This present study assessed the overall flood hazards of Sylhet and Sunamganj districts based on a 1D–2D coupled hydraulic model for the recent flood event in 2022 in the Sylhet region. The model was developed utilizing discharge, water level, cross sections, and rainfall data collected from the BWDB and digital elevation model (DEM), as well as Sentinel imagery data from the USGS and Copernicus Hub, respectively. The 1D model was calibrated and validated using the water level datasets of 2004 and 2010 respectively. Manning’s roughness coefficient was applied as a tuning parameter for model calibration, ranging from 0.013 to 0.015. In addition, the 2D model was also validated by a qualitative comparison between the simulated and remote sensing-based (Sentinel-1) flood inundation maps. From the unsteady flow simulation, the flood hazard parameters (flood depth and velocity) were produced. In the depth map, the maximum value for the entire modeled area is greater than 5 m. Furthermore, it is observed that the ranges of the maximum and minimum flood velocity for the whole modeled area are greater than 2.09 m/s and lower than 0.1 m/s, respectively. The result also shows that Sulla upazilla of Sunamganj district and Balaganj upazilla of Sylhet are the most inundated upazillas of the two districts, respectively. Hence, it can be said that the areas with a higher depth, higher velocity, and longer duration are the most flood-prone and flood-susceptible areas within the study area for the 2022 Sylhet flood event. The findings of the study are expected to aid floodplain management authorities in limiting future flood damage and fatalities.
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Flood Hazard Assessment in the Sylhet Region of Bangladesh Using Hydrodynamics Modeling and Remote Sensing Techniques: A Case Study for a Recent Flood in 2022
Published:
16 May 2024
by MDPI
in OHOW 2023 – The 2nd International Symposium on One Health, One World
session Urban Safety & Disaster Mitigation
Abstract:
Keywords: Hydraulic Model, Flood Hazard, Inundation map, Floodplain Management, Flood Damage
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