Disasters triggered by extreme precipitation events i.e., landslides, debris flows, and floods cause devastating damages to lives, infrastructure, and the economy. Under a warming climate, precipitation extremes and the occurrence of debris flows are further expected to intensify. Driven by extreme runoff, the triggering of debris flows can be simultaneous. Their concurrent occurrence multiplies complexity in decision-making during emergencies. Despite advancements in geotechnics and network science, a systematic framework to analyze the impact of debris flows on road networks is lacking. While network science-based approaches work on large-scale, geotechnics-based damage assessments are done solely on a site-to-site basis. Here we develop an integrated approach to analyze the impacts of simultaneous debris flows on road networks. The approach includes a novel infinite slope-based one-dimensional numerical model that simulates runoff-induced erosion and a network science-based mathematical model for road failures. This study covers multiple catastrophic events of debris flows that occurred in different geological and climate settings i.e., post-earthquake, post-volcanic, and post-wildfire environments. We perform spatio-temporal simulations of initiation and runout of debris flows and calculate the damage caused on individual road segments. We validate the model results using metadata. Our results show even remote local disturbances caused by successive debris flows upstream may lead to complete cascading disruption of the network downstream. Our unified strategy opens avenues to understand the resilience of critical infrastructure networks against catastrophic debris flows.

The warming climate intensifies the frequency and intensity of extreme precipitation events, leading to increases in precipitation-induced disasters. Precipitation-induced disasters such as flooding, landslide, and debris flow possess the potential risk of damage to socio-economic activity. The losses due to concurrent hazards in a region not only depend on the intensity and frequency but also socio-economic condition, topography, and exposure to the affected region. Recent advancements in risk mapping have shown approaches to measure the vulnerability to disaster but not accounting for concurrent hazards can lead to underestimation of risk. Here we propose the framework to assess the risk of concurrent precipitation-induced disasters while incorporating socio-economic, topographic, and land use information. In Kerala, India, the Periyar river basin is selected as a testbed for analysis considering 2018 extreme precipitation events. We perform 2D hydrodynamic flood inundation modeling to analyze the spread of the flood with the Spatio-temporal simulations of shallow landslides and debris flows using infinite slope-based stability and erosion models to identify the exposure of disaster. We evaluate socio-economic vulnerability and topographic vulnerability using disparate techniques from census demographic data and digital elevation model data respectively and exposure using land use information. The risk mapping is performed at the taluka (sub-district) level in the Periyar basin. Our results show better land-use planning considering multi-hazard vulnerability assessments reduces the exposed risk and would be beneficial for risk mitigation measures in high-risk areas