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Modelling coincidence and dependence of flood hazard phenomena in a Probabilistic Flood Hazard Assessment (PFHA) framework: case study in Le Havre

Author

Listed:
  • Amine Ben Daoued

    (Sorbonne University, Université de Technologie de Compiègne)

  • Nassima Mouhous-Voyneau

    (Sorbonne University, Université de Technologie de Compiègne)

  • Yasser Hamdi

    (Institute for Radiological Protection and Nuclear Safety)

  • Claire-Marie Duluc

    (Institute for Radiological Protection and Nuclear Safety)

  • Philippe Sergent

    (Centre d’études et d’expertise sur les risques, l’environnement, la mobilité et l’aménagement (Cerema))

Abstract

Many coastal urban areas and many coastal facilities must be protected against pluvial and marine floods, as their location near the sea is necessary. As part of the development of a Probabilistic Flood Hazard Approach (PFHA), several flood phenomena have to be modelled at the same time (or with an offset time) to estimate the contribution of each one. Modelling the combination and the dependence of several flooding sources is a key issue in the context of a PFHA. As coastal zones in France are densely populated, marine flooding represents a natural hazard threatening the coastal populations and facilities in several areas along the shore. Indeed, marine flooding is the most important source of coastal lowlands inundations. It is mainly generated by storm action that makes sea level rise above the tide. Furthermore, when combined with rainfall, coastal flooding can be more consequent. While there are several approaches to analyse and characterize marine flooding hazard with either extreme sea levels or intense rainfall, only few studies combine these two phenomena in a PFHA framework. Thus this study aims to develop a method for the analysis of a combined action of rainfall and sea level. This analysis is performed on the city of Le Havre, a French urban city on the English Channel coast, as a case study. In this work, we have used deterministic materials for rainfall and sea level modelling and proposed a new approach for estimating the probabilities of flooding.

Suggested Citation

  • Amine Ben Daoued & Nassima Mouhous-Voyneau & Yasser Hamdi & Claire-Marie Duluc & Philippe Sergent, 2020. "Modelling coincidence and dependence of flood hazard phenomena in a Probabilistic Flood Hazard Assessment (PFHA) framework: case study in Le Havre," 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. 100(3), pages 1059-1088, February.
    • Handle: RePEc:spr:nathaz:v:100:y:2020:i:3:d:10.1007_s11069-019-03845-4
    DOI: 10.1007/s11069-019-03845-4
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    References listed on IDEAS

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    1. Franck Mazas, 2019. "Extreme events: a framework for assessing natural hazards," 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. 98(3), pages 823-848, September.
    2. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
    3. Abberger, Klaus, 2004. "A simple graphical method to explore tail-dependence in stock-return pairs," CoFE Discussion Papers 04/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
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