A GIS-Based Tool for Probabilistic Physical Modelling and Prediction of Landslides: Improved GIS-TRIGRS-FORM Landslide Prediction

This work aimed to propose a new framework for regional slope stability based on probabilistic analysis by combining a hydromechanical model, that is, transient rainfall infiltration and grid-based regional slope-stability model (TRIGRS) and the reliability method. A user-friendly software based on geographic information system (GIS) platform called the improved GIS- TRIGRS-FORM landslide prediction toolbox applying the Python programming language for considering the possible uncertainties of model parameters as well as rainfall conditions was developed. To incorporate the probability information of the hydromechanical model incorporating the infinite slope, the first-order reliability method (FORM) is firstly embraced in the analysis. The proposed approach can effectively provide regional hazard distribution maps subject to several indexes in different time phases, for example, the factor of safety (FoS), reliability index (RI), and failure probability (Pf), which can achieve a regionalscaled landslides susceptibility analysis using physically based modelling.