E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||6|
|Section||Probability of floods and storms|
|Published online||20 October 2016|
National scale multivariate extreme value modelling of waves, winds and sea levels
1 HR Wallingford Ltd., Benson Lane, Crowmarsh, Wallingford, UK
2 Environment Agency, Ergon House, Horseferry Rd, London, UK
a Corresponding author: firstname.lastname@example.org
It has long been recognised that extreme coastal flooding can arise from the joint occurrence of extreme waves, winds and sea levels. The standard simplified joint probability approach used in England and Wales can result in an underestimation of flood risk unless correction factors are applied. This paper describes the application of a state-of-the-art multivariate extreme value model to offshore winds, waves and sea levels around the coast of England. The methodology overcomes the limitations of the traditional method. The output of the new statistical analysis is a Monte-Carlo (MC) simulation comprising many thousands of offshore extreme events and it is necessary to translate all of these events into overtopping rates for use as input to flood risk assessments. It is computationally impractical to transform all of these MC events from the offshore to the nearshore. Computationally efficient statistical emulators of the SWAN wave transformation model have therefore been constructed. The emulators translate the thousands of MC events offshore. Whilst the methodology has been applied for national flood risk assessment, it has the potential to be implemented for wider use, including climate change impact assessment, nearshore wave climates for detailed local assessments and coastal flood forecasting.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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