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Extreme Precipitation-induced Concurrent Disasters Risk Assessment through Socio-economic and Topographic Vulnerability
  • Raviraj Dave,
  • Srikrishnan Siva Subramanian,
  • Udit Bhatia
Raviraj Dave
Indian Institute of Technology Gandhinagar

Corresponding Author:[email protected]

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Srikrishnan Siva Subramanian
Indian Institute of Technology Gandhinagar
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Udit Bhatia
Indian Institute of Technology Gandhinagar
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Abstract

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