1. Glenn E. Moglen Department of Civil & Environmental Engineering Virginia Tech Continuous Streamflow Modeling with SWMM CEE 5734 – Urban Hydrology and Stormwater Management Week 10

2. Questions Final Exam will be May 4 (last class meeting) Continuous Streamflow Modeling Basic Idea Why we do it How we do it Where to obtain files Rainfall Observed Streamflow Simulated Streamflow Calibrating Quantifying Goodness-of-fit Today’s Agenda

3. In contrast to “Event Based” modeling which we have been doing all semester to this point, continuous streamflow modeling attempts to model the streamflow behavior of the watershed over periods of both wet and dry weather. Storms produce flood flows with “recovery periods” in between in which the watershed returns to baseflow conditions. Continuous Streamflow Modeling: Concept

4. 1. Once a model is calibrated for a particular watershed, it becomes possible to predict future streamflow behavior under changed land use and/or climate. 2. When predicting pollutant or nutrient loads that are mobilized or transported by streamflow, it is important to first be accurately representing the flow before the transport can be accurately represented. Continuous Streamflow Modeling: Why do we do it?

5. Need to obtain time series of both “driver” (precipitation and maybe temperature) and “resultant” (observed streamflow) data. Run model (EPA-SWMM) with driver data and calibrate model parameters until simulated streamflow approximates observed streamflow. Continuous Streamflow Modeling: How do we do it?

6. Precipitation data: Obtained from NCDC web site – link provided at class web sites SWMM expects hourly (DSI 3240 format) data Format: Space Delimited Without station name Note: must be logged in through vt.edu domain to obtain data for free. Use Virtual Private Network (VPN) Continuous Streamflow Modeling: Files Needed

7. Continuous Streamflow Modeling: Precipitation Data

8. Streamflow data: Obtained from USGS surface water daily data – link provided at class web sites Watershed area reported by USGS as part of “Location Map” information Requires re-formatting: First line: SWMM outlet name Subsequent lines: date, hour, value Save as simple text file “Peasant Model” can be derived from “daily statistics” option at USGS site – more later. Continuous Streamflow Modeling: Files Needed

9. Continuous Streamflow Modeling: Observed Streamflow Data

10. Putting Observed Streamflow Data in SWMM Select from SWMM menu: “Project: Calibration Data…” Enter streamflow data filename in “Node Lateral Inflow” category

11. Continuous Streamflow Modeling: Simulated & Observed Streamflow Data

12. Need to create an “Aquifer” object This is not a visible object so create from left-hand browser panel Continuous Streamflow Modeling: Groundwater/Aquifer Modeling Suggestion!

13. Double-click “Groundwater Flow” Property of any subcatchment object… Continuous Streamflow Modeling: Groundwater/Aquifer Modeling A1 B1 A2 B2 A3

14. Calibrating with an Aquifer Black Solid: Observed streamflow Calibrating with an Aquifer Black Solid: Observed streamflow Red dashed: A1 = 1, B1 = 1 Blue dashed: A1 = 0.01, B1 = 1 Green dashed: A1 = 0.01, B1 = 0.5 Need to experiment…and document!

15. Getting simulation data OUT of SWMM Create a time series plot or a table, then choose: Edit: Copy to… You can then paste into Excel Continuous Streamflow Modeling: Quantifying Goodness-of-fit

16. Nash-Sutcliffe – Definition Why can’t you use the normal R 2 approach from statistics? Continuous Streamflow Modeling: Quantifying Goodness-of-fit Perfect Model: R NS 2 = 1

17. Perfect Model: DG = 1 Gain Coefficient – Definition Continuous Streamflow Modeling: Quantifying Goodness-of-fit “Peasant” Model

18. Deviation Volume Continuous Streamflow Modeling: Quantifying Goodness-of-fit

19. Consider it a “game” with the following rules: 1. Goal is to optimize goodness-of-fit measures 2. Keep good record of trial parameters and simulation outcome. 3. It is good practice to only vary one parameter at a time, otherwise it is difficult to attribute changes in results to a given action. 4. Do not vary model parameters outside of realistic physical limits. Continuous Streamflow Modeling: Calibration

20. Example of record keeping… Continuous Streamflow Modeling: Calibration Trial #Parameter Varied Parameter Value DGDvDv Comments BaseN/A 1A10.01 Baseflows drop too slowly, increase A1 2A20.5 3Conductivity0.5 4 Sub- catchment width 400 5etc…