Simulating climate change impacts on cotton using AquaCrop model in China

文献类型： 外文期刊

第一作者： Li, Na

作者： Li, Na;Yang, Qiliang;Li, Na;Li, Yi;Li, Yi;Biswas, Asim;Dong, Hezhong;Li, Yi

作者机构：

关键词： Climate change; AquaCrop model; Cotton; Statistical analysis

期刊名称：AGRICULTURAL SYSTEMS （ 影响因子：6.6； 五年影响因子：6.9 ）

ISSN： 0308-521X

年卷期： 2024 年 216 卷

页码：

收录情况： SCI

摘要： CONTEXT: Cotton is the most widely planted fiber crop in the world and plays an important role in the national economy. Climate change alters the environmental elements of crop growth such as sunlight, moisture, and soil through changes in temperature and precipitation, which in turn affects the phenology period, growth potential, and cropping system of cotton, and ultimately affects yields. OBJECTIVE: Studying the feedback of cotton growth to climate change is of great practical significance for cotton planting planning and yield increase and stabilization. Crop growth is affected by both climate and management measures, but most studies often ignore the impact of management measures, resulting in the inability to accurately assess the impact of climate. And existing research is mostly based on single sites or some provinces, lacking regional research on the main cotton producing areas in China. METHODS: This study calibrated the AquaCrop model using data from 40 sites from three major cotton growing regions in China collected over different time periods between 1978 and 2018 and simulated the climate change impact on cotton for the subsequent years. RESULTS AND CONCLUSIONS: The model showed good applicability in simulating the growth process of cotton in the study areas. The above -ground biomass (Bio), potential yield (Py) and water use efficiency (WUE) of cotton under the influence of climate change showed an increasing trend of 98% (39/40), 98%, and 93% of the sites, while the actual evapotranspiration (ETa) mainly decreased. Elevated CO2 concentration increased cotton yield. The main climatic variables affecting cotton growth were wind speed, solar radiation, sunshine hours, and minimum and maximum temperature. Climate variables explained the changes in ETa, Bio, Py, and WUE by 65.1-95.5%, 9.7-74.5%, 14.8-68.3%, and 15.2-90.4%, respectively. Overall, cotton growth showed close relation to changes in Ws, Rs, Tmin, and Tmax. The study quantitatively analyzed and identified the main climatic factors affecting cotton growth and found that climate change and elevated CO2 concentrations have a positive impact on cotton production. SIGNIFICANCE: The simulations conducted in this study using multi -site data provided reliable regional information that can help develop future management strategies to maintain current and meet future demand for cotton in China, and provide recommendations and guidance for environmental regulation and sustainable discovery of the cotton growing process.

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