Using 18th century storm-surge data from the Dutch Coast to improve the confidence in flood-risk estimates

Abstract. The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide-gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces the issue of outliers, those particularly extreme values distant from the others which increase the uncertainty on the results. In this study, we investigate how historical information, even partial, of past events reported in archives can reduce statistical uncertainties and relativise such outlying observations. A Bayesian Markov chain Monte Carlo method is developed to tackle this issue. We apply this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide-gauge measurements and 8 historical events, the analysis shows that (1) integrating historical information in the analysis greatly reduces statistical uncertainties on return levels (2) Xynthia's water level no longer appears as an outlier, (3) we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data until the end of 2009 of the same order of magnitude as the standard estimative probability using data until the end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

Section: Introductionmentioning

confidence: 99%

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

Bulteau

Idier

Lambert

et al. 2015

“…The 1953 storm surge was considered as an outlier in our previous work (Hamdi et al, 2014) and in previous research (e.g., Bardet et al, 2011). Indeed, although the Gravelines NPP is designed to sustain very low probabilities of failure and despite the fact that no damage was reported at the French NPPs, the 1953 coastal flooding had shown that the extreme sea levels estimated with the current statistical approaches could be underestimated.…”

Section: Introductionmentioning

confidence: 87%

“…To be considered in the FA, a historical storm surge must be well documented; its date must be known and some information on its magnitude must be available. Mostly, available information concerns the impact and the societal disruption caused at the time of the event (Baart et al, 2011).…”

Section: Hi During and Before The Gauging Periodmentioning

confidence: 99%

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

Hamdi¹,

Garnier²,

Giloy³

et al. 2018

This paper aims to demonstrate the technical feasibility of a historical study devoted to French nuclear power plants (NPPs) which can be prone to extreme coastal flooding events. It has been shown in the literature that the use of historical information (HI) can significantly improve the probabilistic and statistical modeling of extreme events. There is a significant lack of historical data on coastal flooding (storms and storm surges) compared to river flooding events. To address this data scarcity and to improve the estimation of the risk associated with coastal flooding hazards, a dataset of historical storms and storm surges that hit the Nord-Pasde-Calais region during the past five centuries was created from archival sources, examined and used in a frequency analysis (FA) in order to assess its impact on frequency estimations. This work on the Dunkirk site (representative of the Gravelines NPP) is a continuation of previous work performed 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 hazards and it has been applied in previous studies to surge datasets to prevent coastal flooding in the La Rochelle region in France.In a first step, only information collected from the literature (published reports, journal papers and PhD theses) is considered. Although this first historical dataset has extended the gauged record back in time to 1897, serious questions related to the exhaustiveness of the information and about the validity of the developed FM have remained unanswered. Additional qualitative and quantitative HI was extracted in a second step from many older archival sources. This work has led to the construction of storm and coastal flooding sheets summarizing key data on each identified event. The quality control and the cross-validation of the collected in-formation, which have been carried out systematically, indicate that it is valid and complete in regard to extreme storms and storm surges. Most of the HI collected is in good agreement with other archival sources and documentary climate reconstructions. The probabilistic and statistical analysis of a dataset containing an exceptional observation considered as an outlier (i.e., the 1953 storm surge) is significantly improved when the additional HI collected in both literature and archives is used. As the historical data tend to be extreme, the right tail of the distribution has been reinforced and the 1953 "exceptional" event does not appear as an outlier any more. This new dataset provides a valuable source of information on storm surges for future characterization of coastal hazards.

“…This allows to use a larger number of storms in the statistical assessment of the extreme skew surges. Baart et al (2011) pointed out the hitch in recovering accurate historical information. A historical event is the result of a wide investigation of several qualitative and quantitative sources.…”

Section: R Frau Et Al: Historical Information For Regional Analysismentioning

confidence: 99%

The use of historical information for regional frequency analysis of extreme skew surge

Frau

Andreewsky

Bernardara

2018

Abstract. The design of effective coastal protections requires an adequate estimation of the annual occurrence probability of rare events associated with a return period up to 10 3 years. Regional frequency analysis (RFA) has been proven to be an applicable way to estimate extreme events by sorting regional data into large and spatially distributed datasets. Nowadays, historical data are available to provide new insight on past event estimation. The utilisation of historical information would increase the precision and the reliability of regional extreme's quantile estimation. However, historical data are from significant extreme events that are not recorded by tide gauge. They usually look like isolated data and they are different from continuous data from systematic measurements of tide gauges. This makes the definition of the duration of our observations period complicated. However, the duration of the observation period is crucial for the frequency estimation of extreme occurrences. For this reason, we introduced here the concept of "credible duration". The proposed RFA method (hereinafter referenced as FAB, from the name of the authors) allows the use of historical data together with systematic data, which is a result of the use of the credible duration concept.