Year patterns of climate impact models' performance: Long-term simulation of rainfed spring wheat production using five crop models under various climate patterns - Funian Zhao; Qiang Zhang; Heling Wang; Kai Zhang (Agricultural Water Management, 2025)
Crop models serve as powerful tools for investigating the interaction of crop traits, environmental fluctuations, and management practices. However, the calibration of these models relies heavily on experiments conducted under specific conditions or within particular years. The adaptability and efficacy of these calibrated models across different year patterns of climate remain uncertain. Our analysis aimed to evaluate the utility of these models across diverse climatic patterns and explore potential factors contributing to their performance variations. In this study, experiments were conducted in a semi-arid region characterized by significant climate variability, and data collection was undertaken to assess the performance of five distinct crop models (APSIM, AquaCrop, DSSAT, SSM-iCrop, WOFOST). The field experimental results indicated that year patterns of climate for rainfed spring wheat was jointly determined by soil water at planting and atmospheric moisture conditions during the growing season. After calibration, all five crop models effectively captured the growth, development, and yield formation of spring wheat. Notably, both simple and complex models exhibited similar performance in simulating the spring wheat growth and yield formation. However, the simulation results for spring wheat yield varied among the different year patterns of climate. Particularly in drier climate regimes, most models tended to overestimate spring wheat yields, with calculated relative root mean square errors exceeding 30 %. These findings suggested that calibrated models might not universally represent crop growth, development, and yield formation processes across all climatic patterns in regions characterized by substantial climate variability. In specific years, they were prone to either overestimating or underestimating crop yields. Furthermore, our study raised questions about the direct transferability of models to neighboring regions within the same climatic zone and application in future climatic scenarios. Without local climate-specific model calibration and with current climate-specific model calibration, the use of models might lead to inaccurate estimations of crop yields in other climatic area and future dryer climatic scenarios.