The EFDC
Water Quality Model:
Application to
South Puget Sound

• developed by Cerco and Cole (1994)

• Hamrick developed EFDC as hydrodynamic and sediment transport model
• Park et al. adapted ICM and merged it with EFDC to create HEM-3D

• Hamrick and Morton adapted and modified HEM-3D and integrated it into a revised EFDC

• Hamrick 1996. User's manual for EFDC
• Park, Kuo, Shen, and Hamrick, 1995. HEM-3D description
• Cerco and Cole, 1994. Three-dimensional eutrophication model of Chesapeake Bay (CE-QUAL-ICM)
• Morton, 1997. Annotated input file for the EFDC water quality model, application to Peconic Bay by Tetra Tech
• Source code and input files for the EFDC model and application to South Puget Sound (SPSM3)

• EPA/600/3-85/040, Rates, Constants, and Kinetics Formulations in Surface Water Quality Modeling (Second Edition)
• Chapra, 1997. Surface water quality modeling. McGraw-Hill.

Carbon
4. refractory particulate organic carbon (RPOC)
5. labile particulate organic carbon (LPOC)
6. dissolved organic carbon (DOC)

Phosphorus
7. refractory particulate organic phosphorus (RPOP)
8. labile particulate organic phosphorus (LPOP)
9. dissolved organic phosphorus (DOP)
10. total phosphate (TPO4)

Nitrogen
11. refractory particulate organic nitrogen (RPON)
12. labile particulate organic nitrogen (LPON)
13. dissolved organic nitrogen (DON)
14. ammonium nitrogen (NH4N)
15. nitrate nitrogen (NO23N)

Silica
16. particulate biogenic silica (SU)
17. available silica (SA)

Other
18. chemical oxygen demand (COD)
19. dissolved oxygen (DO)
20. total active metal (TAM)
21. fecal coliform bacteria (FCB)

Also (from the EFDC hydrodynamic model and user input):

• temperature
  
• salinity
  
• light
  
• total suspended solids (TSS)

Algae

Px = production rate of algal group x (day-1)
BMx = basal metabolism rate of algal group x (day-1)
PRx = predation rate of algal group x (day-1)
WSx = settling velocity of algal group x (m day-1)
WBx = external loads of algal group x (g C day-1)
V = cell volume (m3)

also can include f4(S) = salinity toxicity to freshwater algae

Nutrient Limitation

Light Limitation

Kremer and Nixon's equation for optimal illumination:

Light attenuation in the water column:

Kess = Keb + KeTSS TSS + KeChl Sumx=c,d,g (Bx/CChlx)

Adaptation to changes in light intensity:

(Io)avg = CIa Io + CIb I1 + CIc I2

See page 4-10 and 4-11 and 9-16 of Cerco and Cole for more detail on the governing equations for light.

Temperature Limitation

See figure 4-4 for a diagram of the temperature effect. Page 9-4 of Cerco and Cole shows data for diatoms, greens, and others.  

Basal Metabolism

BMx = BMrx exp ( KTbx (T - Trx) )

For example of parameter evaluation, see page 9-6 of Cerco and Cole

Predation

• Zooplankton biomass is assumed to be a constant fraction of algal biomass
• Zooplankton activity exponentially increases with temperature
• First-order predation rate constant may be time variable
• Algal matter is returned to the organic and inorganic pools according to distribution constants for each pool (refractory and labile particulate organic, and dissolved organic C, N, P)
• Refractory and labile particulate organic pools may have different settling rates and other kinetics parameters

PRx = BPRx exp ( KTbx (T - Trx) )

See page 4-14, 4-15,4-16,4-17 of Cerco and Cole for effect of predation and metabolism on organic C, N, and P

Derivation of the Predation Equation

dB/dt = ( P - R ) B - G Z

if Z = k B, then

dB/dt = ( P - R - k G ) B

Settling

• specified as an input settling rate (WSx) for each algal group
• seasonal variations of diatoms can be accounted for with time-series of settling velocity

Sediment Model

Sediment Model: State Variables

1-3) particulate organic carbon, G1, G2 and G3 classes in Layer 2
4-6) particulate organic nitrogen, G1, G2 and G3 classes in Layer 2
7-9) particulate organic phosphorus, G1, G2 and G3 classes in Layer 2
10) particulate biogenic silica in Layer 2
11-12) sulfide/methane, Layer 1 and 2
13-14) ammonium nitrogen, Layer 1 and 2
15-16) nitrate nitrogen, Layer 1 and 2
17-18) phosphate phosphorus, Layer 1 and 2
19-20) available silica, Layer 1 and 2
21) ammonium nitrogen flux 22) nitrate nitrogen flux
23) phosphate phosphorus flux 24) silica flux
25) sediment oxygen demand 26) release of chemical oxygen demand
27) sediment temperature

Simplified Water Quality Model

1. algae (one group)
2. organic C
3. organic P
4. total phosphate
5. organic N
6. ammonium N
7. nitrate N
8. chemical oxygen demand
9. dissolved oxygen

Required input files for EFDC

Summary of major EFDC input files

wq3dwc.inp
kinetics constants and coefficients for the water column

wq3dsd.inp
kinetics constants and coefficients for the sediment model

cwqsr01.inp through cwqsr21.inp
time-series tidal boundary conditions for water quality state variables 1-21

wqpsl.inp
time-series river and point source loads for variables 1-21 (UW version of wq3dwc.inp needs to be edited to activate use of this file. Card 5 of wq3dwc.inp: IWQPSL=1. Input file for point source input = WQPSL.INP at third from last line of wq3dwc.inp)

Other Input Files

cell.inp
Horizontal cell type identifier file.

celllt.inp
Horizontal cell type identifier file for saving mean mass transport.

dxdy.inp
File specifying horizontal grid spacing or metrics, depth, bottom elevation, bottom roughness and vegetation classes for either Cartesian or curvilinear-orthogonal horizontal grids.

gcellmap.inp
File specifying a Cartesian grid overlay for a curvilinear-orthogonal grid.

lxly.inp
File specifying horizontal cell center coordinates and cell orientations for either Cartesian or curvilinear-orthogonal grids.

mappgns.inp
Specifies configuration of the model grid to represent a periodic region in the north-south or computational y direction.

mask.inp
File specifying thin barriers to block flow across specified cell faces.

qser.inp
Volumetric source-sink time series file.

restart.inp
File for restarting a simulation.

restran.inp
File with arbitrary time interval averaged transport fields used to drive mass transport only simulations.

salt.inp
File with initial salinity distribution for cold start, salinity stratified flow simulations.

show.inp
File controlling screen print of conditions in a specified cell during simulation runs.

sser.inp
Salinity time series file.

tser.inp
Temperature time series file.

Estimation of loads of state variables from the tidal boundary and rivers:

Available data from Ambient Monitoring:

Exploration of Simplifying Assumptions
And Parameter Evaluation

2. Is it necessary to use dissolved, labile, and refractory particulate organic pools for C, N, and P, or can the model be simplified by using only one particulate organic pool each for C, N, and P? We are considering using only one particulate organic pool each for C, N, and P because data may not be available to distinguish the fraction of labile versus refractory in loading sources at the tidal boundary and in major rivers. Also, the dissolved organic pool of N and P is not well defined. It may be better to estimate dissolved, labile, and refractory pools even if the data are limited to allow flexibility in calibration (e.g. fast-settling versus slow-settling of organic C,N,P from zooplankton predation may be handled by using distribution coefficients to refractory versus labile pools.) Loading data for dissolved, labile, and refractory pools may be estimated from studies of other estuaries. For example, for Chesapeake Bay and Peconic estuaries, the dissolved, labile, and refractory pools of N and P were 50%, 30%, and 20% of the total organic N and P. Labile and refractory particulate organic C was approximately 60% and 40% of the total particulate organic C.

3. Do we need to simulate silica? We are considering omitting simulation of silica under the assumption that N imitation of diatoms is more important than silica limitation. Silica is only used in the model to determine whether silica is more limiting to production than N or P. Is there data to show that silica limitation in South Puget Sound is important?

4. Do we need to simulate Total Active Metal? TAM is the sum of iron and manganese and is mainly used to enhance the details of the kinetics of precipitation of phosphorus. Since P is most likely not a limiting nutrient anyway, and P can be simulated in the model with plenty of detail without including TAM, we have decided not to use the TAM state variable.

5. Should we consider using the simplified water quality model with nine state variables?

6. Recommendations for parameter evaluation for the water column and sediment model kinetics.

7. Summary of available data for calibration and data collection needs.