“…For example, the Monte Carlo stochastic simulation method has been used to generate 10000 sets of risk factors to solve the multi-objective risk analysis model of water resources optimization allocation, and the fundamental target of sustainable utilization of water resources was realized [57,58] . The Bayesian principle [59,60] , the maximum Table 2 The risk optimization models of the WRS…”
The main characteristic of the water resources system (WRS) is its great complexity and uncertainty, which makes it highly desirable to carry out a risk analysis of the WRS. The natural environmental, social economic conditions as well as limitations of human cognitive ability are possible sources of the uncertainties that need to be taken into account in the risk analysis process. In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS are discussed first, from both objective and subjective perspectives. Then the quantitative characterization methods of risk analysis are introduced, including three criteria (reliability, resiliency and vulnerability) and five basic optimization models (the expected risk value model, conditional value at risk model, chance-constrained risk model, minimizing probability of risk events model, and the multi-objective optimization model). Finally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized as random, fuzzy and mixed methods. A more comprehensive risk analysis methodology for the WRS is proposed based on the comparison of the advantages, disadvantages and applicable conditions of these three methods. This paper provides a decision support of risk analysis for researchers, policy makers and stakeholders of the WRS.
“…For example, the Monte Carlo stochastic simulation method has been used to generate 10000 sets of risk factors to solve the multi-objective risk analysis model of water resources optimization allocation, and the fundamental target of sustainable utilization of water resources was realized [57,58] . The Bayesian principle [59,60] , the maximum Table 2 The risk optimization models of the WRS…”
The main characteristic of the water resources system (WRS) is its great complexity and uncertainty, which makes it highly desirable to carry out a risk analysis of the WRS. The natural environmental, social economic conditions as well as limitations of human cognitive ability are possible sources of the uncertainties that need to be taken into account in the risk analysis process. In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS are discussed first, from both objective and subjective perspectives. Then the quantitative characterization methods of risk analysis are introduced, including three criteria (reliability, resiliency and vulnerability) and five basic optimization models (the expected risk value model, conditional value at risk model, chance-constrained risk model, minimizing probability of risk events model, and the multi-objective optimization model). Finally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized as random, fuzzy and mixed methods. A more comprehensive risk analysis methodology for the WRS is proposed based on the comparison of the advantages, disadvantages and applicable conditions of these three methods. This paper provides a decision support of risk analysis for researchers, policy makers and stakeholders of the WRS.
“…It is the largest inter-basin transfer scheme in the world; therefore, it is often taken as an example of inter-basin transfers and has been intensively studied in terms of the ecological and environmental consequences since it was proposed [12,13,[29][30][31][32][33][34]. (Figure 1).…”
Inter-basin water transfer projects are designed to relieve water scarcity around the world. However, ecological problems relating to reductions in protection zone functions can occur during inter-basin transfers. This paper uses the largest inter-basin water transfer project in the world, namely, the South-to-North Water Transfer Project (SNWTP) in China, as an example to analyze the variation of Miyun Reservoir's inner protection zone functions when water is transferred. Specifically, a riparian model (RIPAM) coupled with remote sensing data were used to calculate the nitrogen (N) and phosphorus (P) losses due to plant uptake, and these results were validated by in situ survey data. Then, correlations between water levels and N and P removal were analyzed. The results show that water table disturbances resulting from elevated water levels strongly influence the growth of plants and have obvious negative impacts on N and P removal in the inner protection zone. With the implementation of the middle route of the SNWTP, the water level of Miyun will rise to 150 m in 2020, and subsequently, the total net primary productivity (NPP) could decline by more than 40.90% from the level in 2015, while the N and P uptake could decline by more than 53.03% and 43.49%, respectively, from the levels in 2015, according to the modeling results. This will lead to declines in the inner protection zone's defense effectiveness for N and P interception and increases in risks to the security of water resources. The results of this study provide useful knowledge for managing the defense function of the terminal reservoir's inner protection zone and for ensuring that water quality is maintained during the diversion process.
“…Zhang [13] pointed out that water withdrawals due to the MR-SNWTP represent 35% of flow at the point source. Gu et al [36] found that, in order to reduce the risks of water deficits in the MR-SNWTP source areas, an additional water transfer project should be built, moving at least 100 m 3 /s to the Han River from the Yangtze River.…”
China's South-North Water Transfer Project (SNWTP) has the potential to transfer as much as 44.8 km 3 year −1 of water from the Yangtze River basin to the Yellow River basin. However, the SNWTP has not been assessed from a sustainability perspective. Thus, in this study we evaluated the SNWTP's economic, social, and environmental impacts by reviewing the English literature published in journals that are part of the Web of Science database. We then synthesized this literature using a Triple Bottom Line framework of sustainability assessment. Our study has led to three main findings: (1) whether the SNWTP is economically beneficial depends largely on model assumptions, meaning that economic gains at the regional and national level are uncertain; (2) the SNWTP requires the resettlement of hundreds of thousands of people and challenges existing water management institutions, suggesting possible social concerns beyond the short term; and (3) evidently large environmental costs in water-providing areas and uncertain environmental benefits in water-receiving areas together point to an uncertain environmental future for the geographic regions involved. Thus, the overall sustainability of SNWTP is seriously questionable. Although much work has been done studying individual aspects of SNWTP's sustainability, few studies have utilized the multi-scale, transdisciplinary approaches that such a project demands. To minimize environmental risks, ensure social equity, and sustain economic benefits, we suggest that the project be continuously monitored in all three dimensions, and that integrated sustainability assessments and policy improvements be carried out periodically.
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