Coordinated regulation of water use-efficiency-cost in a winter wheat-summer maize rotation system and optimization of water allocation strategies

In the North China Plain, the winter wheat-summer maize rotation system faces challenges due to the mismatch between precipitation patterns and crop water demands, leading to groundwater over-exploitation and low irrigation efficiency. This study, based on a 2023–2024 field irrigation experiment and...

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Vydáno v:Agricultural water management Ročník 318; s. 109718
Hlavní autoři: Zhao, Li, Han, Congying, Li, Yinong, Zhang, Baozhong, Zheng, Yulu, Cai, Jiabing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.09.2025
Elsevier
Témata:
Dynamic water cycle processes
Multi-objective optimization model
Uncertainty
Water management
Winter wheat-summer maize rotation
Multi-objective optimization model
Winter wheat-summer maize rotation
Uncertainty
Water management
Dynamic water cycle processes
ISSN:0378-3774, 1873-2283
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Shrnutí:In the North China Plain, the winter wheat-summer maize rotation system faces challenges due to the mismatch between precipitation patterns and crop water demands, leading to groundwater over-exploitation and low irrigation efficiency. This study, based on a 2023–2024 field irrigation experiment and the simulation of dynamic field water cycles, examines how water allocation affects crop growth and yield. A multi-objective nonlinear programming model was developed, incorporating triangular fuzzy numbers, accuracy functions, and credibility constraints, to balance actual yield (AY), irrigation water productivity (IWP), and total cost (TC). Results show that water allocation significantly influences crop yield, and a trade-off exists among yield, irrigation water productivity, and cost. As the credibility level increases, cost tends to stabilize, whereas yield and irrigation water productivity show greater variability. Lower credibility values help improve the overall satisfaction of multiple objectives. The optimized scheme increased crop yield by 4.02 %, improved irrigation water productivity by 5.84 %, reduced costs by 7.17 %, enhanced total water productivity by 3.17 %, and cut annual irrigation volume by 15.69 %. •An uncertainty-based optimization model coordinates multi-objective conflicts in agricultural water allocation.•Total yield, irrigation water productivity and total costs are modeled, optimized and coordinated.•Dynamic fuzzy uncertainties in water allocation are managed across growth stages under wheat-maize rotation.
ISSN:0378-3774
1873-2283
DOI:10.1016/j.agwat.2025.109718