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| Titel |
Contribution of insurance data to cost assessment of coastal flood damage to residential buildings: insights gained from Johanna (2008) and Xynthia (2010) storm events |
| VerfasserIn |
C. André, D. Monfort, M. Bouzit, C. Vinchon |
| 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 ; 13, no. 8 ; Nr. 13, no. 8 (2013-08-08), S.2003-2012 |
| Datensatznummer |
250085494
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| Publikation (Nr.) |
 copernicus.org/nhess-13-2003-2013.pdf |
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| Zusammenfassung |
| There are a number of methodological issues involved in assessing damage
caused by natural hazards. The first is the lack of data, due to the rarity
of events and the widely different circumstances in which they occur. Thus,
historical data, albeit scarce, should not be neglected when seeking to
build ex-ante risk management models. This article analyses the input of
insurance data for two recent severe coastal storm events, to examine what
causal relationships may exist between hazard characteristics and the level
of damage incurred by residential buildings. To do so, data was collected at
two levels: from lists of about 4000 damage records, 358 loss adjustment
reports were consulted, constituting a detailed damage database. The results
show that for flooded residential buildings, over 75% of reconstruction
costs are associated with interior elements, with damage to structural components
remaining very localised and negligible. Further analysis revealed a high
scatter between costs and water depth, suggesting that uncertainty remains
high in drawing up damage functions with insurance data alone. Due to the
paper format of the loss adjustment reports, and the lack of harmonisation
between their contents, the collection stage called for a considerable
amount of work. For future events, establishing a standardised process for
archiving damage information could significantly contribute to the
production of such empirical damage functions. Nevertheless, complementary
sources of data on hazards and asset vulnerability parameters will
definitely still be necessary for damage modelling; multivariate
approaches, crossing insurance data with external material, should also be
investigated more deeply. |
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