GNGTS 2021 - Atti del 39° Convegno Nazionale

447 GNGTS 2021 S essione 3.2 Once acquired the datasets, we evaluated their quality comparing the contact resistances recorded before each survey and verifying the differences of saved quadrupoles after the reciprocal check (Cassiani et al., 2006). The process has been performed by applying three different error thresholds of acceptance: 5%, 10% and 20%. Already from this first processing analysis, important differences were found in the quality of the six acquired datasets. Thereafter, knowing the structure of the subsoil from Weidinger et al. (2014), mainly composed by large resistive blocks on the surface and finer conductive materials below, we compared the different resistivity sections obtained from the inversion processes, performed with the code R2 (Binley, 2015), verifying which one of them was better matching with this subsurface model. Finally, considering the obtained results, which will be presented during the oral presentation, we will discuss the advantages and disadvantages of each acquisition mode for the final result. References Binley, A., 2015. Tools and Techniques: Electrical Methods, Treatise on Geophysics: Second Edition. Elsevier B.V. https://doi.org/10.1016/B978-0-444-53802-4.00192-5 Boaga, J., Phillips, M., Noetzli, J., Haberkorn, A., Kenner, R., Bast, A., 2020. A Comparison of Frequency Domain Electro-Magnetometry, Electrical Resistivity Tomography and Borehole Temperatures to Assess the Presence of Ice in a Rock Glacier. https://doi.org/10.3389/feart.2020.586430 Boyd, J., Chambers, J., Wilkinson, P., Uhlemann, S., Merritt, A., Meldrum, P., Swift, R., Kirkham, M., Jones, L., Binley, A., 2019. Linking geoelectrical monitoring to shear strength - A tool for improving understanding of slope scale stability, in: 25th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019. European Association of Geoscientists and Engineers, EAGE, pp. 1–5. https://doi.org/10.3997/2214-4609.201902452 Cassiani, G., Bruno, V., Villa, A., Fusi, N., Binley, A.M., 2006. A saline trace test monitored via time-lapse surface electrical resistivity tomography. Journal of Applied Geophysics 59, 244–259. https://doi. org/10.1016/j.jappgeo.2005.10.007 Hack, R., 2000. Geophysics for slope stability. Surveys in Geophysics 21, 423–448. https://doi. org/10.1023/A:1006797126800 Heinze, T., Möhring, S., Budler, J., Weigand, M., Kemna, A., 2017. Improving water content estimation on landslide-prone hillslopes using structurally-constrained inversion of electrical resistivity data, Geophysical Research Abstracts. Papathoma-Köhle, M., Zischg, A., Fuchs, S., Glade, T., Keiler, M., 2015. Loss estimation for landslides in mountain areas - An integrated toolbox for vulnerability assessment and damage documentation. Environmental Modelling and Software 63, 156–169. https://doi.org/10.1016/j.envsoft.2014.10.003 Petley D. 2012. Global patterns of loss of life from landslides. Geology; 40 (10): 927–930. doi: https://doi. org/10.1130/G33217.1 Weidinger, J.T., Korup, O., Munack, H., Altenberger, U., Dunning, S.A., Tippelt, G., Lottermoser, W., 2014. Giant rockslides from the inside. Earth and Planetary Science Letters 389, 62–73. https://doi. org/10.1016/j.epsl.2013.12.017 Corresponding author: mirko.pavoni@phd.unipd.it