Remote sensing approach to evaluate the effect of short-term land cover change on flood inundation and impact, Lower Awash Basin, Ethiopia.

Abstract

Flood risk management has been severely constrained by limited information on the causes and impacts of flooding. In this study, we evaluated the contribution of short-term land cover change of Logiya catchment to flood inundation and impact on Dubti town and it’s surrounding in the Lower Awash River Basin, Ethiopia. The land cover maps were generated by applying a machine learning algorithm on the Sentinel-2 optical satellite images. Land cover and soil data were used to generate the Curve Number (CN) map of the study area for the period stretching from 2017 and 2023. Sentinel-1 based flood maps show that roads and irrigation canals were washed away by the 2020 extreme flood which led to the inundation and abandoning of the Tendaho irrigation scheme. The runoff generating potential (CN) significantly increased over 27% of the Logiya catchment between 2017 and 2023 contributing to enhance 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 surrounding. Availability of earth observation data (e.g Sentinel-1 SAR on the study area every 6 days at 10m resolution for 7 years) enabled detail characterization of the cause, dynamics and impacts of the historical flood events. This study’s results can guide flood risk management in the study area and serve as a reference for future studies in flood affected area.