Development of a target-site-based regional frequency model using historical information

Nuclear power plants in France are designed to withstand natural hazards. Nevertheless, some exceptional storm surges, considered as outliers, are not properly addressed by classical statistical models. Local frequency estimations can be obtained with acceptable uncertainties if the data set contain...

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Veröffentlicht in:Natural hazards (Dordrecht) 2019-09, Vol.98 (3), p.895-913
Hauptverfasser: Hamdi, Y., Duluc, C.-M., Bardet, L., Rebour, V.
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Sprache:eng
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Zusammenfassung:Nuclear power plants in France are designed to withstand natural hazards. Nevertheless, some exceptional storm surges, considered as outliers, are not properly addressed by classical statistical models. Local frequency estimations can be obtained with acceptable uncertainties if the data set containing the extreme storm surge levels is sufficiently complete and not characterized by the presence of an outlier. Otherwise, additional information such as regional and historical storm surges may be used to mitigate the lack of data and the influence of the outlier by increasing its representativeness in the sample. The objective of the present work is to develop a regional frequency model (RFM) using historical storm surges. Here we propose a RFM using historical information (HI). The empirical spatial extremogram is used herein to form a homogenous region of interest centered on a target site. A related issue regards the reconstitution, at the target site and from its neighbors, of missed storm surges with a multiple linear regression (MLR). MLR analysis can be considered conclusive if available observations at neighboring sites are informative enough and the reconstitution results meet some criteria during the cross-validation process. A total of 35 harbors located on the French (Atlantic and English Channel) and British coasts are used as a whole region with the La Rochelle site as a target site. The Peaks-Over-Threshold frequency model is used. The results are compared to those of an existing model based on the index flood method. The use of HI in the developed RFM increases the representativeness of the outlier in the sample. Fitting results at the right tail of the distribution appear more adequate and the 100-year return level is about 30 cm higher. The 100-year return level in the initial fitting has a return period of about 30 years in the updated fitting.
ISSN:0921-030X
1573-0840
DOI:10.1007/s11069-018-3237-8