Characterization of rock glaciers environments combining structurally-coupled and petrophysically-coupled joint inversions of electrical resistivity and seismic refraction datasets

The degradation of mountain permafrost is well documented at many Alpine sites. Geophysical techniques have been intensively used to monitor these sites, since permafrost degradation is not only a proxy of climate change and global warming but also a possible source of slope instabilities and triggering of mass movements. While the use of non-invasive geophysical techniques is promising, the interpretation of different geophysical results can introduce ambiguities in defining the investigated subsoil and often does not lead to a quantitative estimation of the internal permafrost constituents (rock matrix, ice, liquid water and air contents). To overcome these limitations, we applied an optimized joint inversion approaches of electrical resistivity and refraction seismic tomography datasets collected at two Swiss rock glaciers (Schafberg - Canton Grisons, and Ritigraben - Canton Valais). Firstly, to improve the structural interpretation of the frozen near subsurface, we performed a structurally coupled cooperative joint inversion, optimizing the coupling parameters. Subsequently, we used the petrophysical joint inversion to quantify the composition of these mountain permafrost substrates, optimizing the numerical and petrophysical parameters. The obtained results agree with field observations and the borehole data collected at these two sites, opening new perspectives for the future quantitative monitoring of permafrost constituents. Increasing mean annual temperatures over the last decades has led to glacier melt and permafrost thawing. The degradation of glaciers is easier to quantify as they are visible on the surface, as opposed to permafrost which is found in the subsoil and must therefore be studied with direct drilling techniques or with non-invasive geophysical methods. Drilling investigations are expensive and complicated to perform in high mountain environments and only provide 1D information. Geophysical surveys can be used to quickly and economically characterize larger areas. Since permafrost thawing is a risk factor in high mountain environments (inducing e.g. instability of infrastructure, or triggering rock falls and landslides), it is important to have reliable geophysical techniques to study these environments. In this work, we propose an optimization of two different data analysis processes, applied to geoelectrical and seismic measurements, to better define the structure and composition of two ice-rich mountain permafrost sites in the Swiss Alps.