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| Titel |
Identifying and reducing model structure uncertainty based on analysis of parameter interaction |
| VerfasserIn |
Y. Wang, J. Dietrich, F. Voß, M. Pahlow |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: Large-scale hydrological modelling and the European Union water policies ; Nr. 11 (2007-06-20), S.117-122 |
| Datensatznummer |
250009018
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| Publikation (Nr.) |
 copernicus.org/adgeo-11-117-2007.pdf |
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| Zusammenfassung |
| Multi-objective optimization algorithms are widely used
for the calibration of conceptual hydrological models. Such algorithms yield
a set of Pareto-optimal solutions, reflecting the model structure
uncertainty. In this study, a multi-objective optimization strategy is
suggested, which aims at reducing the model structure uncertainty by
considering parameter interaction within Pareto-optimal solutions. The
approach has been used to develop a nested setup of a rainfall-runoff model,
which is integrated in a probabilistic meso-/macroscale flood forecasting
system. The optimization strategy aided in determining the best combination
of a lumped (computationally efficient in operational real time forecasting)
and a semi-distributed parameterization of the hydrological model. First
results are shown for two subbasins of the Mulde catchment in Germany. The
different phenomena of parameter interaction were analysed in this case
study to reduce the model structure uncertainties. |
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