Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests
In water resources management on a global scale, it is important to reconcile the conflicting interests of different regions and actors regarding water use. To solve this issue more effectively, an optimal allocation model of water resources that coordinates the interests of regional multi-level wat...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-03-01
|
| Series: | Frontiers in Environmental Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2023.1152296/full |
| _version_ | 1811158436095721472 |
|---|---|
| author | Shiwei Zhang Guohua Fang Dasheng Zhang Maosen Ju Huayu Zhong |
| author_facet | Shiwei Zhang Guohua Fang Dasheng Zhang Maosen Ju Huayu Zhong |
| author_sort | Shiwei Zhang |
| collection | DOAJ |
| description | In water resources management on a global scale, it is important to reconcile the conflicting interests of different regions and actors regarding water use. To solve this issue more effectively, an optimal allocation model of water resources that coordinates the interests of regional multi-level water resource managers and balances the benefits acquired by regional multi-level water resource managers was proposed. The model consisted of three components, including option generation, option selection, and fallback bargaining. The Hybrid Strategy Whale Optimization Algorithm (HSWOA) was created to generate the initial alternative set throughout the alternative generation process. In the alternative screening process, quick non-dominated sorting was used to choose Pareto alternatives from the initial alternative set. Through many rounds of negotiations, water resource managers at all levels reached a consensual water resource allocation plan during fallback bargaining. This model was used to reconcile the conflicting water interests of municipal and county water managers in Handan, China, in terms of economic, social, and ecological benefits. It was also compared with the Pareto solution set obtained from NSGA-III. In terms of convergence speed and accuracy, the results demonstrated that HSWOA outperformed the Whale Optimization Algorithm (WOA). The results show that several rounds of discussions between municipal and county water management eventually resulted in Nash equilibrium. In normal flow year, the recommended scheme could yield economic benefit of 315.08×108 Yuan, social benefit of 0.1700, and ecological benefit of 5.70 × 106 m3, whereas in low flow year, the recommended scheme could yield economic benefit of 354.85×108 Yuan, social benefit of 0.2103, and ecological benefit of 57.82 × 106 m3. Compared to existing studies, the recommended scheme has clear advantages in terms of social and ecological benefits. The proposed optimal water resource allocation was Pareto optimal. This paper presented a new way of thinking about reconciling the conflicting interests of different levels of water resource managers in the process of water allocation. |
| first_indexed | 2024-04-10T05:23:32Z |
| format | Article |
| id | doaj.art-53fbfa3e12d7476ab81d97cb83e43507 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-10T05:23:32Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-53fbfa3e12d7476ab81d97cb83e435072023-03-08T04:36:16ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2023-03-011110.3389/fenvs.2023.11522961152296Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interestsShiwei Zhang0Guohua Fang1Dasheng Zhang2Maosen Ju3Huayu Zhong4College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, ChinaHebei Institute of Water Science, Hebei, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, ChinaIn water resources management on a global scale, it is important to reconcile the conflicting interests of different regions and actors regarding water use. To solve this issue more effectively, an optimal allocation model of water resources that coordinates the interests of regional multi-level water resource managers and balances the benefits acquired by regional multi-level water resource managers was proposed. The model consisted of three components, including option generation, option selection, and fallback bargaining. The Hybrid Strategy Whale Optimization Algorithm (HSWOA) was created to generate the initial alternative set throughout the alternative generation process. In the alternative screening process, quick non-dominated sorting was used to choose Pareto alternatives from the initial alternative set. Through many rounds of negotiations, water resource managers at all levels reached a consensual water resource allocation plan during fallback bargaining. This model was used to reconcile the conflicting water interests of municipal and county water managers in Handan, China, in terms of economic, social, and ecological benefits. It was also compared with the Pareto solution set obtained from NSGA-III. In terms of convergence speed and accuracy, the results demonstrated that HSWOA outperformed the Whale Optimization Algorithm (WOA). The results show that several rounds of discussions between municipal and county water management eventually resulted in Nash equilibrium. In normal flow year, the recommended scheme could yield economic benefit of 315.08×108 Yuan, social benefit of 0.1700, and ecological benefit of 5.70 × 106 m3, whereas in low flow year, the recommended scheme could yield economic benefit of 354.85×108 Yuan, social benefit of 0.2103, and ecological benefit of 57.82 × 106 m3. Compared to existing studies, the recommended scheme has clear advantages in terms of social and ecological benefits. The proposed optimal water resource allocation was Pareto optimal. This paper presented a new way of thinking about reconciling the conflicting interests of different levels of water resource managers in the process of water allocation.https://www.frontiersin.org/articles/10.3389/fenvs.2023.1152296/fulloptimal allocation of water resourcesgame theorymulti-level water resources managerswhale optimization algorithm (WOA)fallback bargaining |
| spellingShingle | Shiwei Zhang Guohua Fang Dasheng Zhang Maosen Ju Huayu Zhong Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests Frontiers in Environmental Science optimal allocation of water resources game theory multi-level water resources managers whale optimization algorithm (WOA) fallback bargaining |
| title | Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests |
| title_full | Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests |
| title_fullStr | Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests |
| title_full_unstemmed | Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests |
| title_short | Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests |
| title_sort | water resources optimal allocation model for coordinating regional multi level water resources managers interests |
| topic | optimal allocation of water resources game theory multi-level water resources managers whale optimization algorithm (WOA) fallback bargaining |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2023.1152296/full |
| work_keys_str_mv | AT shiweizhang waterresourcesoptimalallocationmodelforcoordinatingregionalmultilevelwaterresourcesmanagersinterests AT guohuafang waterresourcesoptimalallocationmodelforcoordinatingregionalmultilevelwaterresourcesmanagersinterests AT dashengzhang waterresourcesoptimalallocationmodelforcoordinatingregionalmultilevelwaterresourcesmanagersinterests AT maosenju waterresourcesoptimalallocationmodelforcoordinatingregionalmultilevelwaterresourcesmanagersinterests AT huayuzhong waterresourcesoptimalallocationmodelforcoordinatingregionalmultilevelwaterresourcesmanagersinterests |