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| Titel |
Adaptability and transferability of flood loss functions in residential areas |
| VerfasserIn |
H. Cammerer, A. H. Thieken, J. Lammel |
| 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. 11 ; Nr. 13, no. 11 (2013-11-29), S.3063-3081 |
| Datensatznummer |
250085570
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| Publikation (Nr.) |
 copernicus.org/nhess-13-3063-2013.pdf |
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| Zusammenfassung |
| Flood loss modeling is an important component within flood risk assessments.
Traditionally, stage-damage functions are used for the estimation of direct
monetary damage to buildings. Although it is known that such functions are
governed by large uncertainties, they are commonly applied – even in
different geographical regions – without further validation, mainly due to
the lack of real damage data. Until now, little research has been done to
investigate the applicability and transferability of such damage models to
other regions. In this study, the last severe flood event in the Austrian
Lech Valley in 2005 was simulated to test the performance of various damage
functions from different geographical regions in Central Europe for the
residential sector. In addition to common stage-damage curves, new functions
were derived from empirical flood loss data collected in the aftermath of
recent flood events in neighboring Germany. Furthermore, a
multi-parameter flood loss model for the residential sector was adapted to
the study area and also evaluated with official damage data. The analysis
reveals that flood loss functions derived from related and more similar
regions perform considerably better than those from more heterogeneous
data sets of different regions and flood events. While former loss functions estimate the
observed damage well, the latter overestimate the reported loss clearly. To
illustrate the effect of model choice on the resulting uncertainty of damage
estimates, the current flood risk for residential areas was calculated. In
the
case of extreme events like the 300 yr flood, for example, the range of
losses to residential buildings between the highest and the lowest estimates
amounts to a factor of 18, in contrast to properly validated models with a
factor of 2.3. Even if the risk analysis is only performed for residential
areas, our results reveal evidently that a carefree model transfer in other
geographical regions might be critical. Therefore, we conclude that loss
models should at least be selected or derived from related regions with
similar flood and building characteristics, as far as no model validation is
possible. To further increase the general reliability of flood loss
assessment in the future, more loss data and more comprehensive loss data for model
development and validation are needed. |
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