Quantifying water and heat fluxes at the surface water (SW)–groundwater (GW) interface is crucial for ensuring sustainable water management and quality. However, direct field-based quantification remains challenging due to the dynamic nature of SW-GW interactions, which are influenced by poorly constrained boundary conditions and spatial hydrofacies distributions. Traditionally, these parameters are inferred through model calibration using conventional data, such as hydraulic heads and river discharge. Many regional studies have treated rivers as curvilinear GW divides, with flow either converging toward or diverging from the river center—an assumption rooted in Tóth’s theory, which correlates surface and subsurface drainage boundaries. However, this oversimplification fails to account for geological heterogeneity, river morphology, variable hydraulic conditions, and anthropogenic influences like withdrawals.

While regional-scale studies commonly examine SW-GW exchanges, their coarse resolution limits the ability to resolve localized hydraulic gradients. Understanding flow dynamics in heterogeneous environments, such as alluvial plains, requires a more detailed, integrated approach. Here, we present a multi-method framework to strengthen numerical simulations and improve hydrodynamic and thermal parameter calibration in both space and time. Applied to the Orgeval Critical Zone Observatory (France), our approach estimates SW-GW fluxes using a combination of long-term hydrological data (10 years), time-lapse seismic imaging, and numerical modeling.

We demonstrate how high-resolution geophysical imaging, combined with geotechnical data, enables a detailed characterization of hydrofacies and provides valuable prior constraints on hydrodynamic properties. Time-lapse seismic acquisitions offer a high-resolution view of groundwater table (WT) dynamics, with each seismic snapshot carefully inverted to capture spatial WT variations. By integrating these geophysical insights with long-term hydrogeological observations (hydraulic head and temperature), we refine parameterization within the hydrogeological modeling domain, leading to improved estimates of transient stream-aquifer exchanges. Finally, we outline future steps toward achieving a fully coupled hydrogeophysical model to further enhance SW-GW interaction predictions.

Surface Water - Groundwater interaction, hydrogeophysics, field data, numerical models, data-driven

Agnès RIvière

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