GIS-FSLAM-FORM: A QGIS plugin for fa t probabilistic susceptibility assessment of rainfall-induced landslides at regional scale
- 1Universitat Politècnica de Catalunya, Division of Geotechnical Engineering and Geosciences Department of Civil and Environmental Engineering, Barcelona, Spain (hongzhi.cui@upc.edu)
- 2Geotechnical Research Institute, Hohai University, 210024, Nanjing, China
Landslide susceptibility analysis is the necessary procedure for timely discovering and locking potential sources of slope instabilities in natural terrain areas. The infinite slope model is broadly applied for evaluating the shallow landslide susceptibility coupling the geotechnical and geological parameters with a hydrological model. Because rainfall is one of the major factors inducing landslides, the calculation of the water table and pore water pressure is an important task in our approach. To assess appropriately the most susceptible areas, we propose a new framework for regional slope stability based on probabilistic analysis by combining a hydromechanical model, which couples the Fast Shallow Landslide Assessment Model (FSLAM) and reliability method. A user-friendly software based on the open-source geographic information system (QGIS) platform called the GIS-FSLAM-FORM plugin adopting the Python programming language was designed and developed. Accounting for the potential uncertainties of geotechnical parameters (in particular effective cohesion and friction of soil or root strength), the horizontal hydraulic conductivity, as well as the soil depth. Our now approach is emphasized for its simple hydrologic model and its high computation efficiency. To consider the probabilistic information of the FSLAM incorporating the infinite slope, the first-order reliability method (FORM) is presented during the analysis although inevitably involving iterative computing. The developed plugin using physically-based modelling can directly provide several regional hazard index distribution maps, such as the factor of safety (FoS), reliability index (RI), and failure probability (Pf).
How to cite: Cui, H., Hürlimann, M., Medina, V., and Ji, J.: GIS-FSLAM-FORM: A QGIS plugin for fa t probabilistic susceptibility assessment of rainfall-induced landslides at regional scale, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-295, https://doi.org/10.5194/egusphere-egu23-295, 2023.