This case study aims to understand the behavior of floods in Bihar during 2021, a state considered the most flood-prone in India. To analyze the flood extent, multi-temporal Sentinel-1 (S1) GRDH data was used to monitor the spread of floodwater over time. Water and non-water areas were classified using a fixed threshold on radar backscatter values ( \(\sigma _{0_{VV}}\) dB), and the Absolute Spread of Water (ASW) was calculated at 12-day intervals. Sentinel-2 (S2) imagery was also utilized to support land cover classification, enhancing the accuracy of flood detection. Validation with official records showed that the estimated flood-affected population matched 89% of reported figures, while the image tile covered 87% of the affected districts. Two major flood peaks were observed: on 21st July and 14th August. The difference in flood timing across districts is largely due to the influence of the river Ganges and the Koshi river. Districts located farther from these rivers experienced early flooding driven by local rainfall, while those closer to the rivers faced delayed and prolonged inundation due to river discharge and backwater effects. The findings of the study maps the flood dynamics and their patterns precisely, so the mitigation from heavy flood aftermath could be planned using such a temporal rich study.
