Temperature distribution in a permafrost-affected rock ridge from conductivity and induced polarization tomography

• Published in: Geophysical Journal International
• Main Authors: Duvillard, P-A, Magnin, F, Revil, A, Legay, A, Ravanel, Ludovic, Abdulsamad, F, Coperey, A
• Other Authors: Environnements, Dynamiques et Territoires de la Montagne (EDYTEM), Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: Electrical resistivity tomography (ERT); Hydrogeophysics; Electrical properties; geo; envir; Mont Blanc; permafrost
• Online Access: https://doi.org/10.1093/gji/ggaa597; https://hal.archives-ouvertes.fr/hal-03226968/file/2021-GJI-Tdistribution%20ipermafrost%20Ridge.pdf; https://hal.archives-ouvertes.fr/hal-03226968

International audience Knowledge of the thermal state of steep alpine rock faces is crucial to assess potential geohazards associated with the degradation of permafrost. Temperature measurements at the rock surface or in boreholes are however expensive, invasive, and provide spatially limited information. Electrical conductivity and induced polarization tomography can detect permafrost. We test here a recently developed petrophysical model based on the use of an exponential freezing curve applied to both electrical conductivity and normalized chargeability to infer the distribution of temperature below the freezing temperature. We then apply this approach to obtain the temperature distribution from electrical conductivity and normalized chargeability field data obtained across a profile extending from the SE to NW faces of the lower Cosmiques ridge (Mont Blanc massif, Western European Alps, 3613 m a.s.l., France). The geophysical data sets were acquired both in 2016 and 2019. The results indicate that only the NW face of the rock ridge is frozen. To evaluate our results, we model the bedrock temperature across this rock ridge using CryoGRID2, a 1-D MATLAB diffusive transient thermal model and surface temperature time-series. The modelled temperature profile confirms the presence of permafrost in a way that is consistent with that obtained from the geophysical data. Our study offers a promising low-cost approach to monitor temperature distribution in Alpine rock walls and ridges in response to climate change.