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http://dx.doi.org/10.3741/JKWRA.2009.42.10.773

Application of Rainfall Runoff Model with Rainfall Uncertainty  

Lee, Hyo-Sang (Dept. of Civil Eng., Chungbuk Nat. Univ)
Jeon, Min-Woo (Dept. of Civil Eng., Chungbuk Nat. Univ.)
Balin, Daniela (Institute of Geography, University of Lausanne)
Rode, Michael (Helmholtz Centre for Environmental Research-UFZ)
Publication Information
Journal of Korea Water Resources Association / v.42, no.10, 2009 , pp. 773-783 More about this Journal
Abstract
The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.
Keywords
Rainfall Runoff modelling; Uncertainty analysis; Prediction of streamflow; GLUE;
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Times Cited By KSCI : 3  (Citation Analysis)
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