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| Titel |
How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France) |
| VerfasserIn |
T. Bulteau, D. Idier, J. Lambert, M. Garcin |
| 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 ; 15, no. 6 ; Nr. 15, no. 6 (2015-06-05), S.1135-1147 |
| Datensatznummer |
250119526
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| Publikation (Nr.) |
 copernicus.org/nhess-15-1135-2015.pdf |
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| Zusammenfassung |
| The knowledge of extreme coastal water levels is useful for coastal flooding
studies or the design of coastal defences. While deriving such extremes with
standard analyses using tide-gauge measurements, one often needs to deal
with limited effective duration of observation which can result in large
statistical uncertainties. This is even truer when one faces the issue of
outliers, those particularly extreme values distant from the others which
increase the uncertainty on the results. In this study, we investigate how
historical information, even partial, of past events reported in archives
can reduce statistical uncertainties and relativise such outlying
observations. A Bayesian Markov chain Monte Carlo method is developed to
tackle this issue. We apply this method to the site of La Rochelle (France),
where the storm Xynthia in 2010 generated a water level considered so far as
an outlier. Based on 30 years of tide-gauge measurements and 8 historical
events, the analysis shows that (1) integrating historical information in
the analysis greatly reduces statistical uncertainties on return levels (2)
Xynthia's water level no longer appears as an outlier, (3) we could have
reasonably predicted the annual exceedance probability of that level
beforehand (predictive probability for 2010 based on data until the end of 2009
of the same order of magnitude as the standard estimative probability using
data until the end of 2010). Such results illustrate the usefulness of historical
information in extreme value analyses of coastal water levels, as well as
the relevance of the proposed method to integrate heterogeneous data in such
analyses. |
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