The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 10 of 107
Back to Result List

Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

  • Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed againstExperience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.show moreshow less

Download full text files

  • pmnr555.pdfeng
    (1149KB)

    SHA-1: 34a0bf5f78b5393f2f3dfb99b27c990e0747e166

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Patric KellermannORCiDGND, Christine Schönberger, Annegret Henriette ThiekenORCiDGND
URN:urn:nbn:de:kobv:517-opus4-411915
DOI:https://doi.org/10.25932/publishup-41191
ISSN:1866-8372
Title of parent work (English):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (555)
Publication type:Postprint
Language:English
Date of first publication:2019/01/29
Publication year:2016
Publishing institution:Universität Potsdam
Release date:2019/01/29
Tag:Europe; climate; events; projections
Issue:555
Number of pages:15
Source:Natural Hazards and Earth System Sciences 16 (2016), pp. 2357–2371 DOI 10.5194/nhess-16-2357-2016
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
DDC classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Peer review:Referiert
Publishing method:Open Access
Grantor:Copernicus
License (German):License LogoCC-BY - Namensnennung 4.0 International
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.