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| Titel |
Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall–snowmelt flood regimes |
| VerfasserIn |
D. Lawrence, E. Paquet, J. Gailhard, A. K. Fleig |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 14, no. 5 ; Nr. 14, no. 5 (2014-05-23), S.1283-1298 |
| Datensatznummer |
250118448
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| Publikation (Nr.) |
 copernicus.org/nhess-14-1283-2014.pdf |
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| Zusammenfassung |
| Simulation methods for extreme flood estimation represent an important
complement to statistical flood frequency analysis because a spectrum of
catchment conditions potentially leading to extreme flows can be assessed. In
this paper, stochastic, semi-continuous simulation is used to estimate
extreme floods in three catchments located in Norway, all of which are
characterised by flood regimes in which snowmelt often has a significant
role. The simulations are based on SCHADEX, which couples a precipitation
probabilistic model with a hydrological simulation such that an exhaustive
set of catchment conditions and responses is simulated. The precipitation
probabilistic model is conditioned by regional weather patterns, and a
bottom–up classification procedure was used to define a set of weather
patterns producing extreme precipitation in Norway. SCHADEX estimates for the
1000-year (Q1000) discharge are compared with those of several standard
methods, including event-based and long-term simulations which use a single
extreme precipitation sequence as input to a hydrological model, statistical
flood frequency analysis based on the annual maximum series, and the GRADEX
method. The comparison suggests that the combination of a precipitation
probabilistic model with a long-term simulation of catchment conditions,
including snowmelt, produces estimates for given return periods which are
more in line with those based on statistical flood frequency analysis, as
compared with the standard simulation methods, in two of the catchments. In
the third case, the SCHADEX method gives higher estimates than statistical
flood frequency analysis and further suggests that the seasonality of the
most likely Q1000 events differs from that of the annual maximum flows. The
semi-continuous stochastic simulation method highlights the importance of
considering the joint probability of extreme precipitation, snowmelt rates
and catchment saturation states when assigning return periods to floods
estimated by precipitation-runoff methods. The SCHADEX methodology, as
applied here, is dependent on observed discharge data for calibration of a
hydrological model, and further study to extend its application to ungauged
catchments would significantly enhance its versatility. |
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