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Natural Hazards

, Volume 70, Issue 1, pp 159–172 | Cite as

Probabilistic flood forecasting and decision-making: an innovative risk-based approach

  • Murray Dale
  • Jon WicksEmail author
  • Ken Mylne
  • Florian Pappenberger
  • Stefan Laeger
  • Steve Taylor
Original Paper

Abstract

Flood forecasting is becoming increasingly important across the world. The exposure of people and property to flooding is increasing and society is demanding improved management of flood risk. At the same time, technological and data advances are enabling improvements in forecasting capabilities. One area where flood forecasting is seeing technical developments is in the use of probabilistic forecasts—these provide a range of possible forecast outcomes that indicate the probability or chance of a flood occurring. While probabilistic forecasts have some distinct benefits, they pose an additional decision-making challenge to those that use them: with a range of forecasts to pick from, which one is right? (or rather, which one(s) can enable me to make the correct decision?). This paper describes an innovative and transferable approach for aiding decision-making with probabilistic forecasts. The proposed risk-based decision-support framework has been tested in a range of flood risk environments: from coastal surge to fluvial catchments to urban storm water scales. The outputs have been designed to be practical and proportionate to the level of flood risk at any location and to be easy to apply in an operational flood forecasting and warning context. The benefits of employing a benefit-cost inspired decision-support framework are that flood forecasting decision-making can be undertaken objectively, with confidence and an understanding of uncertainty, and can save unnecessary effort on flood incident actions. The method described is flexible such that it can be used for a wide range of flood environments with multiple flood incident management actions. It uses a risk-based approach taking into account both the probability and the level of impact of a flood event. A key feature of the framework is that it is based on a full assessment of the flood-related risk, taking into account both the probability and the level of impact of a flood event. A recommendation for action may be triggered by either a higher probability of a lower impact flood or a low probability of a very severe flood. Hence, it is highly innovative as it is the first application of such a risk-based method for flood forecasting and warning purposes. A final benefit is that it is considered to be transferrable to other countries.

Keywords

Flood forecasting Decision-support Benefit-cost 

Notes

Acknowledgments

The authors gratefully acknowledge the Environment Agency of England and Wales for funding the research described in this paper (reference: SC0900032) as part of their Flood and Coastal Risk Management R&D Programme. We also acknowledge inputs to the research project from other members of the project team: Hannah Cloke of Kings College London, Keith Fenwick and Charlie Pilling of the Flood Forecasting Centre and Matthew Horritt, Andy Barnes, Yong Wang and Yiming Ji of Halcrow Group Ltd. Project output reviews were undertaken by David Demeritt of Kings College London and Micha Werner of Deltares. Comments from the anonymous reviewers helped to improve the paper.

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Murray Dale
    • 1
  • Jon Wicks
    • 1
    Email author
  • Ken Mylne
    • 2
  • Florian Pappenberger
    • 3
  • Stefan Laeger
    • 4
  • Steve Taylor
    • 4
  1. 1.Halcrow (A CH2M HILL Company)Burderop Park, SwindonUK
  2. 2.Met OfficeExeterUK
  3. 3.European Centre for Medium-Range Weather Forecasting (ECMWF)Reading, BerkshireUK
  4. 4.Environment Agency of England and WalesLondonUK

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