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A two-stage fuzzy chance-constrained water management model

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Abstract

In this study, an inexact two-stage fuzzy gradient chance-constrained programming (ITSFGP) method is developed and applied to the water resources management in the Heshui River Basin, Jiangxi Province, China. The optimization model is established by incorporating interval programming, two-stage stochastic programming, and fuzzy gradient chance-constrained programming within an optimization framework. The hybrid model can address uncertainties represented as fuzzy sets, probability distributions, and interval numbers. It can effectively tackle the interactions between pre-regulated economic targets and the associated environmental penalties attributed to water allocation schemes and reflect the tradeoffs between economic revenues and system-failure risk. Furthermore, uncertainties associated with the decision makers’ preferences are considered in decision-making processes. The obtained results can provide decision support for the local sustainable economic development and water resources allocation strategies under multiple uncertainties.

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Acknowledgements

This research was supported by the Natural Science and Engineering Research Council of Canada. The authors are thankful to the editor and anonymous reviewers for their insightful comments, which have significantly contributed to improving the manuscript.

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Authors and Affiliations

  1. Faculty of Engineering and Applied Science, University of Regina, Regina, SK, S4S 0A2, Canada

    Jiaxuan Xu, Guohe Huang & Jiapei Chen

  2. Department of Civil Engineering, McMaster University, Hamilton, ON, L8S 4L8, Canada

    Zoe Li

Authors
  1. Jiaxuan Xu
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  2. Guohe Huang
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  3. Zoe Li
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  4. Jiapei Chen
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Correspondence to Guohe Huang.

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Responsible editor: Marcus Schulz

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Xu, J., Huang, G., Li, Z. et al. A two-stage fuzzy chance-constrained water management model. Environ Sci Pollut Res 24, 12437–12454 (2017). https://doi.org/10.1007/s11356-017-8725-y

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  • DOI: https://doi.org/10.1007/s11356-017-8725-y

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