Yoon, Seonkyoo Lee, Seunghak Zhang, Jiangjiang Zeng, Lingzao Kang, Peter K. 2024-01-19T10:04:21Z 2024-01-19T10:04:21Z 2023-02-17 2023-02 0022-1694 https://pubs.kist.re.kr/handle/201004/114045 Groundwater contamination is an exacerbating global issue that severely threatens human health. Subsurface remediation thus has gained increased interest in recent years. To effectively remediate subsurface contaminated sites, one needs to identify the locations of contaminant sources and characterize contaminant spreading. Groundwater contamination is often driven by multiple contaminant sources, making source identification problems challenging. Further, when the densities of dissolved contaminants and ambient groundwater differ, the resultant variable-density flows add complexity to the task of source identification. However, most previous studies are limited to a single source identification in a two-dimensional aquifer. This study presents a novel inversion method based on ensemble smoothing that identifies the locations of multiple contaminant sources in three-dimensional heterogeneous aquifer systems. A new covariance localization algorithm based on a clustering method is integrated into the inversion method, which improves the accuracy of multi-source identification. Using the proposed inversion framework, we successfully estimate the locations of multiple contaminant sources and three-dimensional permeability fields utilizing pressure and concentration data from monitoring wells. Further, we investigate and elucidate the effects of aquifer heterogeneity and variable-density flows on multiple source identification. We find that variable-density flow increases the data information contents and thus im-proves the inversion accuracy. This is the first-time demonstration of the effects of variable-density flow on the inversion accuracy of multi-source identification in three-dimensional heterogeneous aquifer systems. English Elsevier BV Inverse estimation of multiple contaminant sources in three-dimensional heterogeneous aquifers with variable-density flows Article 10.1016/j.jhydrol.2022.129041 1 Journal of Hydrology, v.617 Journal of Hydrology 617 N scie scopus 000921112400001 2-s2.0-85145769007 Engineering, Civil Geosciences, Multidisciplinary Water Resources Engineering Geology Water Resources Article GROUNDWATER POLLUTION SIMULTANEOUS IDENTIFICATION HYDRAULIC CONDUCTIVITY DATA ASSIMILATION SOLUTE TRANSPORT PRESSURE DATA POROUS-MEDIA CONVECTION HISTORY ONSET Inverse estimation Multiple contaminant sources 3D heterogeneous aquifer Ensemble smoothing Variable-density flows