Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Flood probability quantification for road infrastructure: Data-driven spatial-statistical approach and case study applications
Stockholm University, Faculty of Science, Department of Physical Geography.
Show others and affiliations
2017 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 581, p. 386-398Article in journal (Refereed) Published
Abstract [en]

Climate-driven increase in the frequency of extreme hydrological events is expected to impose greater strain on the built environment and major transport infrastructure, such as roads and railways. This study develops a data-driven spatial-statistical approach to quantifying and mapping the probability of flooding at critical road-stream intersection locations, where water flow and sediment transport may accumulate and cause serious road damage. The approach is based on novel integration of key watershed and road characteristics, including also measures of sediment connectivity. The approach is concretely applied to and quantified for two specific study case examples in southwest Sweden, with documented road flooding effects of recorded extreme rainfall. The novel contributions of this study in combining a sediment connectivity account with that of soil type, land use, spatial precipitation-runoff variability and road drainage in catchments, and in extending the connectivity measure use for different types of catchments, improve the accuracy of model results for road flood probability.

Place, publisher, year, edition, pages
2017. Vol. 581, p. 386-398
Keywords [en]
Sediment connectivity, Climate change adaptation, GIS, Multivariate statistical model, Decision making
National Category
Water Engineering Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:su:diva-140910DOI: 10.1016/j.scitotenv.2016.12.147ISI: 000394635300037OAI: oai:DiVA.org:su-140910DiVA, id: diva2:1083777
Available from: 2017-03-22 Created: 2017-03-22 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Kalantari, ZahraDestouni, Georgia
By organisation
Department of Physical Geography
In the same journal
Science of the Total Environment
Water EngineeringOceanography, Hydrology and Water Resources

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 35 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf