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Journal article

Critical infrastructure impact assessment due to flood exposure

Abstract:
Critical national infrastructures, including energy, transport, digital communications, and water, are prone to flood damage. Their geographical extent is a determinant of, and is determined by, patterns of human development, which is often concentrated in floodplains. It is important to understand how infrastructure systems react to large-scale flooding. In this paper, we present an integrated framework for critical infrastructure flood impact assessment. Within this integrated framework, we represent interdependent infrastructure assets through spatial network models. We quantify infrastructure flood impacts in terms of disrupted customers linked directly to flood assets and customers disrupted indirectly due to network effects. The analysis shows how spatial network models inform flood risk management practitioners to identify and compare critical infrastructures risks on flooded and non-flooded land, for prioritising flood protection investments and improve resilience of cities. A case study of the Thames catchment in England is presented, which contains key infrastructure assets and highest population concentrations in United Kingdom.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1111/jfr3.12288

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Geography
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Geography
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Environmental Change Institute
Role:
Author


Publisher:
Wiley
Journal:
Journal of Flood Risk Management More from this journal
Publication date:
2017-01-01
Acceptance date:
2016-12-23
DOI:
EISSN:
1753-318X


Keywords:
Pubs id:
pubs:681762
UUID:
uuid:713262bb-63fd-4d54-856f-2d75409b3237
Local pid:
pubs:681762
Source identifiers:
681762
Deposit date:
2017-04-18

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