Projected changes of inundation of cyclonic storms in the Ganges-Brahmaputra-Meghna delta of Bangladesh due to SLR by 2100

Almost every year, Bangladesh experiences disasters such as tropical cyclones, storm surges, coastal erosion or floods. Tropical cyclones originate from the North Indian Ocean and often cause devastating flood inundations in Bangladesh. Storm surges of the Bay of Bengal (BOB) are larger compared to other regions of the world for similar cyclones due to amplification by the shallow water depth, huge continental shelf and convergent coastlines. This scenario of inundation for such storm surges in the future when the sea level rise (SLR) occurs due to global warming will be different from the present. The densely populated coastal region of Bangladesh is likely to become more vulnerable in the future due to SLR. Disaster risks can be reduced if storm surges can be predicted well ahead. To assess the possible changes of inundation in the future, a widely used coastal model, Delft3D, has been applied for this BOB region. The model has been validated for the storm surge of three recent devastating cyclones, namely, Sidr, Aila and Roanu in the southern coast of Bangladesh. The validated model has been run to produce inundation maps and statistics for cyclonic storm surges such as Sidr, Aila and Roanu and probable SLR. Three possible SLR boundary conditions are chosen from the business-as-usual climate scenario representative concentration pathway 8.5 with values of 0.5m (lower limit), 1m (upper limit) and 1.5m (extreme case, considering the subsidence and a rapid collapse of the Antarctic ice sheet). It is found that a category 4 cyclone such as cyclone Sidr would inundate 2.6%, 3.67% and 5.84% of the area of the country if the SLR is 0.5, 1 and 1.5m, which will affect the livelihood of nearly 4.1, 7.0 and 9.1 million people of Bangladesh, respectively. It will also inundate up to 21.0%, 42.1% and 65.1% of the Sundarbans mangrove forest, which will undoubtedly affect the ecology of this unique ecosystem