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http://dx.doi.org/10.3741/JKWRA.2018.51.6.523

Uncertainty assessment of ensemble streamflow prediction method  

Kim, Seon-Ho (Department of Civil and Environmental Engineering, Sejong University)
Kang, Shin-Uk (National Drought Information Analysis Center, Korea Water Resources Cooperation)
Bae, Deg-Hyo (Department of Civil and Environmental Engineering, Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.6, 2018 , pp. 523-533 More about this Journal
Abstract
The objective of this study is to analyze uncertainties of ensemble-based streamflow prediction method for model parameters and input data. ESP (Ensemble Streamflow Prediction) and BAYES-ESP (Bayesian-ESP) based on ABCD rainfall-runoff model were selected as streamflow prediction method. GLUE (Generalized Likelihood Uncertainty Estimation) was applied for the analysis of parameter uncertainty. The analysis of input uncertainty was performed according to the duration of meteorological scenarios for ESP. The result showed that parameter uncertainty was much more significant than input uncertainty for the ensemble-based streamflow prediction. It also indicated that the duration of observed meteorological data was appropriate to using more than 20 years. And the BAYES-ESP was effective to reduce uncertainty of ESP method. It is concluded that this analysis is meaningful for elaborating characteristics of ESP method and error factors of ensemble-based streamflow prediction method.
Keywords
Dam inflow prediction; Ensemble-based streamflow prediction; GLUE method; Uncertainty assessment;
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Times Cited By KSCI : 8  (Citation Analysis)
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