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Geoelectrical techniques are widely used to monitor groundwater processes,while surprisingly few studies have considered audio (AMT) and radio (RMT)magnetotellurics for such purposes. In this numerical investigation, we analyzeto what extent inversion results based on AMT and RMT monitoring data can beimproved by (1) time-lapse difference inversion; (2) incorporation ofstatistical information about the expected model update (i.e., the modelregularization is based on a geostatistical model); (3) using alternative modelnorms to quantify temporal changes (i.e., approximations of l1 and Cauchy normsusing iteratively reweighted least-squares), (4) constraining model updates topredefined ranges (i.e., using Lagrange Multipliers to only allow eitherincreases or decreases of electrical resistivity with respect to backgroundconditions). To do so, we consider a simple illustrative model and a morerealistic test case related to seawater intrusion. The results are encouragingand show significant improvements when using time-lapse difference inversionwith non l2 model norms. Artifacts that may arise when imposing compactness ofregions with temporal changes can be suppressed through inequality constraintsto yield models without oscillations outside the true region of temporalchanges. Based on these results, we recommend approximate l1-norm solutions asthey can resolve both sharp and smooth interfaces within the same model.

Focused time-lapse inversion of radio and audio magnetotelluric data