Applying POT methods to the Revised Joint Probability Method for determining extreme sea levels
| Autor: | Philippe Garat, Franck Mazas, Luc Hamm, Xavier Kergadallan |
|---|---|
| Přispěvatelé: | Sogreah Maritime, Artelia Eau & Environnement [Lyon], Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Direction Eau Mer et Fleuves (Cerema Direction Eau Mer et Fleuves), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Statistique Apprentissage Machine (SAM), Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2014 |
| Předmět: |
Environmental Engineering
010504 meteorology & atmospheric sciences Meteorology 0211 other engineering and technologies Ocean Engineering 02 engineering and technology Residual 01 natural sciences Convolution [SPI]Engineering Sciences [physics] Joint probability distribution Statistics Sea level 14. Life underwater Surge Extreme value theory 0105 earth and related environmental sciences Mathematics Mixture model 021110 strategic defence & security studies Direct method POT Storm surges Parametric model JPM Tide–surge interaction [STAT.ME]Statistics [stat]/Methodology [stat.ME] |
| Zdroj: | Coastal Engineering Coastal Engineering, Elsevier, 2014, 91, pp.140-150. ⟨10.1016/j.coastaleng.2014.05.006⟩ |
| ISSN: | 0378-3839 |
| DOI: | 10.1016/j.coastaleng.2014.05.006 |
| Popis: | International audience; Newly exposed concepts of POT declustering (Bernardara et al., 2014) within the GPD-Poisson model are applied to the joint probability of tide and surge for determining extreme sea levels, as a variation of the Revised Joint Probability Method (RJPM, Tawn and Vassie, 1989). A mixture model is proposed for the meteorological residual (surge) component with a non-parametric (empirical) density for the bulk values and parametric models for both the lower and upper tails. In particular, a distinction is made between values observed at regular time steps, called sequential values, and the clusters of extreme values, or events, on which the statistical extrapolations are performed. The sea level distribution is obtained by convolution of the tide and surge density functions. Confidence intervals are also proposed. This model is applied to the case study of Brest, France using both hourly and high water values. Two methods for handling tide–surge interaction are presented and discussed and a comparison with a direct approach is made. |
| Databáze: | OpenAIRE |
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