Spatiotemporal assessment of multi hazard risk using graph based analysis for case studies in India.

Over the years, India has experienced numerous rainfall-triggered landslides that initiate complex multi-hazard events, resulting in substantial human loss. This study presents a graph-based risk assessment of multi-hazards for two case studies in India: The South Lhonak Lake Glacial Lake Outburst Flood which impacted North Sikkim in October 2023 and the Wayanad Landslides in July 2024, which collectively claimed over 600 lives. This is achieved through a multidimensional methodology which integrates dynamic rainfall and discharge thresholds, stakeholder-informed hazard sequences, spatiotemporal hazard progression, and elements at risk. Heterogeneous data sources including remote sensing, field surveys, hydro-meteorological observations, and gray literature such as government reports and official situation bulletins, are synthesized to construct weighted, directed hazard networks. Graph-theory metrics, including degree centrality, betweenness centrality, and cascade depth, are used to compute sub-basin-level risk scores. Results highlighted critical sequences present in both regions, particularly the transition from extreme rainfall to landslides and subsequent flooding. Also, they identified high-risk zones influenced by both topography and infrastructure exposure. The findings emphasize the need for real-time threshold monitoring and alert systems, hazard-sequence-based operational protocols, and spatiotemporally phased response planning to support coordinated evacuations and early warning. The proposed framework offers actionable guidance for dynamic risk monitoring and multi-hazard governance in vulnerable mountain ecosystems.