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| Titel |
Combination of different types of ensembles for the adaptive simulation of probabilistic flood forecasts: hindcasts for the Mulde 2002 extreme event |
| VerfasserIn |
J. Dietrich, S. Trepte, Y. Wang, A. H. Schumann, F. Voß, F. B. Hesser, M. Denhard |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 2 ; Nr. 15, no. 2 (2008-03-19), S.275-286 |
| Datensatznummer |
250012615
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| Publikation (Nr.) |
 copernicus.org/npg-15-275-2008.pdf |
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| Zusammenfassung |
Flood forecasts are essential to issue reliable flood warnings and to
initiate flood control measures on time. The accuracy and the lead time of
the predictions for head waters primarily depend on the meteorological
forecasts. Ensemble forecasts are a means of framing the uncertainty of the
potential future development of the hydro-meteorological situation.
This contribution presents a flood management strategy based on
probabilistic hydrological forecasts driven by operational meteorological
ensemble prediction systems. The meteorological ensemble forecasts are
transformed into discharge ensemble forecasts by a rainfall-runoff model.
Exceedance probabilities for critical discharge values and probabilistic
maps of inundation areas can be computed and presented to decision makers.
These results can support decision makers in issuing flood alerts. The flood
management system integrates ensemble forecasts with different spatial
resolution and different lead times. The hydrological models are controlled
in an adaptive way, mainly depending on the lead time of the forecast, the
expected magnitude of the flood event and the availability of measured data.
The aforementioned flood forecast techniques have been applied to a case
study. The Mulde River Basin (South-Eastern Germany, Czech Republic) has
often been affected by severe flood events including local flash floods.
Hindcasts for the large scale extreme flood in August 2002 have been
computed using meteorological predictions from both the COSMO-LEPS ensemble
prediction system and the deterministic COSMO-DE local model. The temporal
evolution of a) the meteorological forecast uncertainty and b) the
probability of exceeding flood alert levels is discussed. Results from the
hindcast simulations demonstrate, that the systems would have predicted a
high probability of an extreme flood event, if they would already have been
operational in 2002. COSMO-LEPS showed a reasonably good performance within
a lead time of 2 to 3 days. Some of the deterministic very short-range
forecast initializations were able to predict the dynamics of the event, but
others underpredicted rainfall. Thus a lagged average ensemble approach is
suggested. The findings from the case study support the often proposed added
value of ensemble forecasts and their probabilistic evaluation for flood
management decisions. |
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