Uncertain multi‐objective programming approach for planning supplementary irrigation areas in rainfed agricultural regions
Rainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in...
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| Veröffentlicht in: | Irrigation and drainage Jg. 74; H. 3; S. 1193 - 1214 |
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| Abstract | Rainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in rainfed agricultural regions. The approach incorporates multi‐objective linear programming, interval linear programming, fuzzy goal programming and stochastic expected value programming. In the proposed interval multi‐fuzzy goal stochastic expected‐value programming, uncertainties are expressed in the form of discrete intervals, probability distributions and fuzzy goals. This approach, which considers the randomness of precipitation during the optimization process and allocates limited irrigation water resources to different subareas and crops, was applied to a case study of crop irrigation area planning in Guyuan City, Ningxia Hui Autonomous Region, northwestern China. The maximum economic benefits and the minimum sum of the Gini coefficients among the different subareas and crops were regarded as the planning objectives, and a series of optimal irrigation areas with different crops and subareas under different water levels were obtained. The optimization results revealed that vegetables and fruits consumed large amounts of irrigation water to increase their economic benefits. In addition, allocating a large amount of irrigation water to wheat is essential to decrease the Gini coefficient and meet food security constraints, particularly at extremely low water levels. Compared with current management, the optimized irrigation area decreased by 30%, the crop water deficit index increased by 9%, the economic benefits increased by 3% and the total Gini coefficient of crops decreased by 17%, indicating that the optimization approach could fairly and reasonably allocate irrigation water resources. Our research provides a mathematical approach for decision‐makers to plan supplementary irrigation areas in rainfed agricultural regions.
Résumé
L'agriculture pluviale est nécessaire pour assurer la sécurité alimentaire et hydrique mondiale, et l'irrigation supplémentaire est un moyen efficace d'améliorer les avantages économiques dans les régions agricoles pluviales. Cette étude propose une nouvelle approche d'optimisation incertaine pour optimiser les zones d'irrigation supplémentaires dans les régions agricoles pluviales. L'approche est composée de la programmation linéaire multi‐objective, de la programmation linéaire par intervalles, de la programmation d'objectifs flous et de la programmation par valeurs espérées stochastiques. Dans la programmation par valeurs espérées stochastiques à objectifs flous et à intervalles multiples proposée, les incertitudes sont exprimées sous forme d'intervalles discrets, de distributions de probabilité et d'objectifs flous. Cette approche, qui prend en compte le caractère aléatoire des précipitations lors du processus d'optimisation et alloue des ressources en eau d'irrigation limitées à différentes sous‐zones et cultures, a été appliquée à une étude de cas de planification des zones d'irrigation des cultures dans la ville de Guyuan, région autonome de Ningxia Hui au nord‐ouest de la Chine. On a tenu en considération les bénéfices économiques maximaux et la somme minimale des coefficients de Gini entre les différentes sous‐zones et cultures comme les objectifs de planification, et on a obtenu une série de zones d'irrigation optimales avec différentes cultures et sous‐zones dans le cadre de différents niveaux d'eau. Les résultats de l'optimisation ont indiqué que les légumes et les fruits consommaient de grandes quantités d'eau d'irrigation pour augmenter leurs bénéfices économiques. En outre, il est nécessaire d'allouer une grande quantité d'eau d'irrigation au blé pour diminuer le coefficient de Gini et pour répondre aux contraintes de sécurité alimentaire, en particulier à des niveaux d'eau extrêmement bas. Par rapport à la gestion actuelle, la zone d'irrigation optimisée a diminué de 30%, l'indice de déficit hydrique des cultures a augmenté de 9%, les bénéfices économiques ont augmenté de 3% et le coefficient de Gini total des cultures a diminué de 17%, ce qui indique que l'approche d'optimisation pourrait distribuer de manière juste et raisonnable les ressources en eau d'irrigation. Notre recherche fournit une approche mathématique aux décideurs pour la planification des zones d'irrigation supplémentaires dans les régions agricoles pluviales. |
|---|---|
| AbstractList | Rainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in rainfed agricultural regions. The approach incorporates multi‐objective linear programming, interval linear programming, fuzzy goal programming and stochastic expected value programming. In the proposed interval multi‐fuzzy goal stochastic expected‐value programming, uncertainties are expressed in the form of discrete intervals, probability distributions and fuzzy goals. This approach, which considers the randomness of precipitation during the optimization process and allocates limited irrigation water resources to different subareas and crops, was applied to a case study of crop irrigation area planning in Guyuan City, Ningxia Hui Autonomous Region, northwestern China. The maximum economic benefits and the minimum sum of the Gini coefficients among the different subareas and crops were regarded as the planning objectives, and a series of optimal irrigation areas with different crops and subareas under different water levels were obtained. The optimization results revealed that vegetables and fruits consumed large amounts of irrigation water to increase their economic benefits. In addition, allocating a large amount of irrigation water to wheat is essential to decrease the Gini coefficient and meet food security constraints, particularly at extremely low water levels. Compared with current management, the optimized irrigation area decreased by 30%, the crop water deficit index increased by 9%, the economic benefits increased by 3% and the total Gini coefficient of crops decreased by 17%, indicating that the optimization approach could fairly and reasonably allocate irrigation water resources. Our research provides a mathematical approach for decision‐makers to plan supplementary irrigation areas in rainfed agricultural regions.
Résumé
L'agriculture pluviale est nécessaire pour assurer la sécurité alimentaire et hydrique mondiale, et l'irrigation supplémentaire est un moyen efficace d'améliorer les avantages économiques dans les régions agricoles pluviales. Cette étude propose une nouvelle approche d'optimisation incertaine pour optimiser les zones d'irrigation supplémentaires dans les régions agricoles pluviales. L'approche est composée de la programmation linéaire multi‐objective, de la programmation linéaire par intervalles, de la programmation d'objectifs flous et de la programmation par valeurs espérées stochastiques. Dans la programmation par valeurs espérées stochastiques à objectifs flous et à intervalles multiples proposée, les incertitudes sont exprimées sous forme d'intervalles discrets, de distributions de probabilité et d'objectifs flous. Cette approche, qui prend en compte le caractère aléatoire des précipitations lors du processus d'optimisation et alloue des ressources en eau d'irrigation limitées à différentes sous‐zones et cultures, a été appliquée à une étude de cas de planification des zones d'irrigation des cultures dans la ville de Guyuan, région autonome de Ningxia Hui au nord‐ouest de la Chine. On a tenu en considération les bénéfices économiques maximaux et la somme minimale des coefficients de Gini entre les différentes sous‐zones et cultures comme les objectifs de planification, et on a obtenu une série de zones d'irrigation optimales avec différentes cultures et sous‐zones dans le cadre de différents niveaux d'eau. Les résultats de l'optimisation ont indiqué que les légumes et les fruits consommaient de grandes quantités d'eau d'irrigation pour augmenter leurs bénéfices économiques. En outre, il est nécessaire d'allouer une grande quantité d'eau d'irrigation au blé pour diminuer le coefficient de Gini et pour répondre aux contraintes de sécurité alimentaire, en particulier à des niveaux d'eau extrêmement bas. Par rapport à la gestion actuelle, la zone d'irrigation optimisée a diminué de 30%, l'indice de déficit hydrique des cultures a augmenté de 9%, les bénéfices économiques ont augmenté de 3% et le coefficient de Gini total des cultures a diminué de 17%, ce qui indique que l'approche d'optimisation pourrait distribuer de manière juste et raisonnable les ressources en eau d'irrigation. Notre recherche fournit une approche mathématique aux décideurs pour la planification des zones d'irrigation supplémentaires dans les régions agricoles pluviales. Rainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in rainfed agricultural regions. The approach incorporates multi‐objective linear programming, interval linear programming, fuzzy goal programming and stochastic expected value programming. In the proposed interval multi‐fuzzy goal stochastic expected‐value programming, uncertainties are expressed in the form of discrete intervals, probability distributions and fuzzy goals. This approach, which considers the randomness of precipitation during the optimization process and allocates limited irrigation water resources to different subareas and crops, was applied to a case study of crop irrigation area planning in Guyuan City, Ningxia Hui Autonomous Region, northwestern China. The maximum economic benefits and the minimum sum of the Gini coefficients among the different subareas and crops were regarded as the planning objectives, and a series of optimal irrigation areas with different crops and subareas under different water levels were obtained. The optimization results revealed that vegetables and fruits consumed large amounts of irrigation water to increase their economic benefits. In addition, allocating a large amount of irrigation water to wheat is essential to decrease the Gini coefficient and meet food security constraints, particularly at extremely low water levels. Compared with current management, the optimized irrigation area decreased by 30%, the crop water deficit index increased by 9%, the economic benefits increased by 3% and the total Gini coefficient of crops decreased by 17%, indicating that the optimization approach could fairly and reasonably allocate irrigation water resources. Our research provides a mathematical approach for decision‐makers to plan supplementary irrigation areas in rainfed agricultural regions. |
| Author | Guo, Wenzhong Shi, Rongchao Han, Xiaobei |
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| Notes | Funding information This research was financially supported by the Ningxia Hui Autonomous Region Key Research and Development Plan (2023BCF01047), Ningxia Academy of Agricultural and Forestry Sciences Foreign Scientific and Technological Cooperation Special Project (DW‐X‐2023001), Beijing Postdoctoral Research Foundation (2024‐ZZ‐083), Postdoctoral Research Fund of the Beijing Academy of Agriculture and Forestry Sciences (2023‐ZZ‐015) and Shandong Province Technology Innovation Guidance Plan (YDZX2023017). ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
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| Title | Uncertain multi‐objective programming approach for planning supplementary irrigation areas in rainfed agricultural regions |
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