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Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Paula Rulff·Octavio Castillo-Reyes·Wouter Deleersnyder·Maria C. Mascarell·Burke J. Minsley·Jude King
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Abstract

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

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Paula Rulff, Octavio Castillo-Reyes, Wouter Deleersnyder, Maria C. Mascarell, Burke J. Minsley, Jude King. 2026. Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances. https://doi.org/10.1016/j.jhydrol.2026.135542

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