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A comparative study of models to predict storm impact on beaches

Author

Listed:
  • Iñaki Santiago

    (Université de Pau et des Pays de l’Adour)

  • Denis Morichon

    (Université de Pau et des Pays de l’Adour)

  • Stéphane Abadie

    (Université de Pau et des Pays de l’Adour)

  • Ad J. H. M. Reniers

    (Delft University of Technology)

  • Pedro Liria

    (AZTI-Tecnalia Herrera Kaia)

Abstract

The storm impact scale of Sallenger (J Coast Res 890–895, 2000) was tested on a partially engineered beach. This scale is supposed to provide a convenient tool for coastal managers to categorize the storm impact at the shore. It is based on the relation between the elevation of storm wave runup and the elevation of a critical geomorphic or man-made structures in the present study. Two different approaches were tested to estimate the elevation of extreme storm wave runup: (1) a parametric model based on offshore wave conditions and local beach slope and (2) the XBeach process-based model that solves implicitly the runup. The study shows comparisons between impact regimes computed with the two methods and those derived from video observations acquired during 2 weeks while the site was battered by three consecutive storms. Storms scenario including wave conditions with higher return periods and different tidal range were also investigated. The advantages and disadvantages of the two methods used to compute extreme water level are then compared, and guidelines for the development of early warning system are drawn.

Suggested Citation

  • Iñaki Santiago & Denis Morichon & Stéphane Abadie & Ad J. H. M. Reniers & Pedro Liria, 2017. "A comparative study of models to predict storm impact on beaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 843-865, June.
    • Handle: RePEc:spr:nathaz:v:87:y:2017:i:2:d:10.1007_s11069-017-2830-6
    DOI: 10.1007/s11069-017-2830-6
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    Cited by:

    1. Aurélien Callens & Denis Morichon & Benoit Liquet, 2023. "Bayesian networks to predict storm impact using data from both monitoring networks and statistical learning methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(3), pages 2031-2050, February.

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