 

indicate that Joe Bay appears to receive little water from 

inland areas. Simulated flow velocities to the West Lake 

area are very low (pl. 1), even when the area north of 

West Lake is fully inundated. The West Lake area seems 

to be relatively disconnected hydraulically and insensitive to flows from the Taylor Slough basin. Results 

shown on plate 1 compared well with water-level maps 

generated by spatially interpolating levels from field 

measurement stations (Ball and Schaffranek, 2000b).

The close agreement between measured and computed flow volumes in the coastal creeks is an important 

indicator of SICS model capability to simulate real flow 

dynamics in the area. Measured and computed flows at 

the five monitored creeks are shown in figure 19. The 

best agreement between measured and computed values 

for most of the creeks occurs between October and 

May—the dry season in southern Florida. This would 

tend to indicate that the controlling phenomena in the 

dry season are represented in the model better than those 

in the wet season. The phenomena particular to the wet 
Construction, Calibration, Testing, and Application of Flow and Transport Model 37

15

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McCORMICK CREEK

MUD CREEK

WEST HIGHWAY CREEK

TAYLOR RIVER

TROUT CREEK

SEPTEMBER 1997

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 2930

DISCHARGE, IN CUBIC METERS PER SECOND

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MEASURED

SIMULATED

Figure 17. Measured and computed flows at coastal creeks for calibration simulation in 

September 1997.
38 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS) 9/22/97 9/24/97

9/25/97

80°45 ́ 25°25 ́

25°15 ́

80°40 ́ 

25°20 ́25°10 ́

80°50 ́ 80°3

West Lake

Taylor Slough

Levee 31W

Road

Park Main

EXPLANATION

MEASURED VELOCITY--Length of arrow equals 0.01 meter per second

SIMULATED VELOCITY--Length of arrow equals 0.01 meter per second

BOUNDARY OF THE SOUTHERN INLAND AND COASTAL SYSTEMS(SICS) STUDY AREA

Base from U.S. Geological Survey digital data, 1972Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Old Ingraham Highway

Figure 18. Wetland flow velocities for calibration simulation, September 22, 24, and 25, 1997.
Construction, Calibration, Testing, and Application of Flow and Transport Model 39

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MUD CREEK

WEST HIGHWAY CREEK

TAYLOR RIVER

TROUT CREEK

DISCHARGE, IN CUBIC METERS PER SECOND

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AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUNE JULY

1996 1997

MEASURED

SIMULATED

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SIMULATED

MEASURED

SIMULATED

MEASURED

SIMULATED

Figure 19. Measured and computed creek flows for verification simulation, August 1996 to 

July 1997.
40 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

season are: more inflow from surface-water sources, 

higher rainfall rates, and higher water levels with a 

corresponding difference in frictional resistance.

The ratio of the root mean square difference 

(RMSD) between measurements and simulations to the 

standard deviation σ of the measurements is used to 

describe the ability of the model to reproduce the field 

measurements. The RSMD is the square root of the 

mean of the differences between measured and simulated values for a selected period. The standard deviation 

of the measured data is a representation of the variability 

in the data, with greater variability indicating more difficulty in producing accurate simulations. Thus, the ratio 

RMSD/σ should be a good dimensionless measure of the 

ability to fit versus the difficulty in fitting; the lower the 

value, the better the model performance. 

The best model performance for creek flow 

simulation was at Trout Creek, where RMSD/σ = 

0.673. This is fortunate because, as the highest flow 

outlet to Florida Bay, Trout Creek is the most important 

of the creek flows to represent well. The worst value 

for RMSD/σ is 1.329 at Mud Creek. Flows from this 

creek may be more difficult to represent because it is 

connected to a small-scale set of lakes that may not be 

adequately delineated by the model grid. Other values 

of RMSD/σ were 0.711 at Taylor River, 0.981 at West 

Highway Creek, and 1.072 at McCormick Creek.

The highest water-level gradients occur along the 

coast (pl. 1). For example, on December 1, 1996, the 

model produced a 0.14-m water-level drop across the 

embankment at Taylor River (fig. 2). No gradient 

measurements were available along the coast for this 

simulation period; however, on February 28, 1998, 

water-surface elevation measurements were taken at 

the USGS station at the mouth of Taylor River and at 

an ENP station about 3.22 km upstream of the station 

at the mouth. Measurements taken over a 45-minute 

period revealed an average water-level drop of 0.18 m 

between stations. This measured difference indicates 

that the relatively high water-surface gradients simulated by the model can (and probably do) occur along 

the coast.

A comparison was made between the verification 

simulation results and the measured water levels in the 

wetlands, and results are shown on plate 2. The simulated values do not include ground-water levels below a 

dry cell, so the computed line terminates when the cell 

becomes dry and the stage is 0.0, but the measured data 

continue below land surface under these conditions. 

Occasionally, cells in the model become wet briefly 

when measured data show levels are below land surface 

(see P67 on pl. 2). This is a transient phenomenon, 

however, and the volume associated with those wet 

cells is small. The agreement between measured and 

computed is within 0.03 m for most of the simulation 

time at most of the stations. Under almost all conditions, including wetting and drying, the difference 

between simulations and measurements is less than 

0.1 m.

Velocity measurements were made in the 

wetlands during July 29-31, 1997, which was near the 

end of the verification period. The comparison of simulated velocities with field measurements is shown on 

plate 3. The velocity vectors compare velocities 

measured at the noted times with those computed 

during the period between 3 hours before and 3 hours 

after the measurement time. This accounts for the fact 

that the majority of the small-scale variation in velocities is due to wind forcing, and a 5-hour averaging 

period is used for the wind values. Moreover, the simulated vectors shown on plate 3 are a spatial average of 

10 computational cells—the measurement cell and the 

nine cells that bound that cell. Field values do, 

however, have the same general magnitude and direction as simulated values.

Monthly simulated salinity distributions are 

shown on plate 4. During dry periods, such as from 

December 1, 1996, to April 1, 1997, salinity intrusion 

occurs in Joe Bay and in the subembayments (for 

example, Monroe Lake shown in fig. 2) north of 

McCormick Creek. In Joe Bay, salinities usually are 

greater than 4 g/L and can be as high as 7 g/L (pl. 4). 

The high salinity gradient seen at the coastline is indicative of the effect of the Buttonwood Embankment as a 

barrier to salinity intrusion inland. The only salinity 

intrusion occurs when reversals in creek flows occur; 

the reversals are caused by wind as discussed later.

Sensitivity Analysis

The purpose of the sensitivity analysis is to identify 

the response of the SICS model to variations in input 

parameter values and boundary conditions. This helps 

identify the input error that may contribute to most of 

the output uncertainty. The sensitivity analysis is 

performed using the verification simulation period, 

which includes an extensive output data set (1 year) 

with a wide variety of flow conditions. The sensitivity 

analysis was conducted by increasing and decreasing 

the input values an arbitrary amount and observing the 

effects on simulated coastal creek flows. These creek 
Construction, Calibration, Testing, and Application of Flow and Transport Model 41

flows are integrators of all upstream effects in the 

model, are sensitive to variations in bay water levels, 

and are the quantity of most interest to Florida Bay 

scientists, which makes them ideal for this purpose.

The flow coefficients for the coastal creeks are of 

interest in the sensitivity analysis because of the lack of 

field data for this parameter. The dispersion coefficient 

was not tested because it has no direct effect on flow 

rate. Other important parameters investigated are the 

wind-friction term, evapotranspiration rate as a function of solar radiation, Manning’s n values, boundaryvalue water levels, boundary-value discharges, and 

land-surface elevations. The sensitivity to a sinusoidal 

tide at the western model boundary and the effect of 

salinity on flows were also tested.

Subjective criteria were used to determine a 

reasonable range of parameter values for sensitivity testing. The effective Manning’s n values for the coastal 

creeks (table 3) varied about ±50 percent among creeks, 

so this range was used for Manning’s n testing.

A wind-friction coefficient of 1.2 × 10-3 is used 

in the model. Due to the high uncertainty in determining this value and the wind-sheltering coefficient, a 

±100 percent variation in the wind-friction coefficient 

was used.

The best fit evapotranspiration relation (eq. 7) 

has a correlation coefficient of about 80 percent, indicating that 80 percent of the observed variability in 

evapotranspiration can be explained by the independent 

variables in equation 7. Thus, the sensitivity of the 

model to evapotranspiration variations was assessed by 

varying the only input variable, solar radiation χ, by 

±10 percent. 

As previously discussed, ranges of Manning’s n

values for vegetative frictional resistance were determined from field measurements. The range of average 

values for different vegetation types was given as 

0.08 s/m1/3. Based on this, the sensitivity analysis 

uses a range of 0.10 s/m1/3 (±0.05 s/m1/3).

Boundary water levels along Florida Bay and for 

the culverts under US-1 are determined from coastal 

stations, which should be accurate to 0.015 m. To 

ensure an adequate range, a variation of ±0.03 m is 

used for the sensitivity analysis. Of major concern for 

Everglades restoration is the effect of varying flow at 

Taylor Slough bridge on wetland flows and flows to the 

coast. The flows at Taylor Slough bridge were varied 

±50 percent for the sensitivity analysis.

Errors in land-surface-elevation measurements 

can be quantified. Applying a constant elevation difference to all of the cells in the model is a straightforward 

process. However, an 0.03-m rise in all the cells is 

equivalent, in a relative sense, to lowering the waterlevel boundaries by 0.03 m. To avoid essentially repeating the sensitivity analysis for water-level boundaries, 

an analysis is needed that is more representative of the 

type of error found in measuring land-surface elevations. Sensitivity analysis of land elevations is somewhat different than for other parameters because flow 

can be substantially affected by differences in elevations between cells. Random variance is added to the 

land-surface elevation data by use of the turning bands 

algorithm (TBA) as described by Tompson and others 

(1989). The random application of perturbations is not 

as applicable with other parameters, including the 

evapotranspiration rate and Manning’s n, because flow 

is substantially affected by net changes in the parameter model wide. 

Thirty-two trials were used in the sensitivity 

analysis of land-surface elevation. The TBA was used 

to generate 30 two-dimensional random fields, all with 

a mean of zero and a standard deviation of 0.15 m, 

which was the stated uncertainty in the helicopterbased elevation measurements (Desmond and others, 

2000). The correlation scale was set to 0.1 of the cell 

size, so that the perturbations were uncorrelated 

between cells. For each of the 30 realizations, the 

random field was then added to the elevation data set, 

the model was run, and the statistics were computed. 

The arithmetic average of the statistics from all the 

simulations indicates the sensitivity of the model to 

land-surface elevation perturbations.

Three statistical measures were used to describe 

the difference in coastal creek discharge between verification and sensitivity runs. These statistics are the 

RMSD, mean absolute difference (MAD), and mean 

difference (MD). The RMSD is the square root of the 

mean of the squares of all the differences between verification and sensitivity discharge values. The MAD is the 

mean of all the absolute values of the differences, 

whereas MD is the mean of the differences, which 

allows positive and negative values to offset. Each of 

these statistics states the difference between the flows 

produced by the verification and sensitivity run in a 

different way. The RMSD shows the average difference, 

with no offsetting of positive and negative differences, 

and the effects of outliers are exaggerated. The MAD 

also shows the average differences in instantaneous 
42 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

discharge with no offsetting differences, but all data 

points affect the mean equally. The MD is similar to the 

MAD, but it does allow positive and negative values to 

offset. If creek flows from verification and sensitivity 

model runs are shifted in time, the MAD and RMSD 

cause large differences whereas the MD does not. Any 

input parameter variation that has a major effect on 

output will be detected by one of these three statistical 

measures.

Results of model sensitivity to changes in 

selected parameters are presented in table 4. Most table 

segments give three statistical measures of the difference between computed flows in five coastal creeks for 

this verification simulation, with and without the 

labeled sensitivity modifications. The first segment in 

table 4 gives the same statistical measures of flow 

differences between the verification run and measured 

creek flows.

Table 4. Results of sensitivity analysis 

Each chart segment gives three statistical measures of the difference in flows at each of five creeks discharging to 

Florida Bay. Each chart segment compares creek flow model results for the verification simulation with either field 

data, the first segment, or subsequent computed creek flows from simulations having indicated modifications to 

input data. Acronyms: RMSD, root mean square difference; MAD, mean absolue difference; MD, mean difference. 

Values are shown in cubic meters per second]

Statistic McCormick 

Creek Taylor Creek Mud Creek Trout Creek West Highway Creek

Compared to Field Data

RMSD 2.887 0.945 2.593 9.824 2.092

MAD 2.190 .725 1.758 7.656 1.420

MD 1.195 .210 .412 3.231 .377

Creek Conductances Plus 50 Percent

RMSD 2.119 .875 2.477 5.423 1.312

MAD 1.616 .633 1.604 3.573 1.012

MD .824 .353 .138 1.104 .639

Creek Conductance Minus 50 Percent

RMSD 2.092 .716 2.749 10.374 1.646

MAD 1.769 .611 1.788 4.608 1.199

MD - .861 - .398 - .221 -3.069 - .605

Wind Friction Term Plus 100 Percent

RMSD 1.759 .670 2.895 2.519 1.320

MAD 1.168 .389 1.770 1.895 .977

MD .097 .020 - .304 - .122 - .473

Wind Friction Term Minus 100 Percent

RMSD 1.485 .425 2.149 3.869 2.583

MAD .944 .258 1.271 2.675 1.421

MD .005 .055 .053 .419 .601

Solar Radiation Plus 10 Percent

RMSD 1.289 .786 2.995 1.253 .824

MAD .768 .310 1.555 .717 .583

MD - .024 - .046 - .144 - .415 .058

Solar Radiation Minus 10 Percent

RMSD 1.277 .438 3.558 1.490 .792

MAD .790 .251 1.719 .875 .529

MD .067 .086 .165 - .019 .018
Construction, Calibration, Testing, and Application of Flow and Transport Model 43

Manning’s n Plus 0.05

RMSD 1.286 .409 2.624 10.357 .895

MAD .799 .243 1.469 4.204 .594

MD .161 .042 .057 -3.779 .203

Manning’s n Minus 0.05

RMSD 1.130 0.389 2.735 6.007 0.692

MAD .704 .225 1.467 1.540 .502

MD .069 .037 .153 - .410 - .074

Florida Bay Boundary Water Levels Plus 0.1

RMSD 2.441 .616 4.622 5.009 .798

MAD 1.631 .381 2.447 2.570 .572

MD - .231 - .175 .216 - .117 .003

Florida Bay Boundary Water Levels Minus 0.1

RMSD 1.755 .791 2.398 1.569 .828

MAD 1.319 .375 1.375 1.053 .567

MD - .317 .066 .184 - .410 .021

Sinusoidal Tide Function at Western Boundary with Amplitude 0.30 meter

RMSD 1.507 .397 3.532 10.460 .691

MAD 1.009 .230 1.629 4.569 .496

MD - .017 .059 .263 -4.082 - .031

Taylor Slough Bridge Discharges Plus 50 Percent

RMSD 1.256 0.364 4.337 1.063 .743

MAD .750 .211 1.987 .755 .519

MD .030 .021 .022 .314 .105

Taylor Slough Bridge Discharges Minus 50 Percent

RMSD 1.339 .402 2.405 .925 .824

MAD .853 .215 1.377 .618 .551

MD .040 .002 - .084 - .233 - .041

Density Effects of Salinity Neglected

RMSD 1.224 1.211 2.400 1.090 2.743

MAD .793 .336 1.353 .659 1.568

MD - .054 .113 - .092 - .132 .247

Land-Surface Elevation Standard Deviation 0.15 meter

RMSD 1.130 .389 2.735 6.007 .692

MAD .704 .225 1.467 1.540 .502

MD .069 .037 .153 - .410 - .074

Table 4. Results of sensitivity analysis (Continued)

Each chart segment gives three statistical measures of the difference in flows at each of five creeks discharging to 

Florida Bay. Each chart segment compares creek flow model results for the verification simulation with either field 

data, the first segment, or subsequent computed creek flows from simulations having indicated modifications to 

input data. Acronyms: RMSD, root mean square difference; MAD, mean absolue difference; MD, mean difference. 

Values are shown in cubic meters per second]

Statistic McCormick 

Creek Taylor Creek Mud Creek Trout Creek West Highway Creek
44 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

The RMSD, MAD, and MD parameters 

are summed for all five creeks, and the sensitivity modifications are ranked by impact on 

the statistical measures as presented in table 5. 

Summarizing these results qualitatively, simulation results are most sensitive to the flow 

coefficients for the coastal creeks, followed by 

the frictional resistance of the wetlands 

(Manning’s n), and the wind friction. The 

magnitude of the perturbations in the input 

parameters was based on the uncertainty of the 

parameters. Therefore, the high sensitivity of 

the coastal creek flow coefficient is due, in 

part, to the large variation in input perturbation, which represents the high uncertainly in 

field data.

Model Application Examples

In this section, some examples are given 

to demonstrate how the SICS model can be 

applied to better understand water and salinity 

dynamics in the marsh and coastal and nearshore areas adjacent to northeastern Florida 

Bay (fig. 1, study area). The first example 

shows how details of flows and flow differences can be estimated in regions of special 

interest and where flows are not measured. The 

next example shows various patterns of 

computed water levels, water distribution, and 

salinity throughout the SICS area under different wind and water inflow conditions.

The final part of this section describes a tool to 

allow application of the SICS model in concert with 

future evaluations of proposed CERP alternatives. 

With this tool, results of possible CERP flows 

provided north of the SICS area can be converted to a 

realistic estimate of flow input to the SICS model, 

allowing simulation of marsh and coastal changes due 

to the specific CERP alternative being evaluated.

Flow Estimates at Unmeasured Locations

Flows to the coast of the SICS area are of great 

interest to resource managers and planners as Everglades restoration options are evaluated. The application of the SICS model allows both the estimation of 

flows at locations where field measurements are not 

made, as well as at measured sites for hypothetical 

scenarios. As with the coastal creeks, quantification of 

flow into Joe Bay and other embayments is needed to 

develop a better understanding of flow-related 

processes in the SICS area and to provide boundary 

conditions for future models of Florida Bay. 

Joe Bay (fig. 2) is a prominent feature of the 

shoreline encompassed by the SICS model. It is situated immediately north of the Buttonwood Embankment and in a position to receive water inflow from the 

surrounding marsh before discharging primarily 

through Trout Creek (fig. 20. Flow measurements 

(figs. 17 and 19) indicate that Trout Creek discharge 

from Joe Bay is a predominant source of freshwater to 

northeastern Florida Bay.

 The SICS model was used to identify the 

sources and relative magnitudes of these sources of 

water to Joe Bay under high- and low-water conditions. 

Estimates of flows to Joe Bay across the six crosssectional segments partially encircling the bay were 

Table 5. Summary of sensitivity tests for coastal creeks 

[RMSD, root mean square difference; MAD, mean absolute difference; MD, 

mean difference; %, percent; values are shown in cubic meters per second]

StatisticParameter 

name

Parameter 

modification

Sum of statistics 

for all coastal 

creeks

RMSD

Creek flow coefficient Decreased by 50% 17.58

Manning’s n Increased by 0.05 15.57

Creek flow coefficient Increased by 50% 12.21

Manning’s n Decreased by 0.05 10.95

Wind-friction term Set to 0.0 10.51

MAD

Creek flow coefficient Decreased by 50% 9.98

Creek flow coefficient Increased by 50% 8.44

Manning’s n Increased by 0.05 7.31

Wind-friction term Set to 0.0 6.57

Wind-friction term Set to 0.0024 6.20

MD

Creek flow coefficient Decreased by 50% 5.15

Manning’s n Increased by 0.05 4.24

Creek flow coefficient Increased by 50% 3.06

Wind-friction term Set to 0.0 1.13

Wind-friction term Set to 0.0024 1.02
Construction, Calibration, Testing, and Application of Flow and Transport Model 45

computed for the period August 1996 to July 1997, and 

the results are also shown in figure 20. All flows into 

Joe Bay are defined as positive. Flow through segments 

1 to 5 was predominately occurring into Joe Bay during 

the simulation period, but flow across segment 6 was in 

both directions, with greater flows out of the bay 

during high water-level conditions.

Continuous field measurements of flow were not 

made at Alligator Creek, East Creek, Stillwater Creek, 

Oregon Creek, and Shell Creek (fig. 2) as part of this 

study. Thus, model-computed flows at these creeks 

(fig. 21) become a useful estimate of their contributions 

to Florida Bay. The magnitude of the computed flows 

at these creeks is similar to that of the other creeks 

where continuous flow measurements were made as 

discussed earlier in this report (fig. 19), and the error of 

these estimates should be similar to those given in the 

first segment of table 4.

0

0

1 MILE

1 KILOMETER

1

EXPLANATION

LOCATION AND

NUMBER OF CROSS

SECTION–Color refers

to graph above

1

2

3 4 5

Joe Bay 6

Location of

Joe Bay

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUNE JULY

1996 1997

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FLOW, IN CUBIC METERS PER SECOND

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CROSS SECTION 1

CROSS SECTION 2

CROSS SECTION 3

CROSS SECTION 4

CROSS SECTION 5

CROSS SECTION 6

N

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

A

B

Figure 20. (A) Model-computed flows at each section for verification simulation and (B) map showing flow cross 

sections for Joe Bay.
46 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

ALLIGATOR CREEK

STILLWATER CREEK

OREGON CREEK

EAST CREEK

SHELL CREEK

DISCHARGE, IN CUBIC METERS PER SECOND

15

15

15

15

10

10

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5

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AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUNE JULY

1996 1997

Figure 21. Model-computed flows at selected coastal creeks for verification simulation, 

August 1996 to July 1997.
Construction, Calibration, Testing, and Application of Flow and Transport Model 47

Water Ponding and Salinity Distribution for 

Different Inflow and Wind Conditions

The ability of the SICS model to compute 

ponding of water during low-flow conditions in the 

marsh and overall water and salinity distribution under 

a range of conditions is of great value in determining 

which CERP alternatives best meet restoration objectives. The illustrations on plate 5 show the relative 

importance of two input variables, wind and Taylor 

Slough flow, on computed water levels and ponding 

for typical high- and low-water conditions. The top 

two frames show the water levels computed in the 

SICS area for a high-water condition on September 1, 

1996, and a low-water condition 3 months later. 

These are snapshot excerpts from a simulation run 

from August 1, 1996, to July 31, 1997, and the simulations include measured wind and Taylor Slough 

bridge flows as input. Marsh water levels range from 

about +0.5 m to about -0.2 m below NAVD 88 for 

September 1, 1996, and from about 0.3 m above to 

about -0.2 m below NAVD 88 for December 1, 1996.

To illustrate the effect of wind on computed 

water levels, a second model simulation was conducted 

for the same time period with the wind input set to 

zero and all other input unchanged. Snapshots of 

water levels on the same 2 days (September 1 and 

December 1, 1996) were then compared to the originals, and their differences are shown in the middle tier 

of frames on plate 5.

The high water-level difference map 

(September 1, 1996) shows large areas of very little 

change, particularly in the western part of the SICS 

area. There is some minor increase in water levels 

greater then 0.02 m in the northern and northeastern 

parts of the area and some localized increases concentrated near the shoreline in the eastern part of the SICS 

area. Lack of wind in this case seems to have had minimal effects on water levels and water distribution. For 

the low water-level condition (December 1, 1996), 

there were some areas of increased ponding in the 

absence of wind relative to the original simulation.

Wind forcing on wetland flow directions can be 

observed in the study area (pl. 1); however, the most 

dramatic effects are on flows to the coast. The 

measured discharges at Trout Creek, the largest coastal 

outflow (Hittle, 2000), and also model-computed 

discharges with and without wind effects are shown in 

figure 22. Flow reversals in the creeks are only evident 

in the model simulations when wind is included. 

Because Florida Bay boundary water levels are the 

same for each simulation with and without wind, flow 

reversals are not due to tidal variations in Florida Bay, 

but by seiching in the subembayments or wetlands 

caused by wind forcing.

Of greater relevance to Everglades restoration is 

the effect that changing flows at Taylor Slough bridge 

(a primary water input to the SICS area) may have on 

Everglades conditions. The bottom tier of frames on 

plate 5 shows how increasing Taylor Slough bridge 

flows by 50 percent affects water levels during highand low-water conditions. 

DISCHARGE, IN CUBIC

METERS PER SECOND

AUGUST 3 AUGUST 4 AUGUST 5 AUGUST 6

1996

-20

-15

-10

-5

0

5

10

15

20

25

30

MEASURED

0000

0400

0800

1200

1600

2000

0000

0400

0800

1200

1600

2000

0000

0400

0800

1200

1600

2000

0000

0400

0800

1200

1600

2000

SIMULATED WITHOUT WIND

SIMULATED WITH WIND

Figure 22. Differences in computed flow at Trout Creek with and without wind effects for verification simulation.
48 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

The changes for both high- and low-water conditions are striking, but in different ways. For high-water 

conditions, water levels in a large area near the Taylor 

Slough bridge are raised by 0.02 to 0.03 m due to 

increased water flow. This increase appears to radiate 

outward from the source and causes substantial increases 

in the Joe Bay area and in the downstream area of Taylor 

Slough relative to baseline conditions. For low-water 

conditions, water-level increases are not greatest near the 

point of increased flow. Rather, a large area of increased 

ponding (+0.02 to +0.04 m) is created in the central 

region of Taylor Slough. This is most likely the remnant 

of increased flow in the wetter times.

In general, wind seems to reduce ponding during 

low-water periods and has small effects during high 

water. Increases in Taylor Slough bridge flow appears to 

generally increase water levels throughout the SICS area 

and particularly near the bridge for high water levels.

Similar to illustrations on plate 5, the top two 

frames on plate 6 show salinity distributions computed 

in the SICS area for a high-water condition on September 1, 1996, and a low-water condition on December 1, 

1996. As previously mentioned, these are snapshots 

from a 1-year simulation (August 1, 1996, to July 31, 

1997) and include measured wind and Taylor Slough 

bridge flows as input. Color gradations for all frames on 

plate 6 show marsh salinities varying from near zero 

inland to about 5 g/L at the coast and varying from about 

10 to more than 30 g/L in Florida Bay. Dispersion coefficients, which are estimated in the model, have a greater 

effect on salinity distributions in regions of high salinity 

gradients than regions of lower salinity gradients.

The distribution of marsh and Florida Bay salinity varies substantially between high- and low-water 

conditions, but the effects of wind (middle two frames) 

and increased Taylor Slough bridge flows (bottom two 

frames) are less noticeable than the effects of waterlevel condition on salinity. The absence of wind results 

in some increased salinity intrusion into the marsh 

compared to the baseline condition. The situation is 

mixed for low-water conditions; there is less intrusion 

for the no-wind condition in the eastern part of the 

marsh and some greater salinity intrusion in the central 

marsh relative to the baseline condition. These different 

responses are likely due to varying antecedent wind 

patterns. An increase in inflow of 50 percent at Taylor 

Slough bridge causes very little change in salinity 

distribution for both high- and low-water conditions.

Perhaps the most interesting observation regarding salinity distributions is that salinity intrusion into 

the marsh is significantly greater under high-water 

conditions than low-water conditions. This is counterintuitive because, in most other instances of relatively 

higher freshwater flow in wet seasons, salt is forced 

downstream resulting in reduced intrusion. The dry 

time, December 1, 1996, follows a particularly wet 

October, so the area was still flushed of salinity. The 

wet time, September 1, 1996, still retains some of the 

salinity intruded in the previous dry time. This demonstrates the importance of considering antecedent conditions. The low-water condition shown on December 1, 

1996, followed the heavy rainfall events in October 

1996. Both salinity and water level are fixed at the 

lower boundary. This artificially constrains the system 

from the southern boundary some distance north.

Using SICS Model for Restoration Testing

In order to utilize the SICS model to evaluate 

restoration scenarios, the boundary conditions must be 

altered to allow inclusion of operational changes 

outside the SICS model area. The need is to define the 

flows at Taylor Slough bridge to reflect the strong 

influence of pumpage at station S-332 (fig. 1). One 

method of incorporating changes in operations at S-332 

with SICS boundary inflows at Taylor Slough bridge is 

to use a multiple regression analysis to relate the 

important variables between the two sites.

A multiple regression analysis consists of relating a dependent variable to a set of quantitative independent variables. A first-order regression was used in 

this study, which includes all independent variables, 

but does not include any cross-products or exponents, 

and assumes that the effects of the independent variables are additive and do not interact with each other. 

The general formula used to represent this regression is 

as follows (Ott, 1993, p. 566):

yi = β0 + β1x1 + β2x2 + ... + βixi + ε (16)

where yi is the dependent variable, β0 is the y-intercept 

(the expected value of y when each x is zero), β0 ... βi

are partial slopes (expected change in y for a unit 

increase in x), x1...xi are independent variables, and ε is 

the error term.

An array of different statistics can be calculated 

when running a multiple regression, including the Rp

value, standard error, sum of squares, mean square, tstatistic, and p-values (Helsel and Hirsch, 1992, p. 108-

124). One of the most significant of these terms to the 

SICS model analysis is the Rp value. This value is the 
Construction, Calibration, Testing, and Application of Flow and Transport Model 49

Pearson Product Moment correlation coefficient, a 

dimensionless index that ranges between +1 and -1, 

and reflects the extent of a linear relation between the 

different data sets. The formula used to calculate Rp is 

as follows (Ott, 1993, p. 475):

, (17)

where ni is the number of data points, X is the independent set of observations, and Y is the dependent set of 

observations.

Rp

ni∑XY X Y – ∑ ∑

ni X2 ( ) ∑X 2 [ ] ∑ – ni Y2 ( ) ∑Y 2 [ ] ∑ –

= ----------------------------------------------------------------------------------------------

The northern boundary of the SICS model area is 

defined by discharges at Taylor Slough bridge. A relation had to be established between flows at the bridge 

and a nearby S-332 flow-control structure to use the 

model for operational purposes. This relation was 

accomplished by performing a multiple regression on 

flows at Taylor Slough bridge with respect to pumping 

and rainfall rates at S-332. The regression yielded an 

Rp value of 0.83, which indicates a good relation (fig. 

23) and demonstrates that pumping rates at S-332 and 

daily rainfall rates can be used to estimate daily flows 

at the Taylor Slough bridge.

DISCHARGE, IN CUBIC METERS PER SECOND

JFM AM J J A SOND J FMA M J JAS O N D

SOND J F MAM J J ASON D J FMA

JFM AM J J A

1989 1990 1991

1991 1992 1993 1994

MJ J ASONDJ FMAMJ J ASOND

1994 1995 1996

J FMAMJ J A SOND J FMAMJ J AS OND J FMAMJ J A S

1997 1998 1999

J F MAMJ J ASOND

J FMAMJ J ASO ND

MEASURED

ESTIMATED

MEASURED

ESTIMATED

MEASURED

ESTIMATED

MEASURED

ESTIMATED

14

12

10

8

6

4

2

0

-2

14

12

10

8

6

4

2

0

-2

14

12

10

8

6

4

2

0

-2

14

12

10

8

6

4

2

0

-2

Figure 23. Measured and estimated daily mean flows for Taylor Slough bridge, 1989-99.
50 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

CONCLUSIONS 

To understand flow conditions along the coastal 

areas of Florida Bay, a two-dimensional dynamic 

surface-water model was developed and applied to the 

region encompassing the wetlands at southern ENP and 

the subtidal embayments of northern Florida Bay. The 

model has the capability to simulate drying and flooding, wind forcing, land barriers, and the transport of 

salinity that affects density. Model modifications were 

made to allow areal variations in rainfall, cell-by-cell 

computation of evapotranspiration, and a wind-sheltering coefficient for emergent vegetation. Process studies 

yielded input values for land-surface elevations and 

bathymetry, frictional resistance terms, evapotranspiration computation, location of ground-water inflows, 

and flow data for the coastal creeks and wetlands. 

Results of studies relating wetland vegetation types to 

frictional resistance were combined with areal mapping 

of vegetation to develop Manning’s n terms for the 

model. A least-squares best-fit technique was used to 

relate the pertinent parameters to evapotranspiration 

rates for this area. This information was used to simulate two periods: a 1-month calibration simulation and 

a 1-year verification simulation. Measured coastal 

creek flows and unit discharges measured in the 

wetlands were used for comparison with simulations 

and for model calibration. 

The calibration simulation demonstrated the 

ability of the model to reproduce coastal flows, unit 

discharges in the wetlands, and coastal salinities. The 

verification simulation produced long-term coastal 

flow volumes at creeks and elsewhere. The varying 

distribution of flows at high- and low-water conditions 

was also represented. Numerical experiments showed 

that flow reversals at the coastal creeks are primarily 

due to wind forcing and not due to variations in tidal 

level. Flows into Joe Bay are primarily from Taylor 

Slough during low-water periods. The highest waterlevel simulated gradients occur along the coast where 

the coastal embankment confines overland flow to the 

creeks. This finding is supported by limited field 

measurements.

A sensitivity analysis was performed on the 

major input parameters of the model. Results of the 

sensitivity analysis indicate that the parameters need to 

be better defined. The flow coefficient of the coastal 

creeks was the most critical parameter needing further 

study. Other parameters needing study are the frictional 

effects of wetland vegetation and wind.

The sensitivity analysis included scenarios in 

which wind was neglected as a forcing function, and 

the inflows at the northern boundary of Taylor Slough 

were varied. Wetland water levels and salinity mixing 

at the coast are significantly affected by wind. Higher 

and lower inflows through Taylor Slough bridge do not 

have a significant effect on coastal area water levels, 

but water-level effects are seen nearer to the bridge. 

To utilize the SICS model for evaluating the 

hydrologic response to proposed restoration scenarios, 

a multiple-regression analysis was applied to relate the 

SICS boundary flows from Taylor Slough bridge to 

pumpage at S-332, a pump station north of the SICS 

area. This allows boundary flows at Taylor Slough 

bridge to be estimated from operations at S-332.

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Schaffranek, R.W., 1986, Hydrodynamic simulation of the 

Upper Potomac Estuary: Proceedings of the Water 

Forum 86: World Water Issues in Evolution, American 

Society of Civil Engineers: New York, N.Y., v. 2, 

p. 1572-1581.

——— 1996, Coupling models for canal and wetland interactions in the south Florida ecosystem: U.S. Geological 

Survey Fact Sheet FS-239-96, 8 p.

Schaffranek, R.W., and Ball, M.H., 2000, Flow velocities in 

wetlands adjacent to C-111 Canal in south Florida, U.S. 

Geological Survey Open File Report 00-449, p. 45-47.

Schaffranek, R.W., and Baltzer, R.A., 1988, A simulation 

technique for modeling flow on floodplains and in 

coastal wetlands: Proceedings of the 1988 National 

Hydraulic Engineering Conference, American Society 

of Civil Engineers: New York, N.Y., p. 732-739.

——— 1990, Horizontal density-gradient effects on simulation of flow and transport in the Potomac estuary: Proceedings of the 1990 National Hydraulic Engineering 

Conference, New York, N.Y., p. 1251-1256.

Schaffranek, R.W., Ruhl, H.A., and Hansler, M.E., 1999, An 

overview of the Southern Inland and Coastal Systems 

Project of the U.S. Geological Survey South Florida 

Ecosystem Program: Proceedings of the 3rd International Symposium on Ecohydraulics, Salt Lake City, 

Utah, July 13-16 1999.

Signell, R.P., and Butman, B., 1992, Modeling Tidal 

Exchange and Dispersion in Boston Harbor: Journal of 

Geophysical Research, v. 97, p. 15591-16606. 

Smith, N.P. 2001, Wind-forced interbasin exchanges in Florida Bay: Proceedings of the 2001 Florida Bay Science 

Conference, Key Largo, Fla., April 23-26 2001.

Smith III, T.J. 1998, Imperiled wetlands: review of mangroves and salt marshes: Nature, no. 395, p. 131-132. 

Stewart, Dave, 1997, A GIS interface for environmental systems analysis: application to the south Florida ecosystem: U.S. Geological Survey Fact Sheet FS-193-97, 5 p.

Stewart, M.A., Bhatt, T.N., Fennema, R.J., and Fitterman, 

D.V., 2000, The road to Flamingo, an evaluation of flow 

pattern alterations and salinity intrusion in the lower 

Glades, Everglades National Park, National Park 

Service Report, 36 p.

Swain, E.D., 1999, Numerical representation of dynamic 

flow and transport at the Everglades/Florida Bay interface: Proceedings of the 3rd International Symposium 

on Ecohydraulics, Salt Lake City, Utah, July 13-16 

1999.
54 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

Swain, E.D., Howie, Barbara, and Dixon, Joann, 1996, 

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96-4118, 67 p. 

Thomas, L., Cartwright, J.C., and Wakeling, D.P., 1990, 

Lidar Observation of the Horizontal Orientation of Ice 

Crystals in Cirrus Clouds, Tellus v. 42B, p. 211-216.

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Implementation of the three-dimensional turning bands 

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Areas, Supplement 54, General Design Memorandum 

and Environmental Impact Statement.

——— 1999, Central and southern Florida comprehensive 

review study: Final integrated feasibility report and programmatic environmental impact statement, April 1999.

Van Lent, T.J., Snow, R.W., and James, Fred, 1998, An 

examination of the Modified Water Deliveries Project, 

the C-111 Project and the Experimental Water Deliveries Project: Hydrologic analyses and effects on endangered species: Everglades National Park Technical 

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water modeling: Reviews in geophysics (supplement): 

U.S. National Report to International Union of Geodesy 

and Geophysics, 1987-90, p. 210-217.

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at low and high wind speeds: Journal of Geophysical 

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response of mean annual evapotranspiration to vegetation changes at catchment scale: Water Resources 

Research, v. 37, p. 701-708.
Appendix I 55

APPENDIX I − SWIFT2D SUBROUTINES MODIFIED FOR SOUTHERN INLAND AND 

COASTAL SYSTEMS (SICS) 

SWIFT2D.F: Modified input of point discharges to allow areal gains and losses as user input and areal computation 

of evapotranspiration.

SEPU.F: Modified input of point discharges to allow areal gains and losses as user input and areal computation of 

evapotranspiration. Sheltering coefficient applied for wind forcing in vegetated areas. Wind forcing not applied to 

cells adjacent to water-level boundary.

SEPV.F: Modified input of point discharges to allow areal gains and losses as user input and areal computation of 

evapotranspiration. Sheltering coefficient applied for wind forcing in vegetated areas. Wind forcing not applied to 

cells adjacent to water-level boundary. Error fixed to allow multiple barriers to function properly in the same grid 

column.

DIFU.F: Modified to allow concentrations of constituents to be affected by areal recharge and evapotranspiration. 

Defined zero concentration of all constituents at barriers when barriers run dry.

DIFV.F: Modified to allow concentrations of constituents to be affected by areal recharge and evapotranspiration. 

Defined zero concentration of all constituents at barriers when barriers run dry.

TIDAL.F: Modified input of point discharges to allow areal gains and losses as user input and areal computation of 

evapotranspiration.

TIMSMO.F: Modified input of point discharges to allow areal gains and losses as user input and areal computation 

of evapotranspiration.

BARENU.F: Modified to stop flow across a barrier if an adjacent grid cell runs dry.

BARENV.F: Modified to stop flow across a barrier if an adjacent grid cell runs dry.

SLUCEU.F: Modified to allow grid cells adjacent to barriers to run dry without ending the simulation.

SLUCEV.F: Modified to allow grid cells adjacent to barriers to run dry without ending the simulation.

FLOW.F: Modified so that constituent concentration at selected points is printed at the same time interval as water 

levels and discharges.

OUT.F: Modified so that grid values of water level and velocities are printed to a different file than the remainder 

of the output. Printed velocities are multiplied by 103 rather than 102, which is better for the low velocities in this 

application.
56 Two-Dimensional Hydrodynamic Simulation of Surface-Water Flow and Transport to Florida Bay through the Southern Inland 

and Coastal Systems (SICS)

APPENDIX II − EXCERPT FROM INPUT FILE HIGHLIGHTING AREAL GAINS AND LOSSES 

RUN NUMBER 1 

WETLANDS 15 JUL ‘96 98/ 8/2517:23:39 IDPV514 

 7.5 15.0 0.0 329190999999 120.999999 1440. 1440. 1440. 1440. 

999999999999999999 15. 45. 30.999999 60.999999999999999999 0. 

 0 0 2 0 0 5 1 0 0 0 0 0 

 7 3 4 4 0 4 

 1 

 0 1 1 1 0 0 0 0 0 

 1 0 0 0 0 0 0 

2160 10800 19440 28080 36720 45360 54000 62640 71280 79920 88560 97200 

105840114480123120131760140400149040157680166320174960183600192240200880

209520218160226800235440244080252720261360270000278640287280295920304560 

 

 148 98 1 14 0 9 0 3 5 5 0 1 

 94 122 

 0.5 1 

25.000 0.0 1000. 2.55 0.0 0.3 1. 1.00 0.5 1.0 5.0 300.0 

 32.2 0.0012 0.00237 1.9362 1.0000 14.3 1000.0 0.97 0.0023 

FR80 35SPRO 1.0 1.0 

 25 1 0.0 13.0 20.0 14.0K/HR 5 

 4.0 170.0 2.00 121.0 163.0 1.25 74.0 89.0 1.00 122.0 103.0 1.00 

 1.0 2.0 2.0 2.0 2.0 

 1 1 2 0.5 1.0 -0.40 -0.40 0.25 1.0 0.0 1 1 

 

 25.0 1.0250 0.698 1.0

 1 57 36 CP

 2 109 78 EVER4

 3 100 58 EVER5A

 4 69 45 E146

 5 98 97 E158

 6 142 52 EP12R

 7 139 57 EP1R

 8 123 55 EPGW

 9 120 61 EVER6

 10 110 65 EVER7

 11 74 73 NP67

 12 62 56 P37

 13 89 81 R127

 14 81 66 TSH

 1 90 90 TSB <------------------ FLOW FROM TAYLOR SLOUGH BRIDGE

 2 -68 -70 Old Ingraham <--------- RAINFALL AT OLD INGRAHAM HIGHWAY

 3 -105 -36 Joe Bay <-------------- RAINFALL AT JOE BAY

 4 100 88 L-31W <---------------- FLOW FROM L-31W CANAL

 5 27 45 west culverts <-------- FLOW THROUGH CULVETS ON WEST BOUNDARY

 6 120 64 C-111 <---------------- FLOW FROM C-111 CANAL

 7 -80 -72 GW Leakage <----------- POINT OF PEAK GROUND-WATER INFLOW IN NORTHERN AREA

 8 -80 -26 no GW Leakage <-------- POINT OF NO GROUND-WATER INFLOW IN SOUTHERN AREA

 9 0 0 Pyranometer <---------- TIME SERIES OF PYRANOMETER SOLAR ENERGY

 1 93 31 36 Joe Bay 1

 2 98 36 40 Joe Bay 2

 3 116 34 39 Joe Bay 3
Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

PLATE 1. Water levels and unit discharges for verification simulation

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

EXPLANATION

August 1, 1996

C-111

Joe Bay

Boundary of Southern Inland and

Coastal Systems (SICS) study area

November 1, 1996

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

February 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

May 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

June 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

July 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

March 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

April 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

December 1, 1996

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

January 1, 1997

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

September 1, 1996

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

October 1, 1996

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

WATER LEVEL, IN METERS

DRY -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCE PROGRAM AND THE

Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

Water levels and unit discharges for verification simulation–PLATE 1

U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́ 80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

UNIT DISCHARGE— Length of arrow is 0.05 cubic meters per second per foot

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road
C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

EXPLANATION

PLATE 2. Water-level time series at field stations for verification simulation

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

EVER7

R-127

EVER4

EVER6

EVER5A EPGW/SW

EP12R

E-146

TSH

NP-P37

NP-CP

0.8

0.6

0.4

0.2

0

-0.2

-0.4

NP-P67

STAGE, IN METERS

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

0.8

0.6

0.4

0.2

0

-0.2

STAGE, IN METERS -0.4

AUG SEPT OCT NOV DEC JAN FEB MAR APR MAY JUN JUL

R127

P67

TSH

P37

E146

CP

EVER4

EVER7

EVER5A

EVER6

EPGW/SW

EP12R

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCE PROGRAM AND THE Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow

and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

Water-level time series at field stations for verification simulation–PLATE 2 U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

STAGE U.S. GEOLOGICAL SURVEY

STAGE NATIONAL PARK SERVICE (NPS)

STAGE/CONDUCTIVITY NPS

EVERGLADES NATIONAL PARK

APPROXIMATE AREA OF TAYLOR SLOUGH

BOUNDARY OF SOUTHERN INLAND AND

COASTAL SYSTEMS (SICS) STUDY AREA

MEASURED

SIMULATED

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road
U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

MEASURED VELOCITY—Line length is 0.5

centimeter per second

SIMULATED VELOCITY—Line length is 0.5

centimeter per second

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

80°  ́ 45 25°25 ́ 80°  ́ 40 80°30 ́

25°10 ́

80°50 ́

7/29/97 9:49 AM

7/29/97 10:00 AM

7/29/97 10:20 AM

7/29/97 10:25 AM

7/29/97 10:40 AM

7/29/97 10:45 AM

7/29/97 10:57 AM

7/29/97 12:00 PM

7/29/97 6:07 PM

7/29/97 6:32 PM 7/29/97 7:05 PM

7/29/97 12:15 PM 7/29/97 12:50 PM 7/29/97 3:41 PM

7/29/97 4:06 PM 7/29/97 4:50 PM 7/29/97 5:29 PM

7/29/97 12:45 PM

7/29/97 2:20 PM

7/30/97 10:14 AM

7/30/97 10:52 AM

7/30/97 11:10 AM

7/31/97 8:50 AM

7/31/97 9:10 AM

7/31/97 9:15 AM

7/31/97 9:30 AM

7/31/97 10:00 AM

7/31/97 10:35 AM

7/31/97 10:50 AM

7/31/97 11:21 AM

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCE PROGRAM AND THE

Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

PLATE 3. Wetland flow velocities for verification simulation, July 29-31, 1997

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

Wetland flow velocities for verification simulation, July 29-31, 1997–PLATE 3

80°  ́ 35

25°15 ́

25°20 ́

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Card Sound Road
August 1, 1996 September 1, 1996 October 1, 1996

November 1, 1996 December 1, 1996 January 1, 1997

February 1, 1997 March 1, 1997 April 1, 1997

May 1, 1997 June 1, 1997 July 1, 1997

PLATE 4. Salinity distribution in verification simulation

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

1

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area Boundary of Southern Inland and

Coastal Systems (SICS) study area

C-111

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́

80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́

80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́

80°45 ́ 25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́ 80°45 ́

25°25 ́

25°15 ́

80°40 ́ 80°30 ́

25°20 ́

25°10 ́

80°50 ́ 80°35 ́ 80°25 ́

C-111

C-111

C-111

C-111

1 1

1

Card Sound Road

EXPLANATION

SALINITY, IN GRAMS PER LITER

DRY 0 5 10 15 20 25 30 35

Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow and transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

Salinity distribution in verification simulation–PLATE 4

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCEPROGRAM AND THE

0 1 5 MILES

0 1 5 KILOMETERS 234

234

1

1

1 1 1

1 1 1

U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road
DRY -1.0 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1.0 DRY -0.10 -0.05 0 0.05 0.10

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

September 1, 1996 December 1, 1996

WATER LEVEL, IN METERS WATER-LEVEL DIFFERENCE, IN METERS

EXPLANATION

80°  ́ 45

25°25 ́

15 ́

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

80°  ́ 45

25°25 ́

25°  ́ 15

80°  ́ 40 80°  ́ 30

25°  ́ 20

25°10 ́

80°50 ́ 80°  ́ 35 80°25 ́

WATER-LEVEL DIFFERENCES WITH NO WIND

WATER-LEVEL DIFFERENCES WITH TAYLOR SLOUGH FLOWS PLUS 50 PERCENT

ORIGINAL SIMULATED WATER LEVELS

0 1 5 MILES

0 1 5 KILOMETERS 234

234

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCE PROGRAM AND THE Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow and

transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

PLATE 5. Effects of wind and Taylor Slough bridge flows on water levels

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

U.S. DEPARTMENT OF THE INTERIOR Effects of wind and Taylor Slough bridge flows on water levels–PLATE 5

U.S. GEOLOGICAL SURVEY

Base from U.S. Geological Survey digital data, 1972

Universal Transverse Mercator projection, Zone 17, Datum NAD 27

25°

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road
SALINITY, IN GRAMS PER LITER

0 5 10 15 20 25 30 35

EXPLANATION

DRY

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

C-111

Joe Bay

Barnes Sound

FLORIDA BAY

West Lake

Taylor Slough

Levee 31W

Road

Park

Main

Taylor

Slough

Bridge

1

Royal Palm

Ranger

Station

Old Ingraham Highway

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

Boundary of Southern Inland and

Coastal Systems (SICS) study area

September 1, 1996 December 1, 1996

0 1 5 MILES

0 1 5 KILOMETERS 234

234

NATIONAL PARK SERVICE CRITICAL ECOSYSTEM STUDIES INITIATIVE

PREPARED AS PART OF THE U.S. GEOLOGICAL SURVEY

PRIORITY ECOSYSTEM SCIENCE PROGRAM AND THE Swain, E.D., and others, 2003, Two-dimensional hydrodynamic simulation of surface-water flow and

transport to Florida Bay through the Southern Inland and Coastal Systems (SICS)

PLATE 6. Effects of wind and Taylor Slough bridge flows on salinity

By

Eric D. Swain, Melinda A. Wolfert, Jerad D. Bales, and Carl R. Goodwin

2003

WATER-RESOURCES INVESTIGATIONS REPORT 03-4287

U.S. DEPARTMENT OF THE INTERIOR Effects of wind and Taylor Slough bridge flows on salinity–PLATE 6

U.S. GEOLOGICAL SURVEY

80°  ́ 45 80°  ́ 45

80°  ́ 45 80°  ́ 45

80°  ́ 45 80°  ́ 45

25°25 ́ 25°25 ́

25°25 ́ 25°25 ́

25°25 ́ 25°25 ́

25°  ́ 15 25°  ́ 15

25°  ́ 15 25°  ́ 15

25°  ́ 15 25°  ́ 15

80°  ́ 30 80°  ́ 30

80°  ́ 30 80°  ́ 30

80°  ́ 30 80°  ́ 30

80°  ́ 40 80°  ́ 40

80°  ́ 40 80°  ́ 40

80°  ́ 40 80°  ́ 40

25°  ́ 20 25°  ́ 20

25°  ́ 20 25°  ́ 20

25°  ́ 20 25°  ́ 20

25°10 ́ 25°10 ́

25°10 ́ 25°10 ́

25°10 ́ 25°10 ́

80°50 ́ 80°50 ́

80°50 ́ 80°50 ́

80°50 ́ 80°50 ́

80°25 ́ 80°25 ́

80°25 ́ 80°25 ́

80°25 ́ 80°25 ́

80°  ́ 35 80°  ́ 35

80°  ́ 35 80°  ́ 35

80°  ́ 35 80°  ́ 35

Salinity with no wind

Salinity with Taylor Slough flows plus 50 percent

Original simulated salinity distribution

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road

Card Sound Road