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Potential impacts of extreme weather events in main maize (Zea mays L.) producing areas of South Africa under rainfed conditions
- Mangani, Robert, Tesfamariam, Eyob H., Engelbrecht, Christien J., Bellocchi, Gianni, Hassen, Abubeker, Mangani, Tshepiso
- Regional environmental change 2019 v.19 no.5 pp. 1441-1452
- General Circulation Models, Zea mays, climate change, corn, crop models, drought, food security, grain yield, heat, issues and policy, meteorological data, planning, radiative forcing, simulation models, yield forecasting, South Africa
- An important topic of global concern is the likely reduction of maize production in response to climate change in association with increased frequency and intensity of extreme weather events, which threatens food security. We quantified the response of maize yield to projected climate changes in three main maize growing areas of South Africa (Bloemfontein, Lichtenburg and Nelspruit) using two crop modelling solutions: existing (EMS) and modified (MMS) CropSyst. The MMS considers explicitly the impact of extreme heat and drought. Both solutions were run with climate data generated from two radiative forcing scenarios using six general circulation models and three time horizons representing baseline (1990–2020), near future (2021–2050) and far future (2051–2080) time periods. Reduced yields were projected with both modelling solutions especially under far future time period. Simulated maize yield using EMS with high radiative forcing for far future decreased (compared with the simulated baseline for EMS) by 30%, 25.9% and 18.3% at Bloemfontein, Lichtenburg and Nelspruit, respectively. Simulated grain yield with MMS showed reductions of 27.6%, 24.3% and 18.7%, respectively (compared with the simulated baseline for MMS). Grain yield differences between the EMS and MMS ranged between 9 and 21%. This difference showed an increasing trend as time progressed from the baseline to the far future and varied across locations. Accounting explicitly for the impact of extreme weather events (MMS) resulted in lower simulated yields compared with the model without (EMS). Findings from this study warrant the need for location-specific model simulation using MMS-type models to improve crop yield predictions under climate change for better food security planning and policy formulation.