Extensive catchment degradation throughout the Ethiopian Highlands induced by long‐term intensified land use, erosion‐prone topography, and climate causes substantial soil erosion that limits agricultural productivity and results in lake sedimentation. However, before taking soil conservation measures, management of the soil loss problem essentially needs catchment‐level modelling to estimate the geographic distribution of erosion hotspots. With the increasing availability of sediment and spatial data and development of physically based models, this study aims multisite calibration of Soil and Water Assessment Tool (SWAT) to map erosion hotspot areas and to assess the effect of well‐known land management alternatives in sediment reduction in the Lake Tana Basin. The SWAT simulations indicated that the goodness of fit between predicted and observed data was satisfactory for all gauge stations except for one, and the model performance was within acceptable evaluation ratings. Simulated average sediment yield (SY) for the period 2001–2016 at subbasin level varies from negligible to about 169 Mg ha⁻¹ yr⁻¹ (basin average 32 Mg ha⁻¹ yr⁻¹). High potential SY (>50 Mg ha⁻¹ yr⁻¹) was simulated for 23% of the subbasins in Megech, upper Rib, upper Gumara, and Gilgel Abay catchments due to steep slope topography, aggressive rainfall, croplands dominance, and low rock fragment cover. The differences in level of erosion risk among subbasins help to prioritize and target specific areas of the basin that need urgent soil conservation activities. Scenario analysis also showed that implementing stone bunds, Acacia decurrens‐based crop rotation, reforestation, and grass contour strips reduces the existing SY by 51–61% at basin level. The potential sediment production could reach tolerable levels by implementing stone bunds, tree‐based crop rotation, reforestation in steep slope areas, and grass contour strips on gentle slopes. Overall, the multisite calibration of SWAT model using the measured run‐off and sediment data produces reasonable results that may support decision makers and planners to implement relevant land management measures and thereby reduce the alarming problems of soil loss in the basin and sedimentation of Lake Tana.

Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment.