Effect of streamflow forecast uncertainty on real-time reservoir operation

Tongtiegang Zhao, Ximing Cai, Dawen Yang

Research output: Contribution to journalArticlepeer-review


Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (pseudo-PSF, pPSF), and ensemble or probabilistic streamflow forecast (denoted as real-PSF, rPSF). DSF represents forecast uncertainty in the form of deterministic forecast errors, pPSF a conditional distribution of forecast uncertainty for a given DSF, and rPSF a probabilistic uncertainty distribution. Compared to previous studies that treat the forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the dynamic evolution of uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. Through a hypothetical example of a single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases but the magnitude depends on the forecast products used. In general, the utility of the reservoir operation with rPSF is nearly as high as the utility obtained with a perfect forecast. Meanwhile, the utilities of DSF and pPSF are similar to each other but not as high as rPSF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, pPSF, and rPSF.

Original languageEnglish (US)
Pages (from-to)495-504
Number of pages10
JournalAdvances in Water Resources
Issue number4
StatePublished - Apr 2011


  • Deterministic streamflow forecast
  • Martingale Model of Forecast Evolution
  • Probabilistic streamflow forecast
  • Real-time reservoir operation
  • Streamflow forecast uncertainty

ASJC Scopus subject areas

  • Water Science and Technology


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