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 Runoff 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 Runoff 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/m2‐

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.
Page 9

Table 3 – Scenario Definitions and Results

All Scenarios: Long‐Term Flow‐Weighted‐Mean Design Target = 11.5 ppb (equivalvent to LT Geometric Mean ~ 9.3 ppb), 2005‐2009 Source TP Concentrations

FEB Vol. 

ID Label Description West Cent East West Cent East Total West Cent East Total kac‐ft Effect Total West 34 2+B East 

1 Current ** Current System without Comp B & C 214 131 187 8.9 24.8 11.8 45.5 0.0 0.0 0.0 0.0 45.5 50.0 29.7 25.5 33.2 34.6 

2 Current

+ Comp B & C **

Current System with Comp B & C 214 131 187 13.0 31.7 11.8 56.5 0.0 0.0 0.0 0.0 56.5 62.1 18.3 15.7 20.3 34.1 

3 A ‐ East & Cent STA STA Expansion in East & Central; 12‐ft FEB in West 219 131 187 0.0 15.6 15.0 30.6 7.0 0.0 0.0 7.0 84 37.6 41.4 11.4 11.5 11.5 11.4 

4 B ‐ East STA, Cent FEB 8‐ft FEB in Comp A2, STA in Comp A1,; 12‐ft FEB in West; STA expansion in East 219 131 187 0.0 13.5 15.0 28.5 7.0 3.0 0.0 10.0 108 38.5 42.4 11.5 11.3 11.3 11.4 

5 A/B‐Interim (4 yrs)

Interim Plan for Scenarios 3 or 4; A1

Operated as 4 ft FEB; balance flows to

achieve WQBEL in STA34; Meanwhile

construct A2 8‐ft FEB (or STA), Convert

A1 FEB to STA, expand STA1W; 12‐ft FEB

in West

214 132 188 0.0 0.0 0.0 0.0 0.0 15.0 0.0 15.0 60 15.0 16.5 18.3 11.2 18.2 31.9 

6 C ‐ C51 FEB, Cent STA

C51E Diversion & 44‐ft Rockpit / FEB +

STA Expansion in East & Central; 12‐ft

FEB in West

219 131 160 0.0 22.0 8.0 30.0 7.0 0.0 1.7 8.7 157 38.7 42.5 11.1 11.5 11.5 11.5 

7 D ‐ C51 FEB, Cent FEB

C51E Diversion & Rockpit/FEB in East; 8‐ft FEB, STA Exp in A1 & A2, 12‐ft FEB in

West

219 132 160 0.0 19.0 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 

8 C/D ‐ Interim (4 Yrs)

Interim Plan for Scenarios 6 or 7; C51E

rockpit partially complete (6 ft vs. 44 ft

final); divert L8 flows to coast; some S5A

to west; no C51E diversion; A1 Operatedas 4 ft FEB; achieve WQBEL in STA34;Meanwhile construct other project

components (FEB in Comp A2, CompleteC51 Rockpit, STA1W Expansion)

214 132 188 0.0 0.0 0.0 0.0 0.0 15.0 1.7 16.7 70 16.7 18.4 18.3 11.3 19.2 30.4 

* Preliminary Designs Subject to More Detailed Analysis and Optimization. Approximate Model Uncertainty +/‐ 15% of Predicted Outflow Concentrations.

** Existing & Planned STA Effective Areas listed for Scenarios 1 & 2; STA Expansion areas listed for other scenarios; West = STA‐5, STA‐6, Comp C; Central = STA‐34, Comp B, STA‐2; Eas

*** Bold Fonts Indicate STA's Not Achieving 11.5 ppb LTFWM Target (Existing Conditions or Interim Plans)

Inflow Conc ppb FEB STA Expan. (Effective)* Outflow Effective Area FEB+STA FWM ppb 
Page 10

Table 4 ‐    STA Mass Balances & Performance

Scenario 1 Existing STAs

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 40 

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 194 37.3 155 185 6.5 28.2 3.2 20.1 0.88 0% 26 0.0 0 29 35 

STA1W 6.7 262 68.0 210 263 12.7 39.1 3.3 20.6 1.02 0% 26 40 38 STA2B 8.2 273 50.2 149 275 11.3 33.2 2.8 14.0 0.98 0% 20 40 38 STA34 16.5 611 92.6 123 601 18.9 25.5 3.1 13.1 0.85 1% 23 0.0 0 37 38 

STA5 6.1 143 37.8 214 125 4.8 30.9 2.0 8.9 0.96 1% 18 0.0 0 40 38 

STA6 2.8 64 17.0 214 48 1.6 26.5 1.9 8.7 0.96 7% 20 39 38 Total 45.5 1548 302.7 158 1497 55.7 30.1Scenario 2 Existing STAs + Compartments B & C

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 40 

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 221 44.1 162 211 8.8 34.0 3.6 20.8 0.86 0% 26 0.0 0 38 38 

STA1W 6.7 236 61.2 210 237 10.0 34.1 2.9 18.6 1.02 0% 26 40 38 STA2B 15.1 474 79.9 137 478 12.0 20.3 2.6 13.0 0.99 0% 25 25 38 STA34 16.5 410 62.8 124 401 7.8 15.7 2.1 8.5 0.82 1% 23 0.0 0 5 23 STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 17 0.0 0 18 34 

STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 Total 56.5 1548 302.7 158 1490 42.3 23.0Scenario 3 A‐ STA Expansion

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 40 

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 109 20.4 152 102 1.5 11.6 1.8 7.1 0.75 0% 26 0.0 0 0 2STA1W 21.7 321 78.9 199 327 4.6 11.3 1.2 7.0 0.95 0% 21 2 0 STA2B 15.1 248 46.1 151 253 3.6 11.5 1.4 6.9 0.98 0% 20 0 0 STA34 32.1 602 91.6 123 583 8.3 11.5 1.6 6.6 0.85 1% 21 0.0 0 0 1STA5 7.9 122 24.3 161 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 STA6 5.1 78 15.5 161 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 Total 87.1 1479 276.7 152 1416 20.0 11.5Scenario 4 B‐ STA Expansion with A2 FEB

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 40 

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 107 20.1 152 100 1.4 11.4 1.7 7.1 0.75 0% 26 0.0 0 0 1STA1W 21.7 322 79.2 199 328 4.6 11.4 1.2 7.0 0.95 0% 21 2 0 STA2B 15.1 252 46.8 150 258 3.6 11.3 1.4 7.0 0.98 0% 21 0 0 STA34 30.0 589 85.5 118 570 8.0 11.3 1.6 7.0 0.81 0% 22 3.0 8 0 0 STA5 7.9 122 24.3 162 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 STA6 5.1 78 15.5 162 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 Total 85.0 1470 271.3 149 1408 19.7 11.4
Page 11

Table 4 ‐    STA Mass Balances & Performance (ct.)

Scenario 5 A/B ‐ Interim Plan without C51E Div/FEB

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 4

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 161 32.2 162 152 3.8 20.5 2.6 9.7 0.74 0% 28 0.0 0 20 35 

STA1W 6.7 270 68.0 204 270 12.8 38.3 3.4 20.6 0.99 0% 27 40 38 STA2B 15.1 425 72.6 139 429 9.6 18.2 2.3 11.7 0.98 0% 25 16 35 STA34 16.5 393 47.6 98 383 5.3 11.2 2.0 8.8 0.77 1% 24 15.0 4 0 1 STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 17 0.0 0 18 34 

STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 Total 56.5 1455 275.2 153 1397 35.2 20.4Scenario 6 C ‐ C51E Div/FEB, STA Expan

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 4

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 123 18.7 123 116 1.6 11.5 2.0 7.0 0.70 0% 27 1.7 44 0 1 STA1W 14.7 327 63.2 157 328 4.7 11.5 1.9 8.6 0.57 0% 28 1 0 STA2B 15.1 291 64.0 178 296 4.2 11.5 1.6 7.0 0.97 0% 26 0 1 STA34 38.5 718 110.3 125 693 9.8 11.5 1.6 6.8 0.87 1% 21 0.0 0 0 1STA5 7.9 122 24.2 161 101 1.4 11.4 1.3 3.8 0.61 0% 20 7.0 12 0 3 STA6 5.1 78 15.5 161 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 Total 86.5 1659 296.0 145 1584 22.5 11.5Scenario 7 D ‐C51E Div/FEB, A2 FEB/ STA

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 4

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 123 18.7 123 116 1.6 11.5 2.0 7.0 0.70 0% 27 1.7 44 0 1 STA1W 14.7 327 63.2 157 328 4.7 11.5 1.9 8.6 0.57 0% 28 1 0 STA2B 15.1 291 64.0 178 296 4.2 11.5 1.6 7.0 0.97 0% 26 0 1 STA34 35.5 706 103.1 118 683 9.7 11.5 1.7 7.4 0.83 0% 22 4.0 8 0 2 STA5 7.9 122 24.3 162 101 1.4 11.4 1.3 3.7 0.61 0% 20 7.0 12 0 3 STA6 5.1 78 15.5 162 50 0.7 11.5 1.3 3.7 0.61 2% 19 0 2 Total 83.5 1647 288.8 142 1574 22.4 11.5Scenario 8 C/D ‐ Interim Plan with C51E Div/FEB

Effect STA Inflows STA Outflows 30‐Day Hydraulic Load Depth Settling FEB Area Depth WQBEL Excursions / 4

Area Flow Load Conc Flow Load Conc Mean Max CV Freq Rate kac ft Yearly >2 Yrs 

STA kac kac‐ft mt ppb kac‐ft mt ppb cm/d cm/d  ‐ < 10 cm m/yr FWM > 18 GM > 10 

STA1E 5.1 117 21.9 152 110 1.7 12.9 1.9 8.1 0.77 0% 26 1.7 6 2 3 STA1W 6.7 281 66.0 190 279 12.8 37.3 3.5 21.6 0.95 0% 27 40 38 STA2B 15.1 453 78.7 141 458 10.9 19.2 2.5 12.3 0.98 0% 25 22 35 STA34 16.5 393 47.8 98 384 5.3 11.3 2.0 8.8 0.77 1% 24 15.0 4 0 2 STA5 7.9 126 33.4 214 106 2.4 18.3 1.3 6.1 0.96 2% 17 0.0 0 18 34 

STA6 5.1 81 21.4 214 57 1.3 18.3 1.3 6.0 0.96 8% 17 16 34 Total 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 Scenario
Scenario 1 Existing STAs 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

0

10203040506070

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

0

1020304050607080

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

0

102030405060

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

05

1015202530354045

1960 1970 1980 1990 2000 

FWM ppb 

0

102030405060

1960 1970 1980 1990 2000 

FWM ppb 

05

1015202530354045

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 2 Existing STAs + Compartments B & C 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

0

1020304050607080

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

0

10203040506070

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

05

101520253035

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

05

1015202530

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 3 A‐ STA Expansion 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

02468

101214161820

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 4 B‐ STA Expansion with A2 FEB 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

02468

101214161820

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

02468

101214161820

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 5 A/B ‐ Interim Plan without C51E Div/FEB 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

1015202530354045

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

0

1020304050607080

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

05

1015202530

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

02468

101214161820

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 6 C ‐ C51E Div/FEB, STA Expan 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

05

1015202530

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

02468

101214161820

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 7 D ‐C51E Div/FEB, A2 FEB/ STA 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

05

1015202530

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

05

10152025

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

02468

101214161820

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 

05

10152025

1960 1970 1980 1990 2000 

FWM ppb 
Scenario 8 C/D ‐ Interim Plan with C51E Div/FEB 80% Confidence Intervals for Yearly Flow‐Weighted Me

Model Predictions +/‐ 20%; Rounded to nearest ppb. Solid Line = 18 ppb WQBEL.

STA1E

05

1015202530

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA1W

0

1020304050607080

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

STA2B

05

101520253035

1960 1970 1980 1990 2000 2010

FWM ppb FWM 18 ppb

02468

101214161820

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 

05

101520253035

1960 1970 1980 1990 2000 

FWM ppb 
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 Scenario
Scenario 1 Existing STAs 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

0

102030405060

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

0

102030405060

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

05

1015202530354045

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

05

101520253035

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530354045

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

10152025303540

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 2 Existing STAs + Compartments B & C 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

0

10203040506070

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

0

102030405060

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

05

1015202530

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

05

10152025

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 3 A‐ STA Expansion 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

02468

101214161820

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

02468

101214161820

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

02468

10121416

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 4 B‐ STA Expansion with A2 FEB 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

02468

1012141618

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

02468

101214161820

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

02468

10121416

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

10121416

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 5 A/B ‐ Interim Plan without C51E Div/FEB 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

05

101520253035

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

0

10203040506070

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

05

10152025

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

10121416

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 6 C ‐ C51E Div/FEB, STA Expan 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

02468

1012141618

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

05

10152025

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

02468

1012141618

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 7 D ‐C51E Div/FEB, A2 FEB/ STA 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

02468

1012141618

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

05

10152025

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

02468

1012141618

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

10121416

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 

02468

1012141618

1960 1970 1980 1990 2000 

Geo Mean ppb 
Scenario 8 C/D ‐ Interim Plan with C51E Div/FEB 80% Confidence Intervals for Yearly Geometric Means

Model Predictions +/‐ 20%; Yearly Geo Mean = FWM / 1.23. Solid Line = 10 ppb criterion. Dotted Line = 15 ppb limit for marsh sites in 4‐Part Test

STA1E

05

10152025

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA1W

0

10203040506070

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

STA2B

05

1015202530

1960 1970 1980 1990 2000 2010

Geo Mean ppb GM15 ppb 10 ppb

02468

10121416

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 

05

1015202530

1960 1970 1980 1990 2000 

Geo Mean ppb 
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 Agency
Generalized Flow Chart for WQBEL Scenarios

Flow PathNew DiversionFEB Releases for STA Irrigation, Urban Water Supply (S5A), or Farm Irrigation (None Assumed)

Schematic reflects the general logic of the flow network, not specific locations of the project components

Expanded STA's are modeled as additional flow paths for STA‐6, STA‐34, and STA‐1W.

STA2_CB

S6 +

298

STA34

FEB34

FEB5A

NNR

Wpb

Hills

S8

G136+ 298

S5A

EBWCD

STA1E 

S7 + Lake

+298

Lake

S5A

ECP DIV 

Mia

STA1W

FEB56

STA5

C139 +

Annex

L3

STA6
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 Summary 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

STA1W 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 Qout 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 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 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 Summary 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 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 5.1 221 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 Runoff 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 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 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  ‐ 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 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 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 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 Balance 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 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 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 FEB_S5A 0.000.0 #N/A0 0.0 #N/A0 0

HRT days 60 30 90 30 FEB_34 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 FEB 0.000.0 #N/A0 0.0 #N/A

Max Qin cfs 2000 4000 2500 1000

Max Qout 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 Lake 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 15.6 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

Diversion Rules Mass Balance Summary Base_A1_RES_2project_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 STA34 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 FEB_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 Urban 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 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 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 Rules 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 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 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

NNR 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 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 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 & S351  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

Scale_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 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 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 STA34 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

Max 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 22 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 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% 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 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, C139 12 ft FEB

Diversion Rules Mass Balance Summary C51E_A1_RES_3project_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 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 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 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 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

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 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

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 19 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 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

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

Scale_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 Outflow 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 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

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 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_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 Areas 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
1 February 16, 2010 

2 Modeling Phosphorus Dynamics in Everglades Wetlands and 

3 Stormwater Treatment Areas 

4 

William W. Walker, Jr. 1 and Robert H. Kadlec2 5 

1 6 Environmental Engineer, Concord, Massachusetts, bill@wwwalker.net

7 2Wetland Management Services, Chelsea, Michigan, rhkadlec@chartermi.net, 

8 

9 Submittted to 

10 Based on Presentation at GEER 2008 Symposium 

11 Abstract 

12 

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

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

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 16 . Subsequent implementation of P 

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

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

edge of the Water Conservations Areas (WCAs) to approximately 33 g L-1 19 in 2007-

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

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

22 evolution and application of relatively simple mass-balance models to simulate P storage 

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

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

25 Everglades regional P control plans involving combinations of source controls, water 

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

27 marshes immediately downstream of treated and untreated discharges. 
D R A F T 2

28 Key Words 

29 Everglades, phosphorus, modeling, marsh, engineering, wetland treatment areas 

30 

31 Introduction 

32 

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

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

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

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

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

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

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

marsh ranged from 100-200 g L-1 at the inflows to background levels of 4-8 g L-1 40 

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

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

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

sawgrass communities are viable only at P concentrations below 10 g L-1 44 , expressed as a 

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

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

47 protecting the entire marsh is likely to require inflow P concentrations equivalent to the 

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

49 water bodies where inflows with concentrations exceeding water quality standards do not 

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

51 assimilated in receiving waters. 

52 

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

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

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

56 through implementation of agricultural Best Management Practices (BMPs) and 

57 construction of Stormwater Treatment Areas (STAs) (SFWMD, 2009b). As these control 
D R A F T 3

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

~170 g L-1 in 1980-1989 to ~61 g L-1 59 in 2000-2009. Within the last decade, the threeyear rolling-average inflow concentration decreased from ~64 g L-1 60 in 2001-2004 to 

~33 g L-1 61 in 2007-2009. The historical reductions in inflow concentration have 

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

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

64 outflow concentrations are expected to result from implementation of additional source65 control and treatment measures. 

66 

67 The effect of the P control program is to displace the P gradient upstream of the marsh so 

68 that most of it occurs within STAs constructed on formerly agricultural land (Figure 1). 

69 At the same time, elevated P concentrations driving the gradient are reduced through 

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

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

geometric mean P concentrations ranging from 10 g L-1 72 to background levels of 4-8 g 

L-1 73 . 

74 

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

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

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

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

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

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

81 WCA inflow points. 

82 

83 Model Evolution 

84 

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

86 design alternatives by engineering professionals without requiring site-specific 

87 calibration data or specialized expertise in wetland modeling. Model simplicity results 
D R A F T 4

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

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

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

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

92 2005). These datasets provide bases for calibration and testing under a wide range of 

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

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

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

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

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

98 factors as water depth, hydraulic loads, antecedent soils, and vegetation are considered by 

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

100 consistent with calibration datasets. 

101 

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

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

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

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

106 fluxes between compartments. While P generally moves in both directions between 

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

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

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

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

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

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

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

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

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

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

117 
D R A F T 5

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

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

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

121 al, 2002; Jawitz et al., 2008). They generally account for two-dimensional spatial and 

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

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

124 expertise to calibrate and apply. These requirements generally preclude engineering 

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

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

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

128 response to variations in marsh inflows and other factors projected to occur in response to 

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

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

131 applications to the entire Everglades marsh. 

132 Steady-State STA Design Model (STADM) 

133 

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

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

concentration of 50 g L-1 136 (Burns and McDonnell, 1994). A modified version that places 

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

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

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

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

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

142 2009b). 

143 

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

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

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

147 and three P fluxes: inflow, outflow, and net removal in the accreting peat (Figure 3). 
D R A F T 6

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

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

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

required to support the 50 g L-1 151 STA designs. A steady-state model is not sufficient, 

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

153 inflows (see DMSTA, below) 

154 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

170 time of STADM development. 

171 

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

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

50 g L-1 174 STAs, it was assumed that STA vegetation types and P cycling processes 

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

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

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

178 that the model calibrated to a natural wetland would generate conservative forecasts of 
D R A F T 7

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

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

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

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

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

184 

185 Everglades Phosphorus Model (EPGM) 

186 

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

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

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

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

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

192 (cattails, other rooted vegetation) than by water-column concentration (periphyton, algae, 

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

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

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

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

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

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

199 

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

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

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

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

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

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

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

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

208 between the average P content of accreting peat and the average P concentration in the 
D R A F T 8

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

indicates that soil accretion rates vary from 0.1 to 1.0 kg/m2 210 -yr and the P content of 

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

5 to 100 g L-1 212 . 

213 

214 EPGM has been applied to evaluate the potential impacts of distributing STA outflows 

with a P concentration of 50 g L-1 215 into previously un-impacted marsh areas along the 

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

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

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

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

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

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

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

that marsh areas with water-column P concentrations exceeding 10 g L-1 223 correspond to 

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

225 

226 Dynamic Model for Stormwater Treatment Areas (DMSTA) 

227 

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

of STAs to achieve outflow TP concentrations approaching the 10 g L-1 229 criterion. 

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

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

232 and hydraulics to treat highly pulsed basin runoff. Consideration of these factors requires 

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

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

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

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

237 by Kadlec (1997). Those equations have been refined and calibrated to various emergent 
D R A F T 9

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

239 wetlands and treatment areas. 

240 

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

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

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

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

245 involves specification of cell areas, configurations, depth regimes, hydraulic features, and 

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

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

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

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

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

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

252 

253 The first version of DMSTA (Walker & Kadlec, 2001) was calibrated to data from 

approximately 70 treatment cells and wetlands ranging in size from 10-1 to 107

 m

2 254 . Most 

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

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

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

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

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

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

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

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

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

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

265 2002; Brown and Caldwell, 2002). 

266 

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

268 data from full-scale treatment cells and wetlands with dynamic inflows and water depths 
D R A F T 10

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

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

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

272 well as a calibration for open-water reservoirs. The reservoir calibration is based upon 

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

274 evaluation regional plans involving networks of STAs and storage reservoirs planned for 

275 hydrologic restoration purposes (USACE, 2009). 

276 

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

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

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

submerged vegetation, 18-31 g L-1 280 for periphyton, 27-46 m/yr for mixed vegetation on 

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

categories) are in the 60th to 90th 282 percentile range of the global distribution of settling 

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

284 calibration is applicable under specific ranges of depth, velocity, and concentration, as 

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

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

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

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

289 

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

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

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

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

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

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

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

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

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

299 management, P cycling within wetland communities, measurement errors, and other 
D R A F T 11

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

301 wetland community in the context of data variations induced by the other 

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

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

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

305 and management expectations. 

306 

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

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

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

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

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

312 Dierberg et al., 2005; DB Environmental Labs, 2006). To some extent, the effects of 

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

314 used to represent each cell (Kadlec and Wallace, 2009). DMSTA incorporates a depth315 dependent P uptake function that reflects spatial variations in topography (typically +/- 30 

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

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

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

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

320 consideration of topographic variations within each cell may improve model 

321 performance, particularly when water levels are relatively low and risk of short-circuiting 

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

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

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

325 

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

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

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

329 features useful for design and diagnostic applications. 

330 
D R A F T 12

331 Coupled DMSTA and EPGM 

332 

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

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

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

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

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

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

339 profile generated by the STADM. 

340 

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

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

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

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

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

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

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

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

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

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

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

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

353 dry periods, which the effects of soil P reflux would be greatest (Pant and Reddy, 2003). 

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

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

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

357 water column P variations. 

358 

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

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

361 long-term average water column P concentration (Figure 5). These scales depend upon 
D R A F T 13

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

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

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

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

ambient P concentration of 10 g L-1 366 involves time scales ranging from ~1 to 3 years for 

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

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

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

370 

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

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

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

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

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

376 increases in P load starting 1960’s. P loads gradually decreased between 1995 and 2007 

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

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-1 379 ) is imposed in 2008-2062 

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

g L-1 381 have been estimated from variations in the historical time series. Soil P content in 

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

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

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

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

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

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

388 several decades. 

389 

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

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

392 times for P stored in the soil but increase the time scales for P stored in the vegetation and 
D R A F T 14

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

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

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

396 collected since then provide a basis for refining the structure and calibration in the 

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

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

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

400 further refinements (SFWMD, 2009b). 

401 Future Applications to Everglades Restoration 

402 

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

404 and quality to achieve hydrologic and water quality objectives. Implementation of 

405 hydrologic restoration measures will alter the quantities and timing of marsh inflows 

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

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

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

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

410 measures: 

411 

412 1. Additional BMPs to further reduce runoff P concentrations 

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

414 3. Integration of reservoirs to attenuate peak inflows to the STAs 

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

416 5. Additional STA expansion 

417 

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

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

420 

421 
D R A F T 15

422 References 

423 

424 ADA Engineering, Inc., 2005. EAA Regional Feasibility Study, prepared for South 

425 Florida Water Management District. 

426 

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

428 South Florida Water Management District. 

429 

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

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

432 

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

434 South Florida Water Management District. 

435 

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

437 prepared for South Florida Water Management District. 

438 

439 Burns and McDonnell, 1994, Everglades Protection Project Conceptual Design, prepared 

440 for South Florida Water Management District. 

441 

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

443 Prepared for South Florida Water Management District. 

444 

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

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

447 Florida Water Management District. 

448 

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

450 Plan for Achieving Water Quality Goals, prepared for South Florida Water Management 

451 District. http://www.sfwmd.gov/sta
D R A F T 16

452 

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

454 Florida Water Management District. 

455 

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

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

458 prepared for South Florida Water Management District. 

459 

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

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

462 Wildlife Service. 

463 

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

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

466 Engineering 27 (4): 268-278. 

467 

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

469 Nutrients – Hierarchical Soil Nutrient Mapping for Improved Ecosystem Change 

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

471 Water Science Department. 

472 

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

474 Accumulation in Nutrient-Enriched and Unenriched Everglades Peatlands. Ecological 

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

476 

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

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

479 156. 

480 

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

482 submitted to South Florida Water Management District, West Palm Beach, FL. 
D R A F T 17

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

484 Submerged aquatic vegetation-based treatment wetlands for removing phosphorus from 

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

486 

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

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

489 

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

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

492 Envirometrics, 15: 811–825. 

493 

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

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

496 

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

498 Corps of Engineers and South Florida Water Management District. 

499 

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

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

502 March 1998, West Palm Beach, FL. 

503 

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

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

506 Simulation Engine (TaRSE) for Spatially Distributed Modeling of Phosphorus in the Peat 

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

508 Scientific Investigation Report 2008-5029. 

509 

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

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

512 
D R A F T 18

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

514 172. 

515 

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

517 Impacts in Wetlands, Chapter 27 in: Phosphorus Biogeochemistry in Subtropical 

518 Ecosystems, K.R. Reddy, G.A. O’Connor and C.L. Schelske, eds., Lewis Publishers, 

519 Boca Raton, FL, 621-642. 

520 

521 Kadlec, R.H., 2006. Free Surface Wetlands for Phosphorus Removal: the position of the 

522 Everglades Nutrient Removal Project, Ecological Engineering 27: 361-379. 

523 

524 Kadlec, R. H. and S.D. Wallace, 2009. Treatment Wetlands, Second Edition, CRC Press, 

525 Boca Raton, FL, 1016 pp. 

526 

527 Moustafa, M.Z. and J.M. Hamrick, 2000. Calibration of the Wetland Hydrodynamic 

528 Model to the Everglades Nutrient Removal Project, Water Quality and Ecosystem 

529 Modeling. 1:141-167. 

530 

531 Munson, R.K., S.B. Roy, S.A. Gherini, A.L. MacNeill, R.J.M. Hudson, and V.L. Blette, 

532 2002. Model Prediction of the Effects of Changing Phosphorus Loads on the Everglades 

533 Protection Area, Water, Air and Soil Pollution, 134: 255-273. 

534 

535 Pant, H.K., Reddy, K.R., 2003. Potential internal loading of phosphorus in a wetland 

536 constructed in agricultural land. Water Res. 37, 965–972. 

537 

538 Payne, G., K. Weaver and T. Bennett, 2003. Development of a Numeric P Criterion for 

539 the Everglades Protection Area, Chapter 5, 2003 Everglades Consolidated Report, South 

540 Florida Water Management District. 

541 

542 Payne, G., K. Weaver, and F. Nearhoof, 2008. “ Technical Support Document: 

543 Derivation of the Water Quality Based Effluent Limit (WQBEL) for Phosphorus in 
D R A F T 19

544 Discharges to the Everglades Protection Area”, Florida Department of Environmental 

545 Protection, Bureau of Standards and Special Projects. 

546 

547 Reddy, K.R.,W. F. Debusk, Y. Wang, R.D. De Luane, and M.S. Koch, 1991. Physico548 Chemical Properties of Soils in the Water Conservation Area 2 of the Everglades. 

549 Report to Soith Florida Water Management District, West Palm Beach, Florida. 

550 

551 Reddy, K.R., R.D. De Luane, W.F. DeBusk, and M.S. Koch, 1993. Long-Term Nutrient 

552 Accumulation Rates in the Everglades. Soil. Sci. Soc. Am. J. 57: 1147-1159. 

553 

554 South Florida Water Management District, 2005. Documentation of the South Florida 

555 Water Management Model, Version 5.5. 

556 

557 South Forida Water Management District, 2009a. DBHYDRO Hydrologic and Water 

558 Quality Database. http://www.sfwmd.gov

559 

560 South Florida Water Management District, 2009b. South Florida Environmental Report. 

561 http://www.sfwmd.gov

562 

563 Tetra Tech, Inc., 2008. “Environmental Impact Statement To Construct Stormwater 

564 Treatment Areas on Compartments B and C of the Everglades Agricultural Area, 

565 Florida”, prepared for U.S. Army Corps of Engineers, Jacksonville District. 

566 

567 URS, Inc. 2005. Basis of Design Report, Stormwater Treatment Area 6 Section 2 and 

568 Modifications to Section 1, prepared for South Florida Water Management District. 

569 

570 U.S. Army Corps of Engineers, 2009. Comprehensive Everglades Restoration Plan 

571 (CERP). http://www.evergladesplan.org

572 

573 Walker, W. W., 1995. Design basis for Everglades stormwater treatment areas, Water 

574 Resources Bulletin, 31 (4): 671-685. 
D R A F T 20

575 

576 Walker, W.W., Kadlec, R.H., 1996. A Model for Simulating Phosphorus Concentrations 

577 in Waters and Soils Downstream of Everglades Stormwater Treatment Areas, prepared 

578 for U.S. Department of Interior. http://www.wwwalker.net/epgm

579 

580 Walker, W.W., Kadlec, R.H., 2001. Dynamic Model for Stormwater Treatment Areas, 

581 Model Version 1. 

582 

583 Walker, W.W., Kadlec, R.H., 2005. Dynamic Model for Stormwater Treatment Areas, 

584 Model Version 2. http://www.wwwalker.net/dmsta

585 
D R A F T 21

586 

587 Acknowledgement 

588 

589 This work was supported primarily by the U.S. Department of the Interior. The findings 

590 and conclusions in this article are those of the authors and do not necessarily represent 

591 the views of the supporting agency. Supporting data were provided primarily by South 

592 Florida Water Management District. 

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 Everglades Regional Phosphorus Gradient 

Figure 3 Evolution of Phosphorus Mass Balance Models with Increasing Complexity 

Figure 4 Components of DMSTA 

Figure 5 Time Scales of Phosphorus Storage 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 (after full implementation of P controls). 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 Upstream 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 Everglades Regional Phosphorus Gradient 

Phosphorus concentrations are flow-weighted means. 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 Models with Increasing Complexity 

Aggregated P compartments and net fluxes are shown for four mass balance models developed 

over the 1995-2009 period. Permanent storage represents 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

La

Li = QiCi QC

Jup Jret

Jburial

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 Project 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

Dynamic Model for Stormwater Treatment Areas - Version 2

Model Input Parameters

Summary of Project Cases

Simulate Network of Cases

Overall Mass Balance

Mass Balances for Each Cell

Frequency Distributions

Reservoir Performance

Mass-Balance Schematic

Graphs - Cell Averages

Graphs - Selected Cell

Graphs - Combined Inflows & Outflows

Graphs - Selected Variable

Graphs - Project Summary

Inflow Daily Time Series

Output Time Series - Overall

Output Series - Current Cell

Calibration Range 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

project_examples

project_template

project_reservoirs

Retrieve Project Retrieve Case

Save Case

Run Model

Edit Input Values

Simulate

Case Network

DMSTA 

Website

Test 

Base

Conservative

Uncertainty Analysis

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 ppb

Response Time ( years )

0‐10 cm Soil

0‐2 cm Soil

Emergent Veg.

Submerged Veg.

Figure 5 

Time Scales of Phosphorus Storage in Wetland Soils and Vegetation 

Represent approximate time required for P storage compartments to adjust to a change in the 

long-term average water-column P concentration. 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 2053

Area km2

> 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 2053

Area km2

> 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 2053

Area km2

> 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 2053

Area km2

>500 mg/m2

>1000

>2000

Inflow TP Load

0

20

40

60

80

100

120

1963 1973 1983 1993 2003 2013 2023 2033 2043 2053

TP Load mt/yr

BMPs

STAs

Hypothetical 10 ppb