Surface Runoff and Sediment Yield Responses to Land Use and Cover Changes: Implications for Watershed Management in the Gidabo Watershed, Ethiopia

Abstract

Land use and land cover (LULC) changes, primarily driven by deforestation, agricultural expansion, and urbanisation, have significantly altered hydrological processes in the Gidabo watershed, located in southern Ethiopia. Therefore, this study aims to assess both the historical and projected impacts of LULC changes on surface runoff (Q_surf) and sediment yield (SY). To achieve this, Landsat imagery from 2003 to 2024 was classified using the Random Forest (RF) algorithm within the Google Earth Engine (GEE) platform, achieving 92.1% overall accuracy and a Kappa coefficient of 0.905. In addition, future LULC scenarios for 2030 and 2050 were predicted based on key biophysical and socio-economic drivers and then integrated into the SWAT+ model under constant climate conditions. The model was calibrated and validated using observed streamflow and sediment data from four hydrological stations. The baseline simulation showed Q_surf of 150.23 mm/year and SY of 0.277 t/ha/year. However, under future LULC scenarios, Q_surf is projected to increase by 26.07% in 2030 and 36.51% in 2050, reaching up to 205.73 mm/year, while SY is expected to rise by 54.51% and 74.37%, respectively, peaking at 0.48 t/ha/year in steep and cultivated areas. Moreover, the runoff coefficient showed an increasing trend, indicating reduced infiltration and greater overland flow due to land degradation. Thus, this study demonstrates that combining cloud-based RF classification with SWAT+ modelling provides an effective approach for evaluating hydrological responses to LULC changes. Consequently, the findings imply the urgent need for integrated watershed management strategies such as afforestation, erosion control, and sustainable land use planning to mitigate adverse hydrological impacts and ensure long-term water resource sustainability.