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1. BMP Evaluations Using SWAT Model and Associated Uncertainties A. Shirmohammadi and T. W. Chu. Biological Resources Engineering Department University of Maryland, College PArk

2. “Forests and wetlands trap sediments and help slow the flow of pollutants into the Bay. Their loss, coupled with the decline of grasses and oysters in the 1970s and 1980s, caused the Bay to lose much of its resilience.” Chesapeake Quarterly MD Sea Grant College, Vol. 3, Num. 3 October 2004

3. Ecological Resilience: Provides a measure of the amount of disturbance that an ecosystem can withstand without shifting into an “alternate stable state”

4. For Bay: “The shift from a food web dynamic driven by benthic processes- such as underwater grasses and oysters- to one driven by phytoplankton in the water column is a classic example of regime shift, a shift between stable states.”

6. Identifying Thresholds: “Researchers must develop a systematic way to anticipate when a system is getting close to a threshold or tipping point and prevent it from going over the edge. They also need to develop methods to turn around the state of a system such as the Chesapeake Bay from undesirable to desirable!” ---Load Reduction!

7. Background Hydrologic/ water quality models are the main tools used to tabulate total maximum daily loads (TMDLs) Procedure for tabulating TMDLs Use monitored data as input into model to represent base conditions Simulate alternate management scenarios Choose management scenario that meets water quality standards Determine total load and allocate load among sources

8. Background General expression for TMDL allocations: TMDL=ΣWLA + ΣLA + Future Growth + MOS Waste Load Allocations (WLA)- point source contributions Load Allocations (LA)- non-point source contributions including background sources Margin of Safety (MOS)- accounts for uncertainties about the relationship between pollutant loads and receiving water quality (USEPA, 1999a)

9. Background Types of Uncertainty in Modeling Model Structure Parameter Values Natural Variability (Spatial and Temporal) Data Uncertainty Model Prediction

10. Watershed/Basin Scale Model SWAT (Arnold et al., 1998)

11. Data Source: Study Site: Warner Creek Watershed

13. Stream flow

14. Sediment

15. NO3-N

16. NH4-N

17. TKN

18. PO4-P

21. Background on SWAT Model

22. Components of SWAT Model Hydrology Sedimentation (Erosion) Nutrients Pesticides Bacteria

24. Calibration period (1994-1995). Validation period (1996-2002).

26. Table. Statistical results comparing measured and simulated flow data at station 2A after adjustment to the subsurface flow contribution from outside the watershed.

30. - NO3 - N Statistics

32. List of BMPs Simulated

33. Total areas for row crops planting within Warner watershed

34. Results of BMP Simulation

35. Comparison of annual total streamflow at the outlet of the watershed based on different BMP implementations. *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

36. Comparison of annual surface runoff at the outlet of the watershed based on different BMP implementations. *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

37. Comparison of annual surface runoff at the outlet of the watershed based on different BMP implementations without winter crop planting . *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

38. Comparison of annual sediment loading at the outlet of the watershed based on different BMP implementations. *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

39. Comparison of annual nitrate nitrogen loading at the outlet of the watershed based on different BMP implementations. *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

40. Comparison of annual soluble phosphorus loading at the outlet of the watershed based on different BMP implementations. *Background: up and downhill planting with conventional tillage BMP1: contour planting with conventional tillage BMP2: contour planting with conservation tillage BMP3: contour planting with no-till BMP4: contour stripcropping with no-till

46. Comparison of average annual (1994-2002) model prediction at the outlet of the watershed based on different BMP implementations with and without winter crop planting

47. Latin Hypercubic Sampling For Model Uncertainty

50. Model output distribution of Sediment loading at the watershed outlet

51. Model output distribution of Nitrate loading at the watershed outlet

52. Model output distribution of Streamflow at the watershed outlet 1004 BMP4 BMP4 (1996)

53. Model output distribution of Nitrate loading at the watershed outlet BMP4 (1996) BMP4 (1996) without winter crop

54. Acknowledgement Our Cooperator, Dr. Linda Abbot of USDA/OCE/ORACBA

55. Model output distribution of Sediment loading at the watershed outlet BMP2 BMP4 (1996)