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Data management of extreme marine and coastal hydro-meteorological events / Pieter H. A. J. M. Van Gelder in Journal of hydraulic research, Vol. 46 extra issue (Mars/Avril 2008) 

Public ISBD [article]  in Journal of hydraulic research > Vol. 46 extra issue (Mars/Avril 2008) . - pp. 191-210 Titre : Data management of extreme marine and coastal hydro-meteorological events Titre original : Gestion de données des événements hydrauliques-météorologiques Type de document : texte imprimé Auteurs : Pieter H. A. J. M. Van Gelder, Auteur ; Cong V. Mai, Auteur ; Wen Wang, Auteur Article en page(s) : pp. 191-210 Note générale : Hydraulique Résumé en Français Langues : Anglais (eng) Mots-clés : Data  screening  Extreme  value  analysis  Long-memory  study  Seasonality  analysis  Steadiness  test  Trend  analysis Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : In statistical extreme value analysis and forecast modeling, data screening and management are necessary steps before fitting a probability distribution to represent adequately the observed data. These methods include trend analysis, steadiness tests, seasonality analysis, and long-memory studies; are critically reviewed and applied to coastal datasets. It was shown that the smaller the timescale of the coastal process, the more likely it tends to be non-stationary. The seasonal variations in the autocorrelation structures are present for all the deseasonalized daily, 1/3-monthly and monthly coastal processes. The investigation of the long-memory phenomenon of coastal processes at different timescales shows that, with the increase of timescale, the intensity of long-memory decreases. Only the daily water level series exhibit a strong long-memory. Comparing the stationary test results and the long-memory test results, these two types of tests are more or less linked, not only in that the test results have similar timescale patterns, but also in that there is a general tendency that the stronger the nonstationarity, the more intense the long-memory. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.journalhydraulicresearch.com [article] Data management of extreme marine and coastal hydro-meteorological events = Gestion de données des événements hydrauliques-météorologiques [texte imprimé] / Pieter H. A. J. M. Van Gelder, Auteur ; Cong V. Mai, Auteur ; Wen Wang, Auteur . - pp. 191-210. Hydraulique Résumé en Français Langues : Anglais (eng) in Journal of hydraulic research > Vol. 46 extra issue (Mars/Avril 2008) . - pp. 191-210 Mots-clés : Data  screening  Extreme  value  analysis  Long-memory  study  Seasonality  analysis  Steadiness  test  Trend  analysis Index. décimale : 627 Ingénierie des cours d'eau naturels, des ports, des rades et des cotes. Installations de navigation, de dragage, de récupération et de sauvetage. Barrages et centrales électriques hydrauliques Résumé : In statistical extreme value analysis and forecast modeling, data screening and management are necessary steps before fitting a probability distribution to represent adequately the observed data. These methods include trend analysis, steadiness tests, seasonality analysis, and long-memory studies; are critically reviewed and applied to coastal datasets. It was shown that the smaller the timescale of the coastal process, the more likely it tends to be non-stationary. The seasonal variations in the autocorrelation structures are present for all the deseasonalized daily, 1/3-monthly and monthly coastal processes. The investigation of the long-memory phenomenon of coastal processes at different timescales shows that, with the increase of timescale, the intensity of long-memory decreases. Only the daily water level series exhibit a strong long-memory. Comparing the stationary test results and the long-memory test results, these two types of tests are more or less linked, not only in that the test results have similar timescale patterns, but also in that there is a general tendency that the stronger the nonstationarity, the more intense the long-memory. DEWEY : 627 ISSN : 0022-1686 En ligne : http://www.journalhydraulicresearch.com