A Diagnostic Decision Support System for BMP Selection in Small Urban Watershed

作者：Wang, Yan^*; Montas, Hubert J.; Brubaker, Kaye L.; Leisnham, Paul T.; Shirmohammadi, Adel; Chanse, Victoria; Rockler, Amanda K.

来源：Water Resources Management, 2017, 31(5): 1649-1664.

DOI：10.1007/s11269-017-1605-x

• Best management practices
• Green infrastructures
• Spatial distribution
• Nonpoint pollution
• Stormwater management
• Geographic information system

Best Management Practices (BMPs) have become the most effective way to mitigate non-point source pollution (NPS) issues. Much attention has been paid to NPS in rural areas, where agricultural activities increase nutrients, toxics, and sediments in surface water. Stormwater from urban areas is also a major contributor to NPS pollution. For watersheds bearing various soil types and land uses, a single type of BMP cannot be the panacea to all stormwater problems. To solve these problems, a Diagnostic Decision Support System (DDSS) was developed in this research. The DDSS can identify and locate the most critical NPS areas (hotspots) within a watershed in high spatial resolution. The DDSS can provide a series of spatially distributed small-scale BMPs which are effective in treating the NPS and are suitable for the physical environment. The BMPs, varying in types and locations, are recommended at HRU (Hydrologic Response Unit) level. The DDSS was tested in Watts Branch, a small urban watershed of the Anacostia River in metropolitan Washington D. C., USA. The process-based hydrologic model, Soil and Water Assessment Tool (SWAT), was used to simulate watershed responses. The simulation results were then used by the DDSS for BMP recommendation. Hotspots of different NPS were successfully located and prescribed with spatially distributed BMPs. The DDSS serves as a useful tool to better understand urban watersheds and to make proper stormwater management plans.

• 出版日期2017-3