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. This paper aims to demonstrate the technical feasibility of a historicalstudy devoted to French nuclear power plants (NPPs) which can be prone toextreme coastal flooding events. It has been shown in the literature that theuse of historical information (HI) can significantly improve theprobabilistic and statistical modeling of extreme events. There is asignificant lack of historical data on coastal flooding (storms and stormsurges) compared to river flooding events. To address this data scarcity andto improve the estimation of the risk associated with coastal floodinghazards, a dataset of historical storms and storm surges that hit theNord-Pas-de-Calais region during the past five centuries was created fromarchival sources, examined and used in a frequency analysis (FA) in order toassess its impact on frequency estimations. This work on the Dunkirk site(representative of the Gravelines NPP) is a continuation of previous workperformed on the La Rochelle site in France. Indeed, the frequency model (FM)used in the present paper had some success in the field of coastal hazardsand it has been applied in previous studies to surge datasets to preventcoastal flooding in the La Rochelle region in France. In a first step, only information collected from the literature (publishedreports, journal papers and PhD theses) is considered. Although this firsthistorical dataset has extended the gauged record back in time to 1897,serious questions related to the exhaustiveness of the information and aboutthe validity of the developed FM have remained unanswered. Additionalqualitative and quantitative HI was extracted in a second step from manyolder archival sources. This work has led to the construction of storm andcoastal flooding sheets summarizing key data on each identified event. Thequality control and the cross-validation of the collected information, whichhave been carried out systematically, indicate that it is valid and completein regard to extreme storms and storm surges. Most of the HI collected is ingood agreement with other archival sources and documentary climatereconstructions. The probabilistic and statistical analysis of a datasetcontaining an exceptional observation considered as an outlier (i.e., the1953 storm surge) is significantly improved when the additional HI collectedin both literature and archives is used. As the historical data tend to beextreme, the right tail of the distribution has been reinforced and the1953 “exceptional” event does not appear as an outlier any more. This newdataset provides a valuable source of information on storm surges for futurecharacterization of coastal hazards.

Analysis of the risk associated with coastal flooding hazards: a new historical extreme storm surges dataset for Dunkirk, France