# Attachment H

– Assumptions and Modeling Report

# Page 1 

# Evaluation of Alternatives to Achieve Phosphorus WQBELs

in Discharges to the Everglades Protection Area

prepared for

U.S. Environmental Protection Agency

By

William W. Walker, Jr., Ph.D

Environmental Engineer

Concord, Massachusetts

http://www.wwwalker.net

September 2, 2010

The following summarizes key assumptions and modeling results for alternative plans to

achieve Water Quality Based Effluent Limits (WQBELs) for total phosphorus concentrations in

discharges from Stormwater Treatment Areas (STAs) into the Everglades Protection Area. It is

assumed that follow

‐ up studies will be performed to optimize features of selected

alternative(s), as well as to evaluate schedule and cost factors in order to provide a basis for

selecting the final design.

1) The design target for STA outflow concentrations is 11.5 ppb, expressed long

‐ term (40

‐ year)

flow

‐ weighted mean outflow concentration (LTFWM). This target is approximately

equivalent to a long

‐ term geometric mean (LTGM) of 9.3 ppb, based upon the statistical

derivation of the WQBEL. The target provides a margin of safety for achieving the P

Criterion (LTGM= 10 ppb) and reducing the risk of exceeding the WQBELs.

2) Treatment objectives can be achieved using various combinations of (a) expanded

Stormwater Treatment Areas (STAs), (b) Flow Equalization Basins (FEBs), (c) diversion of

flows with relatively low P concentrations from the C51 East basin into the Refuge STAs, and

(d) distribution of flows across the FEBs and STAs to optimize performance.

3) For purposes of design, no additional phosphorus source controls beyond those in place

during 2005

‐ 2009 are assumed. Source controls, further optimization of the STA designs

and operation, and other measures may be implemented by SFWMD to provide an

additional margin of safety and reduce the risk of exceeding the WQBEL.

4) The existing treatment facilities do not include FEBs. In the scenarios evaluated, FEB

maximum depths range from 8 to 44 feet, as compared with STA maximum depths of ~4

feet. Their primary functions are to improve STA performance by storing and attenuating

# Page 2 

# peak flows during wet periods and by releasing flow during dry periods to help maintain STA

water levels and vegetation. FEBs provide operational flexibility for real

‐ time regional water

management (e.g. balancing flows across STAs; facilitating STA maintenance). These

benefits provide an additional margin of safety that is not reflected in the model

simulations. Optimization of the FEB parameters in subsequent design studies may improve

performance and provide additional operational flexibility.

5) Average source flows, phosphorus loads, and phosphorus concentrations that provide a

basis for design are listed in Table 1. The datasets have been developed jointly with

SFWMD.

6) Flows are derived from Restoration Strategies Baseline South Florida Water Management

Model (RSB2X2) daily simulation of WY 1966

‐ 2005 (May 1, 1966

– April 30, 2005) hydrologic

conditions with current infrastructure.

7) Source concentrations are based upon monthly flow

‐ weighted means computed from

monitoring data collected between Water Years 2005

‐ 2009 (May 1, 2004 to April 30, 2009).

Phosphorus concentrations in releases from Lake Okeechobee to STA

‐ 34 are based upon

data collected at the lake outlet structure.

8) It is assumed that average STA inflow volumes, concentrations, and loads computed from

2005

‐ 2009 data and 2x2 simulated flows will not increase in the future.

9) To account for reductions in watershed area associated with STA or FEB construction,

source flows and loads are reduced based upon the ratio of the effective treatment area of

the project to the existing watershed area in the basin containing the project.

10) For initial planning purposes, the effective treatment area (surface area at normal operating

depth) for each STA or FEB is increased by 10% to estimate the total amount of land

required. This accounts for the associated infrastructure (pumps, canals, levees, roads, etc).

The 10% factor will be adjusted in detailed design depending on the actual site locations

and STA/FEB configuration, as long as the effective treatment area of the final project is not

less than that specified in the planning scenarios.

11) Each scenario is designed to treat all of the flow discharged from the source basins over the

40

‐ year simulation period (WY 1966

‐ 2005). More detailed hydraulic analyses will be

needed to design the infrastructure and operations needed to guarantee that there will be

no untreated bypasses around the STAS into the Everglades under hydrologic conditions

that are reflected in the 40

‐ year simulation period. Infrastructure and operational plans

will be provided to divert infrequent extreme event flows that exceed STA treatment

capacity to the coast or other locations outside of the Everglades Protection Area.

12) None of the WQBEL scenarios rely on future construction or operation of projects that are

outside of the scope of those specified in the scenarios (e.g. CERP or other restoration

projects).

# Page 3 

# 13) The selected alternative will not decrease the average inflow to Loxahatchee Refuge or

adversely impact water levels, as evaluated with the Refuge water balance model (SRSM)

and its associated performance measures. Preliminary analyses indicate that each of the

scenarios meets the Refuge water needs according to these criteria. This will be confirmed

before selecting a final alternative in the subsequent design phase.

14) The Dynamic Model for Stormwater Treatment Areas (DMSTA, Walker & Kadlec, 2005,

http://www.wwwalker.net/dmsta ) is used to simulate the hydraulics and phosphorus

removal performance of the FEBs and STAs. DMSTA was developed explicitly for this

purpose and calibrated to extensive monitoring data from the STAs, test cells, and other

treatment wetlands. The model has been used in several feasibility and detailed design

studies performed by SFWMD and its contractors over the 2001

‐ 2010 period. Despite

inherent modeling uncertainties and limitations, the SFWMD, state, and federal agencies

have agreed that this is the best available tool for use in design. Summary of model input

values is provided in Table 2.

15) Modeling uncertainty is estimated at ± 15% of the predicted LTFWM for each STA. The

total forecast uncertainty is likely to be greater because of variability in future climatologic

conditions and uncertainty in the assumed source flows and phosphorus loads. In addition

to the margin of safety inherent in the specified design target (equivalent to a LTGM = 9.3

vs. 10 ppb), additional measures can be taken to account for performance uncertainty and

reduce risk of exceeding the WQBEL (e.g., source controls, further STA optimization,

research and monitoring to improve treatment technology).

16) The scenarios (Table 3) include four basic alternatives (A, B, C, D) involving different

combinations of expanded STAs, FEBs, and diversion of additional flow into the Everglades

from the C51 East Basin. Each scenario is simulated with a final configuration (full

‐ scale

operation) and interim configuration (partial construction, accelerated to achieve WQBEL in

STA34 and improve performance of the other STAs). For comparison purposes, the

scenarios also include the existing STAs with and without Compartments B & C in operation.

17) Table 4 summarizes the water and phosphorus balances for each STA and scenario. WQBEL

excursion frequencies are calculated from the yearly outflow FWM time series for each STA.

Based upon WQBEL derivation results, the yearly FWM is divided by 1.23 to estimate the

outflow geometric mean. Under full operation (Scenarios A, B, C, D), the predicted number

of excursion events over the 40 year record ranges from 0 to 3. The results do not account

for the inherent uncertainty in climate, source datasets, STA vegetation management, and

modeling. Implementing source controls and additional measures not assumed in the

design calculations will provide a margin of safety and reduce the risk of exceeding the

WQBEL in the context of the uncertainties associated with forecasting project performance.

# Page 4 18) 

# The STA/FEB expansion requirements and outflows to the EPA and Lake Worth for each

alternative under full operation are summarized below. The total area requirements vary

over a relatively narrow range (41

‐ 44 kac). The C51E Diversion/FEB scenarios (C & D)

provide significant increase in total flow to the Everglades without substantially increasing

the total area requirements relative to Scenarios A & B.

Full Operation New Total

Inflow STA FEB Total kac To Ever Estuary

A

‐ East & Cent STA

‐ 30.6 7.0 37.6 41.4 1416 273

B

‐ East STA, Cent FEB

‐ 28.5 10.0 38.5 42.4 1408 203

C

‐ C51 FEB, Cent STA C51E 30.0 8.7 38.7 42.5 1584 16

D

‐ C51 FEB, Cent FEB C51E 27.0 12.7 39.7 43.6 1574 16 New Effective Area kac Outflow kaf/yr

Scenario

# Page 5 

# Table 1

‐ Source Flows & Phosphorus Loads (Prior to STA Expansion) *

Flow Load Conc

Source kac

‐ ft/yr mt/yr ppb

S5A Runoff to WPB 235.4 53.0 182

298

‐ EBWCD 24.2 14.7 492

S361 Runoff to STA1E 9.7 0.9 73

C51 West + ACME 159.7 32.2 163

L8 Runoff to C51W Canal 25.0 4.2 135

S352 Urban Water Supply 2.3 0.3 103

Total STA

‐ 1W+1E 456.3 105.2 187

S5A Runoff to STA2 61.0 16.0 213

S6 Runoff to STA2 181.2 27.8 124

ESWCD & 715 to Hills 31.0 6.3 165

Total STA

‐ 2 + Comp B 273.2 50.2 149

S7 Runoff to STA34 121.5 18.1 121

S7 Runoff to Comp B (redirected) 142.2 21.0 120

S8 Runoff to STA34 219.4 28.3 104

298

‐ SSD 5.2 0.7 112

298

‐ SFCD 19.1 2.6 112

298

‐ SSDD 6.9 1.2 139

C139_G136 to STA34 11.7 3.0 209

S354 Lake Urban WS 19.6 3.7 153

S351 Lake Urban WS 6.8 1.5 178

S354 Lake Reg Release 58.5 12.4 172

Total STA

‐ 34 611.0 92.5 123

C139 South Runof f 176.6 50.1 230

C139 North Runoff (L1/G136) 2.4 0.7 234

C139 Annex 21.3 2.6 97

STA6 Water Supply 6.8 1.4 171

Total STA 5

‐ 6 207.1 54.8 214

Total All Basins 1547.6 302.7 158

C51E Diversion Option

Total C51E Runof f 202.6 23.9 96

C51E Diverted to STA1W/E 187.1 22.1 96

C51E Discharged to Estuary 15.6 1.9 96



# * Assumptions and data developed jointly with SFWMD.

# Page 6 

# Table 2

– Summary of DMSTA Modeling Assumptions

Parameter Comments

General Except where noted, DMSTA parameters for the existing STA cells are derived from the

values assumed in the September 2009 update of the Long

‐ Term Plan and/or updates

specified in SFWMD simulations of WQBEL scenarios. Detailed model parameters are

specified in the DMSTA input file for each scenario.

Simulation Dates Start Date: 1/1/1965 (SFWMM Output); Output Dates: 5/1/1965

‐ 4/30/2005 (Water

Years 1966

‐ 2005)

Number of

Iterations 1 iteration. The initial P storage in each cell is initialized at the average value predicted

from the previous model run; this enables simulation with 1 iteration provided that the

each scenario is simulated at least twice in the course of the design process.

Atmospheric

Deposition Assumed in DMSTA calibration and previous design studies. Dry deposition 20 mg/m 2



# ‐

yr; Rainfall P Concentration = 10 ppb.

Duty Cycle

Factor Duty Cycle

= 0.95 for STAs; refers to the portion of time that an STA is offline for major

maintenance or rehabilitation activities. A value of 0.95 is meant to correspond to an

STA being offline 5% of the time (1 year out of every 20 years). This assumption is

consistent with historical STA operations after startup periods.

Duty Cycle

= 1.0 for FEBs; minimal vegetation management

DMSTA

Vegetation

Types EMG: Emergent or unmanaged vegetation on previously farmed or disturbed soils

SAV: Cells managed to promote submersed aquatic vegetation (SAV); generally deeper

then emergent cells

PSTA: Periphyton treatment area on limerock/shellrock substrate

PEW: Pre

‐ Existent Wetland; emergent or unmanaged veg. on previous wetland or

undisturbed soils

RES: Deep (8

‐ 44 ft); open water; dominated by algae and floating vegetation, as

opposed to emergent or submersed vegetation.

Current STAs contain various combinations of emergent and SAV. STA

‐ 2 cell 2 is

modeled using the PEW calibration (existing).

The EMG/SAV split for new cells in the eastern & central basins is 33/67, typical of the

existing STAs.

# Page 7 The EMG/PEW split for new cells in the western basin is 60/40. Downstream cells in

each flow path of the existing and expanded STAs in the western basin are modeled

using the PEW calibration. Maintenance of SAV in the western basin has proven to be

difficult because of high seepage rates, frequent dry

‐ out, and low calcium levels in the

basin runoff.

The RES calibration is used for FEBs.

None of the cells are modeled with the PSTA calibration, although conversion to

periphyton communities may be a future management option.

Inflow Fraction Total cell area in each flow path / total STA area; balances hydraulic loads across flow

paths within each STA

Mean Width of

Flow Path As constructed for existing cells. The width of new flow paths is computed from area

assuming a 3/1 length to width ratio along each EMG/SAV flow path. A length/width

ratio of 1.0 is assumed to FEBs. Performance is insensitive to width assumptions.

Number of Tanks

in Series A TIS value of 1 is used for FEBs. Consistent with previous design assumptions, a TIS

value of 3 is used in each new STA cell. This assumes that the cell will be constructed

and managed to provide relatively even ground surface and flow distribution across

the width of each flow path (minimal short

‐ circuiting) and contain at least one internal

levee to separate the emergent and SAV communities.

FEB Release

Series Release to STAs to help maintain water levels in droughts. Computed based upon 30

‐

day antecedent average ET

– Rainfall multiplied by the downstream STA area. If ET

exceeds rainfall, a proportionate release is made; potential release from C51 FEB for

urban water supply; release for maintenance of Refuge stage (minimum total inflow to

STA1E+W from all sources = 500 cfs for June

‐ October; not optimized). Minimum

drawdown depth

= 0.5 ft.

FEB Depth Series Monthly regulation schedule specified for FEBs. Range from 0% in wet season (to

capture storms) to 80% of capacity in dry season (stores water for use in STA irrigation,

urban water supply); To be optimized in final design.

FEB Outflow

Hydraulic

Coefficients Slope

= 1; intercept varied to provide specified mean hydraulic residence time in the

FEB (90 days in western FEB, 60 days in central FEB, 30 days in FEB). Values adjusted

based upon simulated water levels, flow capture, and flow attenuation; to be

optimized in final design.

STA Outflow

Control Depth ~1.25 ft. No outflow below this level; typical of existing STA cells

STA Outflow

Hydraulic

Coefficients Slope

= 4, Intercept = 1; typical values calibrated to existing STA cells

# Page 8 STA Bypass

Triggers Each STA is assumed to treat all of the simulated flow without bypass. Simulated

water levels and inflow volumes are generally consistent with that assumption, but will

be confirmed in detailed design, which will provide suitable infrastructure to avoid

untreated bypass.

FEB Bypass

Triggers Maximum depth varies with design (12 ft for West, 8 ft for Central, 44 ft for Eastern

FEB (C51E Project Design)); Maximum inflows (2500, 3000, and 2000 cfs, respectively);

to be optimized in final designs.

Seepage Rates Generally consistent with seepage rates assumed in previous simulations of the

existing STAs (.005

– 0.2 cm/d/cm) ; seepage rates in STA

‐ 34 are reduced by 75%

relative to SFWMD simulations to be more consistent with the observed overall water

budget of STA

‐ 34. No seepage losses assumed for FEBs; seepage rates to be

considered in final design (could be released to STAs or recycled to FEB).

Seepage

Recycling No seepage recycling is included in the simulations. This is conservative with respect

to maintaining STA water levels. Any seepage recycling in new cells would depend on

cell location and configuration relative to existing cells. Seepage collection and

recycling will be optimized in detailed designs.Page9Table3–ScenarioDefinitionsandResultsAllScenarios:Long‐TermFlow‐Weighted‐MeanDesignTarget=11.5ppb(equivalventtoLTGeometricMean~9.3ppb),2005‐2009SourceTPConcentrationsFEBVol.Outflowskac‐ft/yrID Label DescriptionWest Cent East West Cent East Total West Cent East Total kac‐ft Effect Total West 34 2+B East Total WCA1 2A+3A Total Estuary1 Current**CurrentSystemwithoutCompB&C214 131 187 8.9 24.8 11.8 45.50.0 0.0 0.0 0.045.5 50.029.7 25.5 33.2 34.6 30.1448 1050 1497 2732Current+CompB&C**CurrentSystemwithCompB&C214 131 187 13.0 31.7 11.8 56.50.0 0.0 0.0 0.056.5 62.118.3 15.7 20.3 34.1 23.0448 1042 1490 2033 A‐East&CentSTASTAExpansioninEast&Central;12‐ftFEBinWest219 131 1870.015.6 15.0 30.6 7.00.0 0.07.0 84 37.6 41.4 11.4 11.5 11.5 11.4 11.5 429 987 1416 2734 B‐EastSTA,CentFEB8‐ftFEBinCompA2,STAinCompA1,;12‐ftFEBinWest;STAexpansioninEast219 131 1870.013.5 15.0 28.5 7.0 3.00.010.0 108 38.5 42.4 11.5 11.3 11.3 11.4 11.4 429 979 1408 2035 A/B‐Interim(4yrs)InterimPlanforScenarios3or4;A1Operatedas4ftFEB;balanceflowstoachieveWQBELinSTA34;MeanwhileconstructA28‐ftFEB(orSTA),ConvertA1FEBtoSTA,expandSTA1W;12‐ftFEBinWest214 132 1880.0 0.0 0.0 0.0 0.015.00.015.0 60 15.0 16.518.311.218.2 31.9 20.4448 975 1397 2286 C‐C51FEB,CentSTAC51EDiversion&44‐ftRockpit/FEB+STAExpansioninEast&Central;12‐ftFEBinWest219 131 1600.022.0 8.0 30.0 7.00.01.7 8.7 157 38.7 42.5 11.1 11.5 11.5 11.5 11.5 444 1140 1584 167 D‐C51FEB,CentFEBC51EDiversion&Rockpit/FEBinEast;8‐ftFEB,STAExpinA1&A2,12‐ftFEBinWest219 132 1600.019.0 8.0 27.0 7.0 4.0 1.7 12.7 189 39.7 43.6 11.5 11.5 11.5 11.5 11.5 444 1130 1574 168 C/D‐Interim(4Yrs)InterimPlanforScenarios6or7;C51Erockpitpartiallycomplete(6ftvs.44ftfinal);divertL8flowstocoast;someS5Atowest;noC51Ediversion;A1Operatedas4ftFEB;achieveWQBELinSTA34;Meanwhileconstructotherprojectcomponents(FEBinCompA2,CompleteC51Rockpit,STA1WExpansion)214 132 1880.0 0.0 0.0 0.0 0.015.0 1.7 16.7 70 16.7 18.418.311.319.2 30.4 20.0389 1004 1393 226*PreliminaryDesignsSubjecttoMoreDetailedAnalysisandOptimization.ApproximateModelUncertainty+/‐15%ofPredictedOutflowConcentrations.**Existing&PlannedSTAEffectiveAreaslistedforScenarios1&2;STAExpansionareaslistedforotherscenarios;West=STA‐5,STA‐6,CompC;Central=STA‐34,CompB,STA‐2;East=STA‐1W&STA‐1E.***BoldFontsIndicateSTA'sNotAchieving11.5ppbLTFWMTarget(ExistingConditionsorInterimPlans)InflowConcppb FEBEffectiveAreaSTAExpan.(Effective)* OutflowFWMppb***FEB+STAPage10Table4‐STAMassBalances&PerformanceScenario 1 ExistingSTAsEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 194 37.3 155 185 6.5 28.2 3.2 20.1 0.88 0% 260.0 029 35 37STA1W 6.7 262 68.0 210 263 12.7 39.1 3.3 20.6 1.02 0% 26 40 38 40STA2B 8.2 273 50.2 149 275 11.3 33.2 2.8 14.0 0.98 0% 20 40 38 40STA34 16.5 611 92.6 123 601 18.9 25.5 3.1 13.1 0.85 1% 230.0 037 38 40STA5 6.1 143 37.8 214 125 4.8 30.9 2.0 8.9 0.96 1% 180.0 040 38 40STA6 2.8 64 17.0 214 48 1.6 26.5 1.9 8.7 0.96 7% 20 39 38 40Total 45.5 1548 302.7 158 1497 55.7 30.1Scenario 2 ExistingSTAs+CompartmentsB&CEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 221 44.1 162 211 8.8 34.0 3.6 20.8 0.86 0% 260.0 038 38 40STA1W 6.7 236 61.2 210 237 10.0 34.1 2.9 18.6 1.02 0% 26 40 38 40STA2B 15.1 474 79.9 137 478 12.0 20.3 2.6 13.0 0.99 0% 25 25 38 40STA34 16.5 410 62.8 124 401 7.8 15.7 2.1 8.5 0.82 1% 230.0 05 23 24STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 170.0 018 34 35STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 35Total 56.5 1548 302.7 158 1490 42.3 23.0Scenario 3 A‐STAExpansionEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 109 20.4 152 102 1.5 11.6 1.8 7.1 0.75 0% 260.0 00 22STA1W 21.7 321 78.9 199 327 4.6 11.3 1.2 7.0 0.95 0% 21 2 0 2STA2B 15.1 248 46.1 151 253 3.6 11.5 1.4 6.9 0.98 0% 20 0 0 0STA34 32.1 602 91.6 123 583 8.3 11.5 1.6 6.6 0.85 1% 210.0 00 11STA5 7.9 122 24.3 161 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 3STA6 5.1 78 15.5 161 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 2Total 87.1 1479 276.7 152 1416 20.0 11.5Scenario 4 B‐STAExpansionwithA2FEBEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 107 20.1 152 100 1.4 11.4 1.7 7.1 0.75 0% 260.0 00 11STA1W 21.7 322 79.2 199 328 4.6 11.4 1.2 7.0 0.95 0% 21 2 0 2STA2B 15.1 252 46.8 150 258 3.6 11.3 1.4 7.0 0.98 0% 21 0 0 0STA34 30.0 589 85.5 118 570 8.0 11.3 1.6 7.0 0.81 0% 22 3.0 8 0 0 0STA5 7.9 122 24.3 162 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 3STA6 5.1 78 15.5 162 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 2Total 85.0 1470 271.3 149 1408 19.7 11.4Page11Table4‐STAMassBalances&Performance(ct.)Scenario 5 A/B‐InterimPlanwithoutC51EDiv/FEBEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 161 32.2 162 152 3.8 20.5 2.6 9.7 0.74 0% 280.0 020 35 36STA1W 6.7 270 68.0 204 270 12.8 38.3 3.4 20.6 0.99 0% 27 40 38 40STA2B 15.1 425 72.6 139 429 9.6 18.2 2.3 11.7 0.98 0% 25 16 35 37STA34 16.5 393 47.6 98 383 5.3 11.2 2.0 8.8 0.77 1% 24 15.0 4 0 1 1STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 170.0 018 34 35STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 35Total 56.5 1455 275.2 153 1397 35.2 20.4Scenario 6 C‐C51EDiv/FEB,STAExpanEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 123 18.7 123 116 1.6 11.5 2.0 7.0 0.70 0% 27 1.7 44 0 1 1STA1W 14.7 327 63.2 157 328 4.7 11.5 1.9 8.6 0.57 0% 28 1 0 1STA2B 15.1 291 64.0 178 296 4.2 11.5 1.6 7.0 0.97 0% 26 0 1 1STA34 38.5 718 110.3 125 693 9.8 11.5 1.6 6.8 0.87 1% 210.0 00 11STA5 7.9 122 24.2 161 101 1.4 11.4 1.3 3.8 0.61 0% 20 7.0 12 0 3 3STA6 5.1 78 15.5 161 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 2Total 86.5 1659 296.0 145 1584 22.5 11.5Scenario 7 D‐C51EDiv/FEB,A2FEB/STAEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 123 18.7 123 116 1.6 11.5 2.0 7.0 0.70 0% 27 1.7 44 0 1 1STA1W 14.7 327 63.2 157 328 4.7 11.5 1.9 8.6 0.57 0% 28 1 0 1STA2B 15.1 291 64.0 178 296 4.2 11.5 1.6 7.0 0.97 0% 26 0 1 1STA34 35.5 706 103.1 118 683 9.7 11.5 1.7 7.4 0.83 0% 22 4.0 8 0 2 2STA5 7.9 122 24.3 162 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 3STA6 5.1 78 15.5 162 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 2Total 83.5 1647 288.8 142 1574 22.4 11.5Scenario 8 C/D‐InterimPlanwithC51EDiv/FEBEffectSTAInflowsSTAOutflows 30‐DayHydraulicLoad Depth Settling FEBArea DepthWQBELExcursions/40YrsArea FlowLoad Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2Yrs BothSTA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d‐<10cm m/yr FWM>18GM>10 TestsSTA1E 5.1 117 21.9 152 110 1.7 12.9 1.9 8.1 0.77 0% 26 1.7 6 2 3 5STA1W 6.7 281 66.0 190 279 12.8 37.3 3.5 21.6 0.95 0% 27 40 38 40STA2B 15.1 453 78.7 141 458 10.9 19.2 2.5 12.3 0.98 0% 25 22 35 39STA34 16.5 393 47.8 98 384 5.3 11.3 2.0 8.8 0.77 1% 24 15.0 4 0 2 2STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 170.0 018 34 35STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 35Total 56.5 1451 269.1 150 1393 34.4 20.0

# Evaluation of Alternatives to Achieve Phosphorus WQBELs

in Discharges to the Everglades Protection Area

prepared for

U.S. Environmental Protection Agency

By

William W. Walker, Jr., Ph.D

Environmental Engineer

Concord, Massachusetts

http://www.wwwalker.net



# Sept 2, 2010

Attachment 1 : Yearly Flow

‐ Weighted Mean Time Series for Each ScenarioScenario1 ExistingSTAs 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E0102030405060701960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W010203040506070801960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B01020304050601960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA340510152025303540451960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA501020304050601960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA60510152025303540451960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario2 ExistingSTAs+CompartmentsB&C 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E010203040506070801960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W0102030405060701960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA340510152025301960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA5051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA6051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario3 A‐STAExpansion 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA3405101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA505101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA605101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario4 B‐STAExpansionwithA2FEB 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA34024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA505101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA605101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario5 A/B‐InterimPlanwithoutC51EDiv/FEB 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E0510152025303540451960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W010203040506070801960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B0510152025301960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA34024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA5051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA6051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario6 C‐C51EDiv/FEB,STAExpan 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W0510152025301960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA34024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA505101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA605101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario7 D‐C51EDiv/FEB,A2FEB/STA 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W0510152025301960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B05101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA34024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA505101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA605101520251960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbScenario8 C/D‐InterimPlanwithC51EDiv/FEB 80%ConfidenceIntervalsforYearlyFlow‐WeightedMeansModelPredictions+/‐20%;Roundedtonearestppb.SolidLine=18ppbWQBEL.STA1E0510152025301960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA1W010203040506070801960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA2B051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA34024681012141618201960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA5051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppbSTA6051015202530351960 1970 1980 1990 2000 2010

FWM ppbFWM18ppb

# Evaluation of Alternatives to Achieve Phosphorus WQBELs

in Discharges to the Everglades Protection Area

prepared for

U.S. Environmental Protection Agency

By

William W. Walker, Jr., Ph.D

Environmental Engineer

Concord, Massachusetts

http://www.wwwalker.net



# Sept 2, 2010

Attachment 2 : Yearly Geometric Mean Time Series for Each ScenarioScenario1 ExistingSTAs 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E01020304050601960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W01020304050601960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B0510152025303540451960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA34051015202530351960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50510152025303540451960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA605101520253035401960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario2 ExistingSTAs+CompartmentsB&C 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E0102030405060701960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W01020304050601960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B0510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA3405101520251960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario3 A‐STAExpansion 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E024681012141618201960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W024681012141618201960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B02468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA340246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario4 B‐STAExpansionwithA2FEB 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E0246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W024681012141618201960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B02468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA3402468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario5 A/B‐InterimPlanwithoutC51EDiv/FEB 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E051015202530351960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W0102030405060701960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B05101520251960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA3402468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario6 C‐C51EDiv/FEB,STAExpan 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E0246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W05101520251960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B0246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA340246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario7 D‐C51EDiv/FEB,A2FEB/STA 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E0246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W05101520251960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B0246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA3402468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60246810121416181960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbScenario8 C/D‐InterimPlanwithC51EDiv/FEB 80%ConfidenceIntervalsforYearlyGeometricMeansModelPredictions+/‐20%;YearlyGeoMean=FWM/1.23.SolidLine=10ppbcriterion.DottedLine=15ppblimitformarshsitesin4‐PartTestSTA1E05101520251960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA1W0102030405060701960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA2B0510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA3402468101214161960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA50510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppbSTA60510152025301960 1970 1980 1990 2000 2010

Geo Mean ppbGM15ppb10ppb

# Scenario Description

0 Generalized Project Schematic

1 Existing STAs

2 Existing STAs + Compartments B & C

3 A

‐ STA Expansion Only

4 B

‐ STA Expansion with A1 STA & A2 FEB

5 A/B

‐ Interim Plan with Temporary A1 FEB & Balance STA

‐ 34 Inflow

6 C

‐ C51E Diversion /FEB, STA Expansion

7 D

‐ C51E Diversion/FEB, A2 FEB+STA, A1 STA

8 C/D

‐ Interim Plan with Temporary A1 FEB, Balance STA

‐ 34 Inflow, C51E Div/FEB http://www.wwwalker.net



# Sept 2, 2010

Attachment 3 : Scenario Flow Charts By

William W. Walker, Jr., Ph.D

Environmental Engineer

Concord, Massachusetts 

# Evaluation of Alternatives to Achieve Phosphorus WQBELs

in Discharges to the Everglades Protection Area

prepared for

U.S. Environmental Protection AgencyGeneralizedFlowChartforWQBELScenariosFlowPathNewDiversionFEBReleasesforSTAIrrigation,UrbanWaterSupply(S5A),orFarmIrrigation(NoneAssumed)Schematicreflectsthegenerallogicoftheflownetwork,notspecificlocationsoftheprojectcomponentsExpandedSTA'saremodeledasadditionalflowpathsforSTA‐6,STA‐34,andSTA‐1W.STA2_CBS6+298C51WSTA34FEB34FEB5ANNRWpbHillsS8G136+298S5AEBWCDSTA1EC51EC51WS7+Lake+298LakeS361S5AECPDIVLakeMiaSTA1WFEB56STA5C139+AnnexL3STA6L8

# Scenario: 1 Existing STAs Mean Flow kac

‐ ft/yr

STA Expansion kac

257 212 260 0.0

78 276 61

0 0

0 0

0.0 212 260

207

0 0 276 0

0.0

0 2

0.0 0

160

0 0 260 25

0 00

0 00

0 0

0 207 0

273 0

0 0

0

611 0 185 203

64 143 262 203

0.0 0.0 10

0.0

48 125 601 275 263 185

Totals

STA Outflow TP ppb 26.5 30.9 25.5 33.2 39.1 28.2 30.1

STA Expansion kac 0.0 0.0 0.0 0.0

STA Total Area kac 2.8 6.1 16.5 8.2 6.7 5.1 45.5

STA Outflow kacf/yr 48 125 601 275 263 185 1497

WCA Inflow kacft 774 275 448 1497

Inputs for Scenario EvenLess No Expansion or Source Control, Before Comp B & Comp C Operating

Diversion Rules Mass Balance S ummary EvenLess project_evenless.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 1000 Area Flow Load Conc Flow Load Conc HLR HLR Max

S5A Div (ECART) S5A Div HILLS_C 0 800 divert to hills STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 200 low

‐ flow bypass to WPB STA1E 5.1 194 37.3 155 185 6.5 28.2 3.16 20.1

S5A Div to FEB FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 6.7 262 68.0 210 263 12.7 39.1 3.28 20.6

FEB S5A Outflow STA1DW HILLS_C 0 diversion to Hills STA2B 8.2 273 50.2 149 275 11.3 33.2 2.77 14.0

C51W Outflow EAST STA1E 1 direct to STA1E STA34 16.5 611 92.6 123 601 18.9 25.5 3.08 13.1

C51W Outflow EAST STA1_DW 1 direct to STA1DW STA5 6.1 143 37.8 214 125 4.8 30.9 1.96 8.9

C51W Outflow EAST FEB_S5A 1 remainder to East STA6 2.8 64 17.0 214 48 1.6 26.5 1.92 8.7

ST A1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 45.5 1548 302.7 158 1497 55.7 30.1 2.84

S6 Runoff STA2CB NNRC 0 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to STA34

STA56 Distrib STA5 STA6 0.31 Balance STA56 Loads, Hint= 0.314

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 RES_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac blank to ignore FEB FEB_S5A 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

HRT days 60 30 30 30 FEB_34 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Bypass Depth ft 44 8 4 4 FEB_56 0.0 0 0.0 108 0 0.0 #N/A 0 0

LowQ Bypass cfs 100 100 100 200 Total FEB 0.0 0 0.0 #N/A 0 0.0 #N/A

Max Qin cfs 2000 4000 2000 1000

Max Qou t cfs 1000 500 500 100

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5

Regulation Schedule not implemented Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release not implemented kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release not implemented TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Farm Irrig kac not implemented TS_FEBS5A 259.5 67.7 211 358 1.87 5153

TS_STA1DW 2.3 0.3 103 3 9.50 666

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac TS_STA1E 194.4 37.3 155 268 1.07 3318

Fraction SAV 0.67 0.67 0.4 TS_STA2B 273.2 50.2 149 377 1.94 3931

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 0.0 0.0 0 0 #N/A 0

TS_STA34 611.0 92.6 123 843 1.80 8891

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 207.1 54.8 214 286 1.20 4806

Use Lake P Co ncs TRUE for S354 & S351 Lake Rleases Total 1547.6 302.7 158 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 12 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval Days 30 Other

S5A Load Reduc 0% Other

Other Other

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 0.0 0.0 1.00

Scale_S6 105 1 1.00

Scale_s7 120 1 0.0 0.0 1.00

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 0.0 1.00 9/1/10 19:58 STA2_CB S6 +

298

C51W

L8

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV

Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 FEB5AN

# Scenario: 2 Existing STAs + Compartments B & C Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 260

78 75 61 0

142 0

58 0.0

0 0

0.0 212 260 0

207

0 0 75 0 0

0.0

0

0.0 142 0 25

58 25

0 0 0 260

0 00

0 0

0 0 160

0 207 0

415 0

0 0

0

410 0 185 203

81 126 236 203

0.0 0.0 10

0.0

57 106 401 478 237 211

Totals

STA Outflow TP ppb 18.3 18.3 15.7 20.3 34.1 34.0 23.0

STA Expansion kac 0.0 0.0 0.0 0.0

STA Total Area kac 5.1 7.9 16.5 15.1 6.7 5.1 56.5

STA Outflow kacf/yr 57 106 401 478 237 211 1490

WCA Inflow kacft 564 478 448 1490

Inputs for Scenario Nothing Existing Treatment Capacity; Comp B & Comp C Complete

Diversion Rules Mass Balance S ummary Nothing project_nothing.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 Area Flow Load Conc Flow Load Conc HLR HLR Ma x

S5A Div (ECART) S5A Div HILLS_C 0 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 low

‐ flow bypass to WPB STA1E 5.1 221 44.1 162 211 8.8 34.0 3.59 20.8

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 6.7 236 61.2 210 237 10.0 34.1 2.95 18.6

FEB S5A Outflow HILLS_C STA1DW 0 diversion to Hills STA2B 15.1 474 79.9 137 478 12.0 20.3 2.61 13.0

C51W Outflow EAST STA1E 1 direct to STA1E STA34 16.5 410 62.8 124 401 7.8 15.7 2.07 8.5

C51W Outflow EAST STA1_DW 0 direct to STA1DW STA5 7.9 126 33.4 214 106 2.4 18.3 1.34 6.1

C51W Outflow EAST FEB_S5A 0 remainder to East STA6 5.1 81 21.4 214 57 1.3 18.3 1.32 6.0

STA1W Distrib STA1W STA1E 0.1 WPB C STA1E Total STA 56.5 1548 302.7 158 1490 42.3 23.0 2.29

S6 R unoff STA2CB NNRC 0 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to STA34 STA1W+E 448.0 18.8 34.1

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 879.3 19.8 18.2

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 163.1 3.7 18.3

L8 to North C51W North 0 CERP

NNR to CB STA34 Comp B 1 Original Design for Comp B =1

NNR to CB 2 STA34 Comp B 0.48 Additional NNR Diversion to CB

Area Flow L oad Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac FEB_S5A 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

HRT days 14 14 30 30 FEB_34 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Bypass Depth ft 26.4 4 12 4 FEB_56 0.0 0 0.0 68 0 0.0 #N/A 0 0

LowQ Bypass cfs 200 400 50 100 Total FEB 0.0 0 0.0 #N/A 0 0.0 #N/A

Max Qin cfs 2000 2775 2500 2000

Max Qout cfs 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FEB_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release REL_STA REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cf s

Farm WS Release REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 259.5 67.7 211 358 1.87 5153

Frac C51 Urban WS 1 TS_STA1DW 2.3 0.3 103 3 9.50 666

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 0 00 TS_STA1E 194.4 37.3 155 268 1.07 3318

Fraction SAV 0.67 0.67 0.4 TS_STA2B 473.7 79.9 137 654 2.02 6863

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 0.0 0.0 0 0 #N/A 0

TS_STA34 410.5 62.8 124 567 1.75 5959

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 207.1 54.8 214 286 1.20 4806

Use Lake P Concs TRUE for S354 & S351 Lake Rleases Total 1547.6 302.7 158 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New La ke Rel ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S678 Cmax 0

Other C139 Cmax 0

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 0.0 0.0 1.00

Scale_S6 105 1 1.00

Scale_s7 120 1 0.0 0.0 1.00

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 0.0 1.00 9/1/10 19:32 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# Scenario: 3 A

‐ STA Expansion Only Mean Flow kac

‐ ft/yr

STA Expansion kac

257 212 233 0.0

78 242 61

0 0

25 0

0.0 187 233

199

0 0 267 0

0.0

0 2

7.0 0

160

0 0 233 25

0 00

140 0 0

0 0

84 59 0

248 85

57 0

0

602 0 99 203

78 122 321 203

15.6 15.0 10

0.0

50 101 583 253 327 102

Totals

STA Outflow TP ppb 11.5 11.4 11.5 11.5 11.3 11.6 11.5

STA Expansion kac 0.0 15.6 15.0 30.6

STA Total Area kac 5.1 7.9 32.1 15.1 21.7 5.1 87.1

STA Outflow kacf/yr 50 101 583 253 327 102 1416

WCA Inflow kacft 734 253 429 1416

Inputs for Scenario Base_11_5 11.5 ppb Designs, 12 ft FEB in WB, STA Expansion in Other Basins

Diversion Rules Mass Ba lance Summary Base_11_5 project_base_11_5.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 1000 Area Flow Load Conc Flow Load Conc HLR HLR Max

S5A Div (ECART) S5A Div HILLS_C 0 800 divert to hills STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 200 low

‐ flow bypass to WPB STA1E 5.1 109 20.4 152 102 1.5 11.6 1.77 7.1

S5A Div to FEB FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 21.7 321 78.9 199 327 4.6 11.3 1.24 7.0

FEB S5A Outflow STA1DW HILLS_C 0 diversion to Hills STA2B 15.1 248 46.1 151 253 3.6 11.5 1.37 6.9

C51W Outflow EAST STA1E 0.56 600 direct to STA1E STA34 32.1 602 91.6 123 583 8.3 11.5 1.56 6.6

C51W Outflow EAST STA1_DW 1 direct to STA1DW STA5 7.9 122 24.3 161 101 1.4 11.4 1.29 3.7

C51W Outflow EAST FEB_S5A 1 remainder to E ast STA6 5.1 78 15.5 161 50 0.7 11.5 1.27 3.7

STA1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 87.1 1479 276.7 152 1416 20.0 11.5 1.42

S6 Runoff STA2CB NNRC 0.12 S6 divert to NNR

NNR Canal FEB34 STA34 0 100 NNR LowQ Bypass to STA34

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394

Treated Inflow Outflows

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 RES_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 7 F E B

_ S 5 A 0

. 000

. 0 # N / A0 0

. 0 # N / A0 0

HRT days 60 30 90 30 F E B

_ 3 4 0

. 000

. 0 # N / A0 0

. 0 # N / A0 0

Bypass Depth ft 44 12 12 4 FEB_56 7.0 140 39.9 231 84 15.6 151 155 1

LowQ Bypass cfs 100 100 100 200 Total F E B 0

. 000

. 0 # N / A0 0

. 0 # N / A

Max Qin cfs 2000 4000 2500 1000

Max Qo ut cfs 1000 500 500 100

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5

Regulation Schedule FEB_REG not implemented Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release REL_STA not implemented kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release not implemented TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Farm Irrig kac not implemented TS_FEBS5A 233.0 61.7 214 322 1.87 4621

TS_STA1DW 87.8 17.2 158 121 1.38 2679

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 15 15.6 0 TS_STA1E 108.9 20.4 152 150 0.89 644

Fraction SAV 0.67 0.67 0.4 TS_STA2B 247.7 46.1 151 342 1.93 3531

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 0.0 0.0 0 0 #N/A 0

TS_STA34 602.3 91.6 123 831 1.79 8698

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 198.8 53.8 219 274 1.20 4647

Use La ke P Concs TRUE for S354 & S351 Lake Rleases Total 1478.5 290.7 159 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 11.5 Iterations 1 use iter=1 for testing, 2 for final

Output Interval Days 30 Other

S5A Load Reduc 0% Other

Other Other

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 15.0 0.0 0.89

Scale_S6 105 1 1.00

Scale_s7 120 1 1 5.6 0.0 0.87

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 7.0 0.61 9/1/10 21:42 STA2_CB S6 +

298

C51W

L8

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV

Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 FEB5AN

# Scenario: 4 B

‐ STA Expansion with A1 STA & A2 FEB Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 233

78 233 61 0

0 0

0.0

21 0

3.0 191 233 0

199

0 167 254 0 0

0.0

0

7.0 0 0 25

25

0 133 233

423 0 0

140 0 0

33 0 160

84 58 0

252 87

57 0

0

589 0 98 203

78 122 322 203

13.5 15.0 10

0.0

50 101 570 258 328 100

Totals

STA Outflow TP ppb 11.5 11.4 11.3 11.3 11.4 11.4 11.4

STA Expansion kac 0.0 13.5 15.0 28.5

STA Total Area kac 5.1 7.9 30.0 15.1 21.7 5.1 85.0

STA Outflow kacf/yr 50 101 570 258 328 100 1408

WCA Inflow kacft 721 258 429 1408

Inputs for Scenario Base_A1_RES_2 STA in A1, 8

‐ ft FEB in A2,. 12

‐ ft FEB in C139

Di version Rules Mass Balance Summary Base_A1_RES_ 2 project_base_a1_res_2.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 1000 Area Flow Load Conc Flow Load Conc HLR HLR M

S5A Div (ECART) S5A Div HILLS_C 0 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/ d

S5A Div (ECART) S5A Div HILLS_C 0 low

‐ flow bypass to WPB STA1E 5.1 107 20.1 152 100 1.4 11.4 1.74 7.1

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 21.7 322 79.2 199 328 4.6 11.4 1.24 7.0

FEB S5A Outflow HILLS_C STA1DW 0 diversion to Hills STA2B 15.1 252 46.8 150 258 3.6 11.3 1.39 7.0

C51W Outflow EAST STA1E 0.55 600 direct to STA1E STA34 30.0 589 85.5 118 570 8.0 11.3 1.64 7.0

C51W Outflow EAST STA1_DW 1 direct to STA1DW STA5 7.9 122 24.3 162 101 1.4 11.4 1.29 3.7

C51W Outflow EAST FEB_S5A 0 remainder to East STA6 5.1 78 15.5 162 50 0.7 11.5 1.27 3.7

STA1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 85.0 1470 271.3 149 1408 19.7 11.4 1.44

S6 Runoff STA2CB NNRC 0.1 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to S TA34 STA1W+E 428.8 6.0 11.4

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 828.0 11.6 11.3

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 150.9 2.1 11.5

L8 to North C51W North 0 CERP

NNR to CB STA34 Comp B 0 Original Design for Comp B =1

NNR to CB 2 STA34 Comp B 0 Additional NNR Diversion to CB

Other Treated Inflow Outflows

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 3 7 F EB_S5A 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

HRT days 30 30 90 30 FEB_34 3.0 167 24.8 121 133 16.4 100 165 2

Bypass Depth ft 44 8 12 4 FEB_56 7.0 140 40.0 231 84 15.7 151 155 1

LowQ Bypass cfs 200 400 100 100 Total FEB 3.0 167 24.8 121 133 16.4 100

Max Qin cfs 2000 3000 2500 2000

Max Qout cfs 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FEB_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release REL_STA REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release REL_URB+FARM REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 233.0 61.7 214 322 1.87 4621

Frac C51 Ur ban WS 1 TS_STA1DW 89.4 17.5 158 123 1.36 2679

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 15 13.5 0 TS_STA1E 107.3 20.1 152 148 0.89 644

Fraction SAV 0.67 0.67 0.4 TS_STA2B 252.0 46.8 150 348 1.93 3598

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 589.5 89.6 123 814 1.79 8494

TS_STA34 0.0 0.0 0 0 #N/A 0

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 198.8 53.8 219 274 1.20 4647

Use Lake P Concs TRUE for S354 & S351 Lake Rleases Total 1470.0 289.4 159 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 fo r testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S678 Cmax 0

Other C139 Cmax 0

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 15.0 0.0 0.89

Scale_S6 105 1 1.00

Scale_s7 120 1 16.5 3.0 0.84

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 7.0 0.61 9/1/10 20:21 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# Scenario: 5 A/B

‐ Interim Plan with Temporary A1 FEB & Balance STA

‐ 34 Inflow Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 260

78 59 61 0

107 0

45 0.0

0 0

15.0 212 260 0

207

0 215 59 0 0

0.0

0

0.0 107 0 25

45 25

0 199 0 260

179 0 0

0 0

15 0 160

0 207 26

380 38

0 0

0

393 0 121 203

81 126 270 203

0.0 0.0 10

0.0

57 106 383 429 270 152

Totals

STA Outflow TP ppb 18.3 18.3 11.2 18.2 38.3 20.5 20.4

STA Expansion kac 0.0 0.0 0.0 0.0

STA Total Area kac 5.1 7.9 16.5 15.1 6.7 5.1 56.5

STA Outflow kacf/yr 57 106 383 429 270 152 1397

WCA Inflow kacft 546 429 422 1397

Inputs for Scenario Base_A1_FEB Interim Plan: A1 as FEB, No Additional STA in Central Basin

Diversion Ru les Mass Balance Summary Base_A1_FEB project_base_a1_feb.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 1000 Area Flow Load Conc Flow Load Conc HLR HLR Max

S5A Div (ECART) S5A Div HILLS_C 0 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 low

‐ flow bypass to WPB STA1E 5.1 161 32.2 162 152 3.8 20.5 2.61 9.7

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 6.7 270 68.0 204 270 12.8 38.3 3.38 20.6

FEB S5A Outflow HILLS_C STA1DW 0 diversion to Hills STA2B 15.1 425 72.6 139 429 9.6 18.2 2.34 11.7

C51W Outflow EAST STA1E 0.7 600 direct to STA1E STA34 16.5 393 47.6 98 383 5.3 11.2 1.98 8.8

C51W Outflow EAST STA1_DW 0.6 1200 direct to S TA1DW STA5 7.9 126 33.4 214 106 2.4 18.3 1.34 6.1

C51W Outflow EAST FEB_S5A 0 remainder to East STA6 5.1 81 21.4 214 57 1.3 18.3 1.32 6.0

STA1W Distrib STA1W STA1E 0.1 WPB C STA1E Total STA 56.5 1455 275.2 153 1397 35.2 20.4 2.15

S6 Runoff STA2CB NNRC 0 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to STA34 STA1W+E 422.1 16.6 31.9

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 812.3 14.9 14.9

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 163.1 3.7 18.3

L8 to North C51W North 0 CERP

NNR to CB STA34 Comp B 1 Original Design for Comp B =1

NN R to CB 2 STA34 Comp B 0.49 Additional NNR Diversion to CB

Treated Inflow Outflows

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 15 0 FEB_S5A 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

HRT days 30 14 90 30 FEB_34 15.0 215 29.6 112 199 15.7 64 44 1

Bypass Depth ft 44 4 12 4 FEB_56 0.0 0 0.0 108 0 0.0 #N/A 0 0

LowQ Bypass cfs 200 400 100 100 Total FEB 15.0 215 29.6 112 199 15.7 64

Max Qin cfs 2000 2775 2500 2000

Max Qout cfs 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FE B_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release REL_STA REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release REL_URB+FARM REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 259.5 67.7 211 358 1.87 5153

Frac C51 Urban WS 1 TS_STA1DW 40.6 7.9 157 56 1.74 1200

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 0 00 TS_STA1E 130.5 24.6 153 180 0.85 644

Fraction SAV 0.67 0.67 0.4 TS_STA2B 424.6 72.6 139 586 2.00 6153

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 393.8 60.4 124 544 1.73 5579

TS_STA34 0.0 0.0 0 0 #N/A 0

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 207.1 54.8 214 286 1.20 4806

Use Lake P Concs TRUE for S354 & S 351 Lake Rleases Total 1456.2 287.9 160 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S678 Cmax 0

Other C139 Cmax 0

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 0.0 0.0 1.00

Scale_S6 105 1 1.00

Scale_s7 120 1 15.0 15.0 0.75

Scale_s8 120 0 1.00

S cale_Annex 18 1 0.0 0.0 1.00 8/31/10 22:08 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# Scenario: 6 C

‐ C51E Diversion /FEB, STA Expansion Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 239

78 228 61 0

0 0

0.0

155 0

0.0 57 239 0

199

0 0 382 0 0

1.7

249

7.0 0 0 25

25

0 0 103

0 47 112

140 0 173

0 202 160

84 58 0

291 146

57 28

187

718 0 114 16

78 122 327 203

22.0 8.0 10

0.0

50 101 693 296 328 116

Totals

STA Outflow TP ppb 11.5 11.4 11.5 11.5 11.5 11.5 11.5

STA Expansion kac 0.0 22.0 8.0 30.0

STA Total Area kac 5.1 7.9 38.5 15.1 14.7 5.1 86.5

STA Outflow kacf/yr 50 101 693 296 328 116 1584

WCA Inflow kacft 844 296 444 1584

Inputs for Scenario C51E_AA C51E Diversion, STA exp in CB, FEB in C139

Diversion Rules Mass Balance Summary C51E_AA project_c51e_aa.xls Run Da te

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 1 1000 Area Flow Load Conc Flow Load Conc HLR HLR M a

S5A Div (ECART) S5A Div HILLS_C 0 300 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/ d

S5A Div (ECART) S5A Div HILLS_C 0 200 low

‐ flow bypass to WPB STA1E 5.1 123 18.7 123 116 1.6 11.5 2.00 7.0

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 14.7 327 63.2 157 328 4.7 11.5 1.86 8.6

FEB S5A Outflow HILLS_C STA1DW 1 75 diversion to Hills STA2B 15.1 291 64.0 178 296 4.2 11.5 1.61 7.0

C51W Outflow EAST STA1E 0.31 600 direct to STA1E STA34 38.5 718 110.3 125 693 9.8 11.5 1.55 6.8

C51W Outflow EAST STA1_DW 1 300 direct to STA1DW STA5 7.9 122 24.2 161 101 1.4 11.4 1.29 3.8

C51W Outflow EAST FEB_S5A 1 0 remainder to East STA6 5.1 78 15.5 161 50 0.7 11.5 1.27 3.7

STA1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 86.5 1659 296.0 145 1584 22.5 11.5 1.60

S6 Runoff STA2CB NNRC 0.73 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to S TA34 STA1W+E 444.0 6.3 11.5

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 989.4 14.0 11.5

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 150.9 2.1 11.4

L8 to North C51W North 0 CERP

NNR to CB STA34 Comp B 0 Original Design for Comp B =1

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 1.67 7 FEB_S5A 1.7 249 57.7 188 202 45.1 181 561 1

HRT days 30 14 90 30 FEB_34 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Bypass Depth ft 44 4 12 4 FEB_56 7.0 140 40.0 231 84 15.7 151 153 1

LowQ Bypass cfs 200 400 100 100 Total FEB 1.7 249 57.7 188 202 45.1 181

Ma x Qin cfs 2000 4000 2500 2000

Max Qout cfs 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FEB_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release URB+STA+REF REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 351.5 80.9 186 485 1.67 8130

Frac C51 Urban WS 1 TS_STA1DW 148.5 23.2 127 205 0.49 829

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 8 2 2 0 TS_STA1E 123.3 18.7 123 170 0.88 644

Fraction SAV 0.67 0.67 0.4 TS_STA2B 118.3 25.2 173 163 1.80 1499

Ehnanced SAV_3 SAV_3 PEW_3 T S_FEB34 0.0 0.0 0 0 #N/A 0

TS_STA34 717.7 110.3 125 991 1.82 10491

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 198.8 53.8 219 274 1.20 4647

Use Lake P Concs TRUE for S354 & S351 Lake Rleases Total 1658.0 312.1 153 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S 678 Cmax 0

Refuge Min Flow 500 C139 Cmax 0 See FEB_STA Sheet, Provision to direct more flow to refuge in dry years.

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 9.7 1.7 0.91

Scale_S6 105 1 1.00

Scale_s7 120 1 22.0 0.0 0.82

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 7.0 0.61 8/31/10 22:34 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# Scenario: 7 D

‐ C51E Diversion/FEB, A2 FEB+STA, A1 STA Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 239

78 217 61 0

0 0

0.0

155 0

4.0 57 239 0

199

0 215 371 0 0

1.7

249

7.0 0 0 25

25

0 174 103

492 47 112

140 0 173

40 202 160

84 58 0

291 146

57 28

187

706 0 114 16

78 122 327 203

19.0 8.0 10

0.0

50 101 683 296 328 116

Totals

STA Outflow TP ppb 11.5 11.4 11.5 11.5 11.5 11.5 11.5

STA Expansion kac 0.0 19.0 8.0 27.0

STA Total Area kac 5.1 7.9 35.5 15.1 14.7 5.1 83.5

STA Outflow kacf/yr 50 101 683 296 328 116 1574

WCA Inflow kacft 834 296 444 1574

Inputs for Scenario C51E_A1_RES_3 C51E Div + FEB, A2 8 ft FEB + STA Exp, A1 STA, C 139 12 ft FEB

Diversion Rules Mass Balance Summary C51E_A1_RES_ 3 project_c51e_a1_res_3.xls Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 1 1000 Area Flow Load Conc Flow Load Conc HLR HLR Ma

S5A Div (ECART) S5A Div HILLS_C 0 300 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 200 low

‐ flow bypass to WPB STA1E 5.1 123 18.7 123 116 1.6 11.5 2.00 7.0

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 14.7 327 63.2 157 328 4.7 11.5 1.86 8.6

FEB S5A Outflow HILLS_C STA1DW 1 7 5 diversion to Hills STA2B 15.1 291 64.0 178 296 4.2 11.5 1.61 7.0

C51W Outflow EAST STA1E 0.31 600 direct to STA1E STA34 35.5 706 103.1 118 683 9.7 11.5 1.66 7.4

C51W Outflow EAST STA1_DW 1 300 direct to STA1DW STA5 7.9 122 24.3 162 101 1.4 11.4 1.29 3.7

C51W Outflow EAST FEB_S5A 1 0 r emainder to East STA6 5.1 78 15.5 162 50 0.7 11.5 1.27 3.7

STA1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 83.5 1647 288.8 142 1574 22.4 11.5 1.65

S6 Runoff STA2CB NNRC 0.73 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to STA34 STA1W+E 444.0 6.3 11.5

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 979.4 13.9 11.5

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 150.9 2.1 11.5

L8 to North C51W North 0 CERP

NNR to CB STA34 Comp B 0 Original Design for Comp B =1

Area Flow Load Conc Flow Load Conc Depth cm

FE B Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 1.67 4 7 FEB_S5A 1.7 249 57.7 188 202 45.1 181 561 1

HRT days 30 30 90 30 FEB_34 4.0 215 32.4 122 174 21.6 101 163 2

Bypass Depth ft 44 8 12 4 FEB_56 7.0 140 40.0 231 84 15.7 151 155 1

LowQ Bypass cfs 200 400 100 100 Total FEB 5.7 463 90.1 158 376 66.7 144

Max Qin cfs 2000 2500 2500 2000

Max Qout cfs 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FEB_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release URB+STA+REF REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cfs

Fa rm WS Release REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 351.5 80.9 186 485 1.67 8130

Frac C51 Urban WS 1 TS_STA1DW 148.5 23.2 127 205 0.49 829

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 8 1 9 0 TS_STA1E 123.3 18.7 123 170 0.88 644

Fraction SAV 0.67 0.67 0.4 TS_STA2B 118.3 25.2 173 163 1.80 1499

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 706.7 108.7 125 976 1.81 10310

TS_STA34 0.0 0.0 0 0 #N/A 0

Base Period for Concs 1 1= 2005

‐ 2009,2 = 1995

‐ 2009 TS_FEB56 198.8 53.8 219 274 1.20 4647

Use Lake P Concs TRUE for S354 & S351 Lake Rleases Total 1647.1 310.5 153 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Re l ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S678 Cmax 0

Refuge Min Flow 500 C139 Cmax 0 See FEB_STA Sheet, Provision to direct more flow to refuge in dry years.

Watershed Areas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 9.7 1.7 0.91

Scale_S6 105 1 1.00

Scale_s7 120 1 23.0 4.0 0.78

Sc ale_s8 120 0 1.00

Scale_Annex 18 1 0.0 7.0 0.61 9/1/10 21:15 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# Scenario: 8 C/D

‐ Interim Plan with Temporary A1 FEB, Balance STA

‐ 34 Inflow, C51E Div/FEB Mean Flow kac

‐ ft/yr

STA Expansion kac

2

257 212 254

78 59 61 0

107 0

44 0.0

0 0

15.0 212 254 0

207

0 215 59 0 0

1.7

106

0.0 107 0 25

44 25

0 199 0 148

180 7 0

0 29

15 99 160

0 207 24

409 54

0 70

0

393 0 107 203

81 126 281 203

0.0 0.0 10

0.0

57 106 384 458 279 110

Totals

STA Outflow TP ppb 18.3 18.3 11.3 19.2 37.3 12.9 20.0

STA Expansion kac 0.0 0.0 0.0 0.0

STA Total Area kac 5.1 7.9 16.5 15.1 6.7 5.1 56.5

STA Outflow kacf/yr 57 106 384 458 279 110 1393

WCA Inflow kacft 547 458 389 1393

Inputs for Scenario C51E_Interim Phase 1

‐ A1 as 4 ft FEB, C51 Rockpit 10 kacf (6/44 ft ), 3 yrs ), No STA expansion; Partial Diversion to West

Diversion Rules Mass Balance Summary Run Date

Diversion Defaul t Diverted to Fraction Qmax Description Inflows Outflows

C51E Diversion C51W Canal EAST 0 1000 Area Flow Load Conc Flow Load Conc HLR HLR Ma

S5A Div (ECART) S5A Div HILLS_C 0 divert to hills up to qmax STA kac kac

‐ ft mt ppb kac

‐ ft mt ppb cm/d cm/d

S5A Div (ECART) S5A Div HILLS_C 0 low

‐ flow bypass to WPB STA1E 5.1 117 21.9 152 110 1.7 12.9 1.90 8.1

S5A Div to FEB North FEBS5A FEBS5A_N 0 northern STA.FEB STA1W 6.7 281 66.0 190 279 12.8 37.3 3.51 21.6

FEB S5A O utflow HILLS_C STA1DW 1 200 diversion to Hills STA2B 15.1 453 78.7 141 458 10.9 19.2 2.50 12.3

C51W Outflow EAST STA1E 0.6 700 direct to STA1E STA34 16.5 393 47.8 98 384 5.3 11.3 1.98 8.8

C51W Outflow EAST STA1_DW 0.7 1000 direct to STA1DW STA5 7.9 126 33.4 214 106 2.4 18.3 1.34 6.1

C51W Outflow EAST FEB_S5A 0 remainder to East STA6 5.1 81 21.4 214 57 1.3 18.3 1.32 6.0

STA1W Distrib STA1W STA1E 0 WPB C STA1E Total STA 56.5 1451 269.1 150 1393 34.4 20.0 2.14

S6 Runoff STA2CB NNRC 0 S6 divert to NNR

NNR Canal FEB34 STA34 0 NNR LowQ Bypass to STA34 STA1W+E 388.6 14.6 30.4

STA56 Distrib STA5 STA6 0.39 Balance STA56 Loads, Hint= 0.394 STA2+34+B 841.3 16.2 15.6

L8 to STA1N C51W FEBS5A_N 0 To FEB S5AN (Rest to C51W) STA5+6 163.1 3.7 18.3

L8 to No rth C51W North 0 CERP

NNR to CB STA34 Comp B 1 Original Design for Comp B =1

NNR to CB 2 STA34 Comp B 0.48 Additional NNR Diversion to CB

Treated Inflow Outflows

Area Flow Load Conc Flow Load Conc Depth cm

FEB Calculations FEB_S5A FEB_34 FEB_56 FEBS5A_N FEBs kac kac

‐ ft mt ppb kac

‐ ft mt ppb Mean Min

DMSTA calibration RES_3 RES_3 RES_3 EMG_3 FEBS5A_N 0.0 0 0.0 #N/A 0 0.0 #N/A 0 0

Area kac 1.7 15 0 FEB_S5A 1.7 106 27.5 210 99 20.9 171 108 5

HRT days 14 14 90 30 FEB_34 15.0 215 29.7 112 199 15.7 64 45 1

Bypass Depth ft 5.9 4 12 4 FEB_56 0.0 0 0.0 68 0 0.0 #N/A 0 0

LowQ Bypass cfs 200 400 50 100 Total FEB 16.7 321 57.2 144 298 36.6 99

Max Qin cfs 2000 2775 2500 2000

Max Qout cf s 1000 1000 500 500

Control Depth ft 0.5 0.5 0.5 0.5

Min Release Depth ft 0.5 0.5 0.5 0.5 Optional:

Regulation Schedule FEB_REG FEB_REG FEB_REG See FEB_Design Sheet Input Time Series Flow Load Conc Flow Flow CV Flow Max

STA WS Release REL_STA REL_STA REL_STA See input series sheet kac

‐ ft mt ppb cfs

‐ cfs

Farm WS Release REL_FARM "" TS_FEBS5A_N 0.0 0.0 0 0 #N/A 0

Frac Irrig Demand 0.5 0.25 TS_FEBS5A 253.5 66.3 212 350 1.87 5032

Frac C51 Urban WS 1 TS_STA1DW 56.3 10.9 157 78 1.34 1000

STA Expansion STA1WX STA34X STA56X TS_STA1W 0.0 0.0 0 0 #N/A 0

Area kac 0 00 TS_STA1E 116.8 21.9 152 161 0.91 744

Fraction SAV 0.67 0.67 0.4 TS_STA2B 423.7 72.5 139 585 2.00 6132

Ehnanced SAV_3 SAV_3 PEW_3 TS_FEB34 394.7 60.5 124 545 1.73 5600

TS_STA34 0.0 0.0 0 0 #N/A 0

Base Period for Concs 1 1= 2005

‐ 2009, 2 = 1995

‐ 2009 TS_FEB56 207.1 54.8 214 286 1.20 4806

Use Lake P Concs TRUE for S354 & S351 Lake Rleases Total 1452.2 286.9 160 0 0.00 0

C139 Load Reduc 0% Max TP ppb 0

STA Duty Cycle 0.95 New Lake Rel ka 0

Target Conc ppb 11.5 Iterations 1 use i ter=1 for testing, 2 for final

Output Interval 30 S5A/C51 Cmax 0

S5A Load Reduc 0% S678 Cmax 0

Other C139 Cmax 0

Watershed Ar eas Land kac Fraction New STA kac FEB kac Runoff Rescale

Scale_s5A 133 1 1.7 1.7 0.97

Scale_S6 105 1 1.00

Scale_s7 120 1 15.0 15.0 0.75

Scale_s8 120 0 1.00

Scale_Annex 18 1 0.0 0.0 1.00 8/31/10 20:26 STA2_CB S6 +

298

C51W

STA34 FEB34

FEB5A NNR

Wpb

Hills S8

G136+ 298 S5A

EBWCD

STA1E C51E C51W S7 + Lake

+298 Lake

S361 S5A

ECP DIV Lake

Mia

STA1W FEB56

STA5 C139 +X

L3

STA6 STA / FEB5AN

L8

# February 16, 2010 1



# Modeling Phosphorus Dynamics in Everglades Wetlands and 2



# Stormwater Treatment Areas 3

4



# William W. Walker, Jr. 1 

# and Robert H. Kadlec 2 

# 5

1 

# Environmental Engineer, Concord, Massachusetts, bill@wwwalker.net 6

2 

# Wetland Management Services, Chelsea, Michigan, rhkadlec@chartermi.net

, 7

8



# Submittted to 9



# Based on Presentation at GEER 2008 Symposium 10



# Abstract 11

12

Longitudinal gradients in phosphorus (P) stor ed in the water column, vegetation, and 13

soils develop in the wetlands where inflow P concentrations exceed background levels. 14

Prior to the mid 1990’s, the Everglades regional P gradient ranged from 100-200  g L -1 

# 15

in marsh inflows to background levels of 4-8  g L -1 

# . Subsequent implementation of P 16

controls, including agricultural Best Manage ment Practices (BMPs) and Stormwater 17

Treatment Areas (STAs), reduced the averag e inflow concentration along the northern 18

edge of the Water Conservations Areas (WCAs) to approximately 33  g L -1 

# in 2007- 19

2009. Additional P controls are being implemented and further measures beyond those 20

currently planned will be required to restore the entire marsh. This paper describes the 21

evolution and applicatio n of relatively simple mass-balan ce models to simulate P storage 22

and cycling processes along P gradients in th e STAs and downstream marsh. The models 23

are practical engineering tools that have been extensively applied to the design of 24

Everglades regional P control plans involvi ng combinations of s ource controls, water 25

management, reservoirs, and STAs, as well as in simulating P dynamics in natural 26

marshes immediately downstream of treated and untreated discharges. 27

# D R A F T 2



# Key Words 28

Everglades, phosphorus, modeling, marsh, e ngineering, wetland treatment areas 29

30



# Introduction 31

32

As water with elevated phosphorus (P) moves through a wetland ecosystem, P is removed 33

and a gradient of decreasing P concentration is produced along the flow path (Reddy et 34

al., 1993; Craft et al., 1993a; Craft et al, 1993b; Walker, 1995; Kadlec & Walker, 1999). 35

The water-column P gradient is typically accompanied by gradients of P storage in 36

vegetation and soils (Figure 1). Phosphorus originating in inflows and atmospheric 37

deposition is cycled within the marsh and ultimately stored in accreting peat or 38

transported downstream. Historically, the wa ter-column P gradient in the Everglades 39

marsh ranged from 100-200  g L -1 

# at the inflows to background levels of 4-8  g L -1 

# 40

(Figure 2). Nearly two decad es of monitoring and research by the South Florida Water 41

Management District (SFWMD) and other agen cies have established that Everglades 42

wetland ecosystems change dramatically along the P gradient and that native slough and 43

sawgrass communities are viable only at P concentrations below 10  g L -1 

# , expressed as a 44

long-term geometric mean (Payne et al, 2003). With sheet flow hydraulics, water quality 45

at the edge of the marsh is determined by the quality of the inflows. Restoring and 46

protecting the entire marsh is li kely to require inflow P con centrations equivalent to the 47

marsh P criterion (Payne et al, 2008). This is in contrast to la kes or other well-mixed 48

water bodies where inflows with concentratio ns exceeding water quality standards do not 49

trigger violations of ambient standards because they are rapidly dispersed, diluted, and/or 50

assimilated in receiving waters. 51

52

Spatial and temporal variations in the Evergl ades regional P gradient over the past three 53

decades are shown in Figure 2. Substantial progress has been made since 1993 in 54

reducing P concentrations in the inflows to the Water Conservation Areas (WCAs) 55

through implementation of agricultural Be st Management Practices (BMPs) and 56

construction of Stormwater Treatment Areas (STAs) (SFWMD, 2009b). As these control 57

# D R A F T 3

measures were implemented, the combined WCA inflow concentration decreased from 58

~170  g L -1 

# in 1980-1989 to ~61  g L -1 

# in 2000-2009. Within the last decade, the three59

year rolling-average inflow c oncentration decreased from ~64  g L -1 

# in 2001-2004 to 60

~33  g L -1 

# in 2007-2009. The historical reduction s in inflow concentration have 61

cascaded through the networks of canals and ma rshes to cause P concentration reductions 62

in the outflows from each WCA (Figure 2). Further reductions in WCA inflow and 63

outflow concentrations are expected to result from implementation of additional source64

control and treatment measures. 65

66

The effect of the P control program is to disp lace the P gradient ups tream of the marsh so 67

that most of it occurs within STAs construc ted on formerly agricu ltural land (Figure 1). 68

At the same time, elevated P concentrati ons driving the gradie nt are reduced through 69

implementation of BMPs. When long-term re storation objectives are achieved, the marsh 70

gradient will be substantially reduced relative to historical conditions and have long-term 71

geometric mean P concentrations ranging from 10  g L -1 

# to background levels of 4-8  g 72

L -1



# . 73

74

This paper describes the evolution of relativel y simple mass-balance models to simulate P 75

storage and cycling processes along P gradients in the STAs and marsh. In the context 76

of the Everglades restoration effort, the m odels and associated software have provided 77

practical engineering tools for designing P control measures involving combinations of 78

source controls, regional water management, reservoirs, and STAs, as well as for 79

simulating marsh responses to variations in fl ow and P load in transects downstream of 80

WCA inflow points. 81

82



# Model Evolution 83

84

The models described below were develope d to support evaluation of multiple STA 85

design alternatives by engineering profe ssionals without requ iring site-specific 86

calibration data or specialized expertise in wetland modeli ng. Model simplicity results 87

# D R A F T 4

from aggregation of key variables and processes controlling phosphorus storage and 88

cycling. The simplifying assumptions are s upported by calibration and testing against 89

several dozen datasets that describe phosphorus removal in experimental prototypes, 90

field-scale test cells, full-scale STAs, a nd natural wetlands (Walker & Kadlec, 2001; 91

2005). These datasets provide bases for ca libration and testing unde r a wide range of 92

conditions (e.g. size, water depth, P concentr ation, P load, velocity, vegetation types, 93

inflow variability) and for estimating uncertain ty associated with model forecasts. While 94

the modeling effort was initiated to support STA design, the fundamental concepts (mass 95

balance, hydraulics, P cycling mechanisms) operating along a P gradie nt (Figure 1) also 96

apply to natural wetlands. Differences betw een the STAs and naural marsh related such 97

factors as water depth, hydraulic loads, antece dent soils, and vegeta tion are considered by 98

explicitly including t hose factors in the model(s) or by defining limits of application 99

consistent with calibration datasets. 100

101

Figure 3 shows P storage compartments and fl uxes associated with four models that 102

evolved over the 1995-2008 period (Kadlec, 1994; Walker, 1995; Walker & Kadlec, 103

1999; Walker & Kadlec, 2005; Kadlec, 2006). Th ey involve different combinations of 104

three fundamental storage compartments (water column, biota, soil) and associated net 105

fluxes between compartments. While P ge nerally moves in both directions between 106

compartments via different mechanisms, the aggregated models simulate the net fluxes 107

that ultimately drive the mass balance. Model structures represent P storage and net 108

fluxes per unit area of marsh. These are coup led with hydraulic models to predict water 109

movement and P transport. Excel spreadsh eet software developed to support model 110

applications is limited to relatively simple one-dimensional hydraulic models 111

representing sheet flow along a marsh transect or STAs with individual treatment cells 112

connected in series and/or parallel. Th e P cycling variables and equations can be 113

translated to more complex hydraulic models capable of predicting two-dimensional flow 114

and mass transport in an STA or marsh. For example, Chen et al (2009) have included 115

DMSTA’s P cycling algorithms in a tw o-dimensional hydraulic model of WCA-1. 116

117

# D R A F T 5

Models with greater complexity have been developed for describing water and 118

phosphorus movement in STAs (Guar do and Tomasello 1995; HydroQual, 1998 119

Moustafa and Hamrick, 2000) and Everglades marsh (Fitz and Trimbel, 2006; Munson et 120

al, 2002; Jawitz et al., 2008). They genera lly account for two-di mensional spatial and 121

temporal variability and have several state variables and adjustable parameters. Most 122

require enhanced computers, long run times, site-specific calibrati on data, and special 123

expertise to calibrate and a pply. These requirements ge nerally preclude engineering 124

applications to STA design. The Evergl ades Landscape Model (ELM, Fitz and 125

Trimbel,2006) has been extensively used in the Everglades restoration effort. It simulates 126

system-wide variations in marsh hydrology, water quality, soils, and vegetation in 127

response to variations in marsh inflows and other factors project ed to occur in response to 128

long-term restoration efforts. The models described below can be used to evaluate 129

localized impacts of discha rges and to provide inflow boundary conditions for ELM 130

applications to the entire Everglades marsh. 131



# Steady-State STA Design Model (STADM) 132

133

The STA design model (STADM) (Walker, 1995) was used to develop initial designs for 134

~29,000 hectares of STAs to achieve a long-term flow-weighted mean outflow 135

concentration of 50  g L -1 

# (Burns and McDonnell, 1994). A modified version that places 136

a lower bound on P concentration (Kadlec, 1994; Kadlec and Wallace, 2009) was used in 137

the initial design of STA-3/4 (Burns and McDonnell, 1999). Knowledge and experience 138

gained through research, opera tion, and monitoring of these initial STAs subsequently 139

provided a technical basis for optimizing a nd expanding the STAs to achieve lower P 140

concentrations, as well as for improving th e models to support that effort (SFWMD, 141

2009b). 142

143

The STADM simulates the long-term-averag e water-column P gradient along a marsh 144

transect as a function of the average inflow volume, inflow load, flow-path width, and 145

atmospheric deposition. The model includes one P storage compartment (water column) 146

and three P fluxes: inflow, outfl ow, and net removal in the ac creting peat (Figure 3). 147

# D R A F T 6

hort-term variations in P storage and cycli ng in vegetation and soils are essentially 148

embedded in the calibration. Because the desi gn objective was expressed as a long-term 149

flow-weighted mean, predictions of short-term variations in P concentration were not 150

required to support the 50  g L -1 

# STA designs. A st eady-state model is not sufficient, 151

however, for designing STAs to achieve lowe r P concentrations driven by highly pulsed 152

inflows (see DMSTA, below) 153

154

The STADM assumes that the average net P re moval rate per unit area is proportional to 155

the average water-column concentration. No P removal is assumed to occur when the 156

marsh is nearly dry (water depth < 30 cm). The proportionality constant (“net settling 157

rate” = 10.2 +/- 1.4 meters/yr) was calibrated to peat accretion measurements along the P 158

gradient in the WCA-2A marsh downstream of outflows from WCA-1 (Figure 2). The 159

peat data provided an integral measure of net P removal over a 26-year period. Global 160

distribution of fallout from nuclear bomb testing in 1963 pl aced a layer of radioactive 161

Cesium-127 in the soil profile. The accumulated soil P was estimated by vertically 162

integrating from the peak in Cesium-127 content to the surface using soil cores collected 163

at 24 monitoring sites (Reddy et al., 1991, 1993; Craft and Richardson, 1993ab). The 164

model was tested against limited water-colum n concentration data along the same marsh 165

transects (Walker, 1995). Because of th e limited quantity and the high spatial and 166

temporal variability in the water column data, the integrated peat accretion data provided 167

a preferred basis for calibrating the model to predict long-term P removal rates. Data 168

from wetland treatment areas sufficient to suppo rt calibration were not available at the 169

time of STADM development. 170

171

Effects of variability in the inflows, water depth, hydrauli cs, and vegetation types were 172

embedded in the STADM calibration to the ma rsh. In applying the model to design the 173

50  g L -1 

# STAs, it was assumed that STA vege tation types and P cycling processes 174

would be similar to those in the upper porti on of the P gradient in the WCA-2A marsh 175

used for calibration (predominantly cattail). Potentials for regulating STA inflow 176

volumes, flow distribution, water depths, and vegetation to optimize treatment suggested 177

that the model calibrated to a natural wetla nd would generate conservative forecasts of 178

# D R A F T 7

STA performance. Subsequent data from full-scale treatment cells with primarily 179

emergent vegetation indicated an average net settling rate of 11.4 m/yr as compared with 180

the STADM calibrated value of 10.2 m/yr (Walker & Kadlec, 2005). Average net 181

settling rates computed for entire STAs w ith both emergent and submerged vegetation 182

operated in design ranges have ra nged from ~10 to ~25 m/yr. 183

184



# Everglades Phosphorus Model (EPGM) 185

186

The Everglades Phosphorus Gradient Model (EPGM) (Walker & Kadlec, 1996; 187

Kadlec & Walker, 1999) tracks P accumula tion in soils along marsh transects 188

downstream of inflows with P concentrations above mars h background levels (Figure 1, 189

Figure 3). While not required for STA design, predictions of soil P variations in the 190

marsh are useful because some ecosystem comp onents are driven more by soil P content 191

(cattails, other rooted vegeta tion) than by water-column c oncentration (periphyton, algae, 192

invertebrates). There is subs tantially greater uncertainty associated with modeling the 193

soil P compartment, as compared with mode ling the water column. This uncertainty 194

reflects inherent complexities of soil interactions with ve getation and water column, as 195

well as limitations in soils data related to sampling artifacts and hi gh spatial variability 196

(Grunwald et al., 2004; Cohen et al., 2009). EPGM provides the simplest representation 197

of the soil P compartment consistent with the data available for calibration. 198

199

The water-column component of EPGM is id entical to the STA design model. Both 200

assume sheet-flow hydraulics and are calibra ted to data primarily from WCA-2A. 201

Vertical mixing within the soil profile is assumed to be minimal. This assumption is 202

supported by substantial verti cal and longitudinal gradients in soil P content observed in 203

the WCA-2A soil cores used for calibrating the STADM (Kadlec & Walker, 1999). The 204

accumulation of soil mass in EPGM is driv en by a correlation between soil mass 205

accretion rate and soil P accretion rate calib rated to dated soil cores in WCA-2A and 206

tested against limited data from other WCAs. This correlation determines a relationship 207

between the average P content of accreting pe at and the average P concentration in the 208

# D R A F T 8

water column (Kadlec & Walker, 1999). EP GM calibration to WCA- 2A transect data 209

indicates that soil accretion ra tes vary from 0.1 to 1.0 kg/m 2 

# -yr and the P content of 210

accreting peat varies from 500 to 1400 mg/kg as the average water column P varies from 211

5 to 100  g L -1



# . 212

213

EPGM has been applied to evaluate the pot ential impacts of dist ributing STA outflows 214

with a P concentration of 50  g L -1 

# into previously un-impacted marsh areas along the 215

northern edge of the WCAs (Walker & Kadlec, 1996). Impacts are expressed in terms of 216

marsh areas exceeding water-column and soil P cr iteria as a function of time as the soil P 217

gradient (Figure 1) develops downstream of th e STA outflows. Cattail densities are also 218

predicted based upon an empirical correlation wi th soil P contents. The development of 219

steady-state soil P profiles requires one or more decades, depending on the inflow 220

concentration, initial soil P content, dept h of soil being tracked, and marsh hydroperiod. 221

Once the soil P profile is fully developed, the EPGM calibration to WCA-2A indicates 222

that marsh areas with water-colu mn P concentrations exceeding 10  g L -1 

# correspond to 223

areas with steady-state soil P c ontents exceeding ~650 mg/kg. 224

225



# Dynamic Model for Stormwater Treatment Areas (DMSTA) 226

227

DMSTA (Walker & Kadlec, 2001-2005; Kadlec, 2006) was developed to support design 228

of STAs to achieve outflow TP concentrations approaching the 10  g L -1 

# criterion. 229

Achieving low P levels require s designing an STA to operate within limited ranges of 230

inflow P concentrations and loads, as well as optimizing vegetation types, water depths, 231

and hydraulics to treat highly pulse d basin runoff. Considerati on of these factors requires 232

a dynamic model with an additional P stor age compartment to represent labile 233

phosphorus stored in vegetati on and litter (Figure 4). This compartment regulates P 234

uptake, recycling, and generation of stable P residuals stored in accreting peat. The 235

initial structure and equations were similar to the autobiotic wetland P model described 236

by Kadlec (1997). Those equations have been refined and calibrated to various emergent 237

# D R A F T 9

and submerged vegetation types (described be low) based upon data from South Florida 238

wetlands and treatment areas. 239

240

Whereas the STA design model assumed simple sheet-flow hydraulics downstream of the 241

inflows, DMSTA allows simulation of full STA designs involving multiple treatment 242

cells in series and/or parallel with seepag e, bypass constraints based upon water depth or 243

pump capacity, and outlet hydrau lic controls (Figure 4). Design optimization generally 244

involves specification of cell ar eas, configurations, depth re gimes, hydraulic features, and 245

target vegetation communities to achieve trea tment objectives in a cost-effective manner. 246

The model also has a capability for simulati ng regional networks of STAs and reservoirs, 247

driven by 35-year daily flow time series generated by SFWMD’s regional hydrologic 248

models (SFWMD, 2005). Marsh responses downstream of the STAs can also be 249

simulated using the appropriate calibrations. The spreadsheet interface and limited input 250

data requirements facilitate development and comparison of alternative STA designs. 251

252

The first version of DMSTA (Walker & Ka dlec, 2001) was calibra ted to data from 253

approximately 70 treatment cells and wetlands ranging in size from 10 -1 

# to 10 7 

# m 2 

# . Most 254

of the treatment cell datasets were from experi mental tanks and small-scale test cells with 255

different vegetation types operated with cons tant inflows and water depths over periods 256

of one to three years. Data from a trea tment wetland (Boney Marsh) and a full-scale test 257

facility (Everglades Nutrient Removal Pr oject, Chimney et al, 2006) provided the 258

primary bases for calibration. Calibrations were developed for periphyton, emergent 259

vegetation, and submerged vegeta tion based upon data from the largest prototype in each 260

category. A fourth category represented a transition from submerged vegetation to 261

periphyton over a decreasing P gradient. Da ta from the smaller experimental platforms 262

were used for testing calibrations in each vegetation category. This version of DMSTA 263

was used in initial f easibility studies for enhanced STA designs (Burns and McDonnell, 264

2002; Brown and Caldwell, 2002). 265

266

With operation and intensive monitoring of the STAs by SFWMD, substantially more 267

data from full-scale treatment cells and we tlands with dynamic inflows and water depths 268

# D R A F T 10

were available to support development of the second version of DMSTA (Walker and 269

Kadlec, 2005). This most recent version includes calibrations for four wetland types 270

(emergent, submerged, periphyton, and mixed vegetation on natural wetland soils), as 271

well as a calibration for open-wa ter reservoirs. The reser voir calibration is based upon 272

data from shallow lakes in Florida (Burns & McDonnell, 2004) and developed to support 273

evaluation regional plans involvi ng networks of STAs and st orage reservoirs planned for 274

hydrologic restoration purposes (USACE, 2009). 275

276

Steady-state solutions of DMSTA’s P cycling eq uations are mathematically equivalent to 277

the K/C* model (Kadlec, 1994), which is sim ilar to the STA Design Model (Figure 3). 278

Calibrated settling rates are 13-22 m/yr for emergent vegetation, 43-64 m/yr for 279

submerged vegetation, 18-31  g L -1 

# for periphyton, 27-46 m/yr for mixed vegetation on 280

natural wetland soils, and 3-9 m/ yr for reservoirs. The wetland calibrations (first three 281

categories) are in the 60 th 

# to 90 th 

# percentile range of the gl obal distribution of settling 282

rates, based upon data from 282 treatment we tlands (Kadlec and Wallace (2009). Each 283

calibration is applicable under specific ranges of depth, ve locity, and con centration, as 284

determined by the calibration datasets. DMSTA is applicable to treatment cells that have 285

reached a stable operational phase, a process that typically requires one to three years 286

after construction to allow time for the establishment of vegetation and associated P 287

cycles, depending on antecedent soils, water depths, and vegetation. 288

289

The second version of DMSTA has been applie d in several feasibility and design studies 290

providing treatment of additional flows and phosphorus loads from the source basins, as 291

well as integration of STAs and storage re servoirs south and north of Lake Okeechobee 292

(Burns and McDonnell. 2002, 2003; ADA, 2005; Brown and Caldwell, 2002,2005,2007; 293

Black and Veatch, 2006; URS Inc, 2005; HDR Inc, 2006; Camp Dresser and McKee, 294

2007; Tetra Tech, 2008). While developed primarily for use in STA design and 295

optimization, DMSTA can also be used as a di agnostic tool to facilitate interpretation of 296

real-time monitoring data from the STAs. Variations in measured STA outflow 297

concentrations reflect variations in inflow volumes, inflow P loads, water depths, climate, 298

management, P cycling within wetland communities, measurement errors, and other 299

# D R A F T 11

random factors. It is difficult to evaluate the inherent P removal performance of the STA 300

wetland community in the context of da ta variations induced by the other 301

factors. DMSTA factors out the effects of hydrologic variations and STA operations that 302

distribute inflows across cells and regulate water depths. This filtering provides a clearer 303

signal of vegetation function and long-term performance re lative to design simulations 304

and management expectations. 305

306

DMSTA’s structure assumes that flow through each treatment cell is uniformly 307

distributed across its width (sheet flow). While that assumption is consistent with typical 308

design recommendations, hydraulic inefficiencies (short-circu iting, dead zones) can result 309

from spatial variations in ground elevation and remnant farm canals that were not 310

sufficiently filled or plugged at the time of construction (Guardo and Tomasello 1995; 311

Dierberg et al., 2005; DB Envi ronmental Labs, 2006). To so me extent, the effects of 312

these factors are embedded in the DMSTA calibrations and in the tanks-in-series model 313

used to represent each cell (Kadlec and Wa llace, 2009). DMSTA incorporates a depth314

dependent P uptake function that reflects spat ial variations in t opography (typically +/- 30 315

cm relative to the mean ground elevation) and the resulting impacts on hydraulic 316

efficiency. To account for extreme variati ons in topography, the design engineer has the 317

option to adjust the effective treatment area , typically defined as the area flooded at 318

normal operating depth (40 – 60 cm). Fu ture refinements to include explicit 319

consideration of topographi c variations within eac h cell may improve model 320

performance, particularly when water levels ar e relatively low and ri sk of short-circuiting 321

is relatively high. While data requireme nts would limit applicability, the P cycling 322

algorithm can also be superimposed on a full 2-dimensional hydraulic simulation of the 323

STAs, as has been done for WCA-1 (Chen et al., 2009), 324

325

With continued operation and monitoring of the STAs, the database to support further 326

refinement of DMSTA expanded more than three-fold between 2005 and 2009, measured 327

in terms of cell-years. Future versions will provide updated calibrations and additional 328

features useful for design and diagnostic applications. 329

330

# D R A F T 12



# Coupled DMSTA and EPGM 331

332

A fourth model under development links DMSTA and EPGM to simulate three 333

aggregated P storage compartments (water co lumn, vegetation, and soil, Figure 3). In the 334

initial version, the structures and calibrations of the DM STA and EPGM components are 335

unchanged. The soil P compartment is driven by the predicted ne t accretion from the 336

vegetation P storage compartment of DMSTA. The accretion rates are time-variable, as 337

compared with the original EPGM driven by the steady-state water column concentration 338

profile generated by the STADM. 339

340

The long-term decreasing trends in WCA inflow a nd outflow concentrations (Figure 2) 341

suggest that water column P concentrations respond relatively rapidly to reductions in 342

inflow P, despite the substantial of amounts of P stored in the soils of impacted marsh 343

areas, release of which would delay the wate r column response. DMSTA testing results 344

also indicate that explicit simulation of th e soil P compartment may not be necessary for 345

predicting water-column P variations in the natural marsh or in treatment cell outflows in 346

response to trends in the inflow volumes or concentrations once STA vegetation 347

(DMSTA P storage pool) is st abilized. Effects of soil P st orage and exchanges with the 348

water column and vegetation are currently embedded in DMSTA calibrations. Further 349

testing against data in lower P ranges will be possible as STA performance improves and 350

the natural marsh responds to decreasing P load s. Despite greater uncertainty and data 351

limitations, explicit consideration of soil P may improve water-column P simulations in 352

dry periods, which the effect s of soil P reflux would be gr eatest (Pant and Reddy, 2003). 353

While less important for STA design, explicit s imulation of soil P levels may be useful 354

for forecasting the spatial and temporal scales associated with restoration of rooted 355

vegetation and other ecosystem components that respond more to soil P variations than to 356

water column P variations. 357

358

The existing calibrations of DMSTA and EPGM provide a ba sis for estimating the time 359

scales required for P stored in each compartm ent to equilibrate following a change in the 360

long-term average water column P concentr ation (Figure 5). These scales depend upon 361

# D R A F T 13

the ratio of stored phosphorus to the average input P flux to each compartment computed 362

from a steady-state solution of the P cycling m odel. Starting from a given set of initial 363

conditions, time scales are expressed as the number of years required for 90% of the shift 364

to new equilibrium distribution of stored P. Equilibration of storage compartments to an 365

ambient P concentration of 10  g L -1 

# involves time scales ranging from ~1 to 3 years for 366

the vegetation P storage compartment, ~10 years for the 0-2 cm soil horizon, and ~50 367

years for the 0-10 cm soil horizon. Response ti mes are shorter at higher P concentrations 368

because of increases in the P cyc ling and soil accretion rates. 369

370

The temporal and spatial scales of marsh res ponse to increasing or decreasing P loads are 371

further illustrated in Figure 6. The prel iminary model has been applied to simulate 372

variations in P concentrati on and storage along the WCA-2A marsh transect in response 373

to variations in inflow volume and P lo ad over a 100 year period. The 1963-1995 period 374

represents historical conditions when the marsh P gradient developed in response to 375

increases in P load starting 1960’s. P lo ads gradually decrea sed between 1995 and 2007 376

period with implementation of upstream P cont rols and flow diversions. A hypothetical 377

reduction of inflow concentration to a long-term flow-weighted mean of 12  g L -1 

# 378

(approximately equivalent to a geometric mean of 10  g L -1 

# ) is imposed in 2008-2062 379

simulation period. Year-to-year variations in inflow volum e and concentration around 12 380

 g L -1 

# have been estimated from variations in th e historical time series. Soil P content in 381

1963 is initialized at 350 mg/kg based upon ver tical soil P profiles in WCA-2A. Marsh 382

response is expressed as areas exceeding vari ous water column P and soil P criteria in 383

each compartment. Areas are computed from the simulated distance along the transect 384

and an average transect width of 10.5 km (Walker, 1995). As expected based upon the 385

steady-state analysis (Figure 5) , labile P storage in vegetatio n responds within a few years 386

to the reduction in inflow concentration, whereas the soil compartments respond over 387

several decades. 388

389

Processes not directly reflected in the existing model, such as soil P recycling induced by 390

peat oxidation or mining of soil phosphorus by rooted vegetation, may decrease response 391

times for P stored in the soil but increase the time scales for P stored in the vegetation and 392

# D R A F T 14

water column. One limitation of the EPGM co mponent is that it was calibrated to soils 393

cores collected in 1990-1991 and reflected marsh response to an increase in P load over 394

the 1963-1990 period, when inflow P loads were generally increasing. Substantial data 395

collected since then provide a basis for re fining the structure a nd calibration in the 396

coupled EPGM/DMSTA model. Recent data also provide a basis for testing the model 397

in a recovery mode as the WCA2A marsh responds to further decreases in inflow P load. 398

Data from soil and water column transects in other WCAs are also available to support 399

further refinements (SFWMD, 2009b). 400



# Future Applications to Everglades Restoration 401

402

Restoring the Everglades will require deliver y of water with sufficient volume, timing, 403

and quality to achieve hydrologic and wate r quality objectives. Implementation of 404

hydrologic restoration measures will alter th e quantities and timi ng of marsh inflows 405

(USACE, 2009). Changes in timing could have positive or negative impacts on STA 406

performance, depending on how they affect p eak inflow volumes and P loads. DMSTA 407

can play continued roles in engineering solutions to achie ve both hydrologic and water 408

quality goals. These solutions are likely to involve combinations of the following 409

measures: 410

411

1. Additional BMPs to further re duce runoff P concentrations 412

2. Diversions to balance flows and P loads across STAs 413

3. Integration of reservoi rs to attenuate peak inflows to the STAs 414

4. Further optimization of the hydraulics, ve getation, and operation of existing STAs 415

5. Additional STA expansion 416

417

Further refinement of the modeling tools w ill be possible with continued research and 418

monitoring conducted under Florida’s Long- Term Plan (B&M, 2003; SFWMD, 2009b). 419

420

421

# D R A F T 15



# References 422

423

ADA Engineering, Inc., 2005. E AA Regional Feasibility St udy, prepared for South 424

Florida Water Management District. 425

426

Black & Veatch, Inc., 2006. EAA Reservoir A- 1 Basis of Design Report, prepared for 427

South Florida Water Ma nagement District. 428

429

Brown and Caldwell, Inc., 2002. Basin Sp ecific Feasibility Studies, Everglades 430

Stormwater Program Basins, prepared for South Florida Water Management District. 431

432

Brown and Caldwell, Inc., 2005. STA-2 Cell 4 Final Basis for Design, prepared for 433

South Florida Water Ma nagement District. 434

435

Brown and Caldwell, Inc., 2007. Basis of Design Report, Compartment B Build-Out, 436

prepared for South Florida Water Management District. 437

438

Burns and McDonnell, 1994, Everglades Protec tion Project Conceptual Design, prepared 439

for South Florida Water Management District. 440

441

Burns and McDonnell, 1999. Stormwater Treatm ent Area No. 3/4 Alternatives Analysis, 442

Prepared for South Florida Water Management District. 443

444

Burns and McDonnell, 2002, Basin-Specific Feas ibility Studies, Everglades Protection 445

Area Tributary Basins, Evaluation of Alternativ es for the ECP Basins, prepared for South 446

Florida Water Management District. 447

448

Burns and McDonnell, 2003. Everglades Prot ection Area Tributary Basins Long-Term 449

Plan for Achieving Water Quality Goals, pr epared for South Florida Water Management 450

District. http://www.sfwmd.gov/sta 451

# D R A F T 16

452

Burns and McDonnell, 2004, Water Quality Imp acts of Reservoirs, prepared for South 453

Florida Water Management District. 454

455

Camp, Dresser, McKee, Inc., 2007. LOFT Basis of Design Report, Taylor Creek, 456

Nubbin Slough, Brady Ranch, and Lakeside Ranch Stormwater Treatment Areas, 457

prepared for South Florida Water Management District. 458

459

Chen, C., Meselhe, E. A., Waldon, M. G, 2009. A.R.M. Loxahatchee National Wildlife 460

Refuge Hydrodynamic Modeling with MIKE FLOOD, prepared for U.S. Fish and 461

Wildlife Service. 462

463

Chimney, M.J., Goforth, G., 2006. History and description of the Everglades Nutrient 464

Removal Project, a subtropical constructe d wetland in south Florida,. Ecological 465

Engineering 27 (4): 268-278. 466

467

Cohen, M.J., T.Z. Osborne, S. Lamsal, M.W. Clark, “Regional Distribution of Soil 468

Nutrients – Hierarchical Soil Nutrient Mapping for Improved Ecosystem Change 469

Detection”, prepared for U.S. Army Corps of Engineers, University of Florida Soil and 470

Water Science Department. 471

472

Craft, B.B. and C.J. Richardson, 1993a. Peat Accretion and N, P and Organic C 473

Accumulation in Nutrient-Enriched and Unenri ched Everglades Peatlands. Ecological 474

Applications. 3(3):446-458. 475

476

Craft, B.B. and C.J. Richardson, 1993b. P eat Accretion and Phosphorus Accumulation 477

Along a Eutrophication Gradient in the Northern Everglades . Biogeochemistry 22: 13- 478

156. 479

480

DB Environmental, Inc., 2005. Baseline tracer study: STA-2, Cell 3. Final Report 481

submitted to South Florida Water Manage ment District, West Palm Beach, FL. 482

# D R A F T 17

Dierberg, F.E., DeBusk, T.A., Jackson, S.D., Chimney, M.J., Pietro, K., 2002. 483

Submerged aquatic vegetation-based treatm ent wetlands for removing phosphorus from 484

agricultural runoff: response to hydraulic and nutrient loading. Water Res. 36, 1409–422. 485

486

Fitz, H.C. and B. Trimble, 2006. Documenta tion of the Everglades Landscape Model: 487

ELM v2.5. Report from SFWMD, West Palm Beach, FL. https://my.sfwmd.gov/elm 488

489

Grunwald, S., K. R. Reddy, S. Newman, a nd W. F. DeBusk, 2004. Spatial variability, 490

distribution and uncertainty a ssessment of soil phosphorus in a south Florida wetland. 491

Envirometrics, 15: 811–825. 492

493

Guardo, M., Tomasello, R.S., 1995. Hydrodynamic simulations of a constructed wetland 494

in south Florida. Water Resour. Bull. 31, 687–701. 495

496

HDR, Inc., 2006. C44 Reservoir/STA Final Basi s for Design, prepared for U.S. Army 497

Corps of Engineers and South Flor ida Water Management District. 498

499

HydroQual, Inc., 1998. SFWMD Wetlands M odel: Calibration of the Coupled 500

Periphyton/Vegetation Model to the EN R. Report to SFWMD, Project SFWD0105, 501

March 1998, West Palm Beach, FL. 502

503

Jawitz, J.W., R. Muñoz-Carpena, S. Muller, K.A. Grace, A.I. James, 2008. Development, 504

Testing, and Sensitivity and Uncertainty Analyses of a Transport and Reaction 505

Simulation Engine (TaRSE) for Spatially Dist ributed Modeling of P hosphorus in the Peat 506

Marsh Wetlands of Southern Florida, U.S. De partment of the Interior, Geological Survey, 507

Scientific Investig ation Report 2008-5029. 508

509

Kadlec, R. H., 1994. Phosphorus Uptake in Florida Marshes, Water Science and 510

Technology, 30 (8): 225-234. 511

512

# D R A F T 18

Kadlec, R. H., 1997. An Autobiotic Wetland P hosphorus Model, Ecol. Eng. 8 (2): 145- 513

172. 514

515

Kadlec, R.H., Walker, W.W ., 1999. Management Models to Evaluate Phosphorus 516

Impacts in Wetlands, Chapter 27 in: Phos phorus Biogeochemistry in Subtropical 517

Ecosystems, K.R. Reddy, G.A. O’Connor and C.L. Schelske, eds., Lewis Publishers, 518

Boca Raton, FL, 621-642. 519

520

Kadlec, R.H., 2006. Free Surface Wetlands for Phosphorus Removal: the position of the 521

Everglades Nutrient Removal Project, Ecological Engineering 27: 361-379. 522

523

Kadlec, R. H. and S.D. Wallace, 2009. Tr eatment Wetlands, Second Edition, CRC Press, 524

Boca Raton, FL, 1016 pp. 525

526

Moustafa, M.Z. and J.M. Hamrick, 2000. Calibration of the Wetland Hydrodynamic 527

Model to the Everglades Nutrient Remova l Project, Water Quality and Ecosystem 528

Modeling. 1:141-167. 529

530

Munson, R.K., S.B. Roy, S.A. Gherini, A.L. MacNeill, R.J.M. Hudson, and V.L. Blette, 531

2002. Model Prediction of the Effects of Ch anging Phosphorus Loads on the Everglades 532

Protection Area, Water, Air and Soil Pollution, 134: 255-273. 533

534

Pant, H.K., Reddy, K.R., 2003. Potential internal loading of phosphorus in a wetland 535

constructed in agricultural land. Water Res. 37, 965–972. 536

537

Payne, G., K. Weaver and T. Bennett, 2003. Development of a Numeric P Criterion for 538

the Everglades Protection Area, Chapter 5, 2003 Everglades Consolidated Report, South 539

Florida Water Management District. 540

541

Payne, G., K. Weaver, and F. Near hoof, 2008. “ Technical Support Document: 542

Derivation of the Water Quality Based E ffluent Limit (WQBEL) for Phosphorus in 543

# D R A F T 19

Discharges to the Everglades Protection Ar ea”, Florida Department of Environmental 544

Protection, Bureau of Standa rds and Special Projects. 545

546

Reddy, K.R.,W. F. Debusk, Y. Wang, R.D. De Luane, and M.S. Koch, 1991. Physico547

Chemical Properties of Soils in the Water Conservation Area 2 of the Everglades. 548

Report to Soith Florida Water Management District, West Palm Beach, Florida. 549

550

Reddy, K.R., R.D. De Luane, W.F. DeBusk, and M.S. Koch, 1993. Long-Term Nutrient 551

Accumulation Rates in the Everglades. Soil. Sci. Soc. Am. J. 57: 1147-1159. 552

553

South Florida Water Management District, 2005. Documentation of the South Florida 554

Water Management Model, Version 5.5. 555

556

South Forida Water Management District , 2009a. DBHYDRO Hydrologic and Water 557

Quality Database. http://www.sfwmd.gov 558

559

South Florida Water Management District, 2009b. South Florida Environmental Report. 560

http://www.sfwmd.gov 561

562

Tetra Tech, Inc., 2008. “Environmental Impact Statement To Construct Stormwater 563

Treatment Areas on Compartments B and C of the Everglades Agricultural Area, 564

Florida”, prepared for U.S. Army Corp s of Engineers, Jacksonville District. 565

566

URS, Inc. 2005. Basis of Design Report, St ormwater Treatment Area 6 Section 2 and 567

Modifications to Section 1, prepared for South Florida Water Management District. 568

569

U.S. Army Corps of Engineers, 2009. Comp rehensive Everglades Restoration Plan 570

(CERP). http://www.evergladesplan.org 571

572

Walker, W. W., 1995. Design basis for Everglad es stormwater treatment areas, Water 573

Resources Bulletin, 31 (4): 671-685. 574

# D R A F T 20

575

Walker, W.W., Kadlec, R.H., 1996. A Model fo r Simulating Phosphorus Concentrations 576

in Waters and Soils Downstream of Evergl ades Stormwater Treatment Areas, prepared 577

for U.S. Department of Interior. http://www.wwwalker.net/epgm 578

579

Walker, W.W., Kadlec, R.H., 2001. Dynamic M odel for Stormwater Treatment Areas, 580

Model Version 1. 581

582

Walker, W.W., Kadlec, R.H., 2005. Dynamic M odel for Stormwater Treatment Areas, 583

Model Version 2. http://www.wwwalker.net/dmsta 584

585

# D R A F T 21

586



# Acknowledgement 587

588

This work was supported primarily by the U.S. Department of the Interior. The findings 589

and conclusions in this article are those of the authors and do not necessarily represent 590

the views of the supporting agency. Suppor ting data were provided primarily by South 591

Florida Water Management District. 592

593

594

# Walker & Kadlec, GEER 2008 Figures

Figure 1 Phosphorus Gradient in Wetland Vegetation, Water, and Soils under Historical

and Restored Conditions

Figure 2 Long-Term Trends in the Ever glades Regional Phosphorus Gradient

Figure 3 Evolution of Phosphorus Mass Balan ce Models with Increasing Complexity

Figure 4 Components of DMSTA

Figure 5 Time Scales of Phosphorus St orage in Marsh Soils and Vegetation

Figure 6 Simulation of WCA-2A Response to Reductions in Inflow P Concentration

# Figure 1

Phosphorus Gradient in Wetland Vegetation, Water Column, and Soils under Historical and

Restored Conditions.

A - Historical conditions (before implementation of phosphorus controls). The P gradient is

located entirely with the impacted natural marsh.

B - Future restored conditions (a fter full implementation of P contro ls). Most of the P gradient

is moved upstream out of the natural marsh and located with wetland stormwater treatment areas

constructed on adjacent agricultural lands. The remaining gradient within the marsh extends

from 10 ppb in the treatment area outflows to marsh background levels.



# Al d bi d di A Historical Impacted Marsh

B U p stream Treatment Area Restored Marsh TP = 100-200 ppb 4-8 ppb

Plants

Water

Soil

# 0 50 100 150 200 250

To Lake

Lake Out

To WCA

WCA1 Out

WCA2 Out

WCA3 Out TP Conc ppb

1980

‐ 1989

1990

‐ 1999

2000

‐ 2009 WCA

‐ 3A WCA

‐ 2A WCA

‐ 1 EAA Lake Okee.

ENP



# Figure 2

Long-Term Trends in the Everglad es Regional Phosphorus Gradient

Phosphorus concentrations are flow-weighted mean s. Flow and concentration data are from

DBHYDRO (SFWMD, 2009a)

# DMSTA/EPGM 2009



# 1 3 5 7+ Number of Calibration Parameters STA Design Model 1995 EPGM 1996 DMSTA 2002, 2005



# Permanent Storage Water Col. P Water Col. P Water Col. P Water Col. P

Biomass P 

# Biomass P

Soil P Soil P



# Figure 3

Evolution of Phosphorus Mass Balance M odels with Increasing Complexity

Aggregated P compartments and net fluxes are shown for four mass balance models developed

over the 1995-2009 period. Permanent storage repres ents burial of stable P forms in accreting

peat. The number of calibrated parameters increases with model complexity.

# A

‐ P Cycling Model C

‐ Cell Network Configurations

B

‐ Hydraulic Routing Model for One Cell D

‐ User Interface L

a

L i = Q i C i QC

J up J ret

J burial S = variable VC = variable = M

Labile P Storage Water Column P Storage STA Cells in Series Marsh (optional)

2 STA Flow-Ways followed by Marsh

Inflow Distribution Cell (Splitter) , 2 Flow-Ways, & Collector Cell

Reservoir with Release Stream, STA, & Marsh

W. Walker & R. Kadlec for U.S. Dept. of the Interior & U.S. Army Corps of Engineers Version Date: 10/7/2008

Expires: 9/30/2010

Select Project: Select Case: Select Output Sheet :

Select Simulation Type:

press Ctrl-m to return to menu

Project Name: PROJECT_EXAMPLES Project Cases: 22 Pro j ect Networks: 2

Time Series: TS_STA Series Dates: 01/01/65 thru 01/01/65

Current Case: STA_0 Output Dates: 01/01/66 thru 12/31/69

Description: Single Cell with Emergent Calibration 

### D ynamic M odel for S tormwater T reatment A reas - Version 2

Model In p ut Parameters

Summar

y of Pro

j ect Cases

Simulate Network of Cases

Overall Mass Balance

Mass Balances for Each Cell

Fre q uenc y Distributions

Reservoir Performance

Mass-Balance Schematic

Graphs - Cell Averages

Gra p hs - Selected Cell

Gra p hs - Combined Inflows & Outflows

Gra p hs - Selected Variable

Gra p hs - Pro j ect Summar y

Inflow Dail y Time Series

Out p ut Time Series - Overall

Out p ut Series - Current Cell

Calibration Ran g e Check

Go to Sheet STA_SPLITTER

STA_0

STA_1

STA_2

STA_3

STA_4

STA_5

STA_6

STA_7

STA_8

STA_N1

STA_N2

STA_N3

MARSH_1

MARSH_2

RES_1

RES_2

RES_3

RES_4

RES_5

RSTA_1

RSTA_2

Delete Case Run All Cases in

Project p ro j ect_exam p les

p ro j ect_tem p late

p ro j ect_reservoirs Retrieve Project Retrieve Case

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Base

Conservative

Uncertaint y Anal y sis

Disclaimer Check for

Updates



# Figure 4

Components of DMSTA

# 0.1 1.0 10.0 100.0

0 20 40 60 80 100

WC TP Conc ppbResponseTime(years) 

# 0

‐ 10 cm Soil

0

‐ 2 cm Soil

Emergent Veg.

Submerged Veg.



# Figure 5

Time Scales of Phosphorus Storag e in Wetland Soils and Vegetation

Represent approximate time require d for P storage compartments to adjust to a change in the

long-term average water-column P concentrat ion. Computed from EPGM and DMSTA

calibrations.

# Figure 6

Simulation of WCA-2A Response to Reductions in Inflow P Concentration using the Coupled

EPGM/DMSTA Models Soil TP, Depth

= 0

‐ 2 cm

0 20 40 60 80 100 120 140 160 180

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053Areakm2 

## > 500 mg/kg

> 700

> 1000



# Soil TP, Depth

= 0

‐ 10 cm

0 20 40 60 80 100 120 140 160 180

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053Areakm2 

## > 500 mg/kg

> 700

> 1000 

# Water

‐ Column TP Conc

0 20 40 60 80 100 120 140 160 180

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053Areakm2 

## > 10 ppb

> 20

> 50



# Vegetation P Storage

0 20 40 60 80 100 120 140 160 180

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053Areakm2 

## >500 mg/m2

>1000

>2000 

# Inflow TP Load

0 20 40 60 80 100 120

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053TPLoadmt/yr 

## BMPs

STAs



# Hypothetical 10 ppb