Reservoir sedimentation assessment using the Google Earth Engine (GEE)

To implement effective reservoir management practices, critical assessments of sediment deposition are important. In this study, we developed an automated approach using the Google Earth Engine to assess reservoir sedimentation and validated it on two reservoirs: Koka and Gefersa I/II, which are located in the upper Awash River Basin (ARB), Ethiopia. Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM) data from the study period, along with reservoir water level, pre-impoundment reservoir capacity and recent bathymetry survey data, were used. Statistical validation confirmed a strong association between the obtained results and the bathymetric survey results: Koka Reservoir (Pearson correlation coefficient (r) = 0.999, regression coefficient (R²) = 0.976, Nash-Sutcliffe efficiency (NSE) = 0.997) and Gefersa I/II Reservoir (r = 0.997, R² = 0.992, NSE = 0.955). This study highlights that GEE effectively estimates reservoir sedimentation, providing valuable insight for the active management of reservoirs, especially in resource-limited regions.