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Natural Disaster Risk Assessment in the Coastal Area of Bangladesh: A Study on Cox’s Bazar Paurashava

Ashraf Uddin Fahim, Adnan Arif Salim, Sania Sifat Miti

Bangladesh is recognized worldwide as one of the most vulnerable countries to natural disasters, is still struggling to benefit its wider population from the current economic growth and social welfare. Issues like global warming and climate change are putting all the development works into great challenge. In order to overcome these challenges, intensive research on disaster risk reduction programmes are required. This paper works as a basis of such intensive research where combining the socio-economic factors and geographical factors, a combined risk index of a coastal area (Cox’s Bazar Paurashava) has been identified. The study tried to establish some parameters regarding hazard, vulnerability and resiliency of the community in terms of the urban area of the coastal zone. In this way, this study focused on the non-spatial pattern as well as spatial factors of the community like roads and cyclone shelters. In terms of non-spatial risk, it has been derived that weak socio-economic status plays the most dominant role for a family to become vulnerable to natural disaster along with poor infrastructure systems, less chance of access to information etc. which also intensify the vulnerability of the community. Information regarding natural disaster risk assessment of the study area were collected through questionnaire survey and field observation. Members of professionals like professors and officials of disaster management department were selected for key informants’ interview to get some concept, parameters, standards regarding preparing Natural Disaster Risk Assessment Index (NDRAI). In this study, all the factors have been considered together for quantifying the risk of the community. In this way, this research prepared different local map on the basis of hazard, vulnerability and resiliency condition of the people. This study also prepared spatial risk map, non-spatial risk map and final risk map. Thus, this study will certainly help to prioritize government and non-government interventions according to the risk category during emergencies.