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| Titel |
Estimation of high return period flood quantiles using additional non-systematic information with upper bounded statistical models |
| VerfasserIn |
B. A. Botero, F. Francés |
| 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 ; 14, no. 12 ; Nr. 14, no. 12 (2010-12-20), S.2617-2628 |
| Datensatznummer |
250012535
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| Publikation (Nr.) |
 copernicus.org/hess-14-2617-2010.pdf |
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| Zusammenfassung |
| This paper proposes the estimation of high return period quantiles using
upper bounded distribution functions with Systematic and additional
Non-Systematic information. The aim of the developed methodology is to
reduce the estimation uncertainty of these quantiles, assuming the upper
bound parameter of these distribution functions as a statistical estimator
of the Probable Maximum Flood (PMF). Three upper bounded distribution
functions, firstly used in Hydrology in the 90's (referred to in this work
as TDF, LN4 and EV4), were applied at the Jucar River in Spain. Different
methods to estimate the upper limit of these distribution functions have
been merged with the Maximum Likelihood (ML) method. Results show that it is
possible to obtain a statistical estimate of the PMF value and to establish
its associated uncertainty. The behaviour for high return period quantiles
is different for the three evaluated distributions and, for the case study,
the EV4 gave better descriptive results. With enough information, the
associated estimation uncertainty for very high return period quantiles is
considered acceptable, even for the PMF estimate. From the robustness
analysis, the EV4 distribution function appears to be more robust than the
GEV and TCEV unbounded distribution functions in a typical Mediterranean
river and Non-Systematic information availability scenario. In this scenario
and if there is an upper limit, the GEV quantile estimates are clearly
unacceptable. |
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