• 董新宇,张静慧,袁鹏,宋永会.基于多目标优化的低影响开发设施布局方法[J].环境科学学报,2021,41(7):2933-2941

  • 基于多目标优化的低影响开发设施布局方法
  • Low impact development practices layout method based on multi-objective optimization
  • 基金项目:生态环境部业务专项(No.22110302005)
  • 作者
  • 单位
  • 董新宇
  • 1. 中国地质大学(北京)水资源与环境学院, 北京 100083;2. 中国环境科学研究院流域水环境污染综合治理研究中心, 北京 100012
  • 张静慧
  • 中国环境科学研究院流域水环境污染综合治理研究中心, 北京 100012
  • 袁鹏
  • 中国环境科学研究院流域水环境污染综合治理研究中心, 北京 100012
  • 宋永会
  • 1. 中国地质大学(北京)水资源与环境学院, 北京 100083;2. 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012
  • 摘要:以海绵城市试点区-南昌市某分流制区域为例,针对低影响开发(LID)设施的最优成本效益问题,耦合了雨水管理模型(SWMM)和非支配排序遗传算法(NSGA-Ⅱ),对LID设施建设成本、径流SS负荷削减率、径流量削减率3个目标函数进行多目标优化.得到了一系列完整的成本效益曲线(帕累托解集),实现了区域LID设施建设方案的自动寻优.比较不同降雨重现期(P=2、5、15 a)条件下的优化结果,发现LID设施在径流SS负荷控制方面不易受降雨重现期的影响;而在径流量控制方面,受降雨重现期影响较大,高成本LID设施建设方案也难以有效削减高重现期降雨径流.以帕累托解集中3种不同建设成本的方案为例,根据2016年实际降雨对不同方案下的水量水质的控制效果进行了模拟,决策者可以根据资金投入、控制目标、受纳水体环境容量从帕累托解集上选择适合的LID设施建设方案.
  • Abstract:To achieve the optimal cost-effectiveness of Low Impact Development(LID) Practices, a pilot project in Nanchang with Separate Storm Water Sewer Systems was selected to conduct the study. Storm Water Management Model (SWMM) and Non-dominant Sequencing Genetic Algorithm (NSGA-Ⅱ) were coupled to adopt in the study area to get a series of complete cost-benefit curves (Pareto solution sets) with the optimization objectives of three functions of LID practices unit construction cost, runoff SS load reduction rate and runoff volume reduction rate, realizing the automatic optimization of the regional LID practices planning scheme. The results indicate that LID practices are not susceptible to the influence of rainfall recurrence periods in runoff SS load controlling rather than runoff volume controlling by comparing the solution sets under different rainfall recurrence periods (P=2,5,15 a). High-cost LID practices construction schemes are also difficult to reduce the runoff volume effectively under high recurrence period. Three different cost solutions were selected from the Pareto solution set to simulate their control effects on water quantity and quality by using the actual precipitation data available in 2016, and decision makers could select the most suitable LID practices layout scheme from the Pareto solution set according to the investment, control objectives and environmental capacity of receiving water.

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