Geophysical imaging of a groundwater-dependent pond system: a combined electrical resistivity and seismic refraction tomography approach in the South-Albera Massif (Eastern Pyrenees, Spain)

Ponds are small water bodies that play a crucial role in biodiversity conservation and act as key elements of blue landscape connectivity. Under increasing climate pressures, groundwater-dependent ponds can serve as ecological shelters for wildlife, livestock, and agriculture. Understanding their origin and hydrodynamics is essential for improving their management and protection strategies.

This study focuses on an aquifer–pond system located on the granite pediment of the South Albera Massif (Eastern Pyrenees, NE Spain), where a clustered network of weathering basins has developed, some of them hypogenic in origin. The bedrock of the pond system is formed by the Palaeozoic basement of the Pyrenees Range: metasedimentary schists, orthogneisses, and plutonic granodiorites and tonalites, as well as leucogranite dikes. The structure of the area is dominated by the presence of NW-SE trending shear zones, dipping NE 50° to 70°.

Here, we propose a multidisciplinary approach coupling hydrogeological, geomorphological, edaphological and ecological techniques, together with near-surface geophysics, for the characterisation of the pond system, aiming at advancing knowledge on such groundwater-dependent ecosystems and their resilience under climate change scenario.

We applied Electrical Resistivity Tomography (ERT) to characterize the geo-electrical structure beneath temporary ponds and associated depressions, while Seismic Refraction Tomography (SRT) served to decipher the seismic velocity distribution in the subsurface. Independent and structurally coupled joint inversions were performed and compared to analyse the best data treatment method for detecting bedrock structure and the geometry of the pond sediments. The combination of these techniques has led to the 3D reconstruction of the subsurface pond features integrating surface and subsurface data, providing insights on its geomorphological origin and hydrodynamics. Data interpretation, inversion and geomodelling is based on opensource python-based programs and libraries such Refrapy, pyGIMLI and Gempy.