Estimations of statistical dependence as joint return period modulator of compound events – Part 1: Storm surge and wave height

• Published in: Natural Hazards and Earth System Sciences
• Main Author: T. I. Petroliagkis
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2018
• Subjects: Environmental technology. Sanitary engineering; TD1-1066; Geography. Anthropology. Recreation; G; Environmental sciences; GE1-350; Geology; QE1-996.5; Norwegian Sea
• Online Access: https://doi.org/10.5194/nhess-18-1937-2018; https://doaj.org/article/8262cdb5adcd47cdbffe0af2d1a460e6

The possibility of utilizing statistical dependence methods in coastal flood hazard calculations is investigated since flood risk is rarely a function of just one source variable but usually two or more. Source variables in most cases are not independent as they may be driven by the same weather event, so their dependence, which is capable of modulating their joint return period, has to be estimated before the calculation of their joint probability. Dependence and correlation may differ substantially from one another since dependence is focused heavily on tail (extreme) percentiles. The statistical analysis between surge and wave is performed over 32 river ending points along European coasts. Two sets of almost 35-year hindcasts of storm surge and wave height were adopted, and results are presented by means of analytical tables and maps referring to both correlation and statistical dependence values. Further, the top 80 compound events were defined for each river ending point. Their frequency of occurrence was found to be distinctly higher during the cold months, while their main low-level flow characteristics appear to be mainly in harmony with the transient nature of storms and their tracks. Overall, significantly strong values of positive correlations and dependencies were found over the Irish Sea; English Channel; and south coasts of the North Sea, Norwegian Sea, and Baltic Sea, with compound events taking place in a zero-lag mode. For the rest, mostly positive moderate dependence values were estimated even if a considerable number of them had correlations of almost zero or even a negative value.