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Community resilience to climate change through disaster resilient housing practice in coastal area: a case study of dacope upazila in Khulna

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dc.contributor.advisor Rahman, Dr. Md. Mansur
dc.contributor.author Rayhanur Rahman, Md.
dc.date.accessioned 2024-01-14T04:59:31Z
dc.date.available 2024-01-14T04:59:31Z
dc.date.issued 2022-08-13
dc.identifier.uri http://lib.buet.ac.bd:8080/xmlui/handle/123456789/6540
dc.description.abstract Every year natural disasters, specially, cyclonic storm surges disrupt the lives and livelihood of people in the coastal area of Bangladesh. Since 1990s, activities like the construction of cyclone shelters, cyclone warning, and awareness building program play important roles to reduce the fatalities and damages due to such disasters. Though the actions were effective to reducethehumanfatality rate, still manyhouses and theirrelated amenitiesaredamaged on a regular basis due to cyclones and their associated storm surges. Several studies have highlighted the need for more contextual approaches to make the community resilient against cyclone-inducedstormsurges.DisasterResilientHousingwouldbeanalternativeapproachin theDisasterRiskReduction(DRR)throughadoptingitinthestrategyofpre-disasterrecovery. The study aimed to develop and implement a disaster resilient house through involving the community for an area where tracks of the cyclones are observed frequently.To achieve the purpose, two villages in the Kamarkhola Union of Dacope Upazilla in Khulna district were selected fordeveloping and implementing prototypes of disasterresilient houses as this union whichwastheworstvictimbydevastatingCyclonesSIDRandAILA.Tounderstandthecauses for vulnerabilities of the community, primary data was collected using Participatory Rural Appraisal (PRA) tools including social and resource mapping, Focus Group Discussions (FGDs), group discussions, individual interviews, and Key Informant Interviews (KIIs). To evaluatetheperformanceoftheimplementeddesigninthestudyareaagainststormsurgeswith associated high-speed winds and surge height, Likert Scale was used to collect perceptions from the selected beneficiaries. The Cyclone Classifier Model (CCM) was used to collect the damageinformationofthelocallybuildhousingstructureinalargescaletocomparetheresults with observed design performance. Secondary data on real-time cyclones such as cyclone tracks, windspeeds, landfall locations, tidal condition were used in CCM.The study found that the formal supports such as cyclone shelter and warning systems and awareness development activities, which are generated at the national level for community resilience against cyclone-induced hazards, are not properly operational and not easily accessible to community people. Up to 84% of respondents have faced problems understanding warning informationand76%ofrespondentsdidn’tevacuatetothecycloneshelterduetolackofwater, food, and sanitation facilities after listening to warning signals. Results found that 52% of respondentswereconsideredtheirownhouseasasafeplaceratherthanmovingintoacyclone shelter. After the implementation of the participatory design, it is found that the development of disaster-resilient housing is possible when combination of scientific knowledge and local wisdom are integrated. This concept reduced extra cost for the structures as well as enhanced effectivity of community people. This finding is also evaluated with the performances of the houses against consecutive cyclones, like Bulbul and Amphan. It is found that up to 34% of theconventionalhouseswerefullydamagedagainstcycloneBulbulandAmphanrespectively, whiletheimplemented houseswith participatory designsustainedwithout collapsingitsmain structures. en_US
dc.language.iso en en_US
dc.publisher Institute of Water and Flood Management (IWFM) en_US
dc.subject Disaster victims-Housing -- Bangladesh en_US
dc.title Community resilience to climate change through disaster resilient housing practice in coastal area: a case study of dacope upazila in Khulna en_US
dc.type Thesis-MSc en_US
dc.contributor.id 1017282021 en_US
dc.identifier.accessionNumber 119362
dc.contributor.callno 363.583095492/RAY/2022 en_US


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