2006 South Florida Environmental Report Appendix 12-1

Appendix 12-1: Modeling 

Freshwater Inflows and Salinity in 

the Loxahatchee River and Estuary 

Yongshan Wan and Gordon Hu 

SUMMARY 

This appendix describes the hydrologic and salinity models applied in the Northwest Fork of 

the Loxahatchee River Restoration Plan. The Loxahatchee Watershed (WaSh) model was 

developed to simulate freshwater flow from each of the tributaries into the Northwest Fork. The 

WaSh model is based on restructuring HSPF (Hydrologic Simulation Program – Fortran) into a 

cell-based system with the addition of a groundwater model and a full dynamic channel routing 

model (Wan et al., 2003). The model is capable of simulating surface water and groundwater 

hydrology in watersheds with high groundwater tables and dense drainage canal networks. Using 

long-term flow data collected at S-46, Lainhart Dam, Cypress Creek, Hobe Grove Ditch, and 

Kitching Creek, the WaSh model was calibrated and validated. The daily flow outputs from the 

39-year simulation (1965–2003) provide the basis for the base condition and flow restoration 

scenarios of the Northwest Fork ecosystem restoration. 

The Loxahatchee River Hydrodynamics/Salinity (RMA) model was developed to simulate 

the influence of freshwater flows on salinity conditions in the Loxahatchee River and Estuary. 

The RMA model is based on the RMA-2 and RMA-4 and was calibrated against field data from 

five locations and provided salinity predictions for many other sites where field data are not 

available. Tide/salinity data collected since 2002 have provided a field database for the 

investigation of the impact of freshwater inflow on the salinity regime in the Northwest Fork. 

To perform long-term predictions of daily salinity, a Long-Term Salinity Management Model 

(LSMM) was developed to predict salinity and calculate several other performance parameters 

under various ecosystem restoration scenarios. Field data, regression analyses, and results from 

multidimensional hydrodynamic computer models were integrated into the LSMM as a system 

simulation and management tool. This salinity management model is applied to predict daily 

salinity from for the simulation period from 1965 to 2003 under the base condition and various 

restoration scenarios. 

INTRODUCTION 

The Loxahatchee River and Estuary, containing a federally designated Wild and Scenic River 

system located on the east coast in South Florida, provides habitats supporting a wide spectrum of 

ecological resources including seagrasses, oysters, saltwater vegetation, and freshwater 

vegetation. During the past 100 years, the natural hydrologic regime of the Loxahatchee River 

watershed has been altered by drainage activities associated with urban and agricultural 

development. Historically, most of the watershed was drained by the Northwest Fork of the 

Loxahatchee River. Today, much of the watershed has been impacted by the construction of 

canals and levees for drainage and opening of the Jupiter Inlet. These anthropogenic alterations 

 App. 12-1-1 
Appendix 12-1 Volume I: The South Florida Environment

have resulted in significant encroachment of saltwater-tolerant, mangrove-dominated community 

into the freshwater, bald cypress-dominated floodplain. Restoration and protection of the 

Northwest Fork floodplain ecosystem depends largely on providing healthy flow patterns to the 

river. Development of models capable of predicting long-term freshwater inflow and salinity in 

the Loxahatchee River and Estuary is critical for the formulation and evaluation of the restoration 

plan for the Northwest Fork of the Loxahatchee River and Estuary. 

The map in Figure 1 shows the locations of major tributaries and assessment sites that are 

referred to in this appendix. 

Figure 1. Locations of major tributaries and river miles.

Over the past several years, the South Florida Water Management District (SFWMD or 

District) has initiated several projects for data collection and model development. To date, three 

models have been developed to simulate freshwater inflows and salinity conditions in the 

Loxahatchee River and Estuary (Figure 2). These models include a watershed hydrologic model 

(WaSh) simulating long-term freshwater inflows from all tributaries into the Northwest Fork, a 

two-dimensional (2-D) estuarine hydrodynamic and salinity model (RMA) that simulates the 

influence of the freshwater inflows and tide on salinity conditions within the Loxahatchee River 

and Estuary, and a Long-Term Salinity Management Model (LSMM) that predicts daily salinity 

conditions according to freshwater inflows from the Loxahatchee River watershed. The LSMM 

was developed based on the modeling result of the RMA model. During the planning process, a 

39-year period of daily freshwater inflow into the river was simulated with the watershed model 

 App. 12-1-2 
2006 South Florida Environmental Report Appendix 12-1

 App. 12-1-3 

2-D Estuarine 

Hydrodynamic and 

Salinity Model: RMA 

Watershed Model:

WaSh 

Long-Term Daily

Freshwater Flows 

Long-Term Salinity

Management Model: 

LSMM

Long-Term Daily

Salinity Levels 

Evaluation of Ecosystem 

Restoration Scenarios 

to ensure that a wide range of climatic conditions was included. Various flow scenarios were 

proposed and the resulting daily salinity along key assessment locations was simulated with the 

LSMM. An integrated ecological assessment was carried out to evaluate the ecological benefits 

with respect to the health of freshwater floodplain vegetation, oysters, and seagrasses in response 

to these flow scenarios. Such an assessment is critical in selecting restoration alternatives to 

achieve the comprehensive ecologic benefit of all the ecologic components in the entire system. 

The purpose of this appendix is to document the calibration and validation results of these models 

and to provide a description of how these models are used in the evaluation of the Northwest Fork 

restoration alternatives. 

Figure 2. The relationship among the three models used to evaluate 

restoration plan scenarios for the ecosystems in the Loxahatchee River 

watershed. 
Appendix 12-1 Volume I: The South Florida Environment

Table 1 lists the time steps and the length of simulations that the models were designed for. 

Apparently the ecological assessments require long periods of simulations that are beyond the 

capability of a multiple dimensional hydrodynamic model. The Long-Term Salinity Management 

Model (LSMM) provided a bridge between the hydrodynamic model and the VEC models so that 

they could connect on the same time scale. 

Table 1. The time scale of computer models. 

Study 

Components/models

Spatial Resolution Time Step Maximum Length of 

Simulation

Watershed model Site-specific output Daily or monthly Several years to 

several decades

Estuary model Thousands of output 

points that may not 

coincide with specific 

sites

One to 30 minutes Several months to 

several years

Ecosystem Evaluation 

Tools

Require site-specific 

information

Daily, monthly, or 

annual

Require long-term 

(several decades) 

information

MODELING FRESHWATER INFLOWS 

THE WATERSHED MODEL DESCRIPTION 

Freshwater inflows from major tributaries of the Northwest Fork of Loxahatchee River and 

Estuary are simulated with a watershed model. This model was developed based on restructuring 

HSPF (Hydrologic Simulation Program – Fortran, Donigian et al., 1984) into a cell-based system 

with the addition of a groundwater model and a full dynamic channel routing model (Wan et al., 

2003). The WaSh model is capable of simulating hydrology in watersheds with high groundwater 

tables and dense drainage canal networks, which is typical in South Florida. The model consists 

of four basic components: (1) a cell-based representation of the watershed basin land surface, (2) 

a groundwater component that is consistent with the basin cell structure, (3) a surface water 

drainage system, and (4) water management practices. Key features of the model are surface 

water and groundwater interactions, irrigation demands, and transfers between elements of the 

surface water drainage network. For each cell, the model uses an infiltration routine to determine 

the amount of rainfall that infiltrates into the groundwater, evaporates into the atmosphere, or 

drains to the surface water system. Currently, the HSPF (Version 12) modules PWATER and 

IWATER are used for this portion. The infiltrated water is routed to a groundwater model that 

represents the unconfined aquifer in the watershed. The groundwater model receives the 

infiltrated water, exchanges groundwater between cells, and also exchanges water between 

surface water flow and groundwater flow. The surface water drainage system consists of a 

cell-based system and a reach-based system. The reach-based system is typically configured to 

 App. 12-1-4 
2006 South Florida Environmental Report Appendix 12-1

follow the major canals, streams, and rivers and supports branches and common flow structures. 

The water quality component of WaSh is built on the surface water, groundwater, and channel 

flow components of the model. The application of the model in the Loxahatchee River watershed 

focuses on hydrologic simulation. The WaSh model is supported by a Graphic User Interface 

(GUI) that is developed as an ArcView extension. The GUI handles file management (both on the 

local platform and on the server), model configuration, execution, and post processing. The WaSh 

model also supports numerous water management practices such as irrigation, reservoirs, 

Stormwater Treatment Areas (STAs), and land use changes. Key components of the WaSh model 

are summarized in Table 2. 

Model Component Modeling Approach Functions 

Surface Water Flow PWATER and IWATER of HSPF 

with PQUAL, SEDMNT, IQUAL, 

and SOLIDS for water quality 

High water table algorithms of HSPF 

Groundwater Flow A new 2-D unconfined groundwater 

flow model with a prescribed 

leaching function for water quality 

constituents 

Canal drainage and recharge 

Channel Flow A new 1-D fully dynamic shallow 

wave model with a scalar mass 

transport function for water quality 

Structures, branching, point sources 

Water Management Reservoirs, Stormwater Treatment 

Areas, irrigation supply and 

demands, land use changes 

Executed by an ArcView GUI 

Table 2. The watershed (WaSh) model components and functions. 

Model Cell Structure and Cell-Based Routing 

The WaSh model uses a uniform structured grid network. Each cell represents a discrete part 

of the model domain and has associated physical characteristics such as land use, soil type, 

ground elevation, impervious area, and a representative ground slope. Hydrological parameters 

relating runoff, infiltration, and evaporation are specific to these attributes, particularly land use 

types. If tertiary canals are present in the cell, then the length and width of canals in the cell are 

computed and added as a cell attribute. Generally, the cell attributes are obtained by combining 

the cell network with Geographic Information System (GIS) coverage for each of the physical 

characteristics. For the purpose of routing the simulated daily runoff from each cell, a special cell 

attribute is assigned to indicate where runoff from that cell is directed. Each cell is labeled as one 

of three primary types: (1) free cell, (2) canal cell, or (3) reach cell. A free cell represents an area 

of the basin that does not contain canals. Canal cells are any cells with tertiary canals that are not 

coincident with the reaches. Reach cells are cells that contain a reach (major canals) in the 

primary canal system. Some secondary canals can be included in the reach system. These labels 

are needed to designate the types of surface water and groundwater interactions that may occur 

for a given cell. Table 3 lists the methods in which water is routed for each type of cell. 

 App. 12-1-5 
Appendix 12-1 Volume I: The South Florida Environment

Table 3. WaSh water routing operations for each cell type. 

Cell Type Flow Routing Operations 

Free Infiltration is directed to cell groundwater 

Surface water is directed to a nearby cell’s canals 

Canal Infiltration is directed to cell groundwater 

Surface water is directed to cell canals 

Groundwater can be exchanged with canal surface water 

Surface water can be exchanged between the canal and the reach 

Reach Infiltration is directed to cell groundwater 

Surface water is directed to the cell’s reach or nearby cell’s canals 

Groundwater can be exchanged with canal or reach surface water 

Reach water can be exchanged with canal water 

Surface Water and Groundwater Interaction 

The surface water and groundwater is modeled in the same grid network. For each cell, WaSh 

uses the PWATER and IWATER modules of HSPF (Version 12) to simulate surface water 

hydrology (Table 2). A detailed description of these modules is available in the HSPF user’s 

manual (Donigian et al., 1984). Version 12 includes recent model enhancements that simulate 

irrigation demand, high water tables, and wetland conditions that are common in South Florida 

(Aqua Terra, 1996; 1998). The HSPF routine is implemented in one-hour time step for 24-hour 

blocks. Thus, the HSPF-based routine is applied daily for each cell and water balance, consisting 

of rainfall, evaporation, soil storage, surface runoff, and infiltration to groundwater. At the end of 

each one-day simulation period, the accumulated surface runoff and infiltration are routed to the 

drainage and groundwater systems, respectively. All HSPF model parameters are calibrated and 

assigned to each cell based on the land use and soil type characteristics as additional cell 

attributes. 

The groundwater module in WaSh is based on the numerical solution of the standard 

groundwater flow equation for an unconfined aquifer. The model operates on a daily time step, 

during which it receives infiltrated water, loses water to evaporation, and exchanges water with 

adjacent cells and with canals. The basic governing equation for the groundwater module is: 

cx cy SSSS rcei

y

h hhK

yx

h hhK

xt

h

++−+

∂

∂ − ∂∂

+

∂

∂ − ∂∂ = ∂∂

ρ )( )( [1]

where h is the groundwater elevation, ρ is the porosity, Kx and Ky are the hydraulic conductivity 

in the x-, and y- directions, hc is the aquifer base elevation, and Si, Se, Sc, and Sr are source/sink 

terms representing infiltration, evaporation, exchanges with the canal cells, and exchanges with 

reaches. The governing equation is solved numerically using the basin cell structure. A 

second-order finite difference approximation is used for the second derivatives, and an explicit 

backward difference approximation is used for the time derivative. During each time step the 

right-hand side of the equation is evaluated based on current time level conditions, and the new 

water elevation is found. By designating the equation parameters and water elevation h for each 

 App. 12-1-6 
2006 South Florida Environmental Report Appendix 12-1

cell by the indexes i,j, and the time level by the index m, the resulting finite difference equation for 

each cell is: 

m

jir S m

ji c S m

ji e S m

jii S

y

m

ji h m

ji

h

y

ch

m

ji h m

ji h

y

m

ji h m

ji

h

y

ch

m

ji h m

ji h

Ky

x

m

ji h m

ji

h

x

ch

m

ji h m

ji h

x

m

ji h m

ji

h

x

ch

m

ji h m

ji h

x K

t

m

ji h mji h

ji

, ,,,

1, , )

2

, 1, ( , 1, )

2

, 1, (

,1 , )

2

, ,1 ( , ,1 )

2

, ,1 ( , 1 ,

,

1

++−+

Δ

− −

Δ

− − +

−

Δ

− +

Δ

− + +

+

Δ

− −

Δ

− − +

−

Δ

− +

Δ

− + +

=

Δ

− +

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎣

⎡

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

ρ

 [2] 

where Δt is the time step (one day), and Δx and Δy are the grid cell dimensions in each direction. 

During each time step the right-hand side of the equation is evaluated based on current time level 

conditions, and the new water elevation is found by solving for , ji h . m+1

S S

When an active cell is 

adjacent to the grid boundary or to an inactive cell, a no-flow condition is imposed. 

Implementation of the groundwater model has required some modification to the PWATER 

module, primarily to account for evaporation from groundwater and also to link to the irrigation 

and high water table modules. The original HSPF groundwater algorithm is based on groundwater 

storage, AGWS. Changes to the storage for each time step are due to infiltration (GWI), 

evaporation (BASET), and discharge to surface water (AGWO). Infiltration is predicted using 

subroutines representing the Stanford Watershed Model approach. Evaporation is modeled as a 

loss term, which is based on a model parameter BASETP. The discharge is based on a rating 

curve, specified by the model parameters AGWRC and KVARY. This groundwater discharge 

algorithm in HSPF has been disabled and replaced by the equivalent parameters in WaSh. For 

each of the cells, two of the source terms on the right-hand side of the equation, , ji

 and , ji are 

set equal to output variables from HSPF PWATER groundwater subroutine related to infiltration 

(GWI) and evaporation (BASET). The groundwater elevation h

m

i

m

e

i,j replaces the storage variable, 

AGWS, and when combined with the two source terms, represent essentially the same processes 

as AGWO in HSPF. However, this modification provides a process-based approach to represent 

surface water and groundwater interactions when compared with the rating curve-based 

groundwater discharge approach in HSPF. For example, the source/sink terms for a canal/reach 

cell are now defined as: 

A

CH S m c

c ji

Δ = , [3]

A

CH S m r r jiΔ = ,

 [4] 

where ΔH is the difference in groundwater elevation and canal or reach surface water elevation, 

which are dynamically tracked in WaSh, A is the cell area, and Cc and Cr are the conductance of 

canal or reach, respectively. The conductance is physically related to the hydraulic conductivity 

of the stream bed material and the length and width of the canal. In the Loxahatchee River 

watershed, the hydraulic conductivity of the deep canals (reaches) and shallow canals is different. 

The hydraulic conductivity and canal dimension are provided as input data for each cell according 

to the basin hydrography and land use. 

 App. 12-1-7 
Appendix 12-1 Volume I: The South Florida Environment

Irrigation Demand and High Water Table Conditions 

The WaSh groundwater module has also been developed to interact with the irrigation 

module and the high water table module of the HSPF. WaSh simulates the irrigation demand by 

monitoring the moisture in the upper and lower soil zones and generating a demand for water 

based on the existing moisture relative to the desired moisture level that is specified by the user. 

After the irrigation demand is calculated, the algorithm tries to meet the demand by supplying 

water from a number of sources. Groundwater can serve as both an irrigation source and an 

irrigation sink (receptor) in the HSPF irrigation algorithm. In each case, the amount of water 

demanded from, or applied to, the groundwater is extracted or added to the cell’s groundwater 

volume. At the beginning of each day, the irrigation demand is calculated and if groundwater is 

affected, then the groundwater elevation hi,j is adjusted according to the following equation: 

/ ρ ,, V ji h ji h = + Δ [5]

where ΔV is the volume (expressed as depth) of groundwater irrigation demand or application for 

the cell calculated by the HSPF irrigation module, and ρ is the aquifer porosity as defined 

previously in Equation [1]. 

The high water table module in the HSPF requires certain vertically referenced parameters 

and variables to allow for exchange of water between storage components when the groundwater 

level interferes with the upper and lower zone storage (UZS and LZS). For applications in WaSh, 

the vertical referencing is already completed, as the surface elevation (a cell attribute) and the 

groundwater elevation h are all referenced to the same datum. Thus, the only required 

modification is to provide these two variables to the high water table algorithms. The HSPF high 

water table algorithm then calculates the exchange between the storage zones and the 

groundwater. The groundwater elevation is updated with Equation [5], where ΔV now represents 

the exchange between the upper and lower storage zones. 

Drainage Canal Network and Canal Routing 

The surface water drainage canal network is modeled implicitly in the cell-based system and 

explicitly in the reach-based system. The major channels are simulated in the reach-based system 

which consists of a series of reaches and nodes. This drainage system is separated from the cell 

system, but its elements (reaches and nodes) overlay the cell network and coincide with a subset 

of the cells. This system is typically configured to follow the major canals, streams, and rivers in 

the basin. The small or tertiary canals are represented in the cell-based system. These canals 

receive surface and subsurface runoff from the adjacent cells and exchange water with 

neighboring canal cells. 

Flow through the reach-based systems is modeled using the continuity equation, Equation [6], 

and the depth- and width-averaged shallow water wave equation, Equation [7]. The governing 

equations are: 

e

Q

s

q

t

wh

+

∂

∂ = ∂∂ [6]

 App. 12-1-8 
2006 South Florida Environmental Report Appendix 12-1

where q is the flow, u is the width- and depth-average flow velocity, g is the acceleration due to 

gravity, w is the canal width, h is the water depth (referenced to the canal bed), η is the bed 

elevation, t is time, and s is distance along the canal. The bottom stress τb is based on a 

Manning’s n formulation. Boundary conditions can be one of two types: a specified flow or a 

specified water elevation. Specified flow conditions are typically used when a flow structure 

controls the flow out of the system. The water elevation (or head) condition is used when the 

system drains unobstructed into a receiving water body. The governing equations are solved using 

a finite volume procedure, with the reach and node system for a single branch equivalent to a 

finite volume staggered grid approach. 

s

gwhw

s

hgw

s

uq

t

q

b ∂

∂ −−= ∂∂

+

∂

∂

+

∂

∂ η τ

2

2 [7]

TThe source term Qe in the continuity equation, Equation [6], consists of point sources or 

sinks, exchange with groundwater, and exchange with canals from the cell-based system. The 

units for the source term are flow per unit length of channel. The general form for the source term 

can be expressed as: 

e = kp + ki + QQQQ , gwr [8]

where Qkp are external sources or sinks (user-specified time series), Qr,gw is the exchange with the 

groundwater and is equal to Sr, the exchange calculated in the groundwater model, Equation [1], 

and Qki is the exchange with the canal cells where the tertiary canals are connected with the reach. 

When the reach-based system contains branches, the flow in each branch is determined 

independently. The method for estimating the flow between branches depends on whether the 

flow is natural at the connection or whether a structure exists. When a structure is present at the 

branch connections, the flow is determined using a rating curve specific to the structure. Since the 

flow can be bi-directional, the flow direction for the time step is first determined from the water 

elevations in the reaches at the branch juncture. The water elevations for headwater and tailwater 

are then assigned appropriately and the rating curve is used to calculate the flow. It is noted that 

structures can also occur at any node along the reach node system. When a structure is present, 

the flow at that node is determined at the beginning of the time step using the structure flow 

formulas and its value replaces the momentum equation for that node. When no structures are 

present at the branch connections, the flow is solved using the shallow water wave equation, 

Equation [7], and the continuity equation, Equation [6]. The two equations are solved explicitly 

for the flow between branches using the two reaches that connect the branches. The calculated 

flow in the ‘local’ explicit solution is then used as a boundary condition for the implicit solution 

for the upstream branch and as a source to the downstream reach. 

Flow in the cell-based canal system (i.e., the tertiary canals) is represented in the 

WaSh model using the same governing equations and numerical scheme as used for the 

reach-based system. To implement this approach, the cell-based canal parameters are first 

mapped into a ‘local’ branch and reach network. When this mapping is completed, the solution 

algorithm for the reach system can be applied to the local system with only minor modifications 

to the downstream boundary condition and the source terms. The source term in the cell canal 

would then include surface runoff simulated with HSPF routines. 

The tertiary canals are characterized by the total length LC of these canals within the cell, the 

average canal width wc, the average canal bottom elevation, and a critical or ‘design’ water depth. 

 App. 12-1-9 
Appendix 12-1 Volume I: The South Florida Environment

These parameters are attributes of the cell. They can be obtained by mapping GIS hydrologic data 

onto the basin grid and then specifying widths, bottom elevations, and critical depths based on the 

cell land use. The surface water elevation is the dependent variable in the system. In order to map 

these parameters into a branched network, each cell’s canals are designated as a single reach. The 

reach parameters for the cell are determined as follows: 

If the total canal length L is less than the cell length LC, then: 

If the total canal length L is greater than the cell length LC, then: 

Δ = = wwandLs c , [9]

LC

L wwandLCs =Δ , = c * [10]

After the cell-based canal parameters are transformed into reach parameters, the connectivity 

of the branch network is determined. The connectivity of the cells is used directly to establish 

branches and the assignments of reaches within each branch. The canal-to-canal flow is generally 

towards the reaches, but the instantaneous flow is determined by the difference in relative surface 

water elevations between hydraulically connected canal cells. When canal cells exist in cells with 

reaches, the canals are assumed to be hydraulically connected to the reach via a structure. It is in 

these cells that water can flow between the canals and reaches. Between the reaches and tertiary 

canals, the flow is assumed to be controlled by pumps. The pumping capacity is derived from 

land use types, representing the design (or estimated) drainage capacities for the canal systems 

associated with each land use. The drainage capacities of the major land use types are the key 

parameters for calibrating the magnitude of peak flow during a high magnitude and low 

frequency event. 

IMPLEMENTING THE WaSh MODEL 

Watershed Delineation 

The Loxahatchee River watershed is located within northern Palm Beach and southern Martin 

counties and currently drains an area of approximately 240 square miles. Much of the watershed 

remains as undeveloped sloughs and wetlands. In the upper portion of the watershed, nearly half 

of the drainage basin is comprised of wetlands. Agriculture and forested uplands in the northern 

area of the basin comprise one quarter of the watershed. The remaining quarter of the watershed 

consists of developed urban areas. 

The Loxahatchee River watershed was delineated into 12 drainage basins based on local 

hydrology, land use, topography, detailed aerial photography, and field observations. These 

basins represent the same areas as the seven sub-basins described in the Loxahatchee River 

Watershed Action Plan (FDEP, 1998); four of the FDEP sub-basins have been subdivided into 

separate basins to reflect the specific needs of modeling. The basins vary in size from 5 to 

100 square miles, and they provide flow to the three forks of the Loxahatchee River (Figure 3). 

 App. 12-1-10 
2006 South Florida Environmental Report Appendix 12-1

Figure 3. Major drainage basins in the Loxahatchee River watershed. 

 App. 12-1-11 
Appendix 12-1 Volume I: The South Florida Environment

The 1995 land use for these basins has been modified to include changes in the developed areas 

for the year 2000. For purposes of this plan, the 133 land use codes were reduced to six land use 

categories: citrus and vegetables, forest, marsh wetland, other wetland, urban, and other land. 

Table 4 shows the breakdown of land use by basin for the Loxahatchee River watershed. 

Table 4. Loxahatchee River watershed 1995 land use by basin; developed areas 

updated for the year 2000. 

Land Use (acres) 

Total Area by 

Basin 

Basin Citrus & 

Vegetables Forest 

Marsh 

Wetland 

Other 

Wetland Urban 

Other 

Land Acres 

Square 

Miles 

1. Kitch Gauge 16 876 4,954 1,010 309 3,177 10,342 16.2 

2. North Fork 0 95 8,238 735 1,774 156 10,999 17.2 

3. Park River 14 60 2,483 47 31 408 3,044 4.8 

4. Lox Estuarine 591 305 1,155 617 10,536 34 13,237 20.7 

5. C-18/Corbett 1,821 822 43,591 4,749 9,199 3,312 63,494 99.5 

6. Historic Cypress Creek 340 12 2,993 132 85 20 3,581 5.6 

7. Pal-Mar 266 88 19,477 555 1,672 605 22,663 35.4 

8. Grove West 4,107 168 2,878 86 54 906 8,199 12.8 

9. Grove East 1,709 143 397 105 309 345 3,010 4.7 

10. Jupiter Farms 8 89 494 168 9,359 128 10,246 16.0 

11. Wild & Scenic 752 142 2,562 220 278 392 4,345 6.8 

12. Coastal 0 2,190 2,212 2,180 8,899 391 15,872 24.9 

Acres 9,624 4,990 91,434 10,603 42,505 9,874 169,031 Total Area by 

Land Use Square 

Miles 15.1 7.8 143.3 16.6 66.6 15.5 264.9 

Note: Blue shaded rows are watershed basins that discharge into the Northwest Fork of the Loxahatchee River. 

Basin 1: Kitch Gauge. This basin contains the 16.2-square-mile area that contributes water 

to the USGS Kitching Creek flow gauge in Jonathan Dickinson State Park. Almost 50 percent 

(4,654 acres) of this basin is characterized as marsh wetland. Downstream of this basin, Kitching 

Creek discharges into the Northwest Fork. 

Basin 2: North Fork. This basin contains the 17.2-square-mile area that contributes water to

the North Fork of the Loxahatchee River. Approximately 75 percent (8,238 acres) of this basin is 

marsh wetland. The flow from this basin is not gauged. 

Basin 3: Park River. This basin contains the 4.8-square-mile area that drains to the 

Northwest Fork of the Loxahatchee River. It includes the portion of land draining to Kitching 

Creek downstream of the gauge and some smaller tributaries such as Wilson Creek and the creek 

flowing through the Boy Scout Camp. Approximately 82 percent (2,483 acres) of this basin is 

marsh wetland. The flow from this basin is not gauged. 

Basin 4: Lox Estuarine. This central drainage basin is a 20.7-square-mile area and is highly 

developed with urban land uses that contribute significant runoff to the embayment of the 

Loxahatchee River. Consisting of 20.7 square miles of the watershed, this basin provides aquatic 

recreational opportunities that sometimes exceed the river’s carrying capacity on weekends and 

 App. 12-1-12 
2006 South Florida Environmental Report Appendix 12-1

holidays. Runoff and groundwater from this basin discharge to brackish waters of the estuary. 

Approximately 80 percent (10,536 acres) of this basin is urban. The flow from this basin is not 

gauged. 

Basin 5: C-18/Corbett. With 100 square miles, this is the largest basin in the Loxahatchee 

River watershed. Much of the land in this basin encompasses the southwestern portion of the 

watershed, and it is publicly owned and protected. This basin includes the remnants of the 

Hungryland and Loxahatchee sloughs, which historically fed the Northwest Fork of the 

Loxahatchee River. Historically, the Loxahatchee Slough extended south into the area currently 

known as the Grassy Waters Preserve (West Palm Beach Water Catchment Area), which is the 

present source of drinking water for the City of West Palm Beach. Water from this basin 

discharges to the C-18 canal and is either discharged into the Southwest Fork of the Loxahatchee 

River through the S-46 structure or directed through the G-92 structure to the upper end of 

Northwest Fork of the Loxahatchee River. Approximately 69 percent (43,591 acres) of this basin 

is marsh wetland. Flow gauges are located at the G-92 and the S-46 structures. 

Basin 6: Historic Cypress Creek. Cypress Creek is a 5.6-square-mile basin that drains to 

Cypress Creek just downstream of the Cypress Creek flow gauge. The majority of this basin has 

recently been purchased by state and local governments for restoration and preservation. Water 

from this basin flows into Cypress Creek and discharges at the upper end of the Northwest Fork 

near River Mile (RM) 10.3. Approximately 84 percent (2,993 acres) of this basin is marsh 

wetland. The flow from this basin is not gauged. 

Basin 7: Pal-Mar. Pal-Mar is a 35.4-square-mile basin that drains a sizable wetland located 

along the western edge of the watershed and is one of the major tributaries to the Northwest Fork 

of the Loxahatchee River. Most of these wetlands remain intact; however, the eastern flow-ways 

leading to Cypress Creek have been disturbed by rural development. Approximately 86 percent 

(19,477 acres) of this basin is marsh wetland. Water from this basin flows into Cypress Creek 

upstream of the Cypress Creek flow gauge and discharges at the upper end of the Northwest Fork 

near RM 10.3. 

Basin 8: Grove West. The predominant land use in this 12.8-square-mile basin is citrus. 

Although the hydrology in this basin was altered to support agriculture, wildlife utilization is 

relatively good, and the land provides a valuable greenway link between large natural areas 

within the watershed. Approximately 50 percent (4,107 acres) of this basin is used for vegetables 

and citrus. Water from this basin flows into Cypress Creek upstream of the Cypress Creek flow 

gauge and discharges at the upper end of the Northwest Fork. 

Basin 9: Grove East. The predominant land use in this 4.7-square-mile basin is citrus. 

Although the hydrology in this basin was altered to support agriculture, wildlife utilization is 

relatively good, and the land provides a valuable greenway link between large natural areas 

within the watershed. Approximately 57 percent (1,709 acres) of this basin is used for vegetables 

and citrus. Water from this basin flows into Hobe Grove Ditch (RM 9.07) and Moonshine Creek 

(RM 10.0), both of which discharge into the Northwest Fork near RM 9.0. 

Basin 10: Jupiter Farms. This 16-square-mile basin supports substantial rural residential 

development known as Jupiter Farms. The South Indian River Water Control District (SIRWCD) 

manages a stormwater management system of canals to serve this area. Water quality and 

saltwater intrusion in the Northwest Fork are concerns in this basin (FDEP, 1998). Water from 

this basin discharges into the SIRWCD C-14 canal, which flows over Lainhart Dam feeding the 

upper end of the Northwest Fork. The C-18 canal is connected to this basin by the G-92 structure, 

which also provides periodic flows of water over the Lainhart Dam from the C-18 canal. 

Approximately 91 percent (9,359 acres) of this basin is urban land. There is a flow gauge at both 

G-92 and Lainhart Dam. 

 App. 12-1-13 
Appendix 12-1 Volume I: The South Florida Environment

Basin 11: Wild and Scenic. This 6.8-square-mile area basin contains the “Wild and Scenic” 

Northwest Fork of the Loxahatchee River and the northern portion of Riverbend Park. 

Approximately 59 percent (2,562 acres) of this basin is marsh wetland. The flow from this basin 

is not gauged. 

Basin 12: Coastal. The coastal basin contains the 34-square-mile area that drains to the 

Atlantic Ocean or the Intracoastal Waterway and out the Jupiter Inlet. This basin has been 

developed for maximum urban residential, commercial, and recreational use. Very few small and 

isolated natural areas remain. Most of the surface water and groundwater from this basin 

discharge to marine waters rather than toward the freshwater portion of the Northwest Fork. The 

flow from this basin is not gauged. 

Adjacent Basin: L-8/Grassy. This 192.5-square-mile basin is not considered part of the 

Loxahatchee River watershed. However, this basin has several outflow locations, one of which is 

to the C-18/Corbett Basin. Thus, the inter-basin transfers of waters from Grassy Waters to the 

C-18 canal are considered in this plan. There are no flow gauges at this inter-basin location.

Model Setup 

The WaSh model was implemented into four regions of the Loxahatchee River watershed 

(Figure 3). These regions include all of the major drainage basins except the Coastal Basin. The 

JDSP region (A) includes the North Fork, Kitch Gauge, Park River, and the Loxahatchee Estuary 

basins. The Pal-Mar and Grove region (B) includes the Pal-Mar, Historic Cypress Creek, Grove 

West, and Grove East basins. The Jupiter Farms region (C) includes the Jupiter Farms and the 

Wild and Scenic basins. The C-18 region (D) represents the C-18/Corbett Basin and flow 

diversion from the L-8/Grassy Basin. The cells for each of the regions are shown in Figure 2.

The cell size was 750 ft by 750 ft for the Jupiter Farms region, 1000 ft by 1000 ft for the JDSP 

region and Pal-Mal/Grove region, and 1500 ft by 1500 ft for the C-18 region. 

Input data required to generate the model grid include primary and secondary basin 

coverages, polygon features with basin name attributes, hydrography including streams and 

canals as line or polyline features, the 2000 base land use coverage, soil coverage, and land 

surface elevation. The land surface contour was resampled (100-foot intervals) based on 5 ft by 

5 ft Light Detection and Ranging (LIDAR) data to get a smooth land surface profile and to 

remove data artifacts. For limited areas where LIDAR data are not available, the 1-foot contour 

was used. Using the ArcView GUI, these coverages are overlaid to get an aerial extent of the 

model domain along with cell attributes of land use type, soil, canal length and width, and 

elevation. 

When creating the primary reaches for the basins, the hydrography theme is overlaid on the 

grid and those grid cells intersecting with polylines of the hydrography theme are classified as 

canal cells. The canal length in a grid cell is calculated with all the intersecting canal segments 

inside a grid cell. Reach cells are created by digitizing major river segments and canals starting 

from the basin outlet. After digitizing, the length of a reach, which is typically the grid cell size, is 

specified to allow for redistribution of the nodes along the reach network. Each of the reach 

segments has a reach ID along with the width and bottom elevation assigned according to the 

cross-section of the major canal and river segment. In Figure 4, the cells are color coded to 

represent canal cells (turquoise), reach cells (pink), and free cells (light green). The surface 

elevation of cells is used to create flow paths. In general, flow in free cells is routed to the nearest 

canal or reach cell (Figure 4, Region B). A no flow boundary condition is imposed along the 

boundary cells. 

 App. 12-1-14 
2006 South Florida Environmental Report Appendix 12-1

A 

B 

C

D 

Figure 4. The Loxahatchee WaSh model grids: (A) JDSP model, 

(B) Pal-Mar-Grove model, (C) Jupiter Farm model, and (D) C-18 model. 

Free cells, canal cells, and reach cells are color coded turquoise, light 

green, and pink, respectively. In Region A, the blue line represents the 

model boundary, and the nodes represent examples of possible model 

output locations. In Region B, the nodes are shown in the reach system. 

In Region C, flow routing directions are shown with arrows.

Each of the cells is linked with a Master Lookup Database consisting of HSPF parameters, 

evapotranspiration (ET) coefficients, canal parameters, and aquifer properties. Based on the grid 

cell attribute, this master database is queried to populate the respective parameters for each cell in 

the grid. Some of the model parameters can be changed during the model calibration process. 

The other important input data required by the model are rainfall and ET. These data were 

obtained from the District’s South Florida Water Management Model (SFWMM) for the period 

from 1965–2000. The dataset was extended to March 2004 with available rainfall and ET data 

stored in the District’s DBHYDRO database in the model area. Daily rainfall is disaggregated 

into hourly rainfall based on an analysis of available hourly rainfall distribution in South Florida. 

 App. 12-1-15 
Appendix 12-1 Volume I: The South Florida Environment

Model Calibration and Validation 

The Loxahatchee WaSh model has been calibrated with five flow monitoring stations 

(Figure 5). Flow data collected at the G-92 structure are not used since it was found that the data 

are likely not accurate. The Kitching Creek station started to collect data in the early 1980s. The 

data are not continuous until 1990, and thus only the data collected after 1990 are used for 

calibration and validation of the JDSP model. The Hobe Grove and the Cypress Creek stations 

have been collecting data since 1980; however, there are significant periods of time when data 

were not collected or are missing. Data collected from the flow stations at S-46 and Lainhart Dam 

have the longest record. Only the data collected after 1987 were used for WaSh model calibration 

and validation due to structure changes of G-92. All the collected flow data were evaluated for 

their validity before being used for model calibration and validation. In addition, water level data 

collected in two groundwater wells (PB-689 and M-1234) were used. PB-689 is located in the 

C-18/Corbett basin where the land use is dominated by wetland while M-1234 resides in a forest 

land of the Cypress Creek basin. 

Kitching Creek Station 

Lainhart Dam Station S-46 Station 

Hobe Grove Station 

Cypress Creek Station 

PB-689 

Figure 5. Flow (green dots) and groundwater (white dot) monitoring stations in the 

Loxahatchee River watershed for WaSh model calibration arrows. 

M-1234

 App. 12-1-16 
2006 South Florida Environmental Report Appendix 12-1

 Model calibration involves conducting a model simulation of each region for the period of 

record (POR) and comparing the simulated flow with the observed flow. The model parameters 

are then adjusted in subsequent simulations to improve the shape of simulated flow time-series 

until the model output meets the performance criteria. In general, the hydrological calibration is 

conducted in two main steps: 

1. Macro Scale: Adjust hydrological parameters to obtain the long-term basin water budget. 

2. Micro Scale: Fine tune model parameters to get the best match between observed and 

simulated flow. At this stage, the shape of the hydrograph with respect to peak and base flow 

is adjusted. Groundwater levels were also checked with data from observation wells. 

In the first step, the long-term water budget is used to ensure that the model calibrations are 

not biased for one type of climatic condition. Another component of the water budget calibration 

is verifying that the fractions of groundwater and surface water contribution to runoff properly 

reflect the partitioning between surface runoff and subsurface runoff. For this component of the 

simulation, the average annual water budget for each of the land uses as well as for the entire 

watershed were used to make decisions to adjust parameters. An initial run of the model was 

made using model parameters that were calibrated in the St. Lucie Estuary watershed (Wan et al., 

2003). The most sensitive model parameters in completing the water budget calibrations are 

evaporation coefficients for individual months and infiltration parameters of the HSPF. An 

example of the water budget is provided in Table 5 for the Pal-Mar and Grove regions. The water 

budget is partitioned into the Pal-Mar and historic Cypress Creek basins, which consist mostly of 

wetland and forest, and the Grove West and Grove East basins, which consist mostly of irrigated 

citrus groves. Citrus irrigation significantly increases the runoff from a water budget perspective. 

Runoff 

Basins Rainfall Irrigation ET 

Surface Subsurface 

Storage 

Pal-Mar & Historic Cypress Creek 61.2 -- 44.9 13.6 2.6 1.7 

Grove West & Grove East 61.2 8.2 40.2 16.9 11.9 0.2 

Table 5. Average annual water budget (inches) for the Pal-Mar and 

Grove regions. 

 App. 12-1-17 
Appendix 12-1 Volume I: The South Florida Environment

Once the long-term calibration is completed, the next step is to validate the model by 

matching the simulated daily flow hydrograph to the measured daily flow values recorded for 

each of the flow stations. The more significant parameters to be calibrated during this step 

includes the groundwater cell conductance parameters that control the rate at which groundwater 

flows to the canals, the irrigation parameters, and the canal pumping parameters that control the 

rate at which tertiary canals flow to primary reaches. To a lesser degree, the length-scale 

parameter associated with surface drainage (LSUR) has an effect on the shape of the 

hydrographs. Reducing the LSUR increases runoff and decreases infiltration. The model 

validation process is similar to the calibration process, except that a different POR is used for the 

relevant input data. The model parameters are kept constant. Model validation is considered 

complete if the simulation meets the performance criteria. Otherwise, the model is 

recalibrated and validated. 

Model calibration and validation performance are evaluated with two of three criteria 

recommended by the ASCE Task Committee on Definition of Criteria for Evaluation of 

Watershed Models (1993): the deviation of volume, the Nash-Sutcliffe coefficient, and the 

coefficient of daily gain. The coefficient of gain from the daily mean is not used because of its 

similarities with the Nash-Sutcliffe coefficient in this particular case. Instead, the coefficient of 

determination (R2

) is calculated as part of the hydrologic analysis. 

The deviation of volume, DV, quantifies the difference in observed and predicted water 

volumes and is calculated: 

%100

)(

1

1 ×

−

=

∑

∑

=

=

n

i

n

i

Vm

VsVm

DV [11]

where DV is the deviation of volume (%), Vm is the measured water yield for the period of 

comparison, and Vs is the modeled water yield for the period of comparison. The calibration and 

validation is considered satisfactory if the absolute value of CV is less than 10 percent. Donigian 

et al. (1984) indicated that HSPF calibration is considered to be very good if the absolute value of 

DV is less than 10 percent, and good when DV is between 10 and 15 percent. 

The Nash-Sutcliffe coefficient, NS, measures how well the daily simulated flow corresponds 

with the measured flow. This coefficient is calculated: 

∑

∑

=

=

−

−

−= n

i

n

i

QQm

QsQm

NS

1

2

1

2

)(

)(

1 [12]

where Qm is the measured daily discharge, Qs is the simulated daily discharge, and Q is the 

average measured daily discharge. A Nash-Sutcliffe value of 1.0 indicates a perfect fit, while a 

value of 0 indicates that the model is predicting no better than the average of the observed data. 

Daily flow calibration and validation is considered to be satisfactory if NS value is larger than 

0.4. 

 App. 12-1-18 
2006 South Florida Environmental Report Appendix 12-1

The model calibration and validation performance results are summarized in Table 6. Note that 

during the period of model calibration or validation, those days with missing or problematic data 

were excluded, so the count of days indicates the number of days with valid flow data. In general, 

the model simulates daily flow reasonably well with R2

 and NS values of most of the stations 

above 0.5 for both calibration and validation analyses except for the Hobe Grove station. 

the DV ranged from −0.83 to 8.5 percent for calibration and −2.87 to 12.5 percent for validation. Table 6. WaSh model calibration and validation performance results. 

Monitoring Station S-46 Lainhart Dam Cypress Creek 

Station 

Hobe Grove 

Station 

Kitching Creek 

Station 

Calibration Results

 Period 1987–1996 1987–1996 1980–1986 1981–1985 1990–1996 

 Number of days 3193 3193 1680 1058 2192 

 DV (%) −1.78 −0.83 −7.50 −14.67 0.21 

 NS 0.69 0.47 0.43 0.08 0.51 

 R2 0.71 0.53 0.53 0.54 0.51 

Validation Results

 Period 1997–2004 1997–2004 1987–1990 1987–1989 1997–2000 

 Number of days 2587 2587 990 687 1461 

 DV (%) 12.52 9.43 −2.87 10.66 9.09 

 NS 0.71 0.56 0.61 0.27 0.54 

 R2 0.73 0.32 0.72 0.63 0.57 

To aid in the evaluation of model calibration and validation performance, three types of plots 

are prepared: 

1. Daily flow distribution: Plot of the distribution of the measured and modeled daily flow to 

visually examine the overall model performance. Particular attentions are paid to the low 

flow regime. 

2. Double mass curve: To compare the measured and modeled daily flow in a 

cumulative manner along with increasing rainfall. This is a visual check of the DV calculated 

in Table 6. 

3. Daily flow time series of modeled flow and observed flow for selected periods. 

Figure 6 includes the three plots for the Lainhart Dam and S-46 stations, which provide the 

longest period of flow data for model calibration and validation. Panels A and B in 

Figure 5 compare the frequency distribution of the modeled versus the observed daily flows. A 

slight high frequency of flow in the range of about 10 cubic feet per second (cfs) is predicted by 

the model at Lainhart Dam, possibly due to low flow leakage at the structure becoming 

significant but is not measured. The double mass curves for both stations (Figure 6, Panels C and 

D) show consistent model performance when comparing the patterns of the increase of modeled 

and measured flow with increasing rainfall. At Lainhart Dam, the model over-predicted flow for a 

3-month period during the wet season of 1999. This has been attributed partly to the 9 percent of 

DV in Table 5. Panels E and F in Figure 6 are the time-series plots of measured flow and 

modeled flow from 2000 through 2003. Overall, the figure shows that the model simulates daily 

flows over Lainhart Dam and S-46 stations reasonably well. 

 App. 12-1-19 
Appendix 12-1 Volume I: The South Florida Environment

 App. 12-1-20 

Figure 6. WaSh model calibration and validation plots at Lainhart and 

S-46 stations (1/1/87–1/31/04): (A) daily flow distribution at Lainhart Dam 

station, (B) daily flow distribution at S-46 station, (C) double mass curve at 

Lainhart Dam station, (D) double mass curve at S-46 station, (E) time-series 

plot at Lainhart Dam station (2000–2004), and (F) time-series plot at S-46 

station (1999–2004). 

0

100

200

300

400

500

600

0 100 200 300 400 500 600 700 800 900 1000 1100

Cumulative Rainfall (in)

Cumulative Runoff (in)

S46 - Observed

S46 - Modeled

Calibration Period Validation Period

D

0

200

400

600

800

1000

1200

1400

1600

0 100 200 300 400 500 600 700 800 900 1000 1100

Cumulative Rainfall (in)

Cumulative Runoff (in)

1

10

100

1000

10000

0 20 40 60 80 100

Exceedance (%)

Flow (cfs)

1

10

100

1000

10000

0 20 40 60 80 100

Exceedance (%)

Flow (cfs)

Lainhart Dam Observed

Lainhart Measured

Lainhart Modeled

Validation Period

Calibration Period

C

Lainhart Dam Modeled

A

S-46 Observed

S-46 Modeled

B

0

500

1000

1500

2000

2500

3000

Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04

Date

Runoff (cfs)

0

200

400

600

800

1000

Jan-00 Jan-01 Jan-02 Jan-03 Jan-04

Date

Runoff (cfs)

F S46 - Observed Lainhart Dam Observed

Lainhart Dam Modeled

E S46 - Modeled
2006 South Florida Environmental Report Appendix 12-1

 Calibration of the C-18 and Jupiter Farms portion of the model is difficult because the Jupiter 

Farms Basin, the C-18/Corbett Basin, and the Grassy Water Preserve Basin are hydrologically 

connected. The model represented the G-92 structure by using the ‘special structure’ option. In its 

simplest form, the special structure consisted of a weir with a 12-foot elevation located in a reach 

consistent with its location along the C-18 canal. When the water elevation in the C-18 canal is 

above 12 feet, the weir structure will allow water from the C-18 canal to flow out of the basin. 

This discharge was subsequently used as input into the Jupiter Farms Basin as the model 

boundary condition. The flow rate is determined internally by the model, and is dependent on the 

prescribed weir configuration and the water elevation in the C-18 canal. The width of the special 

weir was adjusted in a series of simulations until approximately 50 cfs of water flows during 

normal operations and a maximum of approximately 400 cfs flows under the flood control mode. 

Similarly, for the inter-basin transfer of water from the Grassy Waters Preserve (West Palm 

Beach Water Catchment Area) into the C-18 canal, a special structure was imposed in a separate 

model set up for the L-8 Basin to allow for a time series of flow as the boundary condition for the 

C-18 basin model. Water flow was based on stage in the Water Catchment Area. According to a 

water budget model developed for the West Palm Beach Water Catchment Area (Sculley, 1995), 

an annual contribution of 20,000 ac-ft of water from the Water Catchment Area to the C-18 Basin 

during April 1992 to March 1995 was used as a target to calibrate the special structure. The 

time-series plots for Lainhart Dam and S-46 station (Figure 5, Panels E and F) indicate that the 

special structures provide a reasonable estimation of inter-basin transfers over the G-92 structure 

and through the existing culverts in Grassy Waters Preserve into the C-18 basin. 

The Kitching Creek station collects flow from a large area dominated by forest and wetland. 

Figure 7 presents the performance of the model calibrated and validated at Kitching Creek. 

Overall, the figure shows that the model is capable of simulating flow fairly well in this area. The 

daily flow distribution of the modeled flow matches very well with the measured flow. The 

double mass curves are consistent with 0.21 percent of DV for calibration and 9.09 percent for 

validation shown in Table 5. However, the time-series plot (Figure 7, Panel C) did show that in 

1998 there were a few significant events that are not predicted by the model. Such deviations are 

likely related to the quality of rainfall data. 

The plots for the Cypress Creek and Hobe Grove Ditch stations are shown in Figure 8. The 

plots for the Cypress Creek station are consistent with the model calibration and validation 

performance measures shown in Table 5. Model calibration and validation at the Hobe Grove 

Ditch station is considered to be fair for the total volume. Daily flow calibration, however, did not 

meet the performance criteria. This is likely due to the quality of the data collected at the site. The 

Hobe Grove Ditch dataset is obtained from a stage–flow relationship downstream from several 

culverts that discharge from Gulf Stream Grove (owned by the District) and the structure owned 

by the Hobe St. Lucie Water Control District. Measuring flows under these conditions is 

challenging due to the complexity of the hydrologic connections and grove operations along with 

slight tidal influence in the downstream area. The stage-flow relationship is not as accurate as 

other flow gauges in the District. For example, in 1987 the Hobe Grove Ditch station failed to 

collect accurate data during several significant storm events; these significant events were 

accurately recorded by the nearby Cypress Creek station (Figure 8, Panels E and F). In this case, 

model simulation is considered to be acceptable in light of the poor data quality. 

 App. 12-1-21 
Appendix 12-1 Volume I: The South Florida Environment

1

10

100

1000

10000

0 20 40 60 80 100

Exceedance (%)

Flow (cfs)

Observed

 Modeled

A

0

100

200

300

400

0 100 200 300 400 500 600 700

Cumulative Rainfall (in)

Cumulative Runoff (in)

Observed

Modeled

Calibration Period Validation Period

B

Figure 7. WaSh model calibration and validation plots at Kitching Creek station 

(1990–2000): (A) daily flow distribution, (B) double mass curve, 

and (C) time-series plot (1997–2000). 

0

100

200

300

400

500

600

700

800

01/01/97 07/01/97 01/01/98 07/01/98 01/01/99 07/01/99 01/01/00

Date

Runoff (cfs)

Observed

Modeled

C

 App. 12-1-22 
2006 South Florida Environmental Report Appendix 12-1

Figure 8. Model calibration and validation plots at Cypress Creek and Hobe 

Grove Ditch stations (1981–1990): (A) daily flow distribution at Cypress Creek 

station, (B) daily flow distribution at Hobe Grove Ditch station, (C) double mass 

curve at Cypress Creek station, (D) double mass curve at Hobe Grove Ditch 

station, (E) time-series plot at Cypress Creek station (1984–1987), and (F) 

time-series plot at Hobe Grove Ditch station (1984–1987). 

0

100

200

300

400

500

600

700

800

01/01/84 01/01/85 01/01/86 01/01/87

Date

Runoff (cfs)

Cypress Creek Modeled

Cypress Creek Observed

E

0

100

200

300

0 100 200 300 400

Cumulative Rainfall (in)

Cumulative Runoff (in)

Cypress Creek Modeled

Cypress Creek Observed

Calibration Period Validation Period

C

1

10

100

1000

0 20 40 60 80 100

Exceedance (%)

Flow (cfs)

Cypress Creek Observed 

Cypress Creek Modeled

A

1

10

100

1000

0 20 40 60 80 10

Exceedance (%)

Flow (cfs)

0

Grove Observed

Grove Modeled

B

0

100

200

300

0 100 200 300 400

Cumulative Rainfall (in)

Cumulative Runoff (in)

Grove Modeled

Grove Observed

Calibration Period Validation Period

D

0

100

200

300

400

500

600

700

800

01/01/84 01/01/85 01/01/86 01/01/87

Date

Runoff (cfs)

Grove Modeled

Grove Observed

F

 App. 12-1-23 
Appendix 12-1 Volume I: The South Florida Environment

 The calibration of the groundwater level was conducted in the last step of WaSh model 

validation. Figure 9 shows the time series of the observed and modeled water levels at the two 

groundwater monitoring wells used for validation. The cell hydrology simulated by the model is 

reasonable. Water level predictions could be further refined if the model is to be used for water 

level evaluations. 

PB-689 

C18 Ground Water Calibration

15

17

19

21

23

25

27

29

1/31/93 6/15/94 10/28/95 3/11/97 7/24/98 12/6/99 4/19/01 9/1/02 1/14/04

Time

Elevation (ft)

Observed

Model

12

14

16

18

20

22

11/19/1987 8/15/1990 5/11/1993 2/5/1996 11/1/1998 7/28/2001

Time

Elevation (ft)

Model

Observed

M-1234

Figure 9. Observed and modeled water levels in Groundwater Monitoring 

Well PB-689 and M-1234. Land surface elevation is 24.43 feet at PB689 and 

21.15 feet at M-1234. 

WaSh MODEL SIMULATION RESULTS 

A final long-term simulation for the period from 1965–2003 was conducted after the 

calibration and validation of the Loxahatchee WaSh model was completed. Daily flows from each 

of the tributaries and each of the basins were averaged based on the model output of the 39-year 

simulation. Table 7 is a summary of the data expressed as daily average flows and percentage of 

contributions from each of the basins (tributaries) into the Loxahatchee River and Estuary and the 

Northwest Fork. On average, the Northwest Fork receives about 65 percent of total freshwater 

inflow into the entire Loxahatchee River and Estuary. For total freshwater inflows into Northwest 

Fork, flow over Lainhart Dam (C-18/Corbett G-92 plus Jupiter Farms) accounts for about 

 App. 12-1-24 
2006 South Florida Environmental Report Appendix 12-1

45 percent. The next largest contributor is Cypress Creek (32 percent with Pal-Mar and Grove 

West combined). Kitching Creek at the monitoring station contributes about 8 percent, and Hobe 

Grove Ditch contributes about 5 percent. The remaining 8 percent is contributed from the areas 

that are not currently covered by flow monitoring stations. However, the actual freshwater flow 

contribution varies on a daily basis, depending on the specific hydrologic condition and water 

management practices. For example, there is little freshwater flow from S-46 during the dry 

season, whereas a disproportionately large quantity of fresh water is released from S-46 during a 

flood event. 

Table 7. Flow contributions from each of the basins and major tributaries into the 

Northwest Fork and Loxahatchee River and Estuary. 

Basin Average Daily 

Flow (cfs) 

Flow 

Contribution 

Northwest Fork 

Average Daily Flow 

(cfs) 

Northwest Fork 

Flow Contribution 

1. Kitching Gauge 17.4 5% 17.4 8% 

2. North Fork 20.2 6% --a --a

3. Park River 5.1 2% 5.1 2% 

4. Lox Estuarine 14.4 13% --a --a

5. C-18/Corbett G-92 69.7 22% 69.7 34% 

5. C-18/Corbett S46 51.3 16% --a --a

6. Historic Cypress 

Creek 7.0 2% 7.0 3% 

7. Pal-Mar 57.7 18% 57.7 28% 

8. Grove West 11.1 3% 11.1 5% 

9. Grove East 10.6 3% 10.6 5% 

10. Jupiter Farms 21.9 7% 21.9 11% 

11. Wild and Scenic 6.9 2% 6.9 3% 

Totals 320.3 100% 207.4 100% 

a This basin does not contribute flows to the Northwest Fork of the Loxahatchee River.

Tables 8 and 9 summarize the monthly mean flow for each of the years from 

1965–2003 for flows over the Lainhart Dam and total flow into Northwest Fork covered by the 

four flow monitoring stations (Lainhart Dam station, Cypress Creek station, Hobe Grove station, 

and Kitching Creek station). For flows over Lainhart Dam (Table 7), mean monthly flows less 

than 35 cfs are shaded in red, and flow from 35–65 cfs are shaded in light green. These two flow 

ranges were selected because 35 cfs is the Minimum Flow and Level (MFL) for the Northwest 

Fork (SFWMD, 2002a), and 65 cfs is defined as a flow target in the model for the development of 

the Northern Palm Beach County Comprehensive Water Management Plan (SFWMD, 2002b). 

The Lainhart Dam data (Table 7) shows that a low flow period occurred from 1970–1978. For 

some years, monthly mean flows were less than 35 cfs even during the wet season (June through 

November). Another low flow period occurred from 1987–1990. Extended high flow years 

occurred from 1991–1999. This pattern is consistent with the total Northwest Fork flow presented 

in Table 8; mean monthly flows less than 70 cfs are shaded in red, and flows from 70–130 cfs are 

shaded in light green. The extended low-flow dry season periods in the 1960s, 1970s, and 1980s 

probably coincide with the period during which the floodplain experienced the most significant 

saltwater encroachment. The high flow regime instituted in the 1990s has likely helped the 

floodplain hydrologic condition to recover from the preceding dry years. 

 App. 12-1-25 
Appendix 12-1 Volume I: The South Florida Environment

Years Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual Mean

1965 39 35 14 2 1 14 29 45 10 136 71 10 34

1966 90 76 34 22 53 211 220 127 88 203 63 37 102

1967 22 40 37 18 5 52 89 114 67 193 79 26 62

1968 14 13 7 2 19 302 173 136 197 274 147 62 112

1969 71 45 116 35 154 120 79 131 135 269 173 86 119

1970 113 104 208 237 97 155 112 64 56 71 29 18 105

1971 16 18 12 3 47 19 38 46 136 79 194 73 57

1972 44 39 21 41 191 204 85 50 33 33 68 28 70

1973 28 36 14 9 13 80 66 124 134 168 41 39 63

1974 150 39 45 14 8 131 151 156 54 134 57 63 84

1975 27 30 20 7 33 104 141 31 85 108 39 15 54

1976 9 20 27 5 106 114 30 67 182 72 72 28 61

1977 60 19 10 2 25 33 11 24 271 42 24 139 55

1978 72 30 32 6 14 145 140 145 88 168 263 190 108

1979 193 79 56 47 61 51 31 19 161 146 113 66 85

1980 47 58 39 20 33 29 86 34 32 80 26 17 42

1981 7 9 3 1 2 6 6 152 176 46 53 9 39

1982 12 26 150 200 166 241 124 93 110 145 302 182 146

1983 143 200 172 108 76 141 77 135 268 342 198 157 168

1984 123 86 127 84 102 124 65 48 179 120 196 150 117

1985 72 43 28 61 21 25 65 40 144 110 53 71 61

1986 125 42 102 82 14 93 112 72 76 80 92 99 83

1987 112 36 69 25 15 24 43 30 39 137 234 34 67

1988 57 47 42 14 29 91 116 184 75 18 14 7 58

1989 4 2 17 8 7 8 30 85 25 79 14 15 25

1990 11 6 7 10 7 15 17 77 93 151 22 16 36

1991 142 118 53 141 119 160 128 86 134 192 92 83 121

1992 49 117 66 56 20 122 125 188 217 164 198 95 118

1993 231 204 200 122 92 104 87 85 164 281 149 89 150

1994 96 142 84 82 70 143 114 223 273 209 278 285 166

1995 140 96 98 85 69 101 131 288 186 352 271 153 165

1996 82 73 156 116 137 140 176 96 128 163 123 78 123

1997 81 104 84 121 93 214 109 200 222 105 83 149 130

1998 148 204 161 88 106 53 84 66 208 133 289 102 136

1999 227 89 70 39 30 172 122 109 198 335 206 109 142

2000 81 74 62 91 34 19 40 18 52 174 29 23 58

2001 16 9 46 24 8 43 197 260 254 236 145 78 110

2002 69 125 60 44 15 116 185 57 40 51 43 36 70

2003 22 14 62 46 119 137 48 149 90 73 146 75 82

Monthly Mean 78 65 67 54 57 104 94 104 130 151 120 77 92

Month

Table 8. Monthly mean flows (cfs) over Lainhart Dam from 1965–2003. 

 App. 12-1-26 
2006 South Florida Environmental Report Appendix 12-1

Years Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual Mean

1965 89 106 56 16 10 44 95 129 34 457 259 53 112

1966 281 258 115 82 184 678 682 418 271 628 206 125 328

1967 83 132 122 68 35 158 270 336 210 607 238 94 197

1968 60 54 39 23 74 952 530 420 652 848 436 181 356

1969 204 136 346 108 438 372 256 395 426 876 523 253 363

1970 337 300 671 728 268 452 328 178 167 200 93 64 315

1971 58 64 48 28 148 68 121 135 403 246 633 239 182

1972 138 133 78 137 593 639 252 155 107 110 222 95 221

1973 99 121 59 44 56 242 205 405 408 517 134 126 202

1974 483 133 145 53 39 367 428 479 175 398 181 181 257

1975 89 95 65 36 107 299 436 107 260 323 124 59 167

1976 40 77 80 29 332 354 100 208 560 227 220 99 193

1977 193 67 44 22 95 97 41 78 853 142 84 406 177

1978 234 102 106 32 50 504 449 438 244 522 840 573 343

1979 544 226 152 139 164 147 91 62 517 483 342 192 255

1980 152 173 122 66 110 95 260 107 120 285 106 70 139

1981 39 53 25 18 16 26 28 476 542 154 188 43 134

1982 55 103 504 685 566 749 417 284 356 458 983 476 470

1983 455 656 552 330 203 418 202 388 853 1,074 606 487 517

1984 367 247 382 237 300 345 166 130 563 360 615 466 348

1985 192 116 83 183 65 89 185 115 448 350 160 210 183

1986 400 122 336 232 51 272 341 259 237 255 305 334 263

1987 335 113 218 84 62 88 134 89 143 441 741 119 214

1988 176 154 138 52 92 250 348 583 254 73 58 36 185

1989 30 24 62 38 30 32 88 233 88 246 58 58 83

1990 49 41 34 42 31 46 63 243 333 435 85 68 123

1991 495 374 161 417 345 481 361 267 400 594 282 240 368

1992 147 326 179 160 64 372 415 584 645 496 632 293 359

1993 740 619 598 340 244 274 233 237 447 867 416 238 437

1994 269 438 225 216 185 465 344 670 842 675 887 874 507

1995 417 275 284 227 172 256 343 858 568 1,146 812 401 482

1996 228 186 430 304 380 389 545 270 383 543 409 225 359

1997 247 300 241 372 262 689 343 594 671 314 224 446 392

1998 431 639 485 233 279 133 228 174 661 414 908 301 404

1999 749 261 181 103 84 495 343 299 599 1,079 606 314 427

2000 216 187 161 255 100 60 114 56 150 516 85 73 165

2001 53 37 126 66 39 149 477 794 792 668 387 203 318

2002 175 343 156 151 51 288 532 164 114 138 115 102 193

2003 65 47 202 136 372 392 126 354 235 184 381 181 224

Monthly Mean 241 201 205 166 172 314 280 312 403 470 374 231 281

Month

Table 9. Monthly mean flows (cfs) into the Northwest Fork of the Loxahatchee River 

passing the Lainhart Dam, Cypress Creek, Hobe Grove Ditch, and Kitching Creek 

Flow stations from 1965–2003. 

 App. 12-1-27 
Appendix 12-1 Volume I: The South Florida Environment

 Because of the hydrologic variability during the past 39 years, the 39-year daily flow data at 

Lainhart Dam were analyzed to determine the daily flow distribution for each of the 12 months of 

all the 39 years. This analysis indicates that the daily flow distribution in a month during the 

39 years is not normally distributed. The results are summarized in Figure 10 which plots the 

median flow and the 75th percentile flow in the month. The 75th percentile flow represents the 

flow that is exceeded by only 25 percent of days in that month during the 39 years. Daily flow 

from Lainhart Dam is less than 50 cfs for 50 percent of time during the months of February, 

March, April, and May. Flows in April and May are the lowest among all the months. This also 

shows the importance of flow augmentation during these low flow months. 

Figure 10. Monthly median flow and the 75th percentile flow over Lainhart 

Dam from 1965–2003. 

0

50

100

150

200

250

January

February

March

April

May

June

July

August

September

October

November

December

Month

Flow cfs

Median

75th percentile

 App. 12-1-28 
2006 South Florida Environmental Report Appendix 12-1

MODELING SALINITY 

THE HYDRODYNAMIC/SALINITY (RMA) MODEL DESCRIPTION 

Salinity in the Northwest Fork of the Loxahatchee River and Estuary is controlled by both 

freshwater inflows and tidal circulation, which represent the competition between river and ocean 

influences. A hydrodynamic/salinity (RMA) model was developed to study the influence of 

freshwater flows from the tributaries of the Northwest Fork and S-46 on the salinity conditions in 

the Loxahatchee River and Estuary. In parallel with model development, a data collection 

network was established to measure tide and salinity at five sites from the embayment area near 

the Jupiter Inlet (RM 0.70) to RM 9.12. The objective of salinity data collection and model 

development was to establish the relationship between salinity and the amount of freshwater 

inflow. The requirement to the model is to predict daily average salinity over a long period of 

time such as 30 years under various project scenarios. The main focus of the data collection and 

salinity modeling has been on the upper Northwest Fork of the Loxahatchee River. 

The software programs used in developing the Loxahatchee River hydrodynamics/salinity 

model were RMA-2 and RMA-4 (USACE, 1996). RMA-2 is a 2-D depth-averaged finite element 

hydrodynamic numerical model. It computes water surface elevations and horizontal velocity 

components for subcritical, free-surface flow in two-dimensional flow fields. RMA-2 computes a 

finite element solution of the Reynolds form of the Navier-Stokes equations for turbulent flows. 

Friction is calculated with the Manning’s n or Chezy equation, and eddy viscosity coefficients are 

used to define turbulence characteristics. Both steady and unsteady state (dynamic) problems can 

be analyzed. The program has been used to calculate water levels and flow distribution around 

islands; flow at bridges having one or more relief openings, in contracting and expanding reaches, 

into and out of off-channel hydropower plants, at river junctions, and into and out of pumping 

plant channels; circulation and transport in water bodies with wetlands; and general water levels 

and flow patterns in rivers, reservoirs, and estuaries. 

The water quality model, RMA-4, is designed to simulate the depth-average 

advection-diffusion process in an aquatic environment. The model is used for investigating the 

physical processes of migration and mixing of a soluble substance in reservoirs, rivers, bays, 

estuaries, and coastal zones. This model was used to evaluate salinity and the effectiveness of 

various restoration scenarios. For complex geometries, the model utilizes the depth-averaged 

hydrodynamics from RMA-2. 

Figure 11 is a bathymetric map of the estuary. The estuary is shallow and well-mixed with 

depth for the most part of the estuary ranging from 3 to 10 feet. 

 App. 12-1-29 
Appendix 12-1 Volume I: The South Florida Environment

Figure 11. Loxahatchee Estuary bathymetry.

 App. 12-1-30 
2006 South Florida Environmental Report Appendix 12-1

IMPLEMENTING THE RMA MODEL 

Model Setup 

Based on the most recent bathymetry, freshwater inflow, and tide data, the RMA model was 

updated in early 2004. The current model mesh includes a total of 4,956 nodes with elevations 

derived from the survey data provided by the U.S. Geological Survey (USGS). Figure 12 shows 

the RMA model mesh construction with 1,075 quadrilateral elements and 231 triangular 

elements. Arrows in the figure indicate the locations where freshwater inflows are applied. The 

four tributaries that contribute freshwater to the Northwest Fork are Lainhart Dam, Cypress 

Creek, Hobe Grove Ditch, and Kitching Creek. The RMA model domain also includes the 

Southwest Fork and flows from the S-46 structure. The RMA itself does not predict the amount 

of fresh water entering the system from the watershed or discharge structures. The freshwater 

discharge amounts from these tributaries and structures are provided by the WaSh model or from 

recorded data from the flow gauges. 

Figure 12. The RMA model domain map. KC = Kitching Creek USGS station; 

BD = Boy Scout Dock station, CG – U.S. Coast Guard Station. 

 App. 12-1-31 
Appendix 12-1 Volume I: The South Florida Environment

 The meandering river channel pattern is one of the fundamental characteristics of the natural 

system of the Northwest Fork of the Loxahatchee River. The previous studies have demonstrated 

that restoring the natural oxbows to the Northwest Fork can effectively reduce saltwater intrusion 

into the historically freshwater reaches. The meandering river channel and oxbows of the 

Northwest Fork are preserved in the construction of the RMA model mesh. 

Several natural river channel restoration projects have been implemented in the past decade to 

restore oxbows to the Northwest Fork. Salinity measurements taken before and after the 

implementation of the projects indicate that the oxbows can reduce the extent of saltwater 

intrusion to the Northwest Fork. The RMA model mesh contains the geographic features of the 

river channel. Depending on the time period, the model simulation can be conducted with the 

oxbow restoration projects completed for the post-project period or without the restored oxbows 

for the pre-project period. The current model mesh is also detailed enough to simulate the 

effectiveness of potential channel restoration projects in river reaches up to the Trapper Nelson 

Interpretive Site. The channel above the Trapper Nelson Interpretive Site will be further refined 

in the mesh after an ongoing GIS project is completed that will provide more detailed geometry 

for the river channel above the Trapper Nelson Interpretive Site. On the ocean side, the model 

mesh was extended three miles offshore into the Atlantic Ocean to obtain a relatively stable 

salinity boundary condition (Hu, 2004). 

The RMA model was applied to establish the relationship between the amount of freshwater 

inflow and the salinity regime in the Northwest Fork. The freshwater/salinity relationship 

provided means to assess restoration plan scenarios. 

Model Verification 

In parallel with the preliminary RMA model setup, a data collection program was 

implemented. A bathymetric survey was conducted by the USGS in early 2003. Water depth was 

recorded along survey lines in the Northwest Fork and the North Fork of the Loxahatchee River. 

The Northwest Fork survey covered river reaches from RM 4.0 to the Trapper Nelson’s 

Interpretive Site (RM 10.50). Approximately three miles of the North Fork were also surveyed. In 

addition to the flow gauges located at Lainhart Dam and Kitching Creek, two additional gauges 

were established on Cypress Creek and Hobe Grove Ditch in November 2002. These four flow 

gauges monitor the majority of freshwater input to the Northwest Fork. Four tide and salinity 

stations have also been deployed in the estuary since November 2002 by the USGS. An additional 

tide/salinity gauge was installed at RM 9.12 in October 2003 by the District’s Water Supply 

Department. These five tide/salinity stations monitor the tide and salinity in the estuary 

continuously and record the data at 15-minute intervals. The data is retrieved at scheduled 

maintenance times and reported quarterly after quality assurance and quality control (QA/QC) has 

been conducted. To detect temperature and salinity stratification, three of the tide/salinity stations 

record salinity and temperature measurements at two water depths. The three sites with double 

temperature/salinity sensors are located at RM 9.12, Boy Scout Camp dock (RM 5.92) and the 

U.S. Coastal Guard Station near the Jupiter Inlet (RM 0.70). All sensors were installed at water 

levels below lower low tides to avoid exposure to air. 

In addition to tide and salinity measurements obtained from the USGS sites, the Loxahatchee 

River District (LRD) also has an estuarine data collection program at several additional locations 

that are not covered by the USGS monitoring network. The LRD uses multi-parameter datasondes 

to record time, dissolved oxygen, water depth, conductivity/salinity, pH, and temperature. The 

meters are located near the bottom of the channel in order to track maximum salinity changes in 

the water column. The LRD data were collected at North Bay seagrass survey site (RM 1.48), 

Pennock Point seagrass survey site (RM 2.44), Northwest Fork near the mouth of Kitching Creek 

(RM 8.13), Station 66 in the Wild and Scenic Loxahatchee River, and Station 69 near the 

 App. 12-1-32 
2006 South Florida Environmental Report Appendix 12-1

Indiantown Road (RM 14.93). To measure current velocity, the LRD contracted Scientific 

Environmental Applications to install two bottom mount Acoustic Doppler Current Profiler 

(ADCP) units at various locations in the estuary in 2003. 

The Loxahatchee hydrodynamic/salinity (RMA) model was verified against field data for the 

period from May 1 to August 12, 2003. Figure 13 shows the combined freshwater inflow from 

four major tributaries to the Northwest Fork for this period. Daily averaged flow rates (cfs) from 

flow gauges on upper Northwest Fork at Lainhart Dam, Cypress Creek, Hobe Grove, and 

Kitching Creek were used for the calculation. Discharge from S-46 into the South Fork was based 

on measurements at the discharge structure for the model simulation period. 

Figure 14 is a comparison of tidal data from the Coast Guard station (RM 0.70) with the 

RMA-2 model output for the same location. Because the two curves overlap each other when 

printed in the same chart, the model output and field data are plotted in separate charts using the 

same scale and grid lines for ease of comparison. For RMA-4 applications, a constant salinity of 

35.5 parts per thousand (ppt) was applied on the ocean boundary.

Figure 13. Freshwater inflow from major tributaries to the Northwest Fork of 

the Loxahatchee River. 

0

100

200

300

400

500

600

5/1/035/8/03

5/15/035/22/035/29/03

6/5/03

6/12/036/19/036/26/03

7/3/03

7/10/037/17/037/24/037/31/03

8/7/03

date

Daily average flow(cfs)

 App. 12-1-33 
Appendix 12-1 Volume I: The South Florida Environment

Tide measurements at Coast Guard station 

-3.5

-2.5

-1.5

-0.5

0.5

1.5

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)

Model output tide at Coast Guard station 

-3.5

-2.5

-1.5

-0.5

0.5

1.5

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)

Figure 14. Tide measurements at the Coast Guard station (RM 0.70): field 

data and RMA model output. 

 App. 12-1-34 
2006 South Florida Environmental Report Appendix 12-1

 Field data and model output of tides at Boy Scout Dock (RM 5.92) and Kitching Creek 

(RM 8.13) are plotted in Figure 15 for comparison. The two stations are approximately 2 river 

miles apart and there is no major tributary between these locations. Both field data and model 

output indicate that the tidal regimens at these two sites are similar in terms of range. 

In order to evaluate the model accuracy more precisely, statistical analysis was also 

conducted. The root mean square error (RMS) and the relative RMS error (RRE) were used to 

evaluate model performance. The RMS is the average of the squared differences between 

observed and predicted values: 

( )

2

1

1 Error

N n n

n

RMS O P

N =

= − ∑ (13) 

where N = number of observed-predicted pairs 

On

 = the value of the nth observed data 

Pn

 = the value of the nth predicted data 

The smaller the RMS is, the better the model output tracks the field observation. A RMS 

error of zero is ideal. 

The relative RMS error (RRE) is defined as the ratio of RMS error to the observed change: 

( )2

1

max min

1

100 100

 Change

N n n

n

O P

RMS Error N RRE

Observed O O

=

−

= × = −

∑

× (14) 

where Omax = maximum value of observations 

Omin = minimum value of observations 

(Omax - Omin) is the range of the observation data and N is the total number of the observation 

records. The relative error provides another measurement of the model performance. A zero 

percentage RRE indicates a perfect match. 

Table 10 lists the RMS and RRE of the model tide output at two sites in the Northwest Fork 

and one site near the model boundary. CG is the station ID for the tide gauge at the Coast Guard 

station. BD and KC are station IDs for tide gauges at the Boy Scout Camp Dock and at the mouth 

of the Kitching Creek, respectively. The mean square errors were less than two inches at all the 

three sites. The relative error was less than 3 percent near the model boundary and less than 

5 percent in the Northwest Fork. 

 App. 12-1-35 
Appendix 12-1 Volume I: The South Florida Environment

Table 10. Statistics of model tide output. 

Station ID No. of Obs. RMS(feet) RRE(%) Obs. Range(feet) 

CG 4983 0.1058 2.71% 3.90 

BD 4423 0.1700 4.78% 3.56 

KC 4423 0.1612 4.40% 3.66 

Table 11 compares the model output and field observations in terms of maximum, minimum, 

and mean values. The difference in mean tide over the entire simulation of a three-month period 

was less than one-tenth of an inch near the model boundary. The difference in mean tide in the 

Northwest Fork was about an inch. 

Table 11. Comparison of model tide output with field observations (unit: feet). 

 Station ID Obs. Max Model Max Obs. Min Model Min Obs. Mean Model Mean 

CG 0.5900 0.6150 -3.3100 -3.2900 -1.3710 -1.3833

BD 0.6300 0.7230 -2.9300 -2.9590 -1.2104 -1.3316

KC 0.6500 0.7740 -3.0100 -2.9370 -1.1982 -1.2900

Figure 16 compares model output of depth-averaged salinity with actual field salinity 

measurements from instruments at fixed elevations However, although these two quantities are 

similar, they do not represent the same physical parameters and are not directly comparable. The 

difference between the model output (representing depth-averaged salinity) and the actual field 

measurement (representing salinity at a fixed depth) could be significant when the system is 

stratified. 

The salinity record at Boy Scout Dock increased to 10 ppt between Day 50 and Day 60. This 

sudden salinity increase does not seem to be related to or supported by data from other field 

records. A salinity of 10 ppt usually occurs at this site when freshwater inflow is below 100 cfs. 

The flow gauges actually recorded over 200 cfs for this period. The salinity record from the 

adjacent Kitching Creek station is also inconsistent with the salinity increase at the Boy Scout 

Dock station. Previous studies indicated that 10 ppt at Boy Scout Dock station would have raised 

salinity at Kitching Creek station to 2 ppt or above (Russell and McPherson, 1984); however, 

there was no salinity increase for Kitching Creek during this time period (see the Kitching Creek 

chart in Figure 16). Therefore, the accuracy of the salinity field measurements at Boy Scout 

Dock between Day 50 and Day 60 is questionable. 

Both RMA-2 and RMA-4 are two-dimensional depth-averaged models. When the system is 

minimally stratified, such as the condition near the Jupiter Inlet at the Coast Guard station, the 

modeled salinity output tracks the field salinity data rather closely. However, when the system is 

highly stratified, as occurs in certain areas, the modeled salinity output for that area could give a 

smaller salinity variation between high tide and low tide when compared to the field salinity 

measurements from fixed depths (see the Boy Scout Dock chart in Figure 16). 

The RMA-4 output is depth-averaged salinity, which differs from salinity measured by a 

transducer at a fixed elevation. The conductivity transducers were installed at elevations that 

would remain below the water surface at low tide. Because the range between higher high and 

lower low water is close to 4 feet and the overall water depth is only about 6 feet to 10 feet, the 

 App. 12-1-36 
2006 South Florida Environmental Report Appendix 12-1

conductivity transducers would be situated in the lower water column during high tide. Under 

these conditions, the instrument would take measurements from the surface layer at low tide and 

from the bottom layer at high tide. If the system is well mixed (i.e., no stratification), then there 

should be no difference between the modeled depth-averaged salinity and field salinity 

measurements. However, when the system is stratified, the daily salinity variation recorded by the 

instruments would be wider than the daily salinity variation output from depth-averaged salinity 

model. 

Table 12 lists the statistics of model salinity output accuracy analysis at Stations Kitching 

Creek, Boy Scout Camp Dock, and the U.S. Coast Guard Station. Table 13 lists the statistical 

characteristics of both model salinity output and the observed values. 

Table 12. Statistics of model salinity output. 

 Station ID No. of Obs. RMS(ppt) RRE(%) Obs. Range(ppt) 

KC 4509 0.6047 6.65% 9.1 

BD 3951 2.5454 10.76% 23.65 

CG 4507 1.8713 9.70% 19.3 

Table 13. Comparison of model salinity output with field observations 

(unit: ppt). 

 Station ID Model Mean Obs. Mean Model Max Obs. Max Model Min Obs. Min 

KC 0.7507 0.5732 4.3670 9.2000 0.1500 0.1000

BD 6.3726 4.6928 19.0380 23.8000 0.2220 0.1500

CG 32.3625 31.9756 35.4250 36.0000 19.5460 16.7000

 App. 12-1-37 
Appendix 12-1 Volume I: The South Florida Environment

 App. 12-1-38 

Tide measurements at Boy Scout Dock 

-3

-2

-1

0

1

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)

Model output tide at Boy Scout Dock 

-3

-2

-1

0

1

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)

Tide measurements near Kitching Creek 

-3

-2

-1

0

1

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)

Model output tide near Kitching Creek 

1

-3

-2

-1

0

0 10 20 30 40 50 60 70 80 90 100

Time (days from May 1, 2003)

WSE (ft-NAVD88)
2006 South Florida Environmental Report 

 App. 12-1-39 

0

102030

10 20 30 40 50 60 70 80 90 

Time (days from May 1, 2003)

Salinity (ppt)

Field measurements at a fixed elevation Depth averaged model output

0

102030

10 20 30 40 50 60 70 80 90 

Time (days from May 1, 2003)

Salinity (ppt)

Field measurements at a fixed elevation Depth averaged model output

10203040

10 20 30 40 50 60 70 80 90 

Time (days from May 1, 2003)

Salinity (ppt)

Field measurements at a fixed elevation Depth averaged model output

Boyscout Dock Station

May 10 - Aug 12, 2003

Kitching Creek Station

May 10 - Aug 12, 2003

Coastguard Dock Station

May 10 - Aug 12, 2003

Figure 16. Model output of depth-averaged salinity and field measurements at fixed elevation

water column. 
Appendix 12-1 Volume I: The South Florida Environment

The most likely reason for the difference between model prediction and field measurements is 

that there is additional freshwater inflow to the system that bypasses the four stations on the river 

and the major tributaries. Such additional sources of fresh water may include overland flow and 

groundwater seepage into the system. A groundwater monitoring network that was established in 

2003 indicates active exchanges between the river and the groundwater table. The model 

predicted higher salinity at the beginning of dry periods when the groundwater tables are still 

relatively high and therefore provide additional fresh water to the system. Including groundwater 

input in the model will likely increase the accuracy in salinity prediction. The current model, 

without the input of groundwater input and overland flow, tends to be conservative (predicting 

higher salinity). 

The current model does not include driving forces such as wind, precipitation/evaporation, 

and the exchange between the river and the groundwater which can be significant in the upper 

river reaches. The model verification simulation, which was only driven by major tributary 

freshwater input and ocean tide, was able to predict the tide regimen rather accurately and predict 

the trend of salinity changes over the three-month simulation period that included both low and 

high freshwater input to the estuary. This seems to indicate that the amount of freshwater inflow 

to the estuary and tide are the two most dominant factors that affect the salinity regimen in the 

upper Northwest Fork. 

RMA MODEL SIMULATION RESULTS – FRESHWATER INFLOW 

AND SALINITY RELATIONSHIP 

The tidal circulation and salinity structure of estuaries involves competition between 

freshwater river flows and ocean influences. River flow persistently adds fresh water to the 

estuary, however saltwater may still penetrate far inland due to gravitational and diffusive fluxes 

(MacCready, 2004). Although there are other factors in addition to tide and freshwater inflows 

that affect the salinity regime, the analysis of the field data from the Loxahatchee River suggested 

that tide and freshwater inflow are the two most important factors that determine the salinity 

conditions in the Northwest Fork (Hu, 2004). To establish the relationship between freshwater 

inflow and salinity in the Northwest Fork of the Loxahatchee River, the RMA model was used in 

12 modeling scenarios where the amount of total freshwater flow from all three forks of the 

Loxahatchee River into the estuary was held constant for rates varying from 40 cfs at the low 

flow end to 7,000 cfs at the high flow end. These flow rates were determined based on an analysis 

of freshwater inflows simulated by the watershed model. During RMA model output processing, 

15 study sites were identified for ecological assessment where salinity predictions are needed. 

Information about study and assessment sites is provided in Table 14. Sites noted as USGS 

stations are locations where tide and salinity measurement data are collected by the U.S. 

Geological Survey as discussed in the previous sections. Figure 17 shows the locations of the 

15 assessment sites. 

 App. 12-1-40 
2006 South Florida Environmental Report Appendix 12-1

Coordinatesa Site 

X (feet) Y (feet) Station ID River Mile 

Description 

955325 951200 CG 0.70 USGS Coast Guard 

951456 952232 SGNB 1.48 Seagrass site - North Bay 

949616 951344 SGSB 1.74 Seagrass site - Sand Bar 

949538 950648 PD 1.77 USGS Pompano Drive 

945680 951761 SGPP 2.44 Seagrass site - Pennock Point 

945105 953335 O1 2.70 Oyster site 1 

942902 954999 O2 3.26 Oyster site 2 

942332 957383 O3 3.74 Oyster site 3 

940923 958927 O4 4.13 Oyster site 4 

938854 961625 O5 4.93 Oyster site 5 

936681 963169 O6 5.45 Oyster site 6 

935708 965258 BD 5.92 USGS Boy Scout Dock 

934679 966363 VT9 7.06 Vegetation Transect 9 

931399 966948 KC 8.13 USGS Kitching Creek 

929733 964696 RM9 9.12 USGS RM 9.1; Vegetation 

Transect 7 

a State Plane Florida East NAD83.

Table 14. Salinity and ecological assessment sites. 

 App. 12-1-41 
Appendix 12-1 Volume I: The South Florida Environment

Figure 17. Location of salinity and ecological assessment sites. Red dots 

represent USGS sites; blue dots represent seagrass sites; purple dots 

represent oyster sites; and green dots represent vegetation sites. 

 App. 12-1-42 
2006 South Florida Environmental Report Appendix 12-1

 The objective of the RMA model application is to establish a relationship between the amount 

of freshwater inflow and tidally averaged salinity. The RMA model output was averaged over a 

lunar month that includes a full lunar tidal cycle with both spring and neap tides. Thus, these 

results reflect the daily averaged salinity under an average tidal condition. 

Table 15 is a summary of the RMA model output of average salinity for 12 flow scenarios at 

each of the 15 sites. Regression analysis of the results yielded regression equations with excellent 

curve fitting. The best fit (R2

 = 0.999 for all the 15 sites) was achieved with exponential functions 

in the form of 

Y = Y0 + a e-bX [15] 

where X is freshwater inflow in cubic feet per second and Y is salinity in parts per thousand. Y0, 

a, and b are regression parameters that are listed in Table 10 for each of the 15 sites. 

Table 15. Tidally averaged salinity (ppt) versus freshwater inflow (cfs) for the 

15 study sites in the Loxahatchee River. 

 App. 12-1-43 
Appendix 12-1 Volume I: The South Florida Environment

 The freshwater flow versus salinity relationships tabulated in Table 15 are plotted in 

Figures 18 and 19. Each curve in Figure 18 represents the flow/salinity relationship for each of 

the 15 sites. For each site, salinity increases as freshwater inflow decreases. 

0

5

10

15

20

25

30

35

0 100 200 300 400 500 600 700 800

Total freshwater inflow to the Northwest Fork in cfs

Salinity in parts per thousand

CG

SGNB

SGSB

PD

SGPP

O1

O2

O3

O4

O5

O6

BD

VT9

KC

RM9

Station ID

Figure 18. The relationship between freshwater inflow and salinity at the 

15 study sites.

 App. 12-1-44 
2006 South Florida Environmental Report Appendix 12-1

 In order to show the details of salinity variation at low flow end, the charts were plotted only 

for inflows up to 800 cfs. For salinity regimens with freshwater inflows greater than 1,200 cfs, 

either Table 15 or Equation [15] can be used to determine the salinity value. The curves in 

Figure 19 represent the salinity gradients at various levels of freshwater inflow. Each line 

represents the spatial salinity distribution for a particular inflow scenario. 

0

5

10

15

20

25

30

35

40

01234 56789 10

Distance from Jupiter Inlet in River Miles

Salinity in parts per thousand

32

56

79

119

159

238

397

636

954

1908

3815

5564

Freshwater

flow to NWF

in cfs

Figure 19. Salinity gradients for various freshwater inflow conditions.

Although Equation [15] expresses salinity as a single dependent variable function, there are 

other driving forces that affect salinity including tide, wind, flux between river and groundwater, 

precipitation, and evaporation. However, the analysis of field data indicated that freshwater

inflow is the most important factor affecting salinity. When salinity is plotted against freshwater 

flow, the data points form a clear trend line. Comparing results from Equation [15] with actual

field data provides a reality check. Figures 20 through 23 compare the model results from 

Equation [15] with actual field measurements. As expected, deviations from the modeled

flow/salinity curve indicate the existence of other driving forces that affect salinity. Nonetheless, 

the correlation between salinity and freshwater inflow is significant. Another factor that could 

cause deviations is that the system is under constant transition in response to the changes in the

driving forces. Therefore, it is rare for the system to reach equilibrium as the case in the constant 

flow simulations. The overall trend of the field measurements shows a strong correlation between

the amount of freshwater inflow and salinity throughout the estuary. 

 App. 12-1-45 
Appendix 12-1 Volume I: The South Florida Environment

Salinity at River Mile 9.1 vs. Discharge to Northwest Fork

Observation period: October 15, 2003 - April 14, 2004

0

2

4

6

8

10

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500

Freshwater from 4 tributaries to the Northwest Fork in cfs

Salinity in ppt .

70 cfs

Figure 20. The effects of freshwater inflow on salinity at RM 9.1 

from October 15, 2003–April 14, 2004.

Salinity at Kitching Creek Confluence vs. Discharge to Northwest Fork

Observation period: December 11, 2002 - April 14, 2004

0

2

4

6

8

10

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400 420 440 460 480 500

Freshwater from 4 tributaries to the Northwest Fork in cfs

Salinity in ppt .

130 cfs

Figure 21. The effects of freshwater inflow on salinity at RM 9.1 

from October 15, 2003–April 14, 2004.

 App. 12-1-46 
2006 South Florida Environmental Report Appendix 12-1

Salinity at Boy Scout Camp Dock vs. Discharge to Northwest Fork

Observation period: December 11, 2002 - April 14, 2004

0

5

10

15

20

25

0 50 100 150 200 250 300 350 400 450 500 550 600

Freshwater from 4 tributaries to the Northwest Fork in cfs

Salinity in ppt .

400 cfs

Figure 22. The effects of freshwater inflow on salinity at Boy Scout Dock from

December 11, 2002–April 14, 2004.

Figure 23. The effects of freshwater inflow on salinity at Embayment from 

November 24, 2002–April 14, 2004.

Salinity at Pampano Drive near Sand Bar seagrass site vs. discharge 

from all major tributaries and canals

Observation period: November 24, 2002 - April 14, 2004

0

5

10

15

20

25

30

35

40

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Freshwater from all tributaries and canal in cfs

Salinity in ppt .

 App. 12-1-47 
Appendix 12-1 Volume I: The South Florida Environment

 Freshwater inflows to the Northwest Fork from the four major tributaries, several small 

tributaries, and overland flow were modeled. If the inflows from all the tributaries were 

considered individually, they would form a large array of scenarios. The analysis of the field data 

indicates that there is a good correlation between salinity at various sites with the total freshwater 

flow volume to the Northwest Fork. The physical explanation for this correlation is the strong 

tidal mixing in the Northwest Fork. For example, when the tide rises, freshwater inflows from 

Kitching Creek will be pushed upstream into the river reaches above the mouth of Kitching Creek 

and thus influence the salinity there. It is the total volume of fresh water entering the Northwest 

Fork that matters the most for the reaches between RM 6 and RM 9. The origin of fresh water 

(whether the fresh water was from Kitching Creek or some other tributary) does not seem to be an 

important factor in the current analysis. Such a finding has two implications: 

1. Freshwater from all the tributaries affects the salinity in the Northwest Fork. Therefore, any 

increase of freshwater discharge from any combination of tributaries will help achieve the 

salinity management goal of the Northwest Fork between RM 6 and RM 9. In addition to 

increasing freshwater flows from the G-92, flows from other tributaries and basins such as 

Cypress Creek/Pal Mar, and Kitching Creek should also be fully utilized. 

2. Salinity predictions in the Northwest Fork between RM 6 and RM 9 can be based on total 

freshwater inflow to the Northwest Fork instead of freshwater inflow from each individual 

tributary. Such an approach will allow the testing of more restoration scenarios with limited 

resources. This capability is especially critical in the initial alternative assessment phase of 

the restoration plan since numerous scenarios need to be analyzed. When the total amount of 

freshwater demand is determined, the analysis can then evolve into the next phase, that is, to 

consider the freshwater contribution from each tributary individually to meet the Northwest 

Fork freshwater demand. At that phase, a model with more refined spatial resolution, such as 

the RMA model that was described in the previous sections, can be used for scenarios where 

tributaries are simulated separately from each other. 

The salinity value predicted by Equation [11] is tidally averaged salinity over a lunar tidal 

cycle. The actual salinity in the river constantly varies in response to tides. If the hourly salinity 

variation over each tidal cycle needs to be considered, then the information is available from the 

original model output. 

Figure 24 is the model output of salinity at the Pennock Point seagrass transect in a lunar 

month. The graphs are the output under three freshwater inflow conditions. Total freshwater 

inflows of the three simulations are 500 cfs, 800 cfs, and 1,200 cfs. The amount of freshwater 

inflow affects both the overall salinity level and the range of salinity variation (the difference of 

salinity between high tide and low tide). 

Figure 24 represents the salinity predictions for only one site under three flow conditions. 

The model simulation output included salinity for 15 sites under 12 different inflow conditions; 

thus 180 sets of time-series data were produced. 

 App. 12-1-48 
2006 South Florida Environmental Report Appendix 12-1

SGPP500

5

10

15

20

25

30

35

0 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

days of a lunar month

Figure 24 represents one example from a large array of charts in the model output that cover 

a wide range of freshwater flow. The salinity conditions represented by 500, 800, and 1,200 cfs 

are relatively high flows that begin to affect salinity conditions at the Pennock Point seagrass site 

(RM 2.44). 

The RMA was applied to scenarios with varying amounts of freshwater inflow. Both the field 

data and model simulation indicated that there is a strong correlation between freshwater inflow 

and the salinity regimen in the estuary. Based on model output and field data analysis, a 

relationship was established to predict salinity at various points in the estuary with respect to 

freshwater inflow rates and tidal fluctuations. The salinity/freshwater relationship was applied in 

the Loxahatchee River MFL study (SFWMD, 2002a). The RMA model was also used to provide 

a preliminary assessment of the impacts that inlet deepening and sea level rise have had on the 

salinity regime in the estuary (Hu, 2002). salinity in ppt .

SGPP800

5

10

15

20

25

30

35

0 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

days of a lunar month

t . pp ity in salin

SGPP1200

5

10

15

20

25

30

35

0 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

days of a lunar month

. ppt in salinity

Figure 24. Salinity at Pennock Point seagrass transect in a lunar month; total 

freshwater inflow to the Loxahatchee River: 500, 800, and 1,200 cfs. 

 App. 12-1-49 
Appendix 12-1 Volume I: The South Florida Environment

LONG-TERM SALINITY MANAGEMENT MODEL 

The freshwater/salinity relationship described in the previous section was coded into the 

Loxahatchee Estuary Long-Term Salinity Management Model (LSMM) to predict tidally 

averaged salinity in response to various restoration scenarios. This model can also simulate 

system operation rules and calculate the amount of freshwater demand for salinity management. 

The salinity values in Table 15 are based on an equilibrium state with constant freshwater 

inflows. In the applications of the freshwater input versus salinity relationships, the dynamic 

nature of the system needs to be considered. Under natural conditions, freshwater inflow is rarely 

constant. The salinity conditions observed in the estuary are the result of a series of transitions 

from one state to the next. The changes in salinity lag behind the changes in freshwater inflow. 

Following an increase of freshwater inflow, salinity in the estuary will decrease accordingly and 

gradually approach a new equilibrium state. As the amount of freshwater decreases, the salinity in 

the estuary will increase gradually. Depending on the direction of salinity changes, the process 

can be described as an exponential increase or decay. Figure 25 is a graphic description of 

salinity transition when an increase of freshwater inflow occurs. The dotted line indicates the 

equilibrium salinity at the higher level of freshwater inflow. 

0

5

10

15

20

0 5 10 15

t (days)

Salinity(ppt)

Figure 25. Salinity regimen transition process.

The salinity condition within the estuary consists of a series of transitions from one 

quasi-equilibrium condition to another. This concept was reflected in the LSMM program. The 

program calculates the potential target (equilibrium) salinity based on the amount of freshwater 

inflow. It then calculates the salinity change on daily time steps using the following equation: 

SAL2 = SALEQ + (SAL1-SALEQ)*Exp(-cT) [16] 

where SAL1 is the salinity at the beginning of the time step, SAL2 is the salinity at the end of the 

time step, SALEQ is the equilibrium salinity for certain amount of freshwater inflow after the 

transition has completed. T is time and c is a constant that determines the speed of transition. 

Apparently at the beginning of the time step (T=0), SAL2 = SAL1 and if the freshwater inflow 

remains the same, SAL2 will eventually reach SALEQ. 

 App. 12-1-50 
2006 South Florida Environmental Report Appendix 12-1

Because the freshwater inflow is provided by the watershed model in daily time steps, the 

calculation of the Long-Term Salinity Management Model is carried at fixed time steps of 24 

hours. The predicted salinity depends on both target (equilibrium) salinity and the initial salinity 

condition at the beginning of the time step. If the amount of freshwater inflow changes before the 

transition is completed, then a new transition begins and the program repeats the same 

computational procedure under the new flow condition. 

The LSMM is designed to assess daily average salinity over a long period of time. Because 

the program operates on daily time steps (versus minutes or seconds of a full hydrodynamic 

model), it allows the assessment of long-term data (39 years in this model simulation) at 

minimum cost and computing time. In addition to using hydrologic data provided by the WaSh 

model, the LSMM can also modify the hydrograph based on certain operational rules such as 

MFL criteria. The model also calculates the amount of freshwater demand for salinity 

management and nutrient loadings assuming a target concentration for inflows. 

Figures 26 through 29 depict the salinity calculations of the LSMM. The output was 

compared with real data from four salinity stations in the Northwest Fork and the embayment 

area near the Jupiter Inlet. Table 16 lists the statistical characteristics of both model prediction 

and field data. Statistics of the entire period of 517 days shows that the mean salinity of model 

output is slightly higher than field data at the four stations by 0.1 to 0.6 ppt. This is probably 

because the flow gauges on the Northwest Fork and major tributaries did not control 100 percent 

of the fresh water entering the system. Tables 17 and 18 list the statistics of model prediction and 

field data for two relatively dry periods (March through May) and the rest of the year, 

respectively. In general, the simulated daily salinity matches well with the observed salinities 

statistically. 

Station Name PD BD KC RM9 

Date Type Model Field Model Field Model Field Model Field 

Maximum 34.7 35.5 21.8 20.2 7.6 7.6 2.9 4.4 

Minimum 25.0 22.4 1.1 0.2 0.1 0.1 0.0 0.1 

Mean Value 32.1 31.8 11.1 9.7 2.1 1.5 0.6 0.5 

Median Value 33.1 32.4 12.5 10.1 1.8 0.7 0.4 0.3 

Standard Deviation 2.40 2.50 6.22 5.49 1.94 1.71 0.62 0.58 

Data Count 517 477 517 502 517 506 517 199 

Number of Missing 

Records 0 40 0 15 0 11 0 318 

Table 16. Comparison of statistical characteristics of model and field data. 

 App. 12-1-51 
Appendix 12-1 Volume I: The South Florida Environment

Table 17. Comparison of statistical characteristics of model and field data – 

March through May. 

Station Name PD BD KC RM9 

Date Type Model Field Model Field Model Field Model Field 

Maximum 34.7 35.5 21.8 20.2 7.6 7.6 2.9 4.4 

Minimum 26.2 30.1 3.4 0.3 0.5 0.2 0.2 0.3 

Mean Value 33.5 33.7 15.9 12.3 3.6 2.5 1.0 1.0 

Median Value 33.8 33.9 15.9 13.1 3.1 1.7 0.7 0.5 

Standard Deviation 1.40 1.19 3.98 4.97 2.04 2.08 0.78 0.87 

Data Count 153 117 153 150 153 153 153 61 

Number of Missing 

Records 0 36 0 3 0 0 0 92 

Table 18. Comparison of statistical characteristics of model and field data – 

June through February. 

Station Name PD BD KC RM9 

Date Type Model Field Model Field Model Field Model Field 

Maximum 34.5 35.1 20.3 19.6 6.0 6.9 2.0 0.8 

Minimum 25.0 22.4 1.1 0.2 0.1 0.1 0.0 0.1 

Mean Value 31.5 31.1 9.1 8.6 1.5 1.1 0.4 0.3 

Median Value 32.2 31.7 7.9 8.6 0.7 0.3 0.2 0.3 

Standard Deviation 2.48 2.48 5.90 5.34 1.52 1.32 0.41 0.10 

Data Count 364 360 364 352 364 353 364 138 

Number of Missing 

Records 0 4 0 12 0 11 0 226 

 App. 12-1-52 
2006 South Florida Environmental Report Appendix 12-1

Salinity at River Mile 9.1, Northwest Fork Loxahatchee River

0

5

10

15

20

25

30

35

12/1/2003 1/1/2004 2/1/2004 3/3/2004 4/3/2004

Date

Salinity in ppt.

RM9 RM9SA-Measurements.

Figure 26. Field measurements versus salinity computation results 

for RM 9.12. 

Figure 27. Field measurements versus salinity computation results for 

Kitching Creek (RM 8.13). 

Salinity at Kitching Creek, Northwest Fork Loxahatchee River

0

5

10

15

20

25

30

35

12/1/2002

1/1/2003

2/1/2003

3/4/2003

4/4/2003

5/5/2003

6/5/2003

7/6/2003

8/6/2003

9/6/2003

10/7/2003

11/7/2003

12/8/2003

1/8/2004

2/8/2004

3/10/2004

4/10/2004

Date

Salinity in ppt.

KC KCSA-Measurements.

 App. 12-1-53 
Appendix 12-1 Volume I: The South Florida Environment

Salinity at Boy Scout Camp, Northwest Fork Loxahatchee River

0

5

10

15

20

25

30

35

12/1/02

1/1/03

2/1/03

3/4/03

4/4/03

5/5/03

6/5/03

7/6/03

8/6/03

9/6/03

10/7/03

11/7/03

12/8/03

1/8/04

2/8/04

3/10/04

4/10/04

Date

Salinity in ppt.

BD BDSA-Measurements.

Figure 28. Field measurements versus salinity computation results 

for Boy Scout Dock (RM 5.92). 

Figure 29. Field measurements versus salinity computation results 

for Pompano Drive Embayment Area (RM 1.77). 

Salinity near Sandbar Seagrass Transect, Loxahatchee River

0

5

10

15

20

25

30

35

40

12/1/02

1/1/03

2/1/03

3/4/03

4/4/03

5/5/03

6/5/03

7/6/03

8/6/03

9/6/03

10/7/03

11/7/03

12/8/03

1/8/04

2/8/04

3/10/04

4/10/04

Date

Salinity in ppt.

PD PDSA-Measurements.

 App. 12-1-54 
2006 South Florida Environmental Report Appendix 12-1

MODELING THE NORTHWEST FORK ECOSYSTEM 

RESTORATION SCENARIOS 

The modeling results of the Loxahatchee WaSh model for the POR from 1965–2003 were 

used to establish the base project condition for scenario evaluation of Northwest Fork ecosystem 

restoration. The BASE simulation represents the existing or current conditions with no 

modifications. Five additional simulations were conducted with certain modifications to the 

BASE simulation hydrographs. The modifications represent scenarios that provide additional 

freshwater flows to upper Northwest Fork at Lainhart Dam and tributaries (Cypress Creek, Hobe 

Grove, and Kitching Creek) to reduce salinity in the freshwater segments of the Northwest Fork. 

The five restoration flow scenarios were designed to represent different levels of flows from a 

tributary or a combination of tributaries to the Northwest Fork. The scenarios were selected based 

on information provided by members of the public and agency representatives at meetings held to 

discuss the restoration of the Northwest Fork. For example, a flow of 65 cfs had been used as a 

flow target in the model for the development of the Northern Palm Beach County Comprehensive 

Water Management Plan (SFWMD, 2002b). Table 20 summarizes the flow component(s) of each 

scenario. The LSMM was then used to predict daily salinity under the five scenario conditions at 

15 locations (Figure 18). The simulated flow and salinity results were used to evaluate the 

ecological benefit with respect to each of the ecological components in the Northwest Fork. 

Table 21 presents the salinity gradient of each scenario for the 15 study sites. Salinity ranges 

from near ocean conditions at the U.S. Coast Guard Station (RM 0.70; CG) near Jupiter Inlet to 

freshwater conditions at RM 9.12 in the Northwest Fork of the Loxahatchee River. The five 

scenarios that increase freshwater flows also lower the salinity throughout the river and the 

estuary. It is important to point out that the salinity condition in the Northwest Fork is extremely 

sensitive to the amount of freshwater inflow. A small change in freshwater flow of less than 

10 cfs can cause changes in salinity as high as several ppt in the upper Northwest Fork. Table 21 

only provides the average salinity for each site. Ecological evaluation of these scenarios is based 

on an analysis of daily salinity for the POR. Figure 30 is the graphic presentation of the model 

results in Table 16. The plots shows the average salinity gradients under base condition and each 

scenario that was modeled. 

 App. 12-1-55 
Appendix 12-1 Volume I: The South Florida Environment

Scenario Base Condition 

Hydrograph 

Added Flows 

From Lainhart 

Dam 

Added Flows 

From 

Tributaries 

Total Added 

Flows 

Approximate 

2 ppt Saltwater 

Front Position 

Base 

1965-2003 base 

condition 

generated by 

watershed model 

No additional 

flows 

No additional 

flows 

No additional 

flows from 

Lainhart Dam or 

tributaries 

RM 9.5 

LD65 

1965-2003 base 

condition 

generated by 

watershed model 

Water added as 

needed so flow 

is a minimum of 

65 cfs at all 

times 

No additional 

flows 

Additional flows 

only from Lainhart 

Dam for a 

minimum of 

65 cfs; No 

additional flows 

from tributaries 

RM 8.5 

LD65TB65 

1965-2003 base 

condition 

generated by 

watershed model 

Water added as 

needed so flow 

is a minimum of 

65 cfs at all 

times 

Water added 

as needed so 

flow is a 

minimum of 

65 cfs at all 

times 

Additional flows 

from Lainhart 

Dam and 

tributaries. Total 

flow is a minimum 

of 130 cfs at all 

times. 

RM 8.0 

LD90TB110 

1965-2003 base 

condition 

generated by 

watershed model 

Water added as 

needed so flow 

is a minimum of 

90 cfs at all 

times 

Water added 

as needed so 

flow is a 

minimum of 

110 cfs at all 

times 

Additional flows 

from Lainhart 

Dam and 

tributaries. Total 

flow is a minimum 

of 200 cfs at all 

times 

RM 7.5 

LD200 

1965-2003 base 

condition 

generated by 

watershed model 

Water added as 

needed so flow 

is a minimum of 

200 cfs at all 

times 

No additional 

flows 

Additional flows 

only from Lainhart 

Dam for a 

minimum of 

200 cfs; No 

additional flows 

from tributaries 

RM 7.0 

LD200TB200 

1965-2003 base 

condition 

generated by 

watershed model 

Water added as 

needed so flow 

is a minimum of 

200 cfs at all 

times 

Water added 

as needed so 

flow is a 

minimum of 

200 cfs at all 

times 

Additional flows 

from Lainhart 

Dam and 

tributaries. Total 

flow is a minimum 

of 400 cfs at all 

times 

RM 6.0 

Table 20. Long-Term Salinity Management Model simulation of restoration 

scenarios. 

 App. 12-1-56 
2006 South Florida Environmental Report Appendix 12-1

0

5

10

15

20

25

30

35

0 2 4 6 8 10

River Mile

Salinity in ppt 

BASE

LD65

LD65TB65

LD90TB110

LD200

LD200TB200

Figure 30. Salinity gradient under base condition and five flow scenarios. 

Table 21. Average salinity (ppt) at 15 study sites over the 39-year simulation 

period. 

Salinity Study Site Restoration Scenarios 

Site ID River Mile BASE LD65 LD65TB65 LD90TB110 LD200 LD200TB200 

CG 0.70 33.0 32.8 32.6 32.2 31.8 30.7 

SGNB 1.48 32.0 31.6 31.3 30.4 29.6 27.6 

SGSB 1.74 31.3 30.8 30.3 29.3 28.4 26.0 

PD 1.77 31.2 30.6 30.2 29.2 28.3 25.8 

SGPP 2.44 29.2 28.5 27.9 26.5 25.2 22.0 

O1 2.70 26.9 26.1 25.4 23.7 22.3 18.7 

O2 3.26 24.6 23.5 22.5 20.4 18.7 14.5 

O3 3.74 22.5 21.0 19.9 17.4 15.5 11.0 

O4 4.13 21.0 19.4 18.1 15.4 13.4 8.9 

O5 4.93 16.2 13.9 12.2 9.1 7.2 3.5 

O6 5.45 13.5 10.7 8.9 5.9 4.3 1.6 

BD 5.92 10.9 7.9 6.2 3.7 2.5 0.7 

VT9 7.06 5.8 3.0 1.8 0.7 0.4 0.2 

KC 8.13 2.7 0.8 0.4 0.2 0.1 0.1 

RM9 9.12 1.0 0.2 0.1 0.1 0.1 0.1 

 App. 12-1-57 
Appendix 12-1 Volume I: The South Florida Environment

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Report submitted to South Florida Water Management District, West Palm Beach, FL. 

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District, West Palm Beach, FL. 

ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models of the 

Watershed Management Committee, Irrigation and Drainage Division. 1993. Criteria for 

Evaluation of Watershed Models. Journal of Irrigation and Drainage Engineering, 119(3): 

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Donigian, A.S., J.C. Imoff, B.R. Bicknell and J.L. Kittle. 1984. Application Guide for 

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Environmental Protection Agency, Athens, GA. 

FDEP. 1998. Loxahatchee River Watershed Action Plan. Second Draft. Florida Department of 

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Hu, G. 2004. Modeling Study of Saltwater Intrusion in Loxahatchee River, Florida. In: 

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Hu, G. 2002. The Effects of Freshwater Inflow, Inlet Conveyance and Sea Level Rise on the 

Salinity Regime in the Loxahatchee Estuary. Proceedings of 2002 Environmental 

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July 21-24, 2002. 

MacCready, P. 2004. Toward a Unified Theory of Tidally-Averaged Estuarine Salinity Structure. 

Estuaries, 27(4): 561-570. 

Russell, G.M. and B.F. McPherson. 1984. Freshwater Runoff and Salinity Distribution in the 

Loxahatchee Estuary, Southeastern Florida, 1980-82. USGS Water Resources Investigation 

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