This present study assessed the overall flood hazards of Sylhet city and adjacent floodplain areas 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. 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 (extent of flood, depth, arrival time, velocity, and duration of the flood) were produced. The produced flood extent map shows that about 50% and 20% of the land areas of the entire modelled area and Sylhet city were inundated during that flood event, respectively. In the depth map, the maximum value for the entire modelled area and Sylhet city is greater than 5 m. The modelling results suggest that the maximum and minimum flood arrival times for a 1 m-depth flood in the entire modelled area are more than 50 days and less than 5 days, respectively. It also suggests that the maximum and minimum flood arrival times for 1 m of depth in Sylhet city are more than 20 days and less than 10 days, respectively. Furthermore, it is observed that the ranges of the maximum and minimum flood velocity for the whole modelled area and the city of Sylhet are greater than 0.4 ms^-1 and lower than 0.1 ms^-1, respectively. Finally, the flood duration map shows that the maximum and minimum flood duration times for a 1 m-deep flood in the modelled area and Sylhet city are more than 115 days and less than 60 days, respectively. Hence, it can be said that the areas with a higher depth, lower arrival time, 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 study’s findings are expected to aid floodplain management authorities in limiting future flood damage and fatalities.