Multi-temporal flood mapping and dynamics in Nepal's Terai (2019–2024) using Sentinel-1 SAR and change-detection approaches

Flooding is one of the most devastating natural disasters in Nepal, causing significant socioeconomic losses annually. However, existing studies on multi-temporal and regional-scale flood dynamics are scarce, limiting effective disaster management. In this study, we conducted one of the first long-term, district-level flood mapping studies in Nepal and analyzed the flood dynamics from 2019 to 2024 of three flood-prone districts, Parsa, Bara, and Rautahat. Using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) and CHIRPS rainfall data in Google Earth Engine (GEE), we produced monthly flood maps and evaluated both flood dynamics and the relationship between the short-term cumulative rainfall and flood extent. Our results indicate that the densely populated southern region of the study area is frequently affected by flooding, with two extreme events exceeding 285 km 2 . Flood maps from 2019 to 2024 revealed both monthly and annual variations in flooding, with 5.94% of the study area being inundated 3-4 times. A strong positive correlation between the 3-day cumulative rainfall and flooded area was observed, with > 130mm identified as a preliminary threshold for major events. The regional-scale SAR-based flood mapping in Nepal improves our understanding of the flood patterns, which is significant for developing data-driven mitigation measures and targeted flood risk management strategies to reduce socioeconomic impacts in data-scarce regions.