Revealing Climate-Induced Patterns in Crop Yields and the Water-Energy-Food-Carbon Nexus: Insights from the Pearl River Basin

被引:0
作者
Ye, Changxin [1 ,2 ,3 ,4 ]
Yuan, Ze [1 ,2 ,3 ,4 ]
Chen, Xiaohong [1 ,2 ,3 ,4 ]
Zhong, Ruida [1 ,2 ,3 ,4 ]
Huang, Lie [1 ,2 ,3 ,4 ]
机构
[1] Sun Yat Sen Univ, Sch Civil Engn, Zhuhai 519082, Peoples R China
[2] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China
[3] Sun Yat Sen Univ, Guangdong Engn Technol Res Ctr Water Secur Regulat, Guangzhou 510275, Peoples R China
[4] Sun Yat Sen Univ, Guangdong High Educ Inst, Key Lab Water Cycle & Water Secur Southern China, Guangzhou 510275, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
AquaCrop model; NSGA-II method; Sobol sensitivity analysis; machine learning; climate change; PROCESS-BASED MODEL; AQUACROP MODEL; RICE PRODUCTION; CHINA; MAIZE; IRRIGATION; DEMAND; TEMPERATURE; VALIDATION; MANAGEMENT;
D O I
10.3390/w16243693
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the context of growing concerns over food security and climate change, research on sustainable agricultural development increasingly emphasizes the interconnections within agricultural systems. This study developed a regionally integrated optimization and prediction agricultural model to systematically analyze the impacts of climate change on agricultural systems and their feedback mechanisms from a water-energy-food-carbon (WEFC) nexus perspective. Applied to the Pearl River Basin, the model evaluates future trends in grain yield, water use, energy consumption, and carbon emissions under various climate scenarios throughout this century. The results indicate that rising temperatures significantly reduce crop yields, particularly in the western basin, increasing the environmental footprint per unit of grain produced. However, the CO2 fertilization effect substantially offsets these negative impacts. Under the SSP585 scenario, CO2 concentrations rising from 599.77 ppm to 1135.21 ppm by the century's end led to a shift in crop yield trends from negative (Z = -7.03) to positive (Z = 11.01). This also reduces water, energy, and carbon footprints by 12.82%, 10.62%, and 10.59%, respectively. These findings highlight the critical importance of adaptive management strategies, including precision irrigation, optimized fertilizer use, and climate-resilient practices, to ensure sustainable agricultural production. Despite these insights, the model has limitations. Future research should incorporate uncertainty analysis, diverse adaptation pathways, and advanced technologies such as machine learning and remote sensing to improve predictive accuracy and applicability. This study offers valuable guidance for mitigating the adverse impacts of climate change on the WEFC nexus, supporting sustainable agricultural practices and science-based policy development.
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页数:21
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