An Analysis of Uncertainties in Evaluating Future Climate Change Impacts on Cotton Production and Water Use in China

作者：Ruixue Yuan, Keyu Wang, Dandan Ren, Zhaowang Chen, Baosheng Guo, Haina Zhang, Dan Li, Cunpeng Zhao, Shumin Han, Huilong Li, Shuling Zhang, De Li Liu, Yanmin Yang · 发表于：Agronomy · 年份：2025 · DOI：10.3390/agronomy15051209 · 被引用次数：6 · 研究领域：Climate change impacts on agriculture、Rice Cultivation and Yield Improvement、Environmental and Agricultural Sciences

Global Climate Models (GCMs) are a primary source of uncertainty in assessing climate change impacts on agricultural production, especially when relying on limited models. Considering China’s vast territory and diverse climates, this study utilized 22 GCMs and selected three representative cotton-producing regions: Aral (northwest inland region), Wangdu (Yellow River basin), and Changde (Yangtze River basin). Using the APSIM model, we simulated climate change effects on cotton yield, water consumption, uncertainties, and climatic factor contributions. Results showed significant variability driven by different GCMs, with uncertainty increasing over time and under radiation forcing. Spatial variations in uncertainty were observed: Wangdu exhibited the highest uncertainties in yield and phenology, while Changde had the greatest uncertainties in ET (evapotranspiration) and irrigation amount. Key factors affecting yield varied regionally—daily maximum temperature and precipitation dominated in Aral; precipitation was a major negative factor in Wangdu; and maximum temperature and solar radiation were critical in Changde. This study provides scientific support for developing climate change adaptation measures tailored to cotton production across different regions.