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A Conditional Value-at-Risk Based Inexact Water Allocation Model

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  • L. Shao
  • X. Qin
  • Y. Xu

Abstract

A conditional value-at-risk (CVaR) based inexact two-stage stochastic programming (CITSP) model was developed in this study for supporting water resources allocation problems under uncertainty. A CITSP model was formulated through incorporating a CVaR constraint into an inexact two-stage stochastic programming (ITSP) framework, and could be used to deal with uncertainties expressed as not only probability distributions but also discrete intervals. The measure of risks about the second-stage penalty cost was incorporated into the model, such that the trade-off between system economy and extreme expected loss could be analyzed. The developed model was applied to a water resources allocation problem involving a reservoir and three competing water users. The results indicated that the CITSP model performed better than the ITSP model in its capability of reflecting the economic loss from extreme events. Also, it could generate interval solutions within which the decision alternatives could be selected from a flexible decision space. Overall, the CITSP model was useful for reflecting the decision maker’s attitude toward risk aversion and could help seek cost-effective water resources management strategies under complex uncertainties. Copyright Springer Science+Business Media B.V. 2011

Suggested Citation

  • L. Shao & X. Qin & Y. Xu, 2011. "A Conditional Value-at-Risk Based Inexact Water Allocation Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2125-2145, July.
    • Handle: RePEc:spr:waterr:v:25:y:2011:i:9:p:2125-2145
    DOI: 10.1007/s11269-011-9799-9
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    References listed on IDEAS

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    Cited by:

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    2. Pingale, Santosh M. & Jat, Mahesh K. & Khare, Deepak, 2014. "Integrated urban water management modelling under climate change scenarios," Resources, Conservation & Recycling, Elsevier, vol. 83(C), pages 176-189.
    3. Maryam Soltani & Reza Kerachian & Mohammad Nikoo & Hamideh Noory, 2016. "A Conditional Value at Risk-Based Model for Planning Agricultural Water and Return Flow Allocation in River Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 427-443, January.
    4. Zhang, W.J. & Tan, Q. & Zhang, T.Y., 2021. "A risk-averse stochastic quadratic model with recourse for supporting irrigation water management in uncertain and nonlinear environments," Agricultural Water Management, Elsevier, vol. 244(C).
    5. Maryam Soltani & Reza Kerachian & Mohammad Reza Nikoo & Hamideh Noory, 2016. "A Conditional Value at Risk-Based Model for Planning Agricultural Water and Return Flow Allocation in River Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 427-443, January.
    6. Weini Zhang & Hamed Rahimian & Güzin Bayraksan, 2016. "Decomposition Algorithms for Risk-Averse Multistage Stochastic Programs with Application to Water Allocation under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 385-404, August.
    7. Bin Xu & Ping-an Zhong & Yenan Wu & Fangming Fu & Yuting Chen & Yunfa Zhao, 2017. "A Multiobjective Stochastic Programming Model for Hydropower Hedging Operations under Inexact Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4649-4667, November.

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