Early prediction framework for a rainfall-induced landslide: validation through a real case study

Shallow landslide occurrence is most common in rainy season in the form of flow of debris, costs heavy damages to the infrastructure and human lives. Early prediction framework of such disaster can help to mitigate such damages. The present work deals with prediction framework for initiation of debris flow, which is developed and validated with real case study. In order to test reliability of prediction framework, back analysis of very recent landslide debris flow accrued in the study area, Taliye village of Konkan region of Maharashtra, India on 22 July 2021 was carried out. Simulation results of landslide stability were compared with the leaky barrel-based rainfall-water saturation algorithm. Relations of landslide stability with the water saturation were established through physically based approach using Geo-Studio analysis module. Leaky barrel algorithm was used for study location for monitoring effect of rainfall on water saturation. The result confirms the good predictability of landslide occurrence through a developed early prediction framework. The methodological framework was presented in this paper for prediction of shallow landslide occurrence and recommended for real-time monitoring of landslide prone locations.