Attribution of flood risk in urban areasDawson, R. J., Speight, L. ORCID: https://orcid.org/0000-0002-8700-157X, Hall, J. W., Djordjevic, S., Savic, D. and Leandro, J. (2008) Attribution of flood risk in urban areas. Journal of Hydroinformatics, 10 (4). pp. 275-288. ISSN 1464-7141 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.2166/hydro.2008.054 Abstract/SummaryFlooding in urban areas represents a particular challenge to modellers and flood risk managers because of the complex interactions of surface and sewer flows. Quantified flood risk estimates provide a common metric that can be used to compare risks from different sources. In situations where there are several organisations responsible for flood risk management we wish to be able to disaggregate the total risk and attribute it to different components in the system and/or agents with responsibility for risk reduction in order to target management actions. Two approaches to risk attribution are discussed: Standards-based attribution, which is a deterministic approach, based upon the performance of different engineering components in the system at their “design standard”. Sensitivity-based attribution, which apportions risk between the variables that influence the total flood risk. Whilst both these approaches are feasible for the small system considered here, in practice urban flooding systems involve tens of thousands of variables. The only feasible approach to tackling this problem for large urban systems is therefore by hierarchical simplification of the system, with the attribution analysis being applied in several tiers of detail. In this paper, the applicability of a hierarchical approach is demonstrated in the context of sewer pipe blockages. The results demonstrate the potential of attribution methods to support the development of integrated urban flood risk management strategies, as they can identify the forcing variables and infrastructure components that have the most influence upon flood risk.
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