Probabilistic modelling of extreme storms along the Dutch coast

Li, F., van Gelder, P. H. A. J. M., Ranasinghe, R., Callaghan, D. P. and Jongejan, R. B. (2014) Probabilistic modelling of extreme storms along the Dutch coast. Coastal Engineering, 86 1-13. doi:10.1016/j.coastaleng.2013.12.009


Author Li, F.
van Gelder, P. H. A. J. M.
Ranasinghe, R.
Callaghan, D. P.
Jongejan, R. B.
Title Probabilistic modelling of extreme storms along the Dutch coast
Journal name Coastal Engineering   Check publisher's open access policy
ISSN 0378-3839
1872-7379
Publication date 2014
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.coastaleng.2013.12.009
Open Access Status
Volume 86
Start page 1
End page 13
Total pages 13
Place of publication Amsterdam, The Netherlands
Publisher Elsevier BV
Collection year 2015
Language eng
Subject 2212 Ocean Engineering
2305 Environmental Engineering
Abstract Due to the unprecedented growth in population and economic development along the coastal zone all over the world, knowledge about future extreme oceanographic events will assist in ensuring human and property safety. This will be a task with increasing significance in the light of projected climate change impacts. A joint estimation of extreme storm events' variates of deep water wave conditions was performed. It can be used for multivariate descriptions of wave climate variates, such as wave height, period, steepness, and storm duration. The storm sequences can be simulated and extrapolated from limited observational data for optimal structure protection strategies and various disaster risk analysis, like erosion or overtopping. The analysis not only shows the effectiveness of the proposed statistical approaches for improving multivariate modelling of the storm parameters but also highlights the most compatible approach for the Dutch wave climate data from 1979 to 2009. We used the Monte-Carlo method and four methods to construct the dependency structures, based on copula functions, physical relationship and extreme value theory. The marginal probabilistic distribution functions of wave climate variables and the joint probability were then obtained. The simulated data group performs a reasonable similarity to the field measurements according to the goodness-of-fit test, and the Gaussian copula model was found to be the best wave climate simulation method for the Dutch coast.
Keyword Copulas
Dependence
Multivariate analysis
Sea storm simulation
Wave climate
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
Official 2015 Collection
 
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