Evaluation Criteria and Model for Risk Between Water Supply and Water Demand and its Application in Beijing

Qian, Longxia; Wang, Hongrui; Zhang, Keni

doi:10.1007/s11269-014-0624-0

Cited by 27 publications

(30 citation statements)

References 24 publications

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“…entropy principle [61][62][63] and Markov chain [64,65] can also be introduced into the study framework to solve the stochastic features of risk analysis in the WRS. The Bayesian method has been used to analyze atmosphere-ocean global circulation models under uncertainty, and further analyze the water demand-consumption risk by Monte Carlo stochastic simulation [59] .…”

Section: Optimization Models Objective Functions Constraints Referencesmentioning

confidence: 99%

Risk analysis methods of the water resources system under uncertainty

Gui¹,

Zhang²,

Li³

et al. 2015

Front. Agr. Sci. Eng.

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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.

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Section: Optimization Models Objective Functions Constraints Referencesmentioning

confidence: 99%

Risk analysis methods of the water resources system under uncertainty

Gui¹,

Zhang²,

Li³

et al. 2015

Front. Agr. Sci. Eng.

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“…The challenge of economic development and water shortage in this region has received on-going concern [1][2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Industrial Structure and Water Use in Beijing-Tianjin-Hebei Region: A Multiplier Analysis

Lin¹,

Sha²,

Jiang³

et al. 2017

dtem

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Abstract. This study investigates the regional economic structure of Beijing-Tianjin-Hebei region with focus on the impacts of water resources on the regional economic development. The multiplier model is used to analyze the effects of the regional water sector on the other accounts. The results show that 1) the regional water sector has limited effects on the regional economic output and on the other sectors, and 2) the region has a relatively reasonable economic structure regarding water use, but 3) the structure shows a labor-and capital-intensive economic feature rather than technology intensive feature. The policy implication is that the integration efforts in Beijing-Tianjin-Hebei region, which aimed at alleviating water scarcity stress and increasing regional sustainability, should concentrate on industrial structure adjustment towards technology advance.

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“…In fact, measuring potential water-supply problems caused by droughts needs to jointly consider severity and spatial extension of droughts, water use relative to reliable water supply, and drought-resistant measures, which few studies are devoted to [8][9][10][11]. Furthermore, most of the risk indices established in such studies are based on the evaluation indices proposed by Hashimoto, but these indices reflect the performance of the water resources system, and the nature of risk is not taken into account [12,13]. Therefore, a suitable performance index is necessary to quantify the characteristics of water scarcity induced by drought.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of drought-induced water scarcity in upper and middle reaches of Xiu River

Liu

2017

IOP Conf. Ser.: Earth Environ. Sci.

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Evaluation Criteria and Model for Risk Between Water Supply and Water Demand and its Application in Beijing

Cited by 27 publications

References 24 publications

Risk analysis methods of the water resources system under uncertainty

Risk analysis methods of the water resources system under uncertainty

Industrial Structure and Water Use in Beijing-Tianjin-Hebei Region: A Multiplier Analysis

Risk assessment of drought-induced water scarcity in upper and middle reaches of Xiu River

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