A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity

A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity

Abstract Accurate identification of groundwater contamination sources is important for designing efficacious site remediation strategies. Currently, the methods for identifying contamination sources mainly fall into three distinct categories: simulation optimization, Bayesian inference, and data ass...

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Bibliographic Details
Main Authors:	Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng
Format:	Article
Language:	English
Published:	Wiley 2024-04-01
Series:	Water Resources Research
Subjects:	simulation optimization Bayesian inference surrogate model data assimilation groundwater contamination source identification hyperparameter optimization
Online Access:	https://doi.org/10.1029/2023WR036051
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