Development of Storm Surge Inundation Model and Database for Enhanced Climate Services in Bangladesh
Ali Mohammad Rezaie and Anisul Haque
Published in ‘Frontiers in Water’
Abstract
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 the 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 to climate changes. This study developed a storm surge inundation model and database using the available tropical cyclones' database and simulated inundation for the past 31 cyclones in the Bay of Bengal, near the coastal regions of Bangladesh. The model uses a suite of Delft3D hydrodynamic and Delft Dashboard cyclone models. The model was calibrated and validated for two major cyclones, namely Sidr and Aila, using the available data for different bed roughness, track sources, and wind drag coefficient conditions. The results suggested that spatially varying bed roughness and wind varying drag conditions provide a more reliable prediction of inundation over the coast. The results also show that historical track data from Indian Meteorological Department optimize the model performances. The inundation database indicates that depending on the intensity and location, tropical cyclones can cause the maximum inundation of 1–5 m in the coastal lands of Bangladesh. More than 70% of the storms lead to the maximum inundation of more than 2 m, and about 25 and 7% of the storms can cause the maximum inundation of more than 3 and 4 m, respectively. The study also discusses the potential applications and shares insights on the implications of the inundation database that can offer improved information for enhanced climate services in Bangladesh. The database can be advanced with information about sectoral loss and damage 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.