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Keywords:

  • Annualised risk;
  • flood damages;
  • flood modelling;
  • flood proofing;
  • flood risk;
  • flood risk management;
  • graphics processing unit;
  • Monte Carlo sampling.

Abstract

This study presents an analysis approach using an existing Monte Carlo (MC) flood risk framework to compare annualised risk reductions from flood control alternatives targeting various recurrence interval events. The annualised risk approach is demonstrated by analysing the relative flood risk mitigation benefits of flood proofing in Swannanoa watershed, North Carolina. Using the MC framework, 54 design flows are sampled from the flow distribution and used to drive a graphics card based two-dimensional flood model. The computed flood depths are used to create flood damage frequency and annualised risk curves. It was hypothesised that flood proofing for a higher probability event would result in a greater relative level of damage reduction for lower cost compared with the traditional use of a 1% annual exceedance flood event. The MC framework was used to test the hypothesis by producing a distribution of annualised risk over various return periods. Confirming the hypothesis, the 12% flood event was found to have the highest annualised risk for the case study in this paper. Simulations were executed to determine the relative costs and benefits of the 12% flood proofing (alternate case) and 1% flood proofing (base case) alternatives. The results showed that the base case reduced the expected annual damage (EAD) by 98.9% compared with the status quo. The alternate case reduced the EAD by 80.4% compared with the status quo. Comparing estimated annual implementation cost with flood damage reductions, annually, for every dollar spent on flood proofing, the 12% design resulted in twice the reduction in flood damages compared with the 1% design. This preliminary study thus confirms the potential of an alternative analysis approach that may be applied for identifying desired flood control level based on flood risk mitigation potential.