ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flood risk assessments require different disciplines to understand and model the underlying components hazard, exposure, and vulnerability. Many methods and data sets have been refined considerably to cover more details of spatial, temporal, or process information. We compile case studies indicating that refined methods and data have a considerable effect on the overall assessment of flood risk. But are these improvements worth the effort? The adequate level of detail is typically unknown and prioritization of improvements in a specific component is hampered by the lack of an overarching view on flood risk. Consequently, creating the dilemma of potentially being too greedy or too wasteful with the resources available for a risk assessment. A “sweet spot” between those two would use methods and data sets that cover all relevant known processes without using resources inefficiently. We provide three key questions as a qualitative guidance toward this “sweet spot.” For quantitative decision support, more overarching case studies in various contexts are needed to reveal the sensitivity of the overall flood risk to individual components. This could also support the anticipation of unforeseen events like the flood event in Germany and Belgium in 2021 and increase the reliability of flood risk assessments.〈/p〉
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: BMBF http://dx.doi.org/10.13039/501100002347
    Description: Federal Environment Agency http://dx.doi.org/10.13039/501100010809
    Description: http://howas21.gfz-potsdam.de/howas21/
    Description: https://www.umwelt.niedersachsen.de/startseite/themen/wasser/hochwasser_amp_kustenschutz/hochwasserrisikomanagement_richtlinie/hochwassergefahren_und_hochwasserrisikokarten/hochwasserkarten-121920.html
    Description: https://download.geofabrik.de/europe/germany.html
    Description: https://emergency.copernicus.eu/mapping/list-of-components/EMSN024
    Description: https://data.jrc.ec.europa.eu/collection/id-0054
    Description: https://oasishub.co/dataset/surface-water-flooding-footprinthurricane-harvey-august-2017-jba
    Description: https://www.wasser.sachsen.de/hochwassergefahrenkarte-11915.html
    Keywords: ddc:551.48 ; decision support ; extreme events ; integrated flood risk management ; risk assessment
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2017-12-06
    Description: Flash floods are caused by intense rainfall events and represent an insufficiently understood phenomenon in Germany. As a result of higher precipitation intensities, flash floods might occur more frequently in future. In combination with changing land use patterns and urbanisation, damage mitigation, insurance and risk management in flash-flood-prone regions are becoming increasingly important. However, a better understanding of damage caused by flash floods requires ex post collection of relevant but yet sparsely available information for research. At the end of May 2016, very high and concentrated rainfall intensities led to severe flash floods in several southern German municipalities. The small town of Braunsbach stood as a prime example of the devastating potential of such events. Eight to ten days after the flash flood event, damage assessment and data collection were conducted in Braunsbach by investigating all affected buildings and their surroundings. To record and store the data on site, the open-source software bundle KoBoCollect was used as an efficient and easy way to gather information. Since the damage driving factors of flash floods are expected to differ from those of riverine flooding, a post-hoc data analysis was performed, aiming to identify the influence of flood processes and building attributes on damage grades, which reflect the extent of structural damage. Data analyses include the application of random forest, a random general linear model and multinomial logistic regression as well as the construction of a local impact map to reveal influences on the damage grades. Further, a Spearman's Rho correlation matrix was calculated. The results reveal that the damage driving factors of flash floods differ from those of riverine floods to a certain extent. The exposition of a building in flow direction shows an especially strong correlation with the damage grade and has a high predictive power within the constructed damage models. Additionally, the results suggest that building materials as well as various building aspects, such as the existence of a shop window and the surroundings, might have an effect on the resulting damage. To verify and confirm the outcomes as well as to support future mitigation strategies, risk management and planning, more comprehensive and systematic data collection is necessary.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...