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| Titel |
Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin |
| VerfasserIn |
J. D. Giraldo Osorio, S. G. García Galiano |
| 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 ; 15, no. 11 ; Nr. 15, no. 11 (2011-11-29), S.3605-3615 |
| Datensatznummer |
250013034
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| Publikation (Nr.) |
 copernicus.org/hess-15-3605-2011.pdf |
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| Zusammenfassung |
| The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is
characterized by high rainfall variability and rapid population growth. In
this region, heavy storm events frequently cause extensive damage.
Nonetheless, the projections for change in extreme rainfall values have
shown a great divergence between Regional Climate Models (RCM), increasing
the forecast uncertainty. Novel methodologies should be applied, taking into
account both the variability provided by different RCMs, as well as the
non-stationary nature of time series for the building of hazard maps of
extreme rainfall events. The present work focuses on the probability density
functions (PDFs)-based evaluation and a simple quantitative measure of how
well each RCM considered can capture the observed annual maximum daily
rainfall (AMDR) series on the Senegal River basin. Since meaningful trends
have been detected in historical rainfall time series for the region,
non-stationary probabilistic models were used to fit the PDF parameters to
the AMDR time series. In the development of PDF ensemble by bootstrapping
techniques, Reliability Ensemble Averaging (REA) maps were applied to score
the RCMs. The REA factors were computed using a metric to evaluate the
agreement between observed -or best estimated- PDFs, and that simulated with
each RCM. The assessment of plausible regional trends associated to the
return period, from the hazard maps of AMDR, showed a general rise, owing to
an increase in the mean and the variability of extreme precipitation. These
spatial-temporal distributions could be considered by Organization for the
Development of the Senegal River (Organisation pour la mise en valeur du
fleuve Sénégal, OMVS), in such a way as to reach a better balance
between mitigation and adaptation. |
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