Automated Rapid Estimation of Flood Depth using Digital Elevation Model and EOS-04 Satellite derived Flood inundation

Abstract. Rapid flood assessment is vital for effective relief, rehabilitation, and flood mitigation strategies. Developing and implementing automated, rapid methods for flood depth and inundation estimation is necessary for near real-time information dissemination. This paper presents an end-to-end automated floodwater delineation and depth estimation process using EOS-04 (RISAT 1A) Synthetic Aperture Radar (SAR) images and a Digital Elevation Model (DEM). Flood inundation is estimated using an Automated Tile-based Segmentation technique. Flood depth is estimated by the Trend Surface Analysis (TSA) method, a novel technique requiring only the inundated water layer and DEM, unlike various hydrodynamic models needing extensive data. This method is applied to most flood prone areas in Andhra Pradesh, Assam, Bihar, and Uttar Pradesh states of India. Water levels estimated at river gauge stations using TSA technique are validated with real-time field measurements and compared with Floodwater Depth Estimation Tool (FwDET) derived results. The TSA technique outperforms FwDET, showing lower RMSE values.