The objectives of flood control, power generation, water supply and ecology for reservoir operation are neither completely coordinated nor completely opposed, and its optimal operation and decision-making is very complicated. This study proposed a method of multi-objective optimization and multi-attribute decision making for reservoir operation (MODRO). The correlation analysis method was used to analyze the competitive relationship among the extracted objectives, and the multi-objective optimal operation model was constructed. The NSGA-II-SEABODE algorithm was applied to solve the MODRO problem. The objective extraction, model construction, optimization solution and scheme selection were coupled to form a multi-objective optimization and multi-attribute decision making method with the whole process of “Objective-Modeling-Optimization-Selection”. Huangjinxia Reservoir, which is located in Shaanxi, China, was selected as the case study. The results show that: (1) Quantifying the degree of conflict among objectives makes the construction of the multi-objective optimal operation model more reasonable. (2) The NSGA-II-SEABODE algorithm are used to obtain the decision-making scheme, which provides decision-making basis for managers. (3) For Huangjinxia Reservoir, water diversion is negatively related to power generation and ecology, and power generation is positively related to ecology. The results can promote the efficient utilization of water resources, improve the comprehensive benefits of reservoirs, and provide decision-making support for actual reservoir operation.

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A Method of Multi-Objective Optimization and Multi-Attribute Decision-Making for Huangjinxia Reservoir

A Model Coupling Water Resource Allocation and Canal Optimization for Water Distribution

In traditional ecological operation, it is difficult to coordinate the balance among the interests of stakeholders, and stakeholders find it difficult to accept the operation scheme. To address these problems, this study proposed a method of multi-stakeholder coordinated operation of reservoir (MSCOR). By comprehensively considering the interest demands of stakeholders, the multi-stakeholder interval coordination mechanism (MSICM) for reservoir operation was established. The multi-stakeholder coordinated operation model (MSCOM) was constructed. The multi-stakeholder solution algorithm based on the MSICM, the non-dominated sorting genetic algorithm II, and the approach of successive elimination of alternative schemes based on the k-order and p-degree of efficiency (MSIC-NSGA-II-SEABODE) were applied to solve the MSCOR problem. The coordination mechanism, model construction, multi-stakeholder optimization, and multi-attribute decision making were coupled to establish a multi-stakeholder coordinated operation method, comprising the whole process of mechanism–modeling–optimization–decision making. Taking Baojixia Reservoir as an example, the performance of the coordinated operation method was compared with that of the traditional optimal operation method, and the relationship between the irrigation benefits and ecological benefits of the reservoir was explored. The results show that: (1) On the premise of the same satisfaction degree of basic irrigation interests, the ecological AAPFD value of coordinated operation decreased by 0.184, 0.469, and 0.886 in a normal year, dry year, and extraordinary dry year, respectively. The effect of coordinated operation on balancing various stakeholders was more obvious with the decrease in water inflow. (2) The MSICM ensures that the multi-stakeholder operation of the reservoir conforms to the principles of comprehensiveness, balance, and sustainability. (3) The coordination scheme obtained by the MSIC-NSGA-II-SEABODE algorithm is more reasonable and feasible. The research results provide a new idea and method to address the MSCOR problem.

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Multi-Stakeholder Coordinated Operation of Reservoir Considering Irrigation and Ecology

Copula-based analysis of socio-economic impact on water quantity and quality: A case study of Yitong River, China.

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.

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Water resources optimal allocation model for coordinating regional multi-level water resources managers’ interests

A Copula-based interval linear programming model for water resources allocation under uncertainty.

China plays an important role in the international trade of agricultural commodities. Considering the dynamic reactive nitrogen (Nr) losses of agricultural systems in China, a hypothesis was proposed that crop conversion in China would be correlated with the extent of crop trade, influencing Nr losses in agricultural systems. The objective of this study was to verify the hypothesis based on a hybrid approach, which incorporated life cycle analysis (LCA), copula–Markov chain Monte Carlo (MCMC) simulation, and copula sampling. The approach was proven to be of benefit in (a) evaluating Nr losses in crop planting based on a LCA framework, (b) identifying dependencies and co-movements of the correlated variables in planting structures and crop trade using copula–MCMC simulations, and (c) recognizing fluctuations in Nr losses of crop planting in the future using copula-based sampling method. The planting structures and international trade of four types of crops (i.e. wheat, soybeans, maize, and rice) in 20 provinces of China indicated significant correlations, thus supporting the initial hypothesis. With the improvement of self-sufficiency in crop production, especially soybeans, Nr losses from the crop production of China in 2025 and 2030 would decrease by 8.43% and 4.26%, compared with those in 2018 (i.e. 1916.74 kt N).

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Gaseous reactive nitrogen losses of agricultural systems in China influenced by crop trade

Based on a grey water footprint method, NPS pollution in the urban agglomeration of Shenzhen, Dongguan and Huizhou was evaluated in this research. The results showed that the NPS pollution level in this urban agglomeration decreased from 1995 to 2019. The grey water footprint of NPS pollution in the cities of Shenzhen, Dongguan and Huizhou had similar variation characteristic, which showed a trend of first increasing, then decreasing, and finally increasing during the research period. The largest source of grey water footprint of NPS pollution was land use, followed by livestock and poultry breeding. The water pollution level of NPS pollution was highest in Shenzhen and lowest in Huizhou, which was in the same order as gross domestic product (GDP) in this agglomeration. Thus, city governments should attach more importance to prevention and control of NPS pollution in the process of economic development, especially for land use source.

https://doi.org/10.1088/1755-1315/1011/1/012038

Evaluation of non-point source pollution based on grey water footprint method: A case study in the urban agglomeration of Shenzhen, Dongguan and Huizhou

Shujie Yu

Papers

A Copula-based interval linear programming model for water resources allocation under uncertainty.

Gaseous reactive nitrogen losses of agricultural systems in China influenced by crop trade

Evaluation of non-point source pollution based on grey water footprint method: A case study in the urban agglomeration of Shenzhen, Dongguan and Huizhou