Development of Storm Surge Inundation Model and Database for Enhanced Climate Services in Bangladesh - Rezaie, Ali Mohammad; Haque, Anisul (Frontiers in Water, 2022)
Bangladesh’s vulnerability to storm surge and success in reducing their impacts on the coastal communities are well known. However, global warming is expected to increase both the frequency and intensity of tropical cyclones. Also, the country still lacks in good quality data and information that can offer enhanced services to effectively design coastal defense systems and adapt with climate changes. This study developed a storm surge inundation model and database using available tropical cyclones database and simulated inundation for 31 past cyclones in the Bay of Bengal, near the coastal regions of Bangladesh. The model is applied a suite of Delft 3D hydrodynamic and Delft Dashboard cyclone model. The model was calibrated and validated for two major cyclones, Sidr and Aila using available data for different bed roughness, track sources and wind drag co-efficient conditions. The results suggested spatially varying bed roughness and wind varying drag conditions provide more reliable prediction of inundation over the coast. Results also shows that historical track data from Indian Meteorological Department optimizes the model performances. The inundation database indicates that depending on intensity and location, tropical cyclones can cause a range of 1 to 5m of maximum inundation in the coastal lands of Bangladesh. More than 70% of the storms lead to a more than 2m of maximum inundation and about 25% and 7% can cause more than 3 and 4m of maximum inundation, respectively. The study also discusses potential application and share insights on implications of the inundation database that can offer improved information that can offer enhanced climate services. The database can be advanced with sectoral loss and damage information as well as citizen science that will not only provide necessary information to design coastal protection structures and emergency measurements but also contribute to build long term climate adaptation plans in the data scarce region.