Modeling climate change impact on dryland wheat production for increased crop yield in the Free State, South Africa, using GCM projections and the DSSAT model

Introduction: The impact of climate change on food production in South Africa is likely to increase due low rainfall and frequent droughts, resulting insecurity the future. use well-calibrated validated crop models with data important for assessing impacts developing adaptation strategies. In this study, decision support system agrotechnology transfer (DSSAT) model was used predict yield using observed projected data. Materials Methods: Climate, soil, management were collected from wheat-growing study sites Bethlehem, Africa. DSSAT wheat (CROPSIM-CERES) already calibrated, by Serage et al. (Evaluating Climate Change Adaptation Strategies Disaster Risk Management: Case Study Bethlehem Wheat Farmers, Africa, 2017) three cultivar coefficients obtained experiment ARC-Small Grain Institute. run historical eastern Free State (Bethlehem) 1999 2018 as baseline period. To determine effects change, simulation future projections four Global Models (GCM): BCC-CSM1_1, GFDL-ESM2G, ENSEMBLE, MIROC 2020 2077. Results: average historic 1145.2 kg/ha slightly lower than highest 1215.9 GCM ENSEMBLE during Representative concentration pathways (RCP) 2.6, while lowest 29.8 produced RCP 8.5 (GCM GFDL-ESM2G). Model GFDL-ESM2G yields (29.8–47.74 kg/ha) 6.0, respectively. range BCC-CSM1_1 770.2 2.6 921.68 4.5 547.84 700.22 MIROC. Conclusion: This showed a declining trend RCP2.6 RCP8.5, indicating that possible higher temperatures reduced will decrease State. measures mitigate potential could include changes planting dates cultivars. Using simulate response crops variations weather conditions can be useful generate advisories farmers prevent yield.