Modelling Climate Uncertainty and Adaptations for Soybean-Based Cropping System
Climate uncertainty is a serious risk to agriculture sector impacting food security. Soybean crop is not exception to climate change. Crop growth simulation modelling approach has been established as a valuable tool to determine climate uncertainty on soybean yield. However, the crop growth model must be calibrated and evaluated for new regions before application for climate change assessment. Limited studies are available about evaluation of CSM-CROPGRO-Soybean model and its application for climate change impact on soybean in spring and autumn seasons under arid conditions. Field experiments were conducted in spring and autumn season in 2019 and 2020 at farmer field in Multan, Pakistan. During spring season experiments, cultivars Williams-82, NARC-1 and Ajmeri were placed in main plots in both seasons, while dates were 10th Jan, 20th Jan, 01st Feb, 10th Feb and 20th Feb during spring season while sowing dates were 01st Jul, 15th Jul, 01st Aug, 15th Aug and 30th Aug in autumn were allocated in sub plots. Results indicated that after calibration, performance of model was well due to acceptable ranged values of error and root mean square error (RMSE). In sensitivity analysis, model was responsive to CO2, temperature and rainfall. Climate change reduced more seed yield in autumn season as compared to spring season. Without adaptation strategies, seed yield will be reduced by 22.73% in spring and 35.91% in autumn season during mid-century at all GCMs at RCP 8.5. With adopting adaptation strategies of seven days earlier sowing of spring soybean and ten days delay sowing of autumn crop, along with growing climate resilient cultivars can minimize the negative impact of climate change.