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<p>A multiobjective optimization (MOP) control method for integrated urban drainage systems (UDSs) was proposed to mitigate the impact of overflow pollution on ecosystems. Existing research often targets single rainfall events, individual objectives, or isolated facilities, lacking a comprehensive, long-term strategy. To address this, the proposed method incorporates long-term rainfall data to optimize performance across key system components in the UDSs, including drainage pipelines, pumping stations, detention pipelines, intelligent diversion wells (IDWs) and sewage treatment plants (STPs). This MOP approach dynamically coordinates infrastructure to reduce combined sewer overflows (CSOs) and pollutant loads while balancing operational costs and facility performance. Applied to a case study of Yuhang District, Hangzhou, China under a six-month rainfall sequence, the method achieved average CSOs reduction rates of 47.87% under moderate rain and 33.60% under heavy rain, with corresponding pollutant discharge reductions of 77.55% and 71.37%. The optimization also improved pumping stations efficiency, reducing operating hours by 13.76%. Key IDWs influencing system performance were recognized, with IDWs 9, 10, and 14 being the most critical. These results indicate that this approach can significantly improve the long-term hydraulic and environmental performance of UDSs, offering theoretical insights and practical guidance for sustainable urban water management.</p>

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Multiobjective optimization control for multifacility coordination in integrated urban drainage systems

  • 期刊论文

  • 发表日期：

    2025年7月12日

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  • Xiaomei Liu,
  • Siyu Zeng

摘要

A multiobjective optimization (MOP) control method for integrated urban drainage systems (UDSs) was proposed to mitigate the impact of overflow pollution on ecosystems. Existing research often targets single rainfall events, individual objectives, or isolated facilities, lacking a comprehensive, long-term strategy. To address this, the proposed method incorporates long-term rainfall data to optimize performance across key system components in the UDSs, including drainage pipelines, pumping stations, detention pipelines, intelligent diversion wells (IDWs) and sewage treatment plants (STPs). This MOP approach dynamically coordinates infrastructure to reduce combined sewer overflows (CSOs) and pollutant loads while balancing operational costs and facility performance. Applied to a case study of Yuhang District, Hangzhou, China under a six-month rainfall sequence, the method achieved average CSOs reduction rates of 47.87% under moderate rain and 33.60% under heavy rain, with corresponding pollutant discharge reductions of 77.55% and 71.37%. The optimization also improved pumping stations efficiency, reducing operating hours by 13.76%. Key IDWs influencing system performance were recognized, with IDWs 9, 10, and 14 being the most critical. These results indicate that this approach can significantly improve the long-term hydraulic and environmental performance of UDSs, offering theoretical insights and practical guidance for sustainable urban water management.