2006 South Florida Environmental Report Appendix 12-1



# Appendix 12-1: Modeling Freshwater Inflows and Salinity in the Loxahatchee River and Estuary

Yongshan Wan an d Gordon Hu



## SUMMARY This appendix describes the hydrol ogic and salinity models applied in the Northwest Fork of the Loxahatchee River Restoration Plan. Th e 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 (Hyd rologic Simulation Program – Fortran) into a cell-based system with the addition of a groundw ater 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 ta bles and dense drainage canal networks. Using long-term flow data collected at S-46, Lainha rt Dam, Cypress Creek, Hobe Grove Ditch, and Kitching Creek, the WaSh mode l was calibrated and validated. The daily flow outputs from the 39-year simulation (1965–2003) provide the basi s 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 cond itions 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 sin ce 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 sa linity, a Long-Term Salinity Management Model (LSMM) was developed to predict salinity and calculate several other performance parameters under various ecosystem restoration scenarios. Fiel d data, regression analyses, and results from multidimensional hydrodynamic computer models were integrated into the LSMM as a system simulation and management tool. This salinity ma nagement 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 natu ral hydrologic regime of the Loxahatchee River watershed has been altered by drainage activ ities associated with urban and agricultural development. Historically, most of the waters hed was drained by the Northwest Fork of the Loxahatchee River. Today, much of the waters hed has been impacted by the construction of canals and levees for drainage and opening of th e Jupiter Inlet. These anthropogenic alterations

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### 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 predic ting 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 Flor ida Water Management District (SFWMD or District) has initiated several projects for data co llection and model devel opment. To date, three models have been developed to simulate fr eshwater 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 fro m 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 sa linity conditions within the Loxahatchee River and Estuary, and a Long-Term Sa linity Management Model (LSMM) that predicts daily salinity conditions according to freshwater inflows fro m 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. 12-1-22006 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 ke y assessment locations was simulated with the LSMM. An integrated ecological assessment was carri ed out to evaluate the ecological benefits with respect to the health of freshwater floodpl ain vegetation, oysters, and seagrasses in response to these flow scenarios. Such an assessment is cr itical in selecting restoration alternatives to achieve the comprehensive ecologic benefit of a ll the ecologic components in the entire system. The purpose of this appendix is to document th e calibration and validation results of these models and to provide a description of how these models ar e used in the evaluation of the Northwest Fork restoration alternatives.

Figure 2. The relationship among the th ree models used to evaluate restoration plan scenarios for the ec osystems in the Loxahatchee River watershed.Appendix 12-1 Volume I: The South Florida Environment



### Table 1 lists the time steps and the length of simu lations 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 hy drodynamic 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 th e 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, Do nigian et al., 1984) into a cell-based system with the addition of a groundwater model and a fu ll dynamic channel routing model (Wan et al., 2003). The WaSh model is capable of simulating h ydrology 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 transf ers 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 gr oundwater, evaporates in to the atmosphere, or drains to the surface water system. Curren tly, 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 wate rshed. The groundwater model receives the infiltrated water, exchanges groundwater between cells, and also exchanges water between surface water flow and groundwater flow. The su rface water drainage system consists of a cell-based system and a reach-based system. The r each-based system is typically configured to

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### follow the major canals, streams, and rivers a nd supports branches and common flow structures. The water quality component of WaSh is built on the surface water, gr oundwater, 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 Ar cView extension. The GUI handles file management (both on the local platform and on the server), model configur ation, execution, and post processing. The WaSh model also supports numerous water manageme nt practices such as irrigation, reservoirs, Stormwater Treatment Areas (STAs), and land u se 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 represen tative ground slope. Hydr ological parameters relating runoff, infiltration, and evaporation are specific to these attributes, particularly land use types. If tertiary canals are present in the cell, th en 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 Syst em (GIS) coverage for each of the physical characteristics. For the purpose of routing the si mulated daily runoff from each cell, a special cell attribute is assigned to indicate where runoff from th at cell is directed. Each cell is labeled as one of three primary types: (1) free cell, (2) canal ce ll, 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 wate r 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.

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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 Grou ndwater 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 enhancem ents 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 runo ff, and infiltration to groundwater. At the end of each one-day simulation period, the accumulated su rface 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 a quifer. The model operates on a daily time step, during which it receives infiltrated water, loses wa ter to evaporation, and exchanges water with adjacent cells and with canals. The basic gove rning equation for the groundwater module is:

rcei cy cx 

### SSSS y h hhK yx h hhK xt h ++−+ ∂ ∂

− ∂ ∂ + ∂ ∂

− ∂ ∂

= ∂ ∂ )( )( ρ [1]

where h is the groundwater elevation, ρ is the porosity, K x 

### and K y 

### are the hydraulic conductivity in the x -, and y - directions, h c 

### is the aquifer base elevation, and S i 

### , S e 

### , S c 

### , and S r 

### are source/sink terms representing infiltration, evaporation, exch anges 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 u sed 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 th e equation parameters and water elevation h for each

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### cell by the indexes i,j 

### , and the time level by the index m 

### , the resulting finite difference equation for each cell is:

m ji r S m ji c S m ji e S m ji i S y m

ji h m ji h

y c h m ji h m ji h

y m ji h m ji h

y c h m ji h m ji h

Ky x m ji h m ji h

x c h m ji h m ji h

x m ji h m ji h

x c h m ji h m ji h

x K t m ji h m ji 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 Δ t is the time step (one day), and Δ x

and Δ y 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 elev ation is found by solving for ji , 

### . 

### h m 1 +

S S 

### When an active cell is adjacent to the grid boundary or to an in active 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 H SPF 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 paramete r 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 pr ovides a process-based a pproach 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 c

m
c ji 

### Δ

=

, 

### [3]

A CH S r

m r ji Δ

=

, 

### [4]

where 

### H Δ 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 C c 

### and C r 

### 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.

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### 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 lowe r soil zones and generating a demand for water based on the existing moisture relative to the desire d moisture level that is specified by the user. After the irrigation demand is calculated, the al gorithm 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 h i,j 

### is adjusted according to the following equation:



### ρ /

,, V ji h ji h Δ + = [5]

where Δ V is the volume (expressed as depth) of grou ndwater 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 ex change between the storage zones and the groundwater. The groundwater elevation is updated with Equation [5], where Δ V 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 ch annels 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) overl ay 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 re presented 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 sy stems is modeled using the con tinuity equation, Equation [6], and the depth- and width-averaged shallow wa ter wave equation, Equation [7]. The governing equations are:



### e Q s q
t wh + ∂ ∂

= ∂ ∂ [6]

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### 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 τ b 

### 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 conditi ons 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 equa tions 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]



### T

T



### he source term Q e 

### in the continuity equation, Equation [6], consists of point sources or sinks, exchange with groundwat er, 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:

gwr ki kp e 

### QQQQ

, 

### + + = 

### [8]

where Q kp 

### are external sources or sinks (user-specified time series), Q r,gw 

### is the exchange with the groundwater and is equal to S r 

### , the exchange calculated in the groundwater model, Equation [1], and Q ki 

### is the exchange with the canal cells where the tertiary canals are connected with the reach. When the reach-based system cont ains branches, the flow in each branch is determined independently. The method for estimating the fl ow between branches depends on whether the flow is natural at the connection or whether a stru cture exists. When a structure is present at the branch connections, the flow is de termined 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 r each node system. When a structure is present, the flow at that node is determined at the begi nning 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, Equati on [6]. The two equations are solved explicitly for the flow between branches using the two reach es 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., th e tertiary canals) is represented in the WaSh model using the same governing equatio ns and numerical scheme as used for the reach-based system. To implement this appro ach, 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 w c 

### , the average canal bottom elevation, a nd a critical or ‘design’ water depth.

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### These parameters are attributes of the cell. They can be obtained by mapping GIS hydrologic data onto the basin grid and then specifying widths, bo ttom elevations, and critical depths based on the cell land use. The surface water elevation is the depe ndent 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: c 

### wwandLs = = Δ , [9]



### LC

L wwandLCs

c 

### * , = =Δ [10]

After the cell-based canal parameters are transf ormed into reach parameters, the connectivity of the branch network is determined. The connectiv ity 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 ca nal 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 canal s 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 estim ated) drainage capacities for the canal systems associated with each land use. The drainage cap acities 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 with in northern Palm Beach and southern Martin counties and currently drains an area of approxima tely 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 wate rshed. 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 aeria l 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 th e 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 ).

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

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### The 1995 land use for these basins has been modifi ed to include changes in the developed areas for the year 2000. For purposes of this plan, the 133 land use codes were re duced 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 basi n for the Loxahatchee River watershed.

Table 4. Loxahatchee River watershed 1995 la nd 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 contribut e 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 some times exceed the ri ver’s carrying capacity on weekends and

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### 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 th e largest basin in the Loxahatchee River watershed. Much of the land in this b asin 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 hist orically fed the Northwest Fork of the Loxahatchee River. Historically, the Loxahatch ee 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 dischar ged 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 disch arges 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 wate rshed 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. A pproximately 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 altere d to support agriculture, wildlife utilization is relatively good, and the land provides a valuab le 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 altere d to support agriculture, wildlife utilization is relatively good, and the land provides a valuab le 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 ba sin supports substantia l 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 c oncerns 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. 12-1-13Appendix 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 i s 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 a nd out the Jupiter Inlet. This basin has been developed for maximum urban residential, commerc ial, 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 basi n has several outflow loca tions, 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 Gaug e, Park River, and the Loxahatchee Estuary basins. The Pal-Mar and Grove region (B) includ es the Pal-Mar, Historic Cypress Creek, Grove West, and Grove East basins. The Jupiter Farm s 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 mode l 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 b ase land use coverage, so il coverage, and land surface elevation. The land surf ace 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 availabl e, 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 basi ns, the hydrography theme is overlaid on the grid and those grid cells intersecting with poly lines of the hydrography theme are classified as canal cells. The canal length in a grid cell is ca lculated 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 nod es 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. 12-1-142006 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 ce lls are color coded turquoise, light green, and pink, respectively. In Regi on A, the blue line represents the model boundary, and the nodes repr esent 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 consisti ng of HSPF parameters, evapotranspiration (ET) coefficients, canal parame ters, 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 Wa ter Management Model (SFWMM) for the period from 1965–2000. The dataset was extended to Marc h 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 availa ble hourly rainfall distribution in South Florida.

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



### Model Calibration and Validation
The Loxahatchee WaSh model has been calibra ted 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 1 990, and thus only the data coll ected after 1990 are used for calibration and validation of the JDSP model. Th e Hobe Grove and the Cypress Creek stations have been collecting data since 1980; however, th ere 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 calibrati on and validation. In add ition, 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 dominat ed by wetland while M-1234 resides in a forest land of the Cypress Creek basin.

Kitching Creek Station

S-46 Station Lainhart Dam 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. 12-1-162006 South Florida Environmental Report Appendix 12-1



### Model calibration invo lves 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 adju st 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 E ast basins, which consist mostly of irrigated citrus groves. Citrus irrigation significantly in creases 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. 12-1-17Appendix 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, a nd 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 runo ff and decreases infiltration. The model validation process is similar to the calibration pro cess, except that a different POR is used for the relevant input data. The model parameters are kept constant. Model va lidation is considered complete if the simulation meets the performance criteria. Otherwise, the model is recalibrated and validated. Model calibration and validation performance ar e evaluated with two of three criteria recommended by the ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models (1993): the de viation 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 ( R 2 

### ) is calculated as part of the hydrologic analysis. The deviation of volume, DV , quantifies the difference in observed and pr edicted 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 consid ered 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. 12-1-182006 South Florida Environmental Report Appendix 12-1



### The model calibration and validation pe rformance 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 num ber of days with valid flow data. In general, the model simulates daily flow reasonably well with R 2 

### and NS values of most of the stations above 0.5 for both calibration and validation an alyses 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 R

2 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 R

2 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 rainfa ll. 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 ab out 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 do uble mass curves for both stations ( Figure 6, Panels C and D) show consistent model performance when co mparing 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 h as 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, th e figure shows that the model simulates daily flows over Lainhart Dam and S-46 stations reasonably well.

App. 12-1-19Appendix 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 dist ribution 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

Validation Period Calibration 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 2 0 4 0 6 0 8 0 1 0 0 Exceedance (%)Flow (cfs)

1 10 100 1000 10000

0 2 0 4 0 6 0 8 0 1 0 0 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 DateRunoff (cfs)

0 200 400 600 800 1000

Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 DateRunoff (cfs) F S46 - Observed Lainhart Dam Observed Lainhart Dam Modeled E S46 - Modeled2006 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 wate r 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 targ et 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 ca librated 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 ma tches 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 consiste nt with the model ca libration 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 to tal 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 st age–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 hydrol ogic connections and grove operations along with slight tidal influence in the downstream area. Th e 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 n earby 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. 12-1-21Appendix 12-1 Volume I: The South Florida Environment

1 10 100 1000 10000

0 2 0 4 0 6 0 8 0 1 0 0 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 distributi on, (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 

### DateRunoff (cfs) Observed Modeled 

### C

App. 12-1-222006 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 distri bution at Cypress Creek station, (B) daily flow distribution at Hobe Grove Ditch station, (C) double mass

curve at Cypress Creek st ation, (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 DateRunoff (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 2 0 4 0 6 0 8 0 1 0 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 DateRunoff (cfs) Grove Modeled Grove Observed F

App. 12-1-23Appendix 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 le vels 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 TimeElevation (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 TimeElevation (ft) Model Observed M-1234

Figure 9. Observed and modeled water levels in Groundwater Monitoring Well PB-689 and M-1234. Land surface el evation is 24.43 feet at PB689 and 21.15 feet at M-1234.



### WaSh MODEL SIMULATION RESULTS A final long-term simulation for the pe riod 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 Estu ary. For total freshwater inflows into Northwest Fork, flow over Lainhart Dam (C-18/Corbett G-92 plus Jupiter Farms) accounts for about

App. 12-1-242006 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 re maining 8 percent is contributed from the areas that are not currently covered by flow monitori ng 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 Loxaha tchee 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 t he 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 tota l flow into Northwest Fork covered by the four flow monitoring stations (Lainhart Dam sta tion, 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 Comprehens ive 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 occurre d 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. 12-1-25Appendix 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. 12-1-262006 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. 12-1-27Appendix 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 dail y flow distribution for each of the 12 months of all the 39 years. This analysis indicates that th e 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 75 th 

### percentile flow in the month. The 75 th 

### 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 augmen tation during these low flow months.

Figure 10. Monthly median flow and the 75 th percentile flow over Lainhart Dam from 1965

– 2003. 

### 0 50 100 150 200 250

Janu ary
F ebr u ary M arch April M ay Ju ne July August

S

e ptemb er Octobe r Novem ber

Decemb er



## MonthFlow cfs Median 75th percentile

App. 12-1-282006 South Florida Environmental Report Appendix 12-1



## MODELING SALINITY

THE HYDRODYNAMIC/SALINITY (RMA) MODEL DESCRIPTION Salinity in the Northwest Fork of the Loxahatc hee 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 Northw est Fork and S-46 on the salinity conditions in the Loxahatchee River and Estuary. In paralle l 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 pr edict daily average salinity over a long period of time such as 30 years under various project scenario s. The main focus of the data collection and salinity modeling has been on the upper Nort hwest 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 leve ls and flow distribution around islands; flow at bridges having one or more re lief openings, in contrac ting 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 wate r bodies with wetlands; a nd general water levels and flow patterns in rive rs, 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 geom etries, 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. 12-1-29Appendix 12-1 Volume I: The South Florida Environment

Figure 11. Loxahatchee Estuary bathymetry.

App. 12-1-302006 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 structur e. The RMA itself does not predict the amount of fresh water entering the system from the wate rshed 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. 12-1-31Appendix 12-1 Volume I: The South Florida Environment



### The meandering river channel pattern is on e of the fundamental characteristics of the natural system of the Northwest Fork of the Loxahatch ee River. The previous studies have demonstrated that restoring the natural oxbows to the Northwest Fork can effectively re duce saltwater intrusion into the historically freshwater reaches. Th e 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. Salinit y measurements taken before and after the implementation of the projects indicate that th e 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 me sh is also detailed enough to simulate the effectiveness of potential channel restoration pr ojects 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 comple ted that will provide more detailed geometry for the river channel above the Trapper Nelson In terpretive 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 re lationship between the amount of freshwater inflow and the salinity regime in the Northw est 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 mi les 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 Gr ove 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 estua ry 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 in tervals. 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 obt ained 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 channe l 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), Northw est 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. 12-1-322006 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) mode l 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 La inhart Dam, Cypress Creek, Hobe Grove, and Kitching Creek were used for the calculation. Disch arge 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. B ecause the two curves overlap each other when printed in the same chart, the model output and fi eld 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 trib utaries to the Northwest Fork of the Loxahatchee River. 0 100 200 300 400 500 6005/1/035/8/035/15/035/22/035/29/036/5/036/12/036/19/036/26/037/3/037/10/037/17/037/24/037/31/038/7/03

dateDaily average flow(cfs)

App. 12-1-33Appendix 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. 12-1-342006 South Florida Environmental Report Appendix 12-1



### Field data and model output of tid es 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 be tween these locations. Both field data and model output indicate that the tidal regimens at th ese 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

O n 

### = the value of the nth observed data
P n 

### = the value of the nth predicted data

The smaller the RMS is, the better the mode l 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 N RMS Error RRE Observed O O = 

### −
= × =

− 

# ∑

× (14)



### where O max 

### = maximum value of observations

O min 

### = minimum value of observations

(O max 

### - O min 

### ) 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 gaug es 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. 12-1-35Appendix 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 observa tions in terms of maximum, minimum, and mean values. The difference in mean tide ove r 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-averag ed salinity with actual field salinity measurements from instruments at fixed eleva tions 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 dept h) could be significant when the system is stratified. The salinity record at Boy Scout Dock increas ed to 10 ppt between Day 50 and Day 60. This sudden salinity increase does not seem to be relate d to or supported by data from other field records. A salinity of 10 ppt usually occurs at th is site when freshwater inflow is below 100 cfs. The flow gauges actually recorded over 200 cfs fo r this period. The salinity record from the adjacent Kitching Creek station is also inconsiste nt 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 tid e. 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. 12-1-362006 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 measu rements 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 betwee n the modeled depth-averaged salinity and field salinity measurements. However, when the system is stratif ied, the daily salinity variation recorded by the instruments would be wider than the daily salin ity 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 ou tput 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. 12-1-37Appendix 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 ReportAppendix 12-1App. 12-1-390102030102030405060708090100Time (days from May 1, 2003)

Salinity (ppt)Field measurements at a fixed elevationDepth averaged model output0102030102030405060708090100Time (days from May 1, 2003)

Salinity (ppt)Field measurements at a fixed elevationDepth averaged model output10203040102030405060708090100Time (days from May 1, 2003)

Salinity (ppt)Field measurements at a fixed elevationDepth averaged model outputBoyscout Dock StationMay 10 - Aug 12, 2003Kitching Creek StationMay 10 - Aug 12, 2003Coastguard Dock StationMay 10 - Aug 12, 2003Figure 16.Model output of depth-averaged salinity and field measurements at fixed elevations in thewater 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 sour ces 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 dr y periods when the groundwater tables are still relatively high and therefore provide additional fr esh water to the system. Including groundwater input in the model will likely increase the accura cy in salinity prediction. The current model, without the input of groundwater input and overl and flow, tends to be conservative (predicting higher salinity). The current model does not include driving fo rces 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 pred ict the tide regimen rather accurately and predict the trend of salinity changes over the three-mont h 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. Rive r flow persistently adds fresh water to the estuary, however saltwater may still penetrate fa r 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 th e 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 c onstant for rates varying from 40 cfs at the low flow end to 7,000 cfs at the high flow end. These fl ow rates were determined based on an analysis of freshwater inflows simulated by the waters hed model. During RMA model output processing, 15 study sites were identified for ecological asse ssment 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. 12-1-402006 South Florida Environmental Report Appendix 12-1

Coordinates a 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. 12-1-41Appendix 12-1 Volume I: The South Florida Environment

Figure 17. Location of salinity and ecologic al assessment sites. Red dots

represent USGS sites; blue dots re present seagrass sites; purple dots

represent oyster sites; and green dots represent vegetation sites.

App. 12-1-422006 South Florida Environmental Report Appendix 12-1



### The objective of the RMA model applicati on 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 cycl e with both spring and neap tides. Thus, these results reflect the daily averaged salin ity 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 ( R 2 

### = 0.999 for all the 15 sites) was achieved with exponential functions in the form of



### Y = Y 0 

### + a e -bX [15]



### where X is freshwater inflow in cubic feet per second and Y is salinity in parts per thousand. Y 0 

### , 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. 12-1-43Appendix 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 in creases 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 cfsSalinity 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. 12-1-442006 South Florida Environmental Report Appendix 12-1



### In order to show the details of salinity variatio n 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 dete rmine the salinity value. The curves in Figure 19 represent the salinity gradients at variou s 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 1 0
Distance f r om Jupiter Inlet i n R i ver M ilesSalinity inparts perthousand 32 56 79 11 9 15 9 23 8 39 7 63 6 95 4 1 908 3 815 5 564 Freshwate r fl o w t o N W F in cf s

Figu re 1 9

. Salin it y gradien t s f o r variou s f r eshw at er in f l ow con d it ion s

.



### Although E q uation [ 1 5 ] expresses sali n it y as a sing le dependent variable function, there are other drivi ng forces that af fect salinity i n cluding tide, wind, flux between river and groundw ater, precipitation, and evaporation. However, the anal y s is of field data indicat ed that fresh water inflow is the m o st im portant factor affecting sa linit y

. When salinity is plotted a g ainst freshwater flow, the data points form a clear trend line. Co m p aring results from Equation [ 1 5 ] with actual field data provides a real ity check. Figures 20 thr ough 23 com p are the model results from Equation [ 15] with actual field m e asurem ents. As expected, deviations fr om the m odeled flow/salinity curve indicate the existenc e of other dri v ing forces t h at affe ct s a li nity . Nonetheless, the correlation between salinit y and freshwater infl ow is significant. Another factor that could cause deviations is that the sy stem is under consta nt transition in response to the changes in the driving force s . Therefore, it is rare for t h e sy stem to reach equilibrium as the case in the constant flow sim u lations. The over a ll trend of th e fiel d m e asu rem e nts shows a strong correlation between the am ount of freshwater in flow and salinit y thr oug ho ut the estuary.

A pp. 12-1-4 5Appendix 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 cfsSalinity 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 cfsSalinity 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. 12-1-462006 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 cfsSalinity 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. Salinit y at Pampano Drive near Sand Bar sea g rass site vs. dischar g e 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 trib utaries and canal in cfsSalinity in ppt .

App. 12-1-47Appendix 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 ar ray of scenarios. The analysis of the field data indicates that there is a good correlation between sa linity 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 exampl e, 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 combin ation 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 be tween RM 6 and RM 9 can be based on total freshwater inflow to the Northwest Fork inst ead 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 n eed 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 consid ered, 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 th e 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. 12-1-482006 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 c onditions represented by 500, 800, and 1,200 cfs are relatively high flows that begin to affect sa linity 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 in let 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 montht.ppity insalin

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.pptinsalinity

Figure 24. Salinity at Pennock Point seagrass transect in a lunar month; total freshwater inflow to the Loxahatc hee River: 500, 800, and 1,200 cfs.

App. 12-1-49Appendix 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 Mana gement 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. U nder natural conditions, freshwater inflow is rarely constant. The salinity conditions observed in the est uary are the result of a series of transitions from one state to the next. The changes in salin ity 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 th e direction of salinity changes, the process can be described as an e xponential increase or decay. Figure 25 is a graphic description of salinity transition when an increase of freshwate r 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 cons ists of a series of transitions from one quasi-equilibrium condition to another. This c oncept was reflected in the LSMM program. The program calculates the potential target (equilibri um) 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 c onstant 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. 12-1-502006 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 targ et (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 transiti on begins and the program repeats the same computational procedure unde r 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 (versu s minutes or seconds of a full hydrodynamic model), it allows the assessment of long-term da ta (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 hydrog raph based on certain operational rules such as MFL criteria. The model also calculates th e 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 sta tions 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 (Mar ch 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 charac teristics of model and field data.

App. 12-1-51Appendix 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. 12-1-522006 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 DateSalinity 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 /1/200 3 3/ 4/200 3 4/4 /200

3 5/5/2 00

3 6/5/20 0 3 7/6/2003
8 /6/200 3 9/ 6/200 3 10/7/2003 11/ 7 /2003 12/ 8 /2003 1/8/20 0 4
2 /8/200 4

3

/1 0/200

4 4/ 1 0/2004

DateSalinity in ppt.

KC KCSA-Measurements.

App. 12-1-53Appendix 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 3/4/0 3 4/ 4/03 5/5/03 6/5/0 3 7 /6/03 8/6/03 9/ 6/03 10/ 7/0

3 11 / 7/03 12/ 8/03 1/8/0 4 2/ 8/04 3/ 10/0

4 4/10/04

DateSalinity 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 3/4/0 3 4/ 4/03 5/5/03 6/5/0 3 7 /6/03 8/6/03 9/ 6/03 10/ 7/0

3 11 / 7/03 12/ 8/03 1/8/0 4 2/ 8/04 3/ 10/0

4 4/10/04

DateSalinity in ppt.

PD PDSA-Measurements.

App. 12-1-542006 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 si mulations were conducted with certain modifications to the BASE simulation hydrographs. The modifications represent scenarios that provide additional freshwater flows to upper Northwest Fork at La inhart 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 th e 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 th e ecological components in the Northwest Fork. Table 21 presents the salinity gradient of each scenar io 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 lo wer 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 sm all 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. 12-1-55Appendix 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. 12-1-562006 South Florida Environmental Report Appendix 12-1



### 0 5 10 15 20 25 30 35

0 2 4 6 8 10
River MileSalinity 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. 12-1-57Appendix 12-1 Volume I: The South Florida Environment



## LITERATURE CITED
AQUA TERRA Consultants. 1998. Addition of Irri gation Module to the HSPH Model. Final Report submitted to South Florida Water Mana gement District, West Palm Beach, FL. AQUA TERRA Consultants. 1996. Modifications to HSPF for High Water Table and Wetland Conditions in South Florida, Final Report s ubmitted to South Florida Water Management District, West Palm Beach, FL.
ASCE Task Committee on Definition of Criteria for Evaluation of Wate rshed Models of the Watershed Management Committee, Irrigation a nd Drainage Division. 1993. Criteria for Evaluation of Watershed Models. Journal of Irrigation and Drainage Engineering , 119(3): 429-442. Donigian, A.S., J.C. Imoff, B.R. Bicknell and J.L. Kittle. 1984. Application Guide for Hydrological Simulation Program – FORTRAN (HSPF). EPA-600/3-84-065. U.S. Environmental Protection Agency, Athens, GA.
FDEP. 1998. Loxahatchee River Wa tershed Action Plan. Second Draf t. Florida Department of Environmental Protection, Tallahassee, FL. Hu, G. 2004. Modeling Study of Saltwater Intr usion in Loxahatchee River, Florida. In: Proceedings of the 8th International Conference on Estuarine and Coastal Modeling

. In print, American Society of Civil Engineers, 2004. Hu, G. 2002. The Effects of Freshwater Inflow, Inlet Conveyance and Sea Level Rise on the Salinity Regime in the Loxahatchee Estu ary. Proceedings of 2002 Environmental Engineering Conference, Environmental & Water Resources Institute, American Society of Civil Engineers – Canadian Society of Civil Engineers, Niagara Falls, Ontario, Canada, 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 Report 83-4244. Sculley, S. 1995. West Palm Beach Water Ca tchment Area Water Conservation Study Technical Memorandum No. 2 Water Budget Model. Fina l Report (under Contract No. C-6113) submitted to the South Florida Water Management District, West Palm Beach, FL.
SFWMD. 2002a. Technical Documentation to Su pport Development of Minimum Flows and Levels for the Northwest Fork of the Loxaha tchee River. South Florida Water Management District, West Palm Beach, FL.
SFWMD. 2002b. Northern Palm Beach Count y Comprehensive Water Management Plan Planning Document: Volume I. South Florida Water Management District, West Palm Beach, FL.

App. 12-1-582006 South Florida Environmental Report Appendix 12-1



### USACE. 1996. Users' Guide to RMA-2 Version 4.3. U.S. Army Corps of Engineers, Waterways Experiment Station, Hydraulic Laboratory. Wan, Y., C. Reed and E. Roaza. 2003. Modeling Watersheds with High Groundwater Tables and Dense Drainage Canals. p. 10. In: Proceedings of 2003 AWRA International Congress: Watershed Management for Water Supply , June 29–July 2, 2003, New York, NY.

App. 12-1-59