| Autor: |
Michael Rode, Min-Woo Jeon, Hyosang Lee, Daniela Balin |
| Rok vydání: |
2009 |
| Předmět: |
|
| Zdroj: |
Journal of Korea Water Resources Association. 42:773-783 |
| ISSN: |
1226-6280 |
| DOI: |
10.3741/jkwra.2009.42.10.773 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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