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基于SWMM耦合NSGA-II多目标优化算法的LID布局方案
周立新, 曾鹏飞, 沙有生, 周晋军, 王昊
长江科学院院报 ›› 2026, Vol. 43 ›› Issue (11) : 182-190.
PDF(2442 KB)
PDF(2442 KB)
基于SWMM耦合NSGA-II多目标优化算法的LID布局方案
Multi-objective LID Optimization Coupled with SWMM and NSGA-II
低影响开发( LID)设施通过增强雨水滞蓄与下渗能力可有效缓解内涝风险,然而其防涝效果对于不同强度与历时的降雨存在差异。为识别LID对不同降雨的防涝效果,以北京市某老旧小区为例,基于暴雨洪水管理模型( SWMM)和NSGAII多目标优化算法,以管网节点溢流总量和LID建设成本为目标函数,针对不同重现期和历时的降雨情景优化LID设施布设方案。结果表明:优化方法获得的最佳LID布设方案组合在各个降雨情景下均表现出较好的节点溢流控制效果,溢流控制率可达76.8%~95.8%;在不同重现期的长、短历时降雨中LID方案空间分布相似的区域占比分别为8.7%和14.8%,这些区域是规划和建设的关键。提出的LID优化方法可减少节点溢流量,识别重点布设位置,为LID设施选址与规模决策提供了科学方法。
[Objective] Low Impact Development (LID) facilities can effectively mitigate urban waterlogging risks by enhancing rainwater retention and infiltration. However, their flood control performance varies with rainfall intensity and duration. This study aims to evaluate the effectiveness of LID under different rainfall conditions to support efficient and scientific decision-making for sponge city renovation in old residential areas. [Method] Taking an old residential area in Beijing as a case study, a Storm Water Management Model (SWMM) was constructed. The NSGA-II multi-objective optimization algorithm was employed to optimize the LID scale in each sub-catchment, with LID construction cost and total overflow volume of drainage network nodes selected as key optimization objectives. By analyzing Pareto optimal solution sets under different design rainfall scenarios, the relationship between LID optimization schemes and rainfall characteristics was systematically explored. LID layout schemes were optimized for rainfall scenarios with varying return periods and durations. [Results] The optimal LID layout combinations obtained through the proposed method demonstrated effective node overflow control across all rainfall scenarios, with overflow control rates ranging from 76.8% to 95.8%. The proportion of areas with similar spatial distribution of LID schemes under long- and short-duration rainfall with different return periods was 8.7% and 14.8%, respectively, identifying these areas as key zones for planning and construction. [Conclusions] The proposed LID optimization method reduces node overflow and identifies priority deployment locations, providing a scientific approach for LID site selection and scale determination. Coupling SWMM with the NSGA-II algorithm enables reasonable optimization of LID layout and scale under different rainfall scenarios. The resulting optimal schemes significantly control node overflow, effectively mitigating urban waterlogging disasters.
低影响开发 / SWMM / 溢流控制 / 多目标优化 / 设计降雨
low impact development / SWMM / overflow control / multi-objective optimization / design rainfall
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