Remote sensing approach for detection and attribution of flood inundation, Lower Awash Basin, Ethiopia - Bekele, T. W.; Negash, E. D.; Asfaw, W.; Haile, Alemseged Tamiru (Arba Minch University, 2024)
Flood risk management has been severely constrained by limited information on the causes and impacts of flooding. In this study, we evaluated the effect of short-term land cover change of Logiya Catchment on flood inundation to impact Dubti town and its surroundings in the Lower Awash Basin, Ethiopia. We used Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data to detect flood but Sentinel-2 (S-2) optical satellite data to classify land cover by applying a machine learning algorithm. We also used land cover and soil data to generate the Curve Number (CN) map of the study area from 2017 to 2023. The flood maps showed that roads and irrigation canals were washed away by the 2020 extreme flood, which led to the inundation and abandonment of the Tendaho Irrigation Scheme. The runoff generation potential (CN) was above 27% at the Logiya Catchment from 2017 to 2023, contributing to severe flooding. The remote sensing analysis showed that overflow of the Logiya River in 2020 was intercepted and conveyed by the main irrigation canal of the Tendaho Scheme resulting in inundation of the Dubti and its surroundings. The flood extent at Dubti and its surroundings was 59.22 km2 in 2020. It increased by 26% from 2017 to 2019. Frequent (6-days), high resolution (10m) and time-series 7 years Sentinel-1 data helped to get a detailed characterization of the cause, dynamics, and impacts of the historical flood events. The approach and results of this study can guide flood risk management in the study area and serve as a reference for future studies in other flood affected areas.