Statistical techniques for extreme wave condition analysis in coastal design
PublisherUniversity of Plymouth
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The study of the behaviour of the extreme values of a variable such as wave height is very important in engineering applications such as flood risk assessment and coastal design. Storm wave modelling usually adopts a univariate extreme value theory approach, essentially identifying the extreme observations of one variable and fitting a standard extreme value distribution to these values. Often it is of interest to understand how extremes of a variable such as wave height depend on a covariate such as wave direction. An important associated concept is that of return level, a value that is expected to be exceeded once in a certain time period. The main areas of research discussed in this thesis involve making improvements to the way that extreme observations are identified and to the use of quantile regression as an alternative methodology for understanding the dependence of extreme values on a covariate. Both area of research provide developments to existing return level methodology so enhancing the accuracy of predicted future storm wave events. We illustrate the methodology that we have developed using both coastal and offshore wave data sets.