Articles | Volume 15, issue 6
https://doi.org/10.5194/nhess-15-1135-2015
https://doi.org/10.5194/nhess-15-1135-2015
Research article
 | 
05 Jun 2015
Research article |  | 05 Jun 2015

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

T. Bulteau, D. Idier, J. Lambert, and M. Garcin

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Cited articles

Arns, A., Wahl, T., Haigh, I. D., Jensen, J., and Pattiaratchi, C.: Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practice, Coast. Eng., 81, 51–66, https://doi.org/10.1016/j.coastaleng.2013.07.003, 2013.
Baart, F., Bakker, M. A. J., van Dongeren, A., den Heijer, C., van Heteren, S., Smit, M. W. J., van Koningsveld, M., and Pool, A.: Using the 18th century storm-surge data from the Dutch Coast to improve the confidence in flood-risk estimates, Nat. Hazards Earth Syst. Sci., 11, 2791–2801, https://doi.org/10.5194/nhess-11-2791-2011, 2011.
Batstone, C., Lawless, M., Tawn, J., Horsburgh, K., Blackman, D., McMillan, A., Worth, D., Laeger, S., and Hunt, T.: A UK best-practice approach for extreme sea-level analysis along complex topographic coastlines, Ocean Eng., 71, 28–39, https://doi.org/10.1016/j.oceaneng.2013.02.003, 2013.
Benito, G., Lang, M., Barriendos, M., Llasat, M., Frances, F., Ouarda, T., Thorndycraft, V., Enzel, Y., Bardossy, A., Couer, D., and Bobbe, B.: Use of systematic, paleoflood and historical data for the improvement of flood risk estimation: review of scientific methods, Nat. Hazards, 31, 623–643, 2004.
Bertin, X., Bruneau, N., Breilh, J.-F., Fortunato, A.B., and Karpytchev, M.: Importance of wave age and resonance in storm surges: The case Xynthia, Bay of Biscay, Ocean Model., 42, 16–30, https://doi.org/10.1016/j.ocemod.2011.11.001, 2012.
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Short summary
Extreme value analyses of sea-level using tide-gauge measurements usually suffer from limited effective duration of observation which can result in large uncertainties, especially when outliers are present. To tackle this issue, a Bayesian MCMC method is developed integrating historical data in extreme sea-level analyses. A real case study shows a significant improvement in return values estimation and the usefulness of the Bayesian framework to predict future annual exceedance probabilities.
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