Abstract:

Accurate characterization and monitoring of the spatiotemporal distribution of contaminants in groundwater have become crucial objectives for effective groundwater management. However, the elusive nature and heterogeneity of groundwater contamination constrain the precise characterization of contamination distribution and migration paths. Geophysical methods offer advantages such as being non-invasive, low-cost, and efficient, while providing continuous information, and have thus emerged as important tools for characterizing and monitoring groundwater contamination. This review summarizes mature geophysical methods in the field of groundwater contamination, outlining their basic principles, models, and research examples. Through integrated column experiments and micro-scale imaging techniques, interpretive models for geophysical responses in porous media under contaminant influence were established. A series of petrophysical models were developed to relate hydrogeological parameters to geophysical data, demonstrating the potential for direct inversion of contaminant concentrations from field-scale geophysical measurements. Structure-constrained inversion methods that incorporate prior information were developed to reduce uncertainty in the results. Novel numerical simulation approaches were introduced to integrate and couple simulations of multi-source data. To address the problems of uncertainty in geophysical methods, various mechanistic models, inversion methods, and multi-source data fusion approaches have been developed. Future research should focus on the pore-scale mechanisms of contaminant migration and establish a unified petrophysical database of geophysical responses to groundwater contamination. Moreover, by combining new technologies such as artificial intelligence and data assimilation, it will be possible to describe, predict, and manage contaminated groundwater sites with greater accuracy and comprehensiveness.

Key words: groundwater contamination, geophysical methods, petrophysical models, characterization and monitoring, future challenges