Allocation of fresh water recourses in China with nested probabilistic-numerical linguistic information in multi-objective optimization

doi:10.1016/j.knosys.2019.105014

Knowledge-Based Systems

Volume 188, 5 January 2020, 105014

https://doi.org/10.1016/j.knosys.2019.105014 Get rights and content

Abstract

Fresh water resources are made of conventional water resources (CWRs) and unconventional water resources (UWRs), and they are one of the important natural resources that cannot be replaced. The purpose of this paper is to predict and allocate China’s fresh water resources in 2025 under complex environment. According to historical data, we first conduct data reprocessing including data collection, data prediction and discussion. In order to achieve an appropriate tradeoff between ecological environment and economic development, a multi-objective optimization model is constructed based on market mechanism. Specifically, we establish two objective functions: one is to minimize the total cost, the other is to minimize the whole amount of CWRs, and then, we optimize the parameters in the model based on nested probabilistic-numerical linguistic information. After that, the solution and the strategy of fresh water resources are obtained, and the sustainable development and risk response by adjusting and adding the parameters are further analyzed. The results show that the model is effective, feasible and applicable. Finally, we make some discussions about the strengths and weakness of the model, and the suggestions for the fresh water resources in China.

Introduction

Fresh water resources are divided into two categories that are the conventional water resources (CWRs) and the unconventional water resources (UWRs) [1]. The UWRs differ from the CWRs due to its circular utilization. The CWRs contain surface water, ground water and other water sources, while the UWRs mainly consist of rainwater, brackish water, recycled water, salt water and seawater. Fresh water almost covers every aspect of human activities such as agriculture, industry, daily life and ecology. Nowadays, Fresh water resource is the limiting constraint for development in much of the world, especially in China. The per capita fresh water resource of this country is only 2200 m $^{3}$ , which is only 1/4 of the world average level. Although China is rich in water resources, it is still one of the countries short of fresh water [2], [3], [4], [5], [6]. This is mainly caused by the following four aspects: (1) The geographical distribution of fresh water resource is uneven, as well as precipitation and surface runoff. (2) The heavy losses of soil erosion affect water resources and sustainable development, especially in the upper reaches of the Yellow River and the southwest mountains. (3) Serious pollution results in fresh water resource shortage in the south of China despite of the seemingly abundant water resources. (4) The groundwater level drops sharply, which leads to the deterioration of the ecological environment. Therefore, in order to satisfy the requirement of sustainable economic development, it is necessary to study the rational allocation and management of fresh water resources [7].

Over the years, some approaches have been developed for water allocation, such as game theory [8], analytical methods [9], [10] and multi-objective optimization models [11], [12], [13]. Especially, multi-objective optimization models are popular in dealing with such a problem, because water allocation is a multidimensional task with several objectives to a certain extent. To be specific, models are used to maximize the benefit or production of allocated water to agriculture, domestic industry, and hydropower. Considering economic, environmental, and social factors [14], the goals are to minimize water shortage, sewage drainage, and amounts of polluted water [15], [16] by using linear, non-linear, dynamic and optimization methods [17]. Therefore, multi-objective optimization models can work out physically, economically, and socially feasible allocation schemes from the perspective of the whole region. However, there are great uncertainties about parameters in the multi-objective models during the evaluation process, and many factors should be considered including qualitative information and quantitative information in complex circumstances. For example, when evaluating the parameter “cost”, the qualitative information may be taken into account, such as “climate”, “geographic feature”, and “geomorphic feature”, meanwhile, the quantitative information may also be considered, such as “distance” and “flow”. Therefore, it is a challenge for managers to determine appropriate parameters according to multiple and different situations, and many existing researches almost assume that some parameters are constants.

Since there are uncertainties about parameters in the multi-objective model, we use the nested probabilistic-numerical linguistic term sets (NPNLTSs) [18] to optimize the parameters. Compared with other popular linguistic sets [19], [20], [21], [22], such as hesitant fuzzy linguistic term sets (HFLTSs) [23] and probabilistic linguistic term sets (PLTSs) [24], the NPNLTS is a different and more powerful tool to fully represent people’s preferences. Besides, the distance and similarity measures of NPNLTSs have been proposed [25], and an optimization problem about maneuvering target tracking has been solved with the nested probabilistic-numerical linguistic information [26]. In this paper, we optimize the allocation of the limited fresh water resources and establish the multi-objective model based on market mechanism. The most important factor for establishing the market mechanism is to set up a reasonable price system. Therefore, the price of public resources has to face a dilemma: Market-oriented price can guarantee the supplier’s profit, while it may cause the relative lack of supply and excessive demands. Moreover, a part of demands may not be satisfied and social welfare may be lost. On the other hand, if the price of fresh water resources is regulated by the government, it may lead to some negative effects such as the low price of fresh water resources, the meager profits of manufacturer, the overuse of the resource and the resource depletion.

In this paper, our work mainly focuses on three aspects: (1) How to establish reasonably multi-objective optimization model. (2) How to comprehensively optimize parameters in the model. (3) How to allocate fresh water resources in China to satisfy the predicted demands in 2025. Since it is a complex and practical problem, data preprocessing is necessary for scholars to collect data and predict data. Moreover, it is useful and valuable to establish the multi-objective model based on market mechanism, because objective functions aim at the cost and the amount of water resources, while constraint conditions focus on demand and supply of various water resources in practice. Additionally, NPNLTSs are used to optimize the parameters in the model because of their superiorities in group decision making. Based on which, we obtain the solution and the strategy, and provide some suggestions, including the sustainable development and risk response with the parameters. Fig. 1 shows the main idea of this paper in detail.

The main contributions of the paper can be summarized as follows: (1) A multi-objective optimization model is constructed based on market mechanism which has two objective functions: One is to minimize the total cost, and the other is to minimize the whole amount of CWRs. (2) Considering qualitative information and quantitative information in complex evaluation environment, we optimize the parameters in the multi-objective model based on nested probabilistic-numerical linguistic information. (3) A strategy of fresh water resource is proposed to meet the predicted demands of China in 2025 by comparing predicted data with the current conditions of each region and considering the costs. The proposed model can provide technical support for water allocation, and it is effective, feasible and cost-efficient to meet the predicted demands of China.

To do so, the paper is organized as follows: Section 2 presents the assumptions and notations. In Section 3, we give the methodologies including data preprocessing, establishing multi-objective model and optimizing parameters. Section 4 focuses on the solution and gives the strategy of fresh water resources due to the results. In Section 5, we discuss the sustainable development and risk response about the utilization of fresh water resources. Section 6 ends the paper with some conclusions, concerning strengths, weakness and suggestions.

Section snippets

Assumptions and notations

For convenience and simplicity of the future discussions, some basic assumptions and the main notations are listed as follows:

Methodology

In order to utilize fresh water resources rationally and increase effective supply, we first conduct data preprocessing including data collection and data prediction, and then establish a multi-objective optimization model considering the minimum cost and the minimum amount of CWRs. Furthermore, some parameters in the model are optimized by using nested probabilistic-numerical linguistic information.

Solution and results

In this section, we solve the model with the optimized parameters, and give the strategy of fresh water resources according to the results.

Sustainable development and risk response

With the development of economic society, it is necessary to develop the reasonable and sustainable utilization of fresh water resources to protect our environment. The key point is to find the tradeoff between ecological and economic development. In this section, we discuss the sustainable development and risk response according to the proposed models.

Conclusions

Our method is based on strict mathematical model, which is able to obtain an appropriate tradeoff between ecological environment and economic development. The strategy is a synthesis of the optimization results and the practical situations. Therefore, it is effective, feasible and cost-efficient to meet the predicted demands of China in 2025. Next, we mainly discuss the strengths and weakness of the proposed model, and further give the suggestions according to the results.

Acknowledgment

The work was supported by the National Natural Science Foundation of China (Nos. 71571123, 71771155 and 71801174).

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^☆: No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to https://doi.org/10.1016/j.knosys.2019.105014.

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Allocation of fresh water recourses in China with nested probabilistic-numerical linguistic information in multi-objective optimization☆

Abstract

Introduction

Section snippets

Assumptions and notations

Methodology

Solution and results

Sustainable development and risk response

Conclusions

Acknowledgment

Renew. Sustain. Energy Rev.

J. Hydrol.

J. Environ. Manag.

Knowl.-Based Syst.

Knowl.-Based Syst.

Inform. Sci.

Inform. Sci.

Tectonophysics

J. Statist. Plann. Inference

Ocean Eng.

Appl. Math. Comput.

Knowl.-Based Syst.

Comput. Ind. Eng.

A critical review of the risks to water resources from unconventional shale gas development and hydraulic fracturing in the United States

Environ. Sci. Technol.

National Hydrometeorological Information, China

Water resources management under uncertainty: factorial multi-stage stochastic program with chance constraints

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