Application of models to identify soil erosion processes, estimate sediment accumulations into lakes, technically design best management practices, and monitor and evaluate different management scenarios in the Ethiopian highlands has been growing. However, proper model implementation will require verification of the model against known output parameters. This study investigated the performance and applicability of one such model, Soil and Water Assessment Tool (SWAT). Sequential Uncertainty Fitting-2 (SUFI-2), a SWAT-CUP2012 sub-module computer program, was applied to optimize the parameters of the SWAT using monthly observed sediment yield data at a monitoring site in Maybar experimental watershed, Ethiopia. Thirteen hydrological years were used for model calibration, validation and uncertainty analysis. Multi-objective function statistics: P-factor (23%, 12%), R-factor (0.63, 0.40), Nash-Sutcliffe efficiency, NSE (0.55, 0.53), root mean square error-observations standard deviation ratio (RSR) (0.67, 0.69), coefficient of determination, R-2 (0.55,0.52), and percent bias, PBIAS (-14.6%, 0.8%) for calibration and validation, respectively were obtained. The model evaluation statistics suggested that SWAT extremely under-predicted peak sediment loads in both calibration and validation periods. However, according to model evaluation guidelines and performance ratings, modeled sediment yield can be rated as satisfactory. Although the accuracy of modeling of soil erosion processes using SWAT is likely affected by spatial variation of watershed characteristics, and scale of management, among other factors, Maybar calibrated SWAT model do suggest a broad guide: prediction of sediment yield at ungauged watershed with SWAT could be possible under comparable topography, land use, soil, management and climate condition for the purpose of soil erosion assessment, scenario analysis, and recommendation of best management practices to support watershed management initiatives in the Ethiopian highlands. (C) 2014 Elsevier B.V. All rights reserved.