Integrated Dynamic Multi Hazard Risk Management Framework for GLOFs Landslides and Floods

Abstract

Globally, there has been a significant rise in the average number of disasters, totaling 16,535 from 1900 to 2023, with 3,158 categorized as multi-hazard events. The emergence of multi-hazard scenarios is becoming increasingly unpredictable, with their impact on human life and property multiplying by several times every year. Global frameworks, such as the Sendai Framework for Disaster Risk Reduction (SFDRR) s Target G and the World Meteorological Organization s Global Multi-Hazard Alert System Framework, highlight the urgent requirement for effective multi-hazard risk management frameworks at national, sub-national, and community levels that can anticipate risks and save lives. This doctoral research addresses these critical gaps by developing an Integrated Dynamic Multi-Hazard Risk Management Framework for regions prone to GLOFs, landslides, and floods. The framework advances beyond static single-hazard assessment by incorporating heterogeneous datasets and multi-method approaches to understand triggers, hazard interactions, and spatiotemporal overlap and impact, culminating in a dynamic risk management geospatial interactive platform. The study focuses on two representative mountain regions: North Sikkim in the Eastern Himalayas and Wayanad in the Western Ghats. Hydrometeorological thresholds, encompassing rainfall, water surface elevation, and discharge, form a crucial component of understanding hazard initiation within this framework since they act as primary triggers for landslides and floods. Beyond individual triggers, hazard sequences were identified using hazard interaction matrices developed during expert and community consultations, supplemented by event data gathered through web crawling of disaster databases, reports, and news archives. The spatiotemporal progression of hazards and their impacts was reconstructed through a combination of remote sensing analysis and field-based documentation. This combined approach enabled the identification of dynamic hotspots where multiple hazards overlapped...