Environmental Science and Pollution Research

, Volume 24, Issue 13, pp 12437–12454 | Cite as

A two-stage fuzzy chance-constrained water management model

  • Jiaxuan Xu
  • Guohe HuangEmail author
  • Zoe Li
  • Jiapei Chen
Research Article


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.


Fuzzy gradient Chance-constrained programming Stochastic programming Optimization modeling Water resources management Uncertainty 



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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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Faculty of Engineering and Applied ScienceUniversity of ReginaReginaCanada
  2. 2.Department of Civil EngineeringMcMaster UniversityHamiltonCanada

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