Future Impact of Climate Change on Durum Wheat Growth and Productivity in Northern Tunisia - Mohamed Nejib El Melki; Imen Soussi; Jameel Mohammed Al-Khayri; Othman M. Al-Dossary; Bader Alsubaie; Slaheddine Khlifi (Agronomy, 2024)
This study evaluates the projected impact of climate change on wheat production in Northwest Tunisia, specifically at Medjez El Beb (36.67 m, 9.74°) and Slougia (36.66 m, 9.6°), for the period 2041–2070. Using the CNRM-CM5.1 and GFDL-ESM2M climate models under RCP4.5 and RCP8.5 scenarios, coupled with the AquaCrop and SIMPLE crop growth models, we compared model outputs with observed data from 2016 to 2020 to assess model performance. The objective was to determine how different climate models and scenarios affect wheat yields, biomass, and growth duration. Under RCP4.5, projected average yields are 7.709 q/ha with AquaCrop and 7.703 q/ha with GFDL-ESM2M. Under RCP8.5, yields are 7.765 tons/ha with AquaCrop and 7.198 q/ha with SIMPLE Crop, indicating that reduced emissions could improve wheat growth conditions. Biomass predictions showed significant variation: in Medjez El Beb, average biomass is 17.99 tons/ha with AquaCrop and 18.73 tons/ha with SIMPLE Crop under RCP8.5. In Slougia, average biomass is 18.90 tons/ha with AquaCrop and 19.04 tons/ha with SIMPLE Crop under the same scenario. Growth duration varied, with AquaCrop predicting 175 days in Medjez El Beb and 178 days in Slougia, while SIMPLE Crop predicted 180 days in Medjez El Beb and 182 days in Slougia, with a standard deviation of ±12 days for both models. SIMPLE Crop demonstrated higher accuracy in predicting growth cycle duration and yield, particularly in Slougia, with mean bias errors of −3.6 days and 2.26 q/ha. Conversely, AquaCrop excelled in biomass prediction with an agreement index of 0.97 at Slougia. Statistical analysis revealed significant yield differences based on climate models and emission scenarios, with GFDL-ESM2M under RCP4.5 showing more favorable conditions. These findings emphasize the importance of model selection and calibration for accurately projecting the agricultural impacts of climate change, and they provide insights for enhancing prediction accuracy and informing adaptation strategies for sustainable wheat production in Northwest Tunisia.