Abstract:
The coastal zone of Bangladesh is prone to tropical cyclones and storm surge during pre-monsoon and post monsoon seasons. This is one of the risk-prone regions due to climatic hazards. In Bangladesh, the risk from cyclone induced storm surges is high because majority of the population inhabits in low-lying coastal regions exposed to sea. Several methods of risk assessment are available in literature. But none of the previous studies adequately considered risk minimization by implementing optimum number of adaptation measures. This study is the first attempt towards this direction.
In this study, risk is defined as a function of vulnerability and hazard. Vulnerability is assessed through potential impact indices and adaptation measure indices. To assign appropriate importance to the indicators of the specified indices related to vulnerability due to storm surge hazard, a new weight computation method named as Matrix Based Statistical Framework (MSF) is proposed. MSF is an interacting, simple and easy method to compute weights to large number of indicators which is based on valuation of correlation matrix and Eigenvector associated with Eigen value. MSF is shown to perform the best among other popular methods for weighting. In this study, cyclone strength and landfall location which has a return period of 10 years is selected as a representative cyclone in the study area. By using cyclone wind speed with a 10-years return period, a numerical storm surge model and an analytical thrust force model are applied to compute spatially varying wind speed, surge depth and thrust force in three coastal regions of Bangladesh that represents landfall locations of 10-year return period cyclones. Using these three parameters, storm surge hazard map corresponding to 10-year return period in Bangladesh coastal zone is generated. Critical risk is defined by the magnitude of risk which is equal to or less than the maximum risk value, depending on the level of spatial vulnerability. This maximum risk value contains the adaptation indicator which is the smallest in amount as an adaptation measure. The critical risk is obtained by minimizing the maximum risk value with the increase of the smallest adaptation measure by applying a ‘Trial and Error’ method.
This critical risk value is the minimum risk from where any increase of the smallest adaptation measure will generate an ‘unacceptable’ system response.
The methodology developed in this study is used to get a‘minimum risk condition’ and associated adaptation measures in the coastal region of Bangladesh. Total six adaptation measures distributed over different upazilas are identified in Bangladesh coastal zone which need to be increased to achieve the minimum risk condition. These are: Growth Center, Cyclone Shelter, Health Care Facility, Polder Area, Health Care Provider and Presence of Lifeline.
