Protecting vulnerable communities: a case study of index-based flood insurance in India, powered by flood modeling and remotely sensed rainfall

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cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.affiliationIndian Institute of Water Management (IIWM), Bhubaneswar, Indiaen_US
cg.creator.identifierGiriraj Amarnath: 0000-0002-7390-9800en_US
cg.creator.identifierSurajit Ghosh: 0000-0002-3928-2135en_US
cg.creator.identifierNiranga Alahacoon: 0000-0003-0984-5176en_US
cg.creator.identifierAlok Sikka: 0000-0001-9843-9617en_US
cg.identifier.doihttps://doi.org/10.1016/b978-0-443-14009-9.00006-7en_US
cg.identifier.iwmilibraryH053138en_US
dc.contributor.authorAmarnath, Girirajen_US
dc.contributor.authorGhosh, Surajiten_US
dc.contributor.authorAlahacoon, Nirangaen_US
dc.contributor.authorSikka, Aloken_US
dc.contributor.authorBrahmanand, P. S.en_US
dc.date.accessioned2024-09-30T23:27:10Zen_US
dc.date.available2024-09-30T23:27:10Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/152519en_US
dc.titleProtecting vulnerable communities: a case study of index-based flood insurance in India, powered by flood modeling and remotely sensed rainfallen_US
dcterms.abstractThe poor across the world is vulnerable to floods and drought disasters, which have a detrimental effect on the lives and livelihoods of the poor. Weather-based index insurance is one of the ways of dealing with these disasters. Protecting against floods and providing risk cover against losses due to floods has been a major area of concern for any government. Risk transfer through insurance is an important component in managing agricultural risks from extreme flood events. The study developed the first of its kind of design and implementation of an index-based flood insurance (IBFI) product with the advanced use of satellite data and flood models to estimate crop losses due to floods. IBFI insurance product uses two different data elements, and the first one is based on the flood model using HEC-HMS and HEC-RAS that uses inputs from NASA GPM bias-corrected satellite rainfall estimates, observed water level and discharge data, river characteristics, and digital elevation model to generate flood depth and flood duration to develop predetermined thresholds based on the historical flood events between 1991 and 2015 and the second IBFI product uses only satellite data from NASA MODIS Terra and Aqua satellite data and the Copernicus Sentinel-1 SAR data to generate flood depth and flood duration to develop predetermined thresholds based on the historical flood events and economic losses. More than 7000 farming households in Bihar (India) and northern Bangladesh have signed up for a pilot IBFI scheme, which went live in 2017. The participating farmers have received insurance compensation for crop losses of over $US160,000. In addition to the insurance product implementation, the research evaluated the farming willingness to pay, developing business models for scaling, social equity, and economic benefits of derisk disasters. IBFI initiative promotes a closer linkage between risk transfer and risk reduction that could make this a more sustainable and robust financial instrument for flood-affected communities and reduce the burden of postdisaster relief funds for the government. In summary, index insurance using open-access satellite imagery is a win-win opportunity as it brings down the data development cost, lower insurance premiums, quick settlement, and greater transparency among various users.en_US
dcterms.accessRightsLimited Accessen_US
dcterms.available2024-09-27en_US
dcterms.bibliographicCitationAmarnath, Giriraj; Ghosh, Surajit; Alahacoon, Niranga; Sikka, Alok; Brahmanand, P. S. 2025. Protecting vulnerable communities: a case study of index-based flood insurance in India, powered by flood modeling and remotely sensed rainfall. In Adams III, T. E.; Gangodagamage, C.; Pagano, T. C. (Eds.). Flood forecasting: a global perspective. 2nd ed. London, UK: Academic Press. pp.425-440. [doi: https://doi.org/10.1016/B978-0-443-14009-9.00006-7]en_US
dcterms.extentpp.425-440.en_US
dcterms.issued2025-01en_US
dcterms.languageenen_US
dcterms.licenseCopyrighted; all rights reserveden_US
dcterms.subjectweather index insuranceen_US
dcterms.subjectflood forecastingen_US
dcterms.subjectmodellingen_US
dcterms.subjectremote sensingen_US
dcterms.subjectrainfallen_US
dcterms.subjectcrop insuranceen_US
dcterms.subjectrisk transferen_US
dcterms.subjectvulnerabilityen_US
dcterms.subjectcommunitiesen_US
dcterms.subjectcase studiesen_US
dcterms.typeBook Chapteren_US

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