Urban flooding is a prevalent natural disaster worldwide, and various factors influence it. These factors include the resolution of the Digital Elevation Model (DEM), urban features, initial conditions of river systems, etc. DEMs play a crucial role in the accuracy of flood inundation modeling. Coarser-resolution DEMs may not accurately represent small-scale features, while finer-resolution DEMs can have computational complexities. Moreover, the composition of land use within urban areas, encompassing impervious surfaces such as roads and buildings, vegetation, and water bodies, significantly influences water flow during a flood event, with the height and type of buildings in urban areas further contributing to the impact on floodwater dynamics. This study employs the HEC-RAS model to generate flood inundation maps under various scenarios, including 10 and 30-meter resolution of DEM, dry and wet initial river conditions, and the consideration of the Digital Terrain Model (DTM) and Digital Surface Model (DSM) within the Amite River Basin. Furthermore, we employ sensitivity analysis through multiple simulations of various scenarios to reduce the effects of uncertainties in flood inundation. This process helps to pinpoint the critical factors influencing flood inundation mapping. It would enhance the understanding of flood dynamics, assist in refining flood risk assessment and mitigation strategies, and enable us to identify vulnerabilities while developing more effective flood management measures.
