Print Email Facebook Twitter Considering parameter uncertainty in a GIS-based sliding surface model for large areas Part of: Geotechnical Safety and Risk V· list the conference papers Title Considering parameter uncertainty in a GIS-based sliding surface model for large areas Author Mergili, M. Marchesini, I. Rossi, M. Alvioli, M. Schneider-Muntau, B. Cardinali, M. Ardizzone, F. Fiorucci, F. Valigi, D. Santangelo, M. Bucci, F. Guzzetti, F. Date 2015-10-15 Abstract The GIS-based open source software r.slope.stability computes broad-scale spatial overviews of shallow and deep-seated slope stability through physically-based modelling. We focus on the landslide-prone 90 km2 Collazzone area, central Italy, exploiting a comprehensive set of lithological, geotechnical and landslide inventory data available for that area. Inevitably, the geotechnical and geometric parameters are uncertain, particularly for their three-dimensional variability. Considering the most unfavourable set of geotechnical parameters (worst case scenario, appropriate for engineering purposes) is less useful to obtain an overview of the spatial probability (susceptibility) of landslides over tens of square kilometres. Back-calculation of the parameters based on topographic and geotechnical considerations would better suit for such a purpose, but obtaining one single parameter combination would require information on one of the parameters. Instead, we estimate the slope failure probability by testing multiple combinations of the model parameters sampled deterministically. Our tests indicate that (i) the geotechnical parameterization used allows to reproduce the observed landslide distribution partly (a challenge consists in the appropriate treatment of the variation of the geotechnical parameters with depth); (ii) the evaluation outcome depends strongly on the level of geographical aggregation; and (iii) when applied to large study areas, the approach is computing-intensive, and requires specific strategies of multi-core computing to keep computational times at an acceptable level. Subject GISuncertaintyslope stability model To reference this document use: http://resolver.tudelft.nl/uuid:c8e4747d-eccd-4a97-bc79-123b3e419976 DOI https://doi.org/10.3233/978-1-61499-580-7-952 Part of collection Conference proceedings Document type conference paper Rights (c) 2015 The Authors and IOS Press, Creative Commons CC-BY Files FILE STAL9781614995807-0952 926.14 KB Close viewer /islandora/object/uuid:c8e4747d-eccd-4a97-bc79-123b3e419976/datastream/OBJ/view