Winter Wheat Yield and DSSAT Model Evaluation in a Diverse Semi-Arid Climate and Agronomic Practices

Abstract

Because of human dependence on sustainable food production, it is needed to adopt agricultural production to climate change, and their consequences on associated socioeconomic issues. Crop modelling potentially can contribute to global food and nutrition security. Therefore, in this context DSSAT (decision support system for agro-technology transfer) was validated for predicting growth and yield of wheat under a diverse semi-arid climate (2 years with diverse climates) and different irrigation strategies, planting methods, and nitrogen rates. The irrigation strategies were ordinary furrow irrigation (OFI) and variable alternate furrow irrigation (VAFI), and the planting methods were on-ridge planting (ORP) and in-furrow planting (IFP) methods. The fertilizer levels were 0 (N0), 150 (N1) and 300 (N2) kg N ha−1. Results indicated that water stress and inappropriate weather especially during the stem elongation influences the grain yield remarkably without noticeable effect on straw yield. Furthermore, VAFI strategy did not impose any limitation on top dry matter N concentration in both years. Calibration of DSSAT showed that the model underestimated the actual evapotranspiration at the end of growing season (during spring with high temperature) and resulted in overestimating the soil water content at depths under 10 cm during this period of time. Since the potential transpiration has an important role in calculating the effect of water stress factor, the model overestimated slightly the maximum leaf area index (LAI) and consequently biomass and yield in water stress condition; however, overall, model could statistically simulate LAI (NRMSE = 0.3, d = 0.96, R2 = 0.95), total dry matter (NRMSE = 0.07, d = 0.99, and R2 = 96) and grain yield (NRMSE = 0.13, d = 0.96, and R2 = 90). Model also could reasonably simulate the nitrogen components including the grain N concentration (NRMSE = 0.05, d = 0.95), above-ground nitrogen uptake (NRMSE = 0.11, d = 0.99), and soil nitrate content (NRMSE = 0.23, d = 0.86). However, evaluating the model with data set from 2015 to 2016 indicated that the model could not simulate wheat yield and nitrogen components in validation year due to strong effects of diverse weather condition and water stress on grain yield and crop development.