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AbstractExtreme precipitation (rain or/and snow) in upstream areas of the Himalayan region often triggers water and sediment hazards, including flash floods, landslides, debris flow, and river damming. These hazards often interact with the environmental and human systems, resulting in acute and chronic disasters that deleteriously impact the economy, infrastructure, and livelihoods. As cascading and compound hazards become more common in the Himalayan region, a more holistic approach is needed to understand the complex interaction among human, natural, and engineered systems and tackle problems connected to several system constraints. Recent catastrophes like the 2021 Melamchi disaster cannot be attributed to a single cause; rather, they result from several geomorphologic and hydroclimatic factors and physical processes. Individual and interacting dynamics and their cascading and compounding effects occurred in various settings, from high elevations to river valleys along the Melamchi River. This study diagnoses the likely causal effects of hydroclimatic processes of the 2021 Melamchi disaster by integrating space-borne remotely sensed data, hydrologic and hydrodynamic modeling, and machine learning techniques. We have evaluated several scenarios of landslide damming and breaching and analyzed flooding impacts on major settlements across the Melamchi River. Model outputs evaluated using satellite flood imagery, field-based surveys, and published reports were used to understand the characteristics of the 2021 Melamchi disaster. We find that earlier rain episodes had saturated the soil and increased the river’s water level. Therefore, after the outburst of the landslide dam coupled with heavy downpours, a sudden release of huge water had enormous energy to inundate vast areas of flood plains and damaged settlements near riverbanks far downstream up to the Melamchi Bazar. It was not just one extreme event that led to the devastation but a series of non-extreme events. This further reinforces the idea that not just extreme events, but several not-extreme series of events may lead to disaster. Thus, the chances of such a sequence of cascading events must be investigated for risk computation along with extreme events.