LAKEMAGING: GEOPHYSICAL DATA INTEGRATION FOR GROUNDWATER MODELLING

Groundwater models are often affected by strong uncertainties because hydrogeological information is commonly derived from sparse boreholes, local hydraulic tests, and indirect observations that do not adequately describe subsurface heterogeneity. In this context, geophysical methods, and especially electrical and electromagnetic techniques, provide spatially continuous information that can improve conceptualization of aquifer systems. However, their integration into hydrogeological workflows remains challenging because geophysical datasets may differ in scale, sensitivity, and acquisition time, and because electrical properties are only indirectly related to hydraulic parameters. This thesis develops methodological frameworks for integrating geophysical data and for transferring geophysical information into groundwater modelling. The first part addresses joint inversion of concordant, discordant, and geologically constrained datasets. It shows that combining datasets with complementary sensitivities can reduce non-uniqueness and improve subsurface characterization, while robust inversion strategies based on asymmetric generalized minimum support can mitigate the influence of inconsistent or outdated ancillary data without discarding them entirely. The integration of geological constraints within 3D inversion further improves the structural plausibility of the recovered models in complex settings. The second part focuses on waterborne transient electromagnetic data and their use in groundwater modelling. A dedicated inversion workflow is developed to account for bathymetry, sharp resistivity contrasts, and depth-dependent damping. Synthetic tests and field applications show that these elements are essential to correctly image the water–sediment interface and reduce inversion artifacts in lacustrine environments. The resulting models are then incorporated into groundwater simulations through two complementary approaches: direct petrophysical translation and structurally guided calibration. Two case studies demonstrate that geophysical information can improve aquifer parameterization, preserve mapped heterogeneity, and reduce conceptual uncertainty, although the reliability of direct petrophysical conversion remains strongly site dependent. Overall, the thesis shows that geophysics can play a more active role in groundwater modelling, not only as a qualitative support tool but as a quantitative source of constraints for inversion, model building, and uncertainty reduction.