The current study focuses on the devastating floods along the Kosi River in Bihar in July 2020, which were recorded by Sentinel-1A satellite images. Three flood-affected districts in Saharsa, Supaul, and Madhepura have been selected for this study. Pre- and post-flood images from the Sentinel-1A satellite were utilized to generate the flood-inundated map, and pre-flood Landsat-8 datasets were used to generate the land use and land cover maps. Finally, damage assessment was done by superimposing land use and land cover on a flood-inundated map. The results showed that Madhepura was the most affected district with 57.6% of its barren land experiencing inundation. Furthermore, a comparison of cloud cover percentages during the flood was undertaken using the Sentinel-1A, Sentinel-2B, and Landsat-8 datasets. The findings indicate Sentinel-1A has less than 1% cloud cover, making it suitable for flood monitoring. Due to urbanization and industrialization, land use/cover (LULC) varies rapidly, and the effect on the flood plain must be determined. TerrSet's Land Change Modeler uses cellular automata-Markov modeling to project LULC maps for 2030 and their implications for subsequent flooding. The findings indicate that Saharsa will see an increase in the built-up area of 2.7%, Supaul with a gain of 13.4%, and Madhepura will see a growth of 10.3%. The growth of built-up regions in the near future will encourage greater impermeable layers and more discharge. Therefore, land use planners, environmentalists, and lawmakers should consider these LULC changes in water resource planning.