ES-MDA算法融合ERT数据联合反演地下水污染源与含水层参数  

Joint inversion of contaminant source and aquifer parameters by assimilating ERT data with the ES-MDA algorithm

作　　者：周念清[1] 张瑞城 江思珉[1] 夏学敏 ZHOU Nianqing;ZHANG Ruicheng;JIANG Simin;XIA Xuemin(Department of Hydraulic Engineering,Tongji University,Shanghai 200092,China;School of Environment and Architecture,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]同济大学土木工程学院,上海200092 [2]上海理工大学环境与建筑学院,上海200093

出　　处：《南水北调与水利科技（中英文）》2022年第3期478-486,共9页South-to-North Water Transfers and Water Science & Technology

基　　金：国家自然科学基金项目(42077176)。

摘　　要：针对未知的污染场地,为了准确估计污染物运移模型的参数,提出一种基于多重数据同化集合平滑器(ensemble smoother with multiple data assimilation,ES-MDA)算法的地下水模型参数反演方法,通过融合由高密度电阻率(electrical resistance tomography,ERT)法采集的ERT观测数据,实现对污染源源强和渗透系数场的联合反演。以此为基础设计3组数值算例,比较不同类型观测数据对反演精度的影响。研究结果表明:融合ERT数据的ES-MDA算法对模型参数的反演精度更高,并且将ERT数据和传统的质量浓度与水头观测数据相结合,能进一步优化反演结果。Predicting the migration and transformation process of contaminants by utilizing numerical models is a commonly used method.The accuracy of model parameters could seriously affect the simulation results.While in practical site investigation,model parameters are often unavailable to obtain directly,thus it is needed to be estimated by solving the inverse problem of groundwater.In recent years,data assimilation has become a prevalent method for parametric uncertainty quantification.It can provide an estimate of the unknown model parameters by combining the observation data with the underlying dynamical principles governing the system.When solving high dimensional inversion problems,conventional observation methods can only provide sparse information(such as mass concentration and hydraulic head),so it can hinder the accuracy of the results.To deal with this issue,geophysical methods(such as electrical resistance tomography)are introduced to combine with the data assimilation because they can provide a large amount of continuous observation data.The groundwater flow and solute transport model was constructed with the MODFLOW and MT3 DMS programs and KL expansion was introduced to implement the dimensionality reduction of the hydraulic conductivity field.An inversion method for groundwater model parameters based on the ensemble smoother with multiple data assimilation(ES-MDA)was proposed.The joint inversion of contaminant source strength and hydraulic conductivity field was realized by integrating conventional observation data(mass concentration and hydraulic head)and geophysical data(ERT data)collected through the electrical resistance tomography(ERT).Three numerical cases were designed based on the former ideas to compare the inversion accuracy with different types of observation data.All three cases were the ES-MDA algorithm as the data assimilation method,while Case 1 was integrated the mass concentration and hydraulic head as the observation data;Case 2 was integrated the ERT data as the observation data and Cas

关 键 词：数据同化 集合平滑 地球物理 高密度电阻率法 渗透系数场 

分 类 号：TV213[水利工程—水文学及水资源] X523[环境科学与工程—环境工程]