Comparative Studies on Spatial Prediction Models of Rainfall-Induced Landslide

Landslide in Kerala are often rainfall triggered, which is not only by high rainfalls over a short period but also by much longer rainfalls that elevate the pore pressure. Commonly, landslide susceptibility maps at district/state level scale are developed using statistical methods failing to take the geotechnical aspects into account. The efficacy of such models is less reliable in Kerala. However, deterministic geotechnical models restrain from addressing the randomness associated with soil properties over an area which is crucial when mapping at large scale. Hence, the current study relies on probabilistic approaches to override the limitation. The study also focuses in considering pore pressure variations by developing a geotechnical landslide model, coded in MATLAB to combine TRIGRS for evaluating the influence of rainfall events with an infinite slope stability model, along with FOSM approach to account for the uncertainties associated with the input geotechnical properties in the soil of the considered regolith thickness. For the validation of the developed method/model, Kottayam district of Kerala is considered as a case study. A comparison between the developed model with existing probabilistic geotechnical landslide models like GIS-TISSA and a statistically developed model using the frequency ratio method is carried out for Koottickal village in Kottayam district.