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Titel |
Multivariate return periods of sea storms for coastal erosion risk assessment |
VerfasserIn |
S. Corbella, D. D. Stretch |
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 Science ; 12, no. 8 ; Nr. 12, no. 8 (2012-08-24), S.2699-2708 |
Datensatznummer |
250011059
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Publikation (Nr.) |
copernicus.org/nhess-12-2699-2012.pdf |
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Zusammenfassung |
The erosion of a beach depends on various storm characteristics. Ideally, the
risk associated with a storm would be described by a single multivariate
return period that is also representative of the erosion risk, i.e. a 100 yr
multivariate storm return period would cause a 100 yr erosion return period.
Unfortunately, a specific probability level may be associated with numerous
combinations of storm characteristics. These combinations, despite having the
same multivariate probability, may cause very different erosion outcomes.
This paper explores this ambiguity problem in the context of copula based
multivariate return periods and using a case study at Durban on the east
coast of South Africa. Simulations were used to correlate multivariate return
periods of historical events to return periods of estimated storm induced
erosion volumes. In addition, the relationship of the most-likely design event
(Salvadori et al., 2011) to coastal erosion was investigated. It was found that
the multivariate return periods for wave height and duration had the highest
correlation to erosion return periods. The most-likely design event was found
to be an inadequate design method in its current form. We explore the
inclusion of conditions based on the physical realizability of wave events
and the use of multivariate linear regression to relate storm parameters to
erosion computed from a process based model. Establishing a link between
storm statistics and erosion consequences can resolve the ambiguity between
multivariate storm return periods and associated erosion return periods. |
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