An Effective Kalman Filter-Based Method for Groundwater Pollution Source Identification and Plume Morphology Characterization

Simin Jiang,Ruicheng Zhang,Jinhong Fan,Xuemin Xia,Xianwen Li

doi:10.3390/w10081063

Simin Jiang, Ruicheng Zhang + Show 3 more

Open Access

https://doi.org/10.3390/w10081063

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Abstract

The identification of unknown groundwater pollution sources and the characterization of pollution plume remains a challenging problem. In this study, we addressed this problem by a linked simulation-optimization approach. This approach couples a contaminant transport simulation model with a Kalman filter-based method to identify groundwater pollution source and characterize plume morphology. In the proposed methodology, the concentration field library, the covariance reduction with a Kalman filter, an alpha-cut technique of fuzzy set, and a linear programming model are integrated for solving this inverse problem. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem. The evaluation considered the random hydraulic conductivity filed, erroneous monitoring data, a prior information shortage of potential pollution sources, and an unexpected and unknown pumping well. The identified results indicate that, under these conditions, the proposed Kalman filter-based optimization model can give satisfactory estimations to pollution sources and plume morphology for domains with small and moderate heterogeneity but cannot validate the transport in the relatively high heterogeneous field.

Highlights

Groundwater pollution, which remains undetected for a long time before being detected accidentally, poses a serious threat to the environment
To assess the performance of the proposed Kalman filter-based method for groundwater pollution source identification and plume characterization, we considered a hypothetical aquifer model including the random hydraulic conductivity field, measurement errors, and unknown uncertainty
Step 2: Considering the uncertainty of site information, the random hydraulic conductivity field is generated by the LHS (Latin hypercube sampling) technique assuming hydraulic conductivity in a random process

Summary

Introduction

Groundwater pollution, which remains undetected for a long time before being detected accidentally, poses a serious threat to the environment. Source removal and plume containment are two important aspects of remediation of contaminated sites [1]. The characteristics of groundwater pollution sources and pollutant plume morphology should be determined when groundwater pollution phenomena are discovered. The main purpose of the pollution source identification and plume morphology characterization is to improve the efficiency of remediation techniques or reduce the cleanup costs [2,3,4]. There is little comprehensive information related to the characteristics of groundwater pollution sources since groundwater is stored in the hidden subsurface [5]. To resolve the above-mentioned issue while the actual measurement of contaminant sources is missing, many researchers began to use the inverse solution method to identify groundwater pollution sources

Methods

Discussion

Conclusion