Evaluating crop models for future climate scenarios: wheat yield predictions using APSIM and STICS under combined CO2, warming, and water deficit conditions

Abstract Crop models are essential for predicting climate change impacts on agriculture, yet their validation under multi-stress conditions remains limited. This study evaluated two widely used wheat models, APSIM and STICS, using data from three Free-Air CO2 Enrichment (FACE) experiments (USA, Germany, Australia) combining elevated CO2 (eCO2), water deficit, and warming. Environmental characterization using simulation-based stress indices revealed that intended ‘controls’ frequently experienced hidden heat and water stress, meaning models were calibrated on crops already undergoing physiological adjustments. Evaluation of simulated yield and components revealed a clear hierarchy in prediction errors (RRMSE): unlimited conditions (3%–9%) < single stress (4%–27%, with a need to improve response to heat stress) < combined stress (17%–123%). eCO2 generally increased prediction uncertainty for crops experiencing water stress. Our results suggest that current stress functions from the models fail to capture the synergistic coupling between drought and heat stress. This highlights the urgent need for more mechanistic modelling to improve the reliability of climate change impact assessments.