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基于随机统计方法的地下水污染源反演识别 被引量:6

Groundwater Pollution Source Inverse Identification Based on Random Statistical Methods
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摘要 地下水污染具有存在的隐蔽性、发现的滞后性特点,这给地下水污染修复方案设计、污染风险评估、污染责任认定都带来了很大的困难。以某垃圾填埋场垃圾渗滤液地下泄漏为例,对地下水污染源的反演识别问题进行研究。通过污染质运移模拟模型、替代模型、随机统计方法(伴随状态方法及贝叶斯方法)的综合运用,反演识别地下水污染源的位置、个数及释放历史。结果表明,伴随状态方法和贝叶斯方法的联合运用可以反演识别出污染源的个数、位置及释放历史;贝叶斯方法反演识别污染源过程中,以替代模型作为模拟模型的转化形式,用替代模型代替模拟模型大幅度地减小了计算负荷,并保持较高的精度。 Groundwater pollution is characterized of hidden existence and hysteretic nature,which makes it difficult to design groundwater restoration schemes,evaluate pollution risks,and determine the account ability to pollution.A case of leakage of sewage from a landfill site was studied using inverse identification of groundwater pollution sources.Three techniques,i.e.,solute transport simulation,surrogate model,and random statistical method(with adjoint state method and Bayesian method)were used to identify the pollution sources.Results show that the number,location,and history of pollution discharge could be determined by solving the inverse problem and combining adjoint state method with Bayesian method.In the inverse identification of pollution sources based on Bayesian method,the surrogate model was an alternative to the simulation model.The replacement of the simulation model with the surrogate model could greatly reduce the computational load while maintain a considerable high degree of accuracy.
作者 张宇 吕军 卢文喜 刘洪超 ZHANG Yu;L Jun;LU Wen-xi;LIU Hong-chao(Songliao River Conservancy Commission of the Ministry of Water Resources,Changchun 130021,China;College of New Energy and Environment,Jilin University,Changchun 130021,China)
出处 《科学技术与工程》 北大核心 2020年第2期535-543,共9页 Science Technology and Engineering
关键词 地下水污染 反演识别 伴随状态方法 贝叶斯方法 替代模型 groundwater pollution inverse identification adjoint state method Bayesian method surrogate model
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