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Applying probabilistic flood forecasting in flood incident management

Dale, M., Ji, Y., Wicks, J., Mylne, K., Pappenberger, F. and Cloke, H., (2013) Applying probabilistic flood forecasting in flood incident management. Flood & Coastal Erosion Risk Management Research and Development Programme. Technical Report. Environment Agency, Bristol. pp89. ISBN 9781849112963

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Abstract/Summary

In recent years, various probabilistic flood forecasting techniques have been developed and applied with some success in the UK and worldwide. Developments in quantitative precipitation forecasting, probabilistic storm surge and flood modelling all provide more information for flood forecasting. However, more information does not necessarily improve decision-making, particularly where the probabilistic forecasts are likely to contain conflicting predictions. In order for probabilistic forecasts to be used effectively, methods must assist in rapid decision-making in a real-time flood environment. This report describes a practical approach for using probabilistic flood forecasts to support decision-making in flood incident management (FIM). Three decision support methods have been developed and tested on case studies. The report explains how these methods could be applied to a variety of forecasting situations of different complexity and at different lead times ahead of an event. Also included is an outline of the datasets that would be required to use the decision-support methods in different forecasting situations, and data requirements for real-time use. The report covers the likely operational benefits, opportunities and constraints of using probabilistic flood forecasting in FIM. This work provides a useful resource for suitably qualified professional to investigate how probabilistic flood forecasts could be used to support decision making in flood incident management.

Item Type:Report (Technical Report)
Divisions:Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:86590
Publisher:Environment Agency

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