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The Himalayas are increasingly vulnerable to the impacts of climate change, with recent years experiencing a surge in the frequency of natural hazards. The risk escalates when events unfold in a cascading manner, where a primary hazard triggers a secondary one. Therefore, it is crucial to develop an integrated framework to assess the ramifications of these cascading hazards. This framework plays a pivotal role in providing early warnings, considering the uncertainty introduced by rainfall input. The presented framework simulates the dynamic interplay between intense precipitation events and hill slopes, potentially triggering landslides. It subsequently models the debris flow resulting from the runoff formed by precipitation mixing with landslide deposits, culminating in debris runout. To address data uncertainties, the framework integrates four diverse precipitation data sources: gridded observation datasets, reanalysis data, satellite data, and numerical weather prediction models. The methodology assesses sediment volume originating from hillslopes and anticipates the sediment volume reaching river junctions during extreme events. Additionally, it involves the numerical simulation of the initial stages of the cascading nature of geohazards, specifically the transformation of landslides into debris flows. The framework's validation is conducted using the 2013 North India Floods, an extreme precipitation event that triggered over 6000 landslides and debris flows.
Dixit et al. (Fri,) studied this question.