Stochastic Optimization Models for Risk-Based Reservoir Management*

  • Yu. ErmolievEmail author
  • T. Ermolieva
  • T. Kahil
  • M. Obersteiner
  • V. Gorbachuk
  • P. Knopov


The paper provides an overview of publications on reservoir management and formulates a novel stochastic dynamic optimization model for water balance management in the area affected. The proposed stochastic optimization approach allows multiple key performance indicators such as agriculture and energy production, wetland water and flood protection, biodiversity preservation, and reservoir storage. The two-stage feature of the proposed model induces safety constraints on water supply known as chance conditions in stochastic optimization: safety constraints in nuclear energy, stability constraints in insurance business, or constraints on the Conditional Value-at-Risk (CVaR) in finance. The original nonlinear, nonconvex and often discontinuous model can be reduced to linear programming problems.


stochastic optimization risk water resource management two-stage problem extreme events 


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Yu. Ermoliev
    • 1
    Email author
  • T. Ermolieva
    • 1
  • T. Kahil
    • 1
  • M. Obersteiner
    • 1
  • V. Gorbachuk
    • 2
  • P. Knopov
    • 2
  1. 1.International Institute for Applied Systems AnalysisLaxenburgAustria
  2. 2.V. M. Glushkov Institute of CyberneticsNational Academy of Sciences of UkraineKyivUkraine

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