Abstract
Global wheat production has faced, and will persist in encountering many challenges. Therefore, developing a dynamic cultivation approach generated through modeling is crucial to coping with the challenges in specific districts. The modeling can contribute to achieving global objectives of farmers’ financial independence and food security by enhancing the cropping systems. The current study aims to assess the effects of cultivars and sowing windows intricately on irrigated wheat production using the two models from Coupled Model Intercomparison Project Phase 6 (CMIP6), including ACCES-CM2 and HadGEM31-LL under two shared socioeconomic pathways (SSP245, and SSP585). A two-year on-farm experiment was conducted for parametrization and validation of the APSIM-Wheat model at two locations. The model reasonably simulated the days to anthesis, maturity, biomass production, and yield within all cultivars. The normalized root-mean-square error (RMSE) of the phenological stages was simulated and measured values were 5% and 2–4%, while the index of agreement (IOA) was in the range of 0.84–0.88 and 0.95–0.97. An acceptable agreement of the simulated biomass (RMSE = 5–7% and 0.91 − 0.78) and yield (RMSE = 6–11% and IOA = 0.70–0.94) was identified in the model. Afterward, the LARS-WG model generated the baseline (2000–2014) based on the weather data at the sites and projected the models for the near (2030–2049) and remote future (2050–2070). The models revealed that not only the average maximum and minimum temperatures will rise by 1.85°C and 1.62°C which will exacerbate the reference evapotranspiration (ET0), but also the precipitation and solar radiation will reach + 58%, and + 0.25 Mj m− 2. Our results clearly showed that precipitation volume over the growing seasons would elevate approximately two times as much as the baseline in the future, while there is a significant decrease in water productivity (WP) and yield from the intensive ET0. Based on the wheat simulation, the short-duration cultivar (Kalate) combined with the postponed planting (16-Dec) was determined as a practical alternative; nonetheless, both WP and yield significantly decreased by 40% and 7%, respectively (p < 0.05). In conclusion, identifying and analyzing future farming conditions (e.g., agro-climate, soil and crop management data) would provide a perception of the forthcoming scenarios. When applied, this knowledge can potentially mitigate the adverse impacts of climate change on global wheat production.