| 基于随机理论的地下水环境风险评价 |
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| 引用本文： | 张博,李国秀,程品,孙法圣,王洪义.基于随机理论的地下水环境风险评价[J].水科学进展,2016,27(1):100-106. |
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| 作者姓名： | 张博 李国秀 程品 孙法圣 王洪义 |
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| 作者单位： | 1.吉林大学地下水资源与环境教育部重点实验室, 吉林 长春 130021; |
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| 基金项目： | 国家自然科学基金资助项目(41572216) |
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| 摘 要： | 针对确定性模型难以描述含水层非均质空间分布的问题,提出基于随机理论的地下水环境风险评价方法。以矩形场地地下水污染风险评价为例,采用蒙特卡罗法生成大量渗透系数随机场,模拟含水层参数各种可能的非均质空间分布,在此基础上建立场地地下水流模型与溶质运移模型,分别计算污染物在地下水中的迁移转化情况。统计大量随机模拟中污染事故发生的频率,当模拟次数足够多时,污染频率收敛于污染概率,污染风险即通过污染概率体现出来。该方法将模型参数设为满足一定分布特征的随机变量,避免了确定性方法得出的武断的评价结果,可为工厂的选址、水源地的选址等工作提供科学指导。
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| 关 键 词： | 非确定性模型 环境风险评价 数值模拟 渗透系数随机场 |
| 收稿时间： | 2015-08-24 |
Groundwater environment risk assessment based on stochastic theory |
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| ZHANG Bo,LI Guoxiu,CHENG Pin,SUN Fasheng,WANG Hongyi.Groundwater environment risk assessment based on stochastic theory[J].Advances in Water Science,2016,27(1):100-106. |
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| Authors: | ZHANG Bo LI Guoxiu CHENG Pin SUN Fasheng WANG Hongyi |
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| Institution: | 1.Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China;2.Shandong Survey and Design Institute of Water Conservancy, Ji'nan 250013, China;3.Jilin Soil Moisture Monitoring Station, Changchun 130033, China |
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| Abstract: | This paper proposed a methodology on the assessment of groundwater environmental risk based on stochastic theory. A rectangular domain was taken as an example, random field of hydraulic conductivity coefficient is produced by Monte Carlo method, and spatially heterogeneous distribution of aquifer parameters is simulated. Subsequently groundwater flow and transport model are established and the pollutants migration in groundwater is calculated. The statistical frequency of pollution events in a large number of random simulations is considered to be convergent to pollution probability in sufficient simulation numbers, that is to say, pollution risk is reflected by pollution probability. The proposed method assumes that model parameters are random variable meeting a certain distribution characteristic, which avoids the arbitrary assessment with deterministic method. The conclusions obtained in this study can provide useful insights for site selection of factory and water source. |
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| Keywords: | stochastic model environment risk assessment numerical simulation hydraulic conductivity random field |
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