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| Titel |
Uncertainties on mean areal precipitation: assessment and impact on streamflow simulations |
| VerfasserIn |
L. Moulin, E. Gaume, C. Obled |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 13, no. 2 ; Nr. 13, no. 2 (2009-02-04), S.99-114 |
| Datensatznummer |
250011753
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| Publikation (Nr.) |
 copernicus.org/hess-13-99-2009.pdf |
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| Zusammenfassung |
| This paper investigates the influence of mean areal rainfall
estimation errors on a specific case study: the use of lumped
conceptual rainfall-runoff models to simulate the flood hydrographs of
three small to medium-sized catchments of the upper Loire river. This
area (3200 km2) is densely covered by an operational network of
stream and rain gauges. It is frequently exposed to flash floods and
the improvement of flood forecasting models is then a crucial
concern. Particular attention has been drawn to the development of an
error model for rainfall estimation consistent with data in order to
produce realistic streamflow simulation uncertainty ranges. The
proposed error model combines geostatistical tools based on kriging
and an autoregressive model to account for temporal dependence of
errors. It has been calibrated and partly validated for hourly mean
areal precipitation rates. Simulated error scenarios were propagated
into two calibrated rainfall-runoff models using Monte Carlo
simulations. Three catchments with areas ranging from 60 to 3200 km2
were tested to reveal any possible links between the
sensitivity of the model outputs to rainfall estimation errors and the
size of the catchment. The results show that a large part of the
rainfall-runoff (RR) modelling errors can be explained by the
uncertainties on rainfall estimates, especially in the case of smaller
catchments. These errors are a major factor limiting accuracy and
sharpness of rainfall-runoff simulations, and thus their operational
use for flood forecasting. |
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