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Flood probability quantification for road infrastructure: Data-driven spatial-statistical approach and case study applications
Stockholm University, Faculty of Science, Department of Physical Geography.
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2017 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 581, 386-398 p.Article 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, 386-398 p.
Keyword [en]
Sediment connectivity, Climate change adaptation, GIS, Multivariate statistical model, Decision making
National Category
Water Engineering Oceanography, Hydrology, Water Resources
Identifiers
URN: urn:nbn:se:su:diva-140910DOI: 10.1016/j.scitotenv.2016.12.147ISI: 000394635300037OAI: oai:DiVA.org:su-140910DiVA: diva2:1083777
Available from: 2017-03-22 Created: 2017-03-22 Last updated: 2017-05-02Bibliographically approved

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Kalantari, ZahraDestouni, Georgia
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Department of Physical Geography
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