Modeling Overview for LTCP Development

1. Modeling Overview for LTCP Development Julia Moore, P.E. Limno-Tech, Inc.

2. Items to Be Covered • Modeling and the CSO Control Policy • Combined sewer system (CSS) modeling • Receiving water (RW) modeling • Model review Modeling Overview

3. Expectations of the CSO Policy EPA supports the proper and effective use of models, where appropriate, in the evaluation of the nine-minimum controls and the development of the long-term control plan… • Resource – Combined Sewer Overflows: Guidance for Monitoring and Modeling. EPA 832-B-99-002. January, 1999. Modeling Overview

4. Expectations of the CSO Policy • Event modeling • The permittee should adequately characterize through monitoring, modeling, and other means as appropriate, for a range of storm events, the response of its sewer system to wet weather events… Section II.C.1 • Continuous simulation modeling • EPA believes that continuous simulation models, using historical rainfall data, may be the best way to model sewer systems, CSOs, and their impacts… Section II.C.1.d Modeling Overview

5. Why is CSS Modeling Important? • Good characterization is typically infeasible without models except for small / simple systems • “Stretch” the value of monitoring, saving time and money • Assess conveyance and storage for NMC and LTCP • Optimize LTCP under a range of storm conditions • Provide a tool for projecting results after implementation of CSO controls Modeling Overview

6. Illustration of a Simple CSS Model RAINFALL COMB. SEWAGE URBAN AREA TREATMENT PLANT RECEIVING WATER RELEASE STORAGE Source: Urban Storm Water Modeling and Simulation by Stephan Nix CSO / BYPASS 6 Modeling Overview

7. General Types of CSS Models • Quantity • Rainfall/runoff model • Hydraulic sewer pipe model • Quality • Pollutant accumulation, washoff and transport model Modeling Overview

8. Modeling Quantity • Runoff Modeling • Runoff models are used to estimate stormwater input to the CSS • Usually paired with hydraulic sewer models • CSS Hydraulic Modeling • Predicts sewer pipe flow effects including: • Flow rate components (runoff, sanitary, infiltration and inflow) • Flow velocity and depth at regulators • Frequency, volume, and duration of CSOs Modeling Overview

9. Ability to accurately represent CSS’s hydraulic behavior Ability to accurately represent runoff in the CSS drainage basin Extent of monitoring data available Need for long-term simulations Need to assess water quality in the CSS Need to assess water quality in receiving waters Ability to assess the effects of control alternatives Use of the presumption or demonstration approach Criteria for Selection of CSS Hydraulic Model Modeling Overview

10. Model Complexity • Levels of detail • Coarse (e.g., STORM) • Simplified sewer network • Lumped parameter • Moderate (e.g., SWMM/TRANSPORT) • Major pipes/interceptors only • Unable to simulate complex flow (e.g., backwater conditions, tidal influence) • Fine (e.g., SWWM/EXTRAN, MOUSE) • All major sewer components (storage, pumping, and smaller diameter pipes) • Able to simulate complex flow Modeling Overview

11. Level of Detail • Selection of Appropriate Level • Identify benefits from a finer level of detail • Consider penalties (accuracy) in not modeling a portion of the system • Adopt a staged approach - start from simple model and build complexity as needed and as data become available. Modeling Overview

12. Most Commonly UsedRunoff Models Other Commercial Packages 19% SWMM Family 72% Custom 9% Source: Use of Modeling Tools and Implementation of US EPA Guidelines for CSO Control by S. Rangarajan et al., TetrES Consultants Inc. Modeling Overview

13. Most Commonly UsedHydraulic Models None 19% SWMM Family 66% Other - 9% MOUSE - 2% Sewer CAT - 4% Source: Use of Modeling Tools and Implementation of US EPA Guidelines for CSO Control by S. Rangarajan et al., TetrES Consultants Inc. Modeling Overview

14. Calibration Data • Need range of typical storm events • 3 to 5 storms (minimum) • Small (0.1-0.4”), medium (0.4-1.0”) to large (>1.0”) storms • Individual storm events (return to dry weather) • Measure • Rainfall (hourly data; multiple locations) • Overflow volume • Effluent quality (for input to receiving water model) Modeling Overview

15. Data Review • Flow monitoring data • Consistent with rainfall data • Manning’s Equation (calculate velocity, flow and depth) • Flow balance review (downstream flows are consistent with upstream flows) • Outfall quality data • Can be highly variable • Compare to influent data/literature • Compare to other outfall data Modeling Overview

16. Model Development • Develop pipe network • Establish operational rules for hydraulic controls • Estimate dry weather component of flow • Conduct initial testing of model • Conduct model sensitivities • Guides calibration • Modify model parameters by +/- 25% to assess sensitivity Modeling Overview

17. Calibration Methods, Tools • Calibration process, sequence – volume, peaks/timing, pollutants • Graphical depictions of quality of fit – hydrograph plots, 1:1 plots • Measures of quality of fit – RMS error, SSD, sum of absolute differences Modeling Overview

18. Calibration Methods, Tools • Statistical comparisons of volumes and peak flows • Range of storms • +/- 20% modeled versus observed • Avoid bias Source: Urban Stormwater Modeling and Simulation by Stephan Nix Modeling Overview

19. 8 6 4 Observed (MG) 2 0 0 2 4 6 8 Modeled (MG) Model Calibration – Volume Regression 19

20. Model Calibration – Flow Example 1 20

21. Model Calibration – Flow Example 2 21

22. Why is RW Modeling Important? • Characterize the RW impacts under different CSO loads and conditions • Discern contributions of background and other sources • Predict benefits of CSO alternatives • Demonstrate WQ standards attainment or the need for a TMDL or UAA Modeling Overview

23. Illustration of a Simple Receiving Water Model UPSTREAM FLOW / LOAD CSO #2 Load B WWTP Flow / Load CSO #4 Load CSO #1 Load CSO #3 Load UPSTREAM FLOW / LOAD A C Model output locations 23

24. The General RW Modeling Process • Step 1 – Model selection • Determination that modeling was needed • Evaluation of candidate models • Step 2 – Model development • Model calibration • Model validation • Step 3 – Model application • Forecasting • Post-construction audit Modeling Overview

25. Step 1 – Model Selection Assess likelihood Receiving water characterization of RW impacts Assess loading - qualitative sources -quantitative Rank severity of WQS exceedances Select RW model(s) 25

26. Water Quality Public Health Aesthetics SurfaceWater Type DO Nutr. Sed. Toxics Bact. Clarity Debris Streams: Steep Gradual Rivers: Small Large Lakes: Shallow Deep Least Likely Most Likely Were the Right Parameters Modeled? Source: Peter Moffa, ed. 1997. Control and Treatment of Combined Sewer Overflows, 2nd ed. 26

27. Were the Time and Space Scales Appropriate? Modeling Overview

28. Useful RW Models • Dilution models (steady-state) • Bacteria and toxics near outfall • Well-mixed (stream flow small relative to CSO discharge) • Lateral mixing (include dispersion) • Plug flow (joint effects of multiple pulses) • Time-varying mass balance • Detailed hydrodynamic-based models • Mixing zone models Modeling Overview

29. Why Use Complex Models? • Complex models should only be used when the situation warrants it • Simpler model failed to answer questions • Hydrodynamic • Major changes in RW depth with flow • Complex and incomplete mixing processes (relevant to CSO discharges) • Stratified systems that significantly accentuate or attenuate CSO impacts • Water quality • Dynamic: concentrations change rapidly over time • Concentrations that are dependent on other constituents Modeling Overview

30. Step 2 – Model Development • Are all significant pollutant sources (or loss mechanisms) included? • Are the estimates of discharge volumes and concentrations reasonable? • Do the model input rates fall within accepted values? • Do the model results compare with observed data? Modeling Overview

31. Two Methods of Calibration • Subjective: visual comparison of simulation with data • Often uses additional information • Best option when working with multiple state variables • Employs modeler’s intuition in the process • Objective: quantitative measure of quality of fit (usually minimize error) • Not necessarily better • Make sure kinetic coefficients end up within reasonable range Modeling Overview

32. Creek - Node 1, Wet Weather Survey #1, 2000 May 1-5, 2000 1,000,000 Data Model 100,000 FC (#/100mL) 10,000 1,000 100 5/1 5/2 5/3 5/4 5/5 5/6 Day Did the Model Match the Observed Data? • Bacteria data are within an order of magnitude • General pattern is reproduced Modeling Overview

33. Ways to Display Results 33

34. Temporal Plot of Fecal Coliform at River Mile 3.3 100,000 10,000 1,000 Fecal Coliform 100 (#/100mL) 10 1 5/1 5/31 6/30 7/30 8/29 9/28 10/28 Date Spatial Plot of Fecal Coliform, May 6 100,000 10,000 1,000 Fecal Coliform 100 (#/100mL) 10 1 12 11 10 9 8 7 6 5 4 3 2 1 0 River Mile Ways to Display Results 34

35. Independent data set Sensitivity analyses Component analysis Addition of synthetic loads to identify un-modeled sources A RW model should not be considered truly “calibrated” until the model is tested over a wide range of conditions, produces explainable results, and is validated. Methods for Validation Modeling Overview

36. Model Validation With Independent Data • Demonstrates the model is capable of simulating a wider range of conditions • The model is run with same rates but different loads and environmental conditions that correspond to: • An event from historical data • Another event from the CSO monitoring program • Data collected in the future as part of the continuing planning process Modeling Overview

37. Questions for the LTCP Reviewer to Answer • Were the data sufficient to develop a reliable model? • Was the selected model suitable for assessing the extent of CSO impacts? • Was the model suitable for distinguishing impacts from different sources? • Did the application exceed the known limitations of the model? Modeling Overview

38. Step 3 – Model Application • Was modeling used to help select the recommended plan (watershed example and component analysis)? • Did the modeling demonstrate compliance of selected plan with WQ standards? • If not, did the modeling help define what is needed to comply with WQ standards? Modeling Overview

39. Evaluating RW Impacts of Different Control Alternatives Number of Days Exceeding E. Coli Concentration Average Year 60 Baseline 50 Separation 40 No CSO 30 Number of Days 20 10 0 235 298 406 576 1,000 2,000 5,000 10,000 E. Coli concentration (#/100mL) Modeling Overview

40. Evaluating Conditions at Different Locations • E. Coli—number of days exceeding 126#/100ml 70 60 50 No Control 40 Alt A 30 Alt B 20 10 0 Knox Br Jade Is Oak Point Clove Br Modeling Overview

41. Demonstrating Whether WQ Standards Will be Attained • E. Coli Geomean (#/100ml) April—October 250 No Control Alt A 200 Alt B 150 WQS=126 100 50 0 Knox Br Jade Is Oak Point Clove Br Modeling Overview

42. Questions to Ask About RW Models • Do modeling choices generally agree with LTCP reviewer’s expectations? • What questions need to be answered? • Were the right parameters modeled? • Do results reflect the likely severity of impacts and benefits of control? • Do the selected models fit the time scales of the anticipated problems (hourly–daily–monthly)? • Was the spatial coverage appropriate (impacted river miles)? Modeling Overview

43. Useful RW Modeling References • Moffa, Peter. 1997. The Control and Treatment of Combined Sewer Overflows (2nd Edition). Van Nostrand Reinhold, NY, NY. • EPA. 1997. Compendium of Tools for Watershed Assessment and TMDL Development. US EPA OW, Washington, DC, EPA841-B-97-006. • Chapra, Steven. 1997. Surface Water-Quality Modeling. McGraw-Hill, NY, NY. • Thomann. Robert, Mueller, J. 1987. Principles of Surface Water Quality Modeling and Control. Harper & Rowe, NY, NY. • Bowie, et al. 1985. Rates, Constants, and Kinetics Formulations in Surface Water Quality Modeling (2nd Edition). US EPA ORD, Athens, GA, EPA/600/3-85/040. Modeling Overview

44. Building the Complete Model (System Components) 44

45. Review Philosophy • Reality • There is never “enough” data & information • All models are imperfect representations—some better than others • You can’t double-check everything • So what’s an LTCP reviewer to do? • Adopt realistic review goals • Begin with the “end-in-mind” Modeling Overview

46. Review Approach • Adopt realistic review goals • Look for congruency & consistency (does it all hang together well?) • Check that level of complexity was appropriate • Identify any fatal flaws and deficiencies • Check that all the policy “i”s are dotted and “t”s crossed (use a checklist) • Be cautious of “black box” software • Begin review with the “end-in-mind” • Different models handle certain controls better • Hindsight is 20/20–could model and calibration choices be driving critical LTCP decisions? Modeling Overview

47. Getting Ready • What “end-in-mind” questions need to be answered during the review? • What models are well suited and how should they be calibrated for forecasting benefits of selected alternatives? • Are the model results used appropriately in alternatives analysis? • For example, a model framework oriented and calibrated for peak flow rates, then applied to single design storm events may not work for assessing the benefits of a storage control alternative. Modeling Overview

48. Some Common Modeling Mistakes • Excess complexity in place of sound engineering judgment • Occam’s Razor principle—the simpler of two approaches is more likely to be the correct one • Wasting resources on building a detailed model without answering the questions • Lack of available data to support model capabilities • Example—SWMM dirt accumulation/washoff; STORM first-flush routines are dangerous without data… Modeling Overview

49. Common Modeling Mistakes (Cont.) • Automation run amok? Extra scrutiny is always warranted for: • Automated and “black box” interfaces for radar rainfall, GIS information, runoff to sewer system, point source loads, and statistics output • Program code that replaces judgment about model coefficients • Program code that auto-designs pipe conveyance and pumping or river geometry • Program code that auto-simplifies the system to reduce computation needs • Questions? Seek clarification from the permittee Modeling Overview

50. Model Complexity Issues Modeling Overview