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基于脆弱性的地下水污染监测网多目标优化方法研究
林 茂,苏 婧,孙源媛,周吉峙,纪丹凤,崔驰飞,席北斗,等
作者单位地址
林 茂 上海大学环境与化学工程学院 北京市朝阳区大羊坊八号苑
苏 婧 浩蓝环保股份有限公司 
孙源媛 中国环境科学研究院环境保护部地下水污染模拟与控制重点实验室 
周吉峙 上海大学环境与化学工程学院 
纪丹凤 中国环境科学研究院环境保护部地下水污染模拟与控制重点实验室 
崔驰飞 中国环境科学研究院环境保护部地下水污染模拟与控制重点实验室 
席北斗 中国环境科学研究院环境保护部地下水污染模拟与控制重点实验室 
摘要:
为了以最少的监测费用最大化地获取区域污染风险和污染现状信息,建立了一个基于脆弱性评价的地下水污染监测网多目标优化模型,该模型包括监测井数量最少、监测到污染物浓度最大、监测到的区域脆弱性分值最大三个目标函数。以硝酸盐作为特征污染物,每口井位的地下水脆弱性分值和硝酸盐氮浓度分别通过地下水脆弱性评价和溶质运移模拟得到。采用改进非劣支配遗传算法(NSGA-II)求解该多目标优化模型,并借助质量误差分析确定监测网优化方案。算例研究表明,通过NSGA-II求解该多目标模型得到一系列Pareto最优解,结合质量误差分析结果,监测井数量由原来的60口优化为12口,保证监测效率的同时大大降低了监测成本。此监测网优化方法为决策者选择经济有效的地下水污染监测网布设方案提供了切实有力的参考。
关键词:  地下水污染监测网  多目标优化  数值模拟  脆弱性评价  NSGA-II
DOI:
分类号:X523
基金项目:北京市科技计划项目;中欧环境可持续项目-“松花江辽河流域水质改善污染排放管理示范项目”
Research on Multi-objective Optimization Method Based on Vulnerability Assessment for Monitoring Network Design for Detection of Groundwater Contamination
苏 婧,et al
Abstract:
In order to use least monitoring costs to get maximum information about regional pollution risk and pollution, this study established a multi-objective optimization model for monitoring network for groundwater contamination in which vulnerability and pollution situation in groundwater were considered. The model had three objective functions, including minimizing the number of wells, maximizing pollutant concentration monitored, and maximizing vulnerability indexes of monitoring area. By solute transport simulation and vulnerability evaluation, the concentration of typical pollutant, nitrate and vulnerability index of groundwater at each well site were provided respectively. Non-dominated sorted based algorithm II (NSGA-II) was used to solve the multi-objective optimization model. Case study showed that the multi-objective model was solved by NSGA-II to get a set of Pareto optimal solutions. Synthesizing the result of mass estimation error analysis, monitoring well number was optimized to 12 from 60. This prioritization scheme ensures the monitoring efficiency of monitoring network and greatly reduced the monitoring cost. This multi-objective optimization method could provide policymakers good references to choose a cost-effective layout scheme of monitoring network for groundwater contamination.
Key words:  monitoring network for groundwater contamination  multi-objective optimization  numerical simulation  vulnerability assessment  NSGA-II