Assessing global parameters of slope stability model using Earth data observations for forecasting rainfall – induced shallow landslides

Abstract

Landslides are one of the most widespread natural hazards on earth and pose an intricate challenge in many mountainous terrains, especially in the Himalayas. Rainfall-induced shallow landslides are ubiquitous on steep terrains of the Himalayas and are accountable for substantial damage to properties and loss of human lives and livestock. Climate change has led to an unprecedented increase in frequency and intensity of cloudbursts, and a greater number of landslides are triggered by rainfall, along the hillslopes. In the present study, Transient Rainfall Infiltration and Grid-Based Slope Stability Model (TRIGRS), a dynamic physically based slope stability model with optimised hydro-geomechanical parameters is used for grid-wise simulation of stability of the terrain in the central Himalayas. The present study utilised Earth observation datasets and a comprehensive spatio-temporal landslide inventory to optimise hydro-geomechanical parameters of the slope stability model. The calibrated model with optimised hydro-geomechanical parameters is validated at 9 locations, where rainfall induced landslides have been triggered. The optimised model has better predictive capabilities and could accurately forecast 67% of the landslide events in the study area in comparison with the non-optimised model. Based on the present study, the new calibrated model with optimised hydro-geomechanical parameters is more sensitive and reliable in computing Factor of Safety (FS) and Pore Water Pressure (PWP) during and after the precipitation events and can help policy makers and local administration to propose appropriate mitigation strategies for vulnerable terrains.