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Extreme events: a framework for assessing natural hazards

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  • Franck Mazas

    (Artelia)

Abstract

The two-step framework for over-threshold modelling of environmental extremes proposed in Bernardara et al. (Nat Hazards Earth Syst Sci 14:635–647, 2014) for univariate analyses is generalized to an event-based framework applicable to multivariate analyses. The distinction between sequential values (temporal observations at a given time step) and the event-describing values (such as storm peaks in univariate Peaks-Over-Threshold extrapolations) is further detailed and justified. The classification of multivariate analyses introduced in Mazas and Hamm (Coast Eng 122:44–59, 2017) is refined and linked to the meaning of the concepts of event, sampling and return period that is thoroughly examined, their entanglement being highlighted. In particular, sampling is shown to be equivalent to event definition, identification and description. Event and return period definition are also discussed with respect to the source phenomena or to response (or structure) phenomena. The extreme event approach is thus proposed as a comprehensive framework for univariate and multivariate analyses for assessing natural hazards, seemingly applicable to any field of environmental studies.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:98:y:2019:i:3:d:10.1007_s11069-019-03581-9
    DOI: 10.1007/s11069-019-03581-9
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    Cited by:

    1. 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.
    2. Chi-Hsiang Wang & John D. Holmes, 2020. "Exceedance rate, exceedance probability, and the duality of GEV and GPD for extreme hazard analysis," 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. 102(3), pages 1305-1321, July.
    3. Ivan D. Haigh & Thomas Wahl, 2019. "Advances in extreme value analysis and application to 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 819-822, September.
    4. Zakari Aretouyap & Franck Eitel G Kemgang & Janvier K Domra & Dieudonne Bisso & Philippe N Njandjock, 2021. "Understanding the occurrences of fault and landslide in the region of West-Cameroon using remote sensing and GIS techniques," 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. 109(2), pages 1589-1602, November.
    5. Xavier Silvani & Khaldoun Agha & Steven Martin & Daphné Goirand & Nicolas Bulté, 2022. "IEEE 802.11 Wireless sensor network for hazard monitoring and mitigation," 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. 114(3), pages 3545-3574, December.

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