Rainfall Threshold-Based Landslide Early Warning System for Arunachal Pradesh

Abstract

Landslides are increasingly recognized as significant natural disasters. Over the years, extensive research has led to the development of predictive models and public awareness strategies aimed at reducing their impact. Landslides typically occur due to slope failure, often exacerbated by heavy rainfall. Efforts to mitigate the damage involve both improving forecasting techniques and enhancing community preparedness. In tropical areas, landslides triggered by rainfall are the most common form of mass movement, primarily due to frequent monsoons. Establishing rainfall thresholds (RT) and conducting a comprehensive examination of patterns of rainfall distribution in spatial and temporal are necessary for predicting these landslides. However, creating a regional rainfall threshold is a complex task. Clustering analysis emerges as a valuable approach to effectively manage and interpret this scattered data. In this study, Rainfall Threshold (RT) equation was developed for northeastern region of Arunachal Pradesh by incorporating daily rainfall data along with 2-day, 3-day and 5-day antecedent rainfall. The study determined that the trend line derived from the 3-day antecedent rainfall and daily rainfall is the most suitable rainfall threshold equation for the area. Consequently, the correlation between rainfall thresholds and landslides emerges as an innovative approach for developing early warning systems in regions prone to landslides.