Sampling-based flood risk analysis for fluvial dike systems


A dike system of moderate size has a large number of potential system states, and the loading imposed on the system is inherently random. If the system should fail, in one of its many potential failure modes, the topography of UK floodplains is usually such that hydrodynamic modelling of flood inundation is required to generate realistic estimates of flood depth and hence damage. To do so for all possible failure states may require 1,000s of computationally expensive inundation simulations. A risk-based sampling technique is proposed in order to reduce the computational resources required to estimate flood risk. The approach is novel in that the loading and dike system states (obtained using a simplified reliability analysis) are sampled according to the contribution that a given region of the space of basic variables makes to risk. The methodology is demonstrated in a strategic flood risk assessment for the city of Burton-upon-Trent in the UK. 5,000 inundation model simulations were run although it was shown that the flood risk estimate converged adequately after approximately half this number. The case study demonstrates that, amongst other factors, risk is a complex function of loadings, dike resistance, floodplain topography and the spatial distribution of floodplain assets. The application of this approach allows flood risk managers to obtain an improved understanding of the flooding system, its vulnerabilities and the most efficient means of allocating resource to improve performance. It may also be used to test how the system may respond to future external perturbations.

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The research described in this paper formed part of the “RASP: Risk assessment for flood and coastal defence systems for strategic planning” project, funded by the Environment Agency within the joint DEFRA/EA Flood and Coastal Defence R&D programme. Data used in the case study was provided by The Environment Agency and Black and Veatch Ltd. Dr. Rosu was funded by a European Commission Marie-Curie research fellowship.

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Correspondence to Richard Dawson.

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Dawson, R., Hall, J., Sayers, P. et al. Sampling-based flood risk analysis for fluvial dike systems. Stoch Environ Res Ris Assess 19, 388–402 (2005).

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  • Flood risk assessment
  • Reliability analysis
  • Monte Carlo
  • Infrastructure systems
  • Flood management