Evaluating Controller Performance and Placement on System-level Urban Flooding Reduction and Water Quality Improvement

摘要: Increases in urbanization and climate change are forcing urban drainage engineers to more effectively leverage stormwater storage facilities minimize flooding water quality impacts. This process becomes increasingly challenging due the operations of coordination across system-level watershed. study presents a real-time control simulation for assessing watershed-scale performance. The objective this work is make trade-off between mitigation at flooded nodes stress reduction ponds. An open-source tool called PySWMM was used conduct rule quantity modeling. For testing tool, four rule-based scenarios were performed: baseline control, downstream individual with 11 same controllers, different controllers. Meanwhile, three indicators, including peak depth shaving efficiency, pollutant removal flooded-hour reduction, evaluate controller performance operation coordination. A real-world system, Network A, selected as case study. Our results indicate that most performs best alleviating while has better obtaining global benefits higher Peak Depth Shaving Efficiency (up 7.30% ), Pollutant Removal 66.59%), Flooded-hour Reduction 71.01%). quantitative placement analysis based on Controller Placement Index (CPI) then conducted determine which controllers have positive or negative effects outcomes. CPI values suggest upstream ponds lower capacity should be regulated, those larger volumes ought uncontrolled, maximize benefits. paper provides basis improving design controlled systems.