<p>Coastal landscapes are the major source of income and resources. Despite their high vulnerability to<br />coastal hazards, they are the homes of millions worldwide. Coastal floods are one of the most life-threatening<br />incidents affecting the coastal living. Bound by water on three sides, the flood sensitivity of coastal India largely<br />depends on the spatial exposure of under-equipped population groups. This spatial impact of the coastal flood<br />is likely to rise with the changing climate and exponential rise in the coastal population. The local governments<br />and stakeholders rely on spontaneous methods of coastal flood mitigation, that are temporary, and do not help<br />in long-term resilience.<br />Disaster resilience using spatial planning has been an intensely researched topic by many in this domain for<br />the past few decades. The development and availability of high-resolution remote sensing data and free and<br />open source spatial models have further facilitated the development of down-to-earth interventions for<br />resource-crunched developing nations. The research presents a comparative assessment of Business as Usual<br />Scenario (BAU) and Flood resilient scenario modelling (FResMO), emphasizing the role of spatial<br />planning in reducing coastal flood risk during cyclone YAAS (2021) on Sagar Island, West Bengal. In this<br />analysis, the flood hazard scenario of Sagar Island is developed and validated using a connected bathtub<br />model. The flood risk in the region is estimated as the product of various vulnerability and exposure<br />parameters. The vulnerability is dependent on socio-economic parameters, and exposure is related to the<br />spatial proximity of the region to coastal floods. The vulnerability and exposure parameters are ranked using<br />a multi-criteria decision using Analytical Hierarchical Process and finally integrated for estimating present<br />and future flood risk. The future flood risk scenario for 2030 is developed based on the built-up prediction<br />model &#8216;FUTURES&#8217; that integrates the temporal landuse map, demography and socio-economic factors using<br />a multi-level logistic patch growing algorithm.<br />Keywords: Coastal flood risk, Flood risk modelling, FUTURES, Spatial adaptation, Vulnerability</p>
Flood resilient scenario modelling (FReSMo) through dynamic assessment of climate induced effects on landuse
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