引用本文:林茂,苏婧,孙源媛,周吉峙,纪丹凤,崔驰飞,席北斗,等.基于脆弱性的地下水污染监测网多目标优化方法[J].环境科学研究,2018,31(1):79-86.
LIN Mao,SU Jing,SUN Yuanyuan,ZHOU Jizhi,JI Danfeng,CUI Chifei,XI Beidou,et al.Multi-Objective Optimization Method for Groundwater Contamination Monitoring Network based on Vulnerability Assessment[J].Reserrch of Environmental Science,2018,31(1):79-86.]
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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
林茂1, 苏婧3, 孙源媛2, 周吉峙1, 纪丹凤2, 崔驰飞2, 席北斗2
1. 上海大学环境与化学工程学院, 上海 200444;2. 中国环境科学研究院, 国家环境保护地下水污染模拟与控制重点实验室, 北京 100012;3. 浩蓝环保股份有限公司, 广东 广州 510630
摘要:
区域地下水监测井的优化布设对于区域地下水系统管理有很重要的作用.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,以监测井数量最小、区域污染监测有效性最大、监测到的区域脆弱性分值最大为目标,建立了基于脆弱性评价的地下水污染监测网多目标优化模型.通过地下水脆弱性评价和溶质运移模型计算得到不同点位地下水脆弱性分值和污染物浓度,针对不同脆弱性等级提出区域监测井初设密度,采用改进非劣支配遗传算法(NSGA-Ⅱ)基于初设监测网求解该多目标优化模型,结合质量误差分析确定监测网优化方案.结果表明,阿什河漫滩区和樊家沟流域地下水硝酸盐氮污染相对较严重;地下水脆弱性高和较高等级区域分别分布在抽水井群影响范围和河漫滩;结合NSGA-Ⅱ Pareto最优解及质量误差分析结果,得到该区域地下水监测井最优数量(12口)及其最优布设位置.研究显示,该优化监测网与初设监测网插值所得污染羽的质量误差小于15%,满足监测精度要求.
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:10.13198/j.issn.1001-6929.2017.03.67
分类号:X523
基金项目:北京市科技计划项目(D141100004514001);中欧环境可持续发展计划(DCI-ASIE/2013/323-261)
Multi-Objective Optimization Method for Groundwater Contamination Monitoring Network based on Vulnerability Assessment
LIN Mao1, SU Jing3, SUN Yuanyuan2, ZHOU Jizhi1, JI Danfeng2, CUI Chifei2, XI Beidou2
1. School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China;2. State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Science, Beijing 100012, China;3. CNHOMELAND Environmental Protection Water Pollution Governance Academician Work station, Guangzhou 510630, China
Abstract:
The optimal design of groundwater monitoring plays an important role in regional groundwater system management. In order to use the least monitoring cost to get the maximum information about regional pollution risk and pollution situation, we established a multi-objective optimization model for groundwater contamination monitoring network based on vulnerability assessment, in which there were three objectives, including minmizing number of monitoring wells, maximizing monitoring effectiveness of regional groundwater pollution, and maximizing vulnerability indexes in monitoring area. Through groundwater vulnerability assessment and solute transport simulation, the vulnerability indexes and pollutant concentrations of groundwater in different monitoring sites were calculated respectively. Initial layout density of monitoring wells for regions at different groundwater vulnerability levels were proposed. Non-dominated sorted based algorithm Ⅱ (NSGA-Ⅱ) was applied to solve the multi-objective optimization model contraposing initial monitoring network. The optimized scheme of monitoring network was determined by comprehensively analyzing the result of optimization model and quality error analysis. The research area was located at Ashi River Basin in Harbin City, Heilongjiang Province. The results showed that the nitrate-nitrogen pollution of groundwater in flood plain of Ashi River and Fanjia Ditch Basin was relatively serious; regional groundwater with vulnerability at high and relatively high level was distributed in the influence scope of pumping well group and flood plain of Ashi River. Monitoring well number (12) and its optimal locations were optimized by synthesizing the Pareto optimum solution solved by NSGA-Ⅱ and result of mass error analysis. The estimated mass error of optimized monitoring network compared with initial monitoring network was less than 15%, which met the requirement of monitoring precision.
Key words:  groundwater pollution monitoring network  multi-objective optimization  numerical simulation  vulnerability assessment  NSGA-Ⅱ