LAUSR

Abstract Crop simulation models offer possibilities to evaluate and target agricultural information for sustainable intensification in countries like Ethiopia with inadequate resources for field research. The objectives of this research were to calibrate and evaluate the CERES-Maize, CROPGRO-Dry bean and CROPGRO-Soybean models for practices associated with conservation agriculture and fertilizer N, and to evaluate five generated weather datasets for Ethiopia. Data from multi-year field experiments and additional data obtained from previously conducted national variety trials were used for model evaluation. Generated weather datasets for six agroecologies were evaluated by comparison with observed data and by use of data in the models. Genetic coefficients used in the models for maize, dry bean and soybean were determined by model parametrization and calibration of phenology and yield. The models acceptably simulated the effects of N rate, maize-legume rotation, and crop residue retention plus tillage with average normalized deviation closer to zero, RMSE less or similar to standard deviation of observed data, and with normalized RMSE (nRMSE)