Coastal flooding event definition based on damages: Case study of Biarritz Grande Plage on the French Basque coast

TLDR: In this paper, a statistical analysis was carried out to find the best combination of source variables explaining the reported damages for the identified storms, considering source and aggregated variables based on the empirical run-up formula or the wave energy flux.

About: This article is published in Coastal Engineering.The article was published on 2021-06-01 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Return period.

Figures

Figure 1. Location of the study site on the France map (left panel) with a zoom on the Basque coast (right panel - red rectangle) with buoys (Anglet and Saint-Jean-de-Luz) and tide gauges (Socoa) used on this study.

Figure 2. Photographs of the Grande Plage of Biarritz showing a few of the assets frequently flooded (left panel - ©Google Maps), the Grande Plage waterfront and the the casino building (right panel - ©FranceBallade)

Figure 11. Extrapolation plot for the GPD computed with the time series η +R2% (rule R5) for a threshold of 7.26 m. The lines correspond to the model and its 95% confidence interval, the black dots correspond to the empirical values from the time series.

Figure 12. Maxima of the Run-up R2% versus maxima of water level η during historical events. The left plots corresponds to values computed with a constant beach slope β = 0.09 (similar to Figure 7 without applying distribution correction). The right plots are obtained by computing the Run-up maximum run-up R2% by sampling one random beach slope for each event from a uniform distribution (with parameters min = 0.06 and max = 0.12). Each line corresponds to a different set of random slopes used to compute the run-up on the right panel.

Figure 4. The three steps for validating damage rules with method 1 : 1) apply the rule to the entire dataset, 2) cleanse the dates identified in order to count only one per event, 3) sort the non identified dates between dates arguably attachable to events (close in time) and totally unknown ones. The result can take the form of a count of events based on the damages index (0,1 or 2) if the event is existing or NI for ”Not identified”.

Figure 5. The two steps for validating damage rules with method 2 : 1) apply a threshold ue to the dataset to detect events at least separated by 36H (separation/merging procedure), 2) select one value by cluster by applying the rule function, 3) apply the rule damage threshold and count events. The result can take the form of a count of events based on the damages index (0,1 or 2) if the event is existing or NI for ”Not identified”.

Frequently asked questions

Q1. What have the authors contributed in "Coastal flooding event definition based on damages: case study of biarritz grande plage on the french basque coast" ?

This paper presents a method to include damage at the initial stage of coastal flooding events definition and in return periods computation. The methodology is illustrated within a local study carried out in Biarritz Grande Plage, a meso-tidal, wave dominated beach located on the french basque coast in the south west of France. A statistical analysis was first carried out to find the best combination of source variables explaining the reported damages for the identified storms. Most of the rules formerly studied, except the ones using wave period only as wave parameter, were able to correctly perform this task. Nevertheless, the discrepancy still observed among the different rules calls for further work in this direction. 

Q2. What have the authors stated for future works in "Coastal flooding event definition based on damages: case study of biarritz grande plage on the french basque coast" ?

Then, the rules skill was retrospectively tested over the total time span, showing the existence of efficient rules, which could be potentially used for damage prediction for future events. Nevertheless, from the results of the paper, it seems that there is still significant work to be done to ensure that each individual storm potential impact is assessed accurately on an appropriate metric respecting the point of view defended in this paper. 

Q3. What is the test based on Kendall’s coefficient?

The test based on Kendall’s τ coefficient does not reject independence between the two variables composing the event dataset, allowing the use of equation (8) to estimate the joint probability. 

Q4. How many storms were observed at the Grande Plage?

The number of storms, for which only Biarritz was mentioned is 30 and the number of flood events at the Grande Plage is 13, which represents one third of the storms observed over the period 1950-2014. 

Q5. What is the main reason for the increasing population on the coast?

Whereas the problem is more and more acute due to the growing coastal population and associated infrastructures [1], climate change also increases pressure on the coast by sea level rise which allows the ocean to reach usually protected areas [2]. 

Q6. What is the main limitation of the paper?

another limitation of this study is the unknownbeach profile variability over time during the studied period and its effect on the damages induced by coastal flooding. 

Q7. What is the rule for a storm?

The best rule was the one based on wave energy flux (or equivalently the significant wave height) and water level maxima over the event.• 

Q8. What is the main reason why RP should be used in applied studies?

Stakeholders being mostly concerned by the impacts to the coast and population, RP should reflect this aspect in applied studies. 

Q9. What is the effect of the analysis of quantile graphs on the sea state?

The analysis of quantile/quantile graphs shows an underestimation by the model for extreme sea states, detrimental to this type of study precisely focused on these events. 

Q10. What is the return period of the event x > x,y > y?

The return period of the event {x > x,y > y} is thennaturally computed asRP(x,y) = µP̂r(x > x,y > y)= µP̂r(x > x)P̂r(y > y)= µ{1− Ĝx(x)}{1− Ĝy(y)} ,(8)whereµ = 2015−1949+1∑t∈T 1{x(t)> ux,y(t)> uy} .