Joint Estimation of Adsorptive Contaminant Source and Hydraulic Conductivity Using an Iterative Local Updating Ensemble Smoother with Geometric Inflation Selection

Xuemin Xia, Xiang Li (), Yue Sun and Guoqiang Cheng
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Xuemin Xia: School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
Xiang Li: College of Communication and Art Design, University of Shanghai for Science and Technology, Shanghai 200093, China
Yue Sun: School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
Guoqiang Cheng: Guangdong Branch of China Geological Exploration Center of Building Materials Industry, Guangzhou 510403, China

Sustainability, 2023, vol. 15, issue 2, 1-25

Abstract: The joint estimation of groundwater contaminant source characteristics and hydraulic conductivity is of great significance for reactive contaminant transport models in heterogeneous subsurface media. The accurate determination of the sorption parameters of such contaminants is also a key prerequisite for estimating the parameters of the groundwater system. In this study, to investigate the impact of the sorption parameter field on the accuracy of hydraulic conductivity and source characteristics estimation, numerical experiments were conducted in a synthetic aquifer considering the contaminant sorption process in groundwater models with varying sorption parameter settings. Iterative local updating ensemble smoother with geometric inflation selection (ILUES-GEO) was employed to assimilate hydraulic head and contaminant concentration data to jointly estimate the contaminant source information and hydraulic conductivity in a heterogeneous aquifer. The results indicated that the ILUES-GEO successfully recovers contaminant source information simultaneously with hydraulic conductivity, and its performance improves as more accurate sorption parameters are introduced. Furthermore, the influence of the ILUES algorithm parameters and ensemble size is investigated to improve the estimation accuracy. Additionally, the characterization of contaminant sources and hydraulic conductivity fields is influenced by the number and locations of measurements. This study can help to understand the significance of sorption parameter setting for the joint estimation of reactive contaminant source and hydraulic parameters.

Keywords: adsorptive contaminant; parameter estimation; iterative local updating ensemble smoother; algorithm parameter; distribution coefficient field (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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