基于智慧水务理念的城市排水系统调度技术优化研究OA

The acceleration of urbanization and the increasing frequency of extreme rainfall events have posed prominent problems such as urban flooding and overflow pollution to the urban drainage system.Particularly in areas with severe misconnections between stormwater and wastewater pipelines,where strong rainfall can easily trigger sewage manhole overflow.To address this issue,this study focuses on a China urban area with known storm-sewage misconnections and overflow risks.By investigating the misconnection conditions,installing water-level monitoring devices,and deploying self-developed intelligent pipeline control gates,combined with an SWMM-based hydraulic simulation model,the study reconstructs the hydrodynamic characteristics of the drainage system.The model achieves a Nash-Sutcliffe efficiency coefficient of≥0.75 at key monitoring points,accurately reproducing water-level variations under both dry and wet weather conditions,thereby providing a reliable foundation for scheduling decisions.Under both typical design storms and actual rainfall events,the study evaluates the overflow-control effectiveness of different gate operation combinations.Results indicate that closing a greater number of gates leads to a more pronounced reduction in the peak water level at the overflow-prone point WS7.During the rainfall event on May 22-23,2025,with a cumulative precipitation of 55.8 mm,closing all six gates controlled the peak water level at WS7 to 2.55 m,effectively preventing approximately one hour of overflow while maintaining operational safety margins.Further simulations show that the system with the existing six gates can withstand a similar 12-hour rainfall event with a total precipitation of 95.7 mm.Water-quality monitoring and time-series gate-operation analysis reveal that timely gate closure after a noticeable rise in water level can effectively intercept highly polluted first-flush runoff while reducing the inflow of low-pollution stormwater into the wastewater system,achieving dual benefits in overflow mitigation and water-quality protection.The study verifies the feasibility of a drainage scheduling framework that integrates model-based decision support,intelligent control facilities,and a smart water-management platform.Since its routine deployment in May 2025,the system has successfully prevented overflow events during multiple heavy rainfalls in the study area,demonstrating strong engineering applicability and significant potential for broader implementation.