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| Titel |
Estimating flood damage to railway infrastructure – the case study of the March River flood in 2006 at the Austrian Northern Railway |
| VerfasserIn |
P. Kellermann, A. Schöbel, G. Kundela, A. H. Thieken |
| 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. 11 ; Nr. 15, no. 11 (2015-11-10), S.2485-2496 |
| Datensatznummer |
250119773
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| Publikation (Nr.) |
 copernicus.org/nhess-15-2485-2015.pdf |
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| Zusammenfassung |
| Models for estimating flood losses to infrastructure are rare and their
reliability is seldom investigated although infrastructure losses might
contribute considerably to the overall flood losses. In this paper, an
empirical modelling approach for estimating direct structural flood damage
to railway infrastructure and associated financial losses is presented. Via
a combination of event data, i.e. photo-documented damage on the Northern
Railway in Lower Austria caused by the March River flood in 2006, and
simulated flood characteristics, i.e. water levels, flow velocities and
combinations thereof, the correlations between physical flood impact
parameters and damage occurred to the railway track were investigated and
subsequently rendered into a damage model. After calibrating the loss
estimation using recorded repair costs of the Austrian Federal Railways, the
model was applied to three synthetic scenarios with return periods of 30,
100 and 300 years of March River flooding. Finally, the model results are
compared to depth-damage-curve-based approaches for the infrastructure
sector obtained from the Rhine Atlas damage model and the Damage Scanner
model. The results of this case study indicate a good performance of our
two-stage model approach. However, due to a lack of independent event and
damage data, the model could not yet be validated. Future research in
natural risk should focus on the development of event and damage
documentation procedures to overcome this significant hurdle in flood damage modelling. |
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