Modeling in EE
We recommend you follow this checklist:
A1. Clear statement of study objectives and constraints, including schedule
A2. Area of interest and list of questions/problems to be addressed by modeling defined
A3. Site characteristics, data, and important processes identified
A4. Appropriate model chosen for items A1 to A3
i. Correct equations solved (e.g., 1D/2D/3D, mild slope, hydrostatic assumption)
ii. Important processes included (e.g., long/short waves, rising/plunging flow, stratification/lateral variation)
iii. Computational requirements defined
A5. Data for boundary conditions and validation needs defined and available/acquired
A6. Resources sufficient (i.e., money, time, staff expertise, computer resources, data for boundaries and validation)
A7. Validation criteria established consistent with A1-A6
A8. A1-A7 documented and client concurrence obtained
A9. Tier 1 and Tier 2 Analyses performed
A10. A1-A9 documented and checked by reviewer(s)
B1. Grid sufficiency
i. Boundary locations tested for effect on area of interest and test conditions
ii. Resolution tested by grid refinement test
iii. Bathymetry and features visually checked for accuracy
B2. Boundary conditions established appropriate to A1 – A3
B3. Initial conditions and spin-up shown to be adequate to eliminate transients
B4. B1-B3 documented and checked by separate reviewer(s)
C1. Adjustable parameters set within reasonable ranges of known uncertainty
C2. Model-Prototype agreement consistent with A1-A3 and A7
C3. C1-C2 documented with client concurrence and checked by reviewers(s)
D1. Test conditions consistent with A1-A3
D2. Sensitivity to parameters and plans tested
D3. Results consistent with expectations and other studies and within reasonable ranges
D4. D1-D3 documented with client concurrence and checked by reviewer(s)
E1. Items A-D documented in consistent understandable fashion
E2. Results expressed with appropriate confidence limits and caveats
E3. Interpretation and conclusions are consistent with A1-A3 and E2
E4. Client and reviewer(s) feedback solicited and used to refine report(s)
The model generation process is described in the EFDC_Explorer Knowledge Base. The main points are as follows:
1. Locate a template EFDC.INP file that EFDC_Explorer will use to set many of the standard coefficients and parameters. The user can change any of these later in the model generation process. An EFDC.INP template file is required. A simple EFDC.INP was supplied in the original EFDC_Explorer setup package.
2. Bathymetry is required for the model generation process, but not required for the gridding process. Because the grid generation process is often iterative, it is recommended to skip specifying the “Topographic Information File” and, instead, use the flat bottom option in the “Elevation Options” frame.
3. Select the file containing polygons to trim the model cells (optional). The first polygon in the file should be the main model domain outline. Subsequent polygons in the file are interpreted as cutouts/islands.
4. Set the number of layers.
5. Set the initial water surface elevation. Should be above the flat bottom elevation
6. Set the default bottom roughness height.
7. Select the gridding approach and import or generate a grid.
8. At this point the “Generate” button should be enabled. If it is still grayed out then there is still an essential piece of information that has not been set. The required inputs vary depending on the gridding option chosen. Press the “Generate” button to create a new EFDC model using the options specified. Even though a project directory is requested, this process does not write the files, only creates the model in memory.
9. When the model generation process is complete, EFDC_Explorer pops up a message informing the user as to how many active cells were created and what the maximum I and J were.
10. The last pop up displayed informs the user to review the model and make sure the I and J orientations are reasonable. For some convoluted grids, the L=2 lower left cell may not be correctly assigned. After reviewing the grid in ViewPlan and determining that the IJ mapping needs to be adjusted, the user can use the IJ mapping tools from the main EFDC_Explorer form to flip either I or J and/or transpose the I and J mapping.
11. Review the generated grid in ViewPlan. Load background images and/or polyline overlays to visually check the grid. View and check grid orthogonality.
12. If the grid is acceptable, then apply the bathymetry to this new grid using the “Bottom Elevations” button on the “Initial” conditions tab on the main EFDC_Explorer form.
13. Review the model grid with bathymetry added to make sure important bathymetric features are properly represented. Check the reasonableness of the CFL timestep.
14. Repeat these steps as necessary to obtain the proper balance of grid resolution, computational speed and other project specific factors.
Sometimes I need to do statistical analysis using the raw data (e.g. salinity). Is there a post-processor that can convert the binary output to text?
Yes, registered users may download GetEFDC utility for Fortran and Matlab from this website to do this. Other options include:
• Use the “Export to Tecplot” feature from the ViewPlan
• Write your own using the formats shown in the EEXPOUT.FOR subroutine.
Yes, you can review a run in process by:
• Pausing the EFDC execution (pressing any key within EFDC_DSI will pause the execution).
• Checking the “Reload” checkbox.
• Using the ViewPlan or ViewProfile to review the model progress.
• Restart the model, if desired or stop the model run and make adjustments, save and re-run.
• Repeat as needed.
The EFDC Model
DSI have developed their own modified and improved version of EFDC called EFDC+ (which includes what was formerly EFDC_DSI). Apart from hundreds of vital bugs fixes, the EFDC_DSI version applies dynamic memory allocation so that the user doesn’t need to manually update the array sizes for each model. Moreover, a number of significant new sub-models have been added including internal wind waves, Lagrangian particle tracking, oil spill, ice formation and melt, and the SEDZLJ sediment flume model. Multi-processing has also been integrated into EFDC_DSI which provides significant increases in speed. More detailed information is available here.
DSI has developed an improved version of the EFDC code to help deal with pressure gradient errors that occur in simulations that have steep changes in bed elevation. This new version of the code is called the Sigma Zed code, or EFDC_SGZ. This contrasts with the conventional EFDC code which uses a sigma coordinate transformation in the vertical direction and uses the same number of layers for all cells in the domain. See more information on this here.
To reduce possible data formatting errors, generate a simple XYZ ASCII data listing and use the DAT file extension. See the Knowledge Base for some more guidance.
Is EFDC also suitable for detailed hydrodynamics simulation (very localized, fine meshes, relatively strong 3D or high velocity gradient)?
The “Testcases” section of our web page has some small scan flume examples. We have used it to duplicate a number of published papers. That said, EFDC uses a hydrostatic approximation for the vertical flows. Therefore, EFDC is not to be used in cases where there is significant vertical accelerations. High energy gradients and high velocity gradients are not particularly a problem.
Yes, EFDC has been used in several real-time systems that DSI have developed. An example of one that is available for public access is the West Lake Real-time Hydrodynamic and Water Quality Model
Yes, it is possible to setup EFDC model on a Windows machine and then transfer the model input files to the Linux system. The Linux system will have a different EFDC+ executable than Windows but uses the same input file names and the same extensions of the files. The output generated from Linux can be viewed back in EFDC_Explorer.
Dynamic Solutions International (DSI) has developed step-by-step procedures needed to create an EFDC hydrodynamic model results binary file (*.HYD) that is formatted for linkage as an input file to the WASP7 water quality model. The technical memorandums provided on the website provide the information needed and example problems to show the step-by-step procedures needed to successfully create and apply an EFDC project to export a hydrodynamic file (*.HYD) for linkage as an input file for a WASP7 water quality model project. The description contained in the documents assumes that the user has completed the setup of a working EFDC project for a hydrodynamic model and wishes to generate a binary HYD file as input to a WASP7 water quality model. The user is reminded that the EFDC model and the EFDC_Explorer interface includes a fully functioning coupled sediment transport and water quality model in a single EFDC model source code. The EFDC water quality model is comparable to the state variables included in the WASP7 water quality model.
Two example problems are developed by DSI to show how an EFDC model can be setup and linked to a WASP7 water quality model.
Example Problem#1. A 1D river problem for BOD, nitrogen and dissolved oxygen is setup in EFDC as a hydrodynamic, sediment transport and water quality model. The hydrodynamic results file (HYD) is then used to setup the same 1D river problem in WASP7. The results of the EFDC and WASP7 water quality models are compared to a steady state analytical model as a benchmark solution for the 1D river problem. All input files needed for the EFDC and the WASP7 models are provided for the 1D river problem. (Download Model)
Example Problem#2. A 3D time variable lake model for hydrodynamics, sediment and water quality is setup as an EFDC model. The hydrodynamic results file (HYD) is then used to setup the same 3D lake model in WASP7. All input files needed for the EFDC and the WASP7 models are provided for the 3D lake model problem. (Download Model)
DSI recommends using the EFDC_DSI coupled hydrodynamic and water quality model instead of the EFDC/WASP linkage process because:
- The advantage of quicker run times for a decoupled hydrodynamic model from the water quality transport and kinetics is not valid as the WASP code alone runs 3 to 8 times SLOWER than the fully coupled EFDC_DSI model with water quality. See Table 1 for an example.
- The pre/post processing tools of EFDC_Explorer significantly streamline the modeling process allowing the user to spend more time in producing a better model rather than spending a lot of time with basic model/linkage mechanics.
- For a similarly configured water quality model, the EFDC_DSI results are nearly identical to WASP. See Figure 1.
Figure 1 River 1D dissolved oxygen (D.O.) for the analytical solution compared to the EFDC_DSI and WASP computed results. Note: The results for EFDC_DSI and WASP are nearly identical.
Table 1 EFDC_DSI and WASP runtimes.