Evaluation of AquaCrop model in soybean cultivation under different planting dates and deficit irrigation treatments

Water stress has been identified as the major effective factor on soybean production growth in semiarid regions. Planting date and irrigation management are the most important agronomic practices, which affect soybean growth and economic yield production. Today, to assess the impacts of destructive environmental stresses, calibrated models can be used to simulate and evaluate the growth of the crops under different scenarios. In this research, the AquaCrop model was evaluated for simulation of soybean yields and water productivity on varying irrigation levels and planting dates in northeast of Iran. For this purpose, root mean square error (RMSE), model efficiency (E), coefficient of determination (R2), and prediction error (p e) were applied to test the model performance. The calibrated AquaCrop model predicted soybean grain yield and biomass for all treatments with the prediction error statistics 0.27 RMSE1, 5.1 e 5.6%, 0.91 R21 ha1, R2 of 0.88, and p e of 7.6%. Subsequently, validation results were 0.93 E 0.96; 0.92 R21 for grain and biomass yield, respectively. The soybean yields and growth response to different irrigation water management and planting dates was adequately predicted by the AquaCrop model. Overall, the AquaCrop model is a suitable support tool for decision makers to simulate WP, grain yield (GY), and biomass (Bi) in soybean cultivation under various field managementin semiarid environment.