Combined use of structurally-coupled and petrophysically-coupled joint inversion for the characterization of rock glaciers
- 1Department of Geosciences, University of Padua, Padua, Italy
- 2Institute for Applied Geophysics and Geothermal Energy, RWTH Aachen University, Aachen, Germany
- 3WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
The monitoring of alpine rock glaciers has both scientific and economic relevance. The degradation of mountain permafrost is a relevant proxy of climate change and global warming, but also a possible source of hazards for mountain communities since it can trigger natural processes such as rockfalls, debris flows, and floods. Geophysical techniques have been used to study these periglacial forms, particularly electrical and seismic refraction methods. Nevertheless, the independent data processing applied to these measurements does not lead to quantitative estimation of the physical components (air, water, ice, and rock) in the frozen subsoil. Moreover, the structural interpretation of the ground with independent resistivity and seismic sections can introduce ambiguities. To quantify the composition of the mountain permafrost, Wagner et al. (2019) developed a petrophysical joint inversion approach of electrical resistivity and seismic refraction datasets. We applied this method to several datasets collected in the rock glaciers of Schafberg (Engadin, Switzerland) and Ritigraben (Canton of Valais, Switzerland). To estimate the parameters in Archie’s and Timur’s laws, we performed the petrophysical joint inversion with a range of plausible values, selecting the ones that guaranteed the lowest final root-mean-square (RMS) error between the model response and the observed data. Our approach can be applied wherever information from boreholes is unavailable. This is a common situation in rock glacier studies since drilling in high mountain environments is very complicated and expensive. Finally, to improve the quality of individual resistivity and seismic velocity sections, we applied the structurally-coupled cooperative joint inversion method to our datasets, developed by Günther and Rücker (2008). This approach is based on the exchange of structural information between the independent geophysical inversions of electrical and seismic datasets. The process is driven by 3 different coupling parameters and the choice of their values has been done again by running the inversion with a range of values, choosing those that guaranteed the lowest final RMS. This method can be useful to better define the active layer thickness and the lower boundary of frozen ground. From the obtained results, it is clear that combined use of petrophysically-coupled and structurally-coupled joint inversion can represent a significant improvement for the characterization of mountain permafrost, in comparison to the traditional independent geophysical inversions, even in the absence of prior information from boreholes. In future studies, both structural and petrophysical coupling could be incorporated into a single inversion framework to adaptively allow structural agreement if quantitative petrophysical agreement cannot be satisfied.
References
- Wagner, F.M., Mollaret, C., Günther, T., Kemna, A., & Hauck, C. (2019). Quantitative imaging of water, ice, and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data. Geophysical Journal International, 219(3), 1866–1875. doi:10.1093/gji/ggz402.
- Günther, T., & Rücker, C. (2008). A new joint inversion approach applied to the combined tomography of DC resistivity and seismic refraction data. Symposium on the application of geophysics to engineering and environmental problems 2006 (pp. 1196–1202). doi:10.4133/1.2923578.
How to cite: Pavoni, M., Boaga, J., Wagner, F., Bast, A., and Phillips, M.: Combined use of structurally-coupled and petrophysically-coupled joint inversion for the characterization of rock glaciers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5861, https://doi.org/10.5194/egusphere-egu22-5861, 2022.