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<p>Rainfed wheat plays a critical role in global food security, yet climate change increasingly constrains its productivity. This study evaluates CMIP6 model performance and projects future changes in rainfed wheat yield and production potential across Iran under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. 11 CMIP6 models were evaluated using Root Mean Square Error (RMSE), coefficient of determination (R<sup>2</sup>), and Taylor diagrams, with a Composite Score (CS) used to select the five best-performing models (EC-Earth3, GFDL-ESM4, MPI-ESM1-2-HR, MRI-ESM2-0, and CMCC-ESM2) for constructing a performance-weighted multi-model ensemble (MME). Among three bias-correction methods, Variance Scaling proved superior in preserving statistical distributions while reducing errors. Future projections for 2021–2050, 2051–2080, and 2081–2100 reveal an overall increasing trend in rainfed wheat yield and production potential (100–800&#xa0;kg ha⁻¹ decade⁻¹), with the largest increases in southwestern and northern Iran and reductions (1–2 t ha⁻¹) in western, eastern, and northeastern regions. Changes range from ± 1–2 t ha⁻¹ under SSP1-2.6 to ± 7.5 t ha⁻¹ under SSP5-8.5. These findings highlight the need for region-specific adaptation strategies and demonstrate a transferable framework for climate impact assessment in semi-arid regions.</p>

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Projecting the Future Performance and Yield Potential of Rainfed Wheat Based on CMIP6 Models under Different SSP Scenarios in Iran

  • 期刊论文

  • 发表日期：

    2026年7月30日

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  • Elham Joudaki,
  • Amir Hussain Meshkatee,
  • Gholamali Kamali,
  • Hossein Rezaei

摘要

Rainfed wheat plays a critical role in global food security, yet climate change increasingly constrains its productivity. This study evaluates CMIP6 model performance and projects future changes in rainfed wheat yield and production potential across Iran under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. 11 CMIP6 models were evaluated using Root Mean Square Error (RMSE), coefficient of determination (R2), and Taylor diagrams, with a Composite Score (CS) used to select the five best-performing models (EC-Earth3, GFDL-ESM4, MPI-ESM1-2-HR, MRI-ESM2-0, and CMCC-ESM2) for constructing a performance-weighted multi-model ensemble (MME). Among three bias-correction methods, Variance Scaling proved superior in preserving statistical distributions while reducing errors. Future projections for 2021–2050, 2051–2080, and 2081–2100 reveal an overall increasing trend in rainfed wheat yield and production potential (100–800 kg ha⁻¹ decade⁻¹), with the largest increases in southwestern and northern Iran and reductions (1–2 t ha⁻¹) in western, eastern, and northeastern regions. Changes range from ± 1–2 t ha⁻¹ under SSP1-2.6 to ± 7.5 t ha⁻¹ under SSP5-8.5. These findings highlight the need for region-specific adaptation strategies and demonstrate a transferable framework for climate impact assessment in semi-arid regions.