Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 117-122 |
| Seitenumfang | 6 |
| Fachzeitschrift | Advances in Geosciences |
| Jahrgang | 11 |
| Publikationsstatus | Veröffentlicht - 2007 |
| Extern publiziert | Ja |
Abstract
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.
ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Erdkunde und Planetologie (sonstige)
- Erdkunde und Planetologie (insg.)
- Astronomie und Planetologie
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in: Advances in Geosciences, Jahrgang 11, 2007, S. 117-122.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Identifying and reducing model structure uncertainty based on analysis of parameter interaction
AU - Wang, Y.
AU - Dietrich, J.
AU - Voss, F.
AU - Pahlow, M.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34250736903&partnerID=8YFLogxK
U2 - 10.5194/adgeo-11-117-2007
DO - 10.5194/adgeo-11-117-2007
M3 - Article
AN - SCOPUS:34250736903
VL - 11
SP - 117
EP - 122
JO - Advances in Geosciences
JF - Advances in Geosciences
SN - 1680-7340
ER -