Water Resources Management

, Volume 32, Issue 12, pp 3919–3934 | Cite as

Optimization of Run-of-River Hydropower Plant Design under Climate Change Conditions

  • Parisa Sarzaeim
  • Omid Bozorg-HaddadEmail author
  • Babak Zolghadr-Asli
  • Elahe Fallah-Mehdipour
  • Hugo A. Loáiciga


The assessment of climate change and its impacts on hydropower generation is a complex issue. This paper evaluates the application of representative concentration pathways (RCPs, 2.6, 4.5, and 8.5) with the change factor (CF) method and the statistical downscaling method (SDSM) to generate six climatic scenarios of monthly temperature and rainfall over the period 2020–2049 in the Karkheh basin, Iran. The identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) model was employed to simulate runoff for the purpose of designing a run-of-river hydropower plant in the Karkheh basin. The non-dominated sorting genetic algorithm (NSGA)-II was employed to maximize yearly energy generation and the plant factor, simultaneously. Results indicate the runoff scenarios associated with the SDSM lead to higher run-of-river hydropower generation in 2020–2049 compared to the CF results.


Climate change Design Run-of-river Uncertainty RCP Change factor Statistical downscaling model NSGA-II 



Authors thank Iran’s National Elites Foundation for financial support of this research.

Compliance with Ethical Standards

Conflict of Interests



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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Parisa Sarzaeim
    • 1
  • Omid Bozorg-Haddad
    • 1
    Email author
  • Babak Zolghadr-Asli
    • 1
  • Elahe Fallah-Mehdipour
    • 1
    • 2
  • Hugo A. Loáiciga
    • 3
  1. 1.Department of Irrigation & Reclamation Engineering, Faculty of Agriculture Engineering & Technology, College of Agriculture & Natural ResourcesUniversity of TehranKarajIran
  2. 2.National Elites FoundationTehranIran
  3. 3.Department of GeographyUniversity of CaliforniaSanta BarbaraUSA

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