Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

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

  • 96 Accesses

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.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

References

  1. Abberger K (2005) A simple graphical method to explore tail-dependence in stock-return pairs. Appl Financ Econ 15(1):43–51. https://doi.org/10.1080/0960310042000280429

  2. Apel H, Martinez-Trepat O, Hung NN, Chinh DT, Merz B, Dung NV (2016) Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta. Vietnam. Nat Hazards Earth Syst Sci 16(4):941–961. https://doi.org/10.5194/nhess-16-941-2016

  3. ASN (2013) Protection des installations nucleaires de base contre les inondations externes, guide no. 13, 40 pp. (in french). Technical report, ASN (Nuclear Safety Authority)

  4. Beauval C (2003) Analyse des incertitudes dans une estimation probabiliste de l’aléa sismique, exemple de la france. Ph.D. thesis, Université Joseph-Fourier - Grenoble I

  5. Ben Daoued A, Guimier L, Hamdi Y, Duluc CM, Rebour V (2016) Development of a probabilistic flood hazard assessment (PFHA) for the nuclear safety. In: EGU general assembly

  6. Ben Daoued A, Hamdi Y, Mouhous-Voyneau N, Sergent P (2018) Modelling dependence and coincidence of marine flooding phenomena: methodology and simplified case study in Le Havre in France. In: EGU general assembly

  7. Bensi M, Kanney J (2015) Development of a framework for probabilistic storm surge hazard assessment for united states nuclear power plants. In: SMiRT-23

  8. Bernardara P, Mazas F, Kergadallan X, Hamm L (2014) A two-step framework for over-threshold modelling of environmental extremes. Nat Hazards Earth Syst Sci. https://doi.org/10.5194/nhess-14-635-2014

  9. Bozzoni F, Corigliano M, Lai C, Salazar W, Scandella L, Zuccolo E, Latchman J, Lynch L, Robertson R (2011) Probabilistic seismic hazard assessment at the Eastern Caribbean Islands. Bull Seismol Soc Am 101:2499–2521. https://doi.org/10.1785/0120100208

  10. Chebana F, Ouarda T (2011) Multivariate quantiles in hydrological frequency analysis. Environmetrics 22(1):63–78

  11. Coles S (2001) An introduction to statistical modeling of extreme values. Springer series in statistics. Springer, London

  12. DEFRA (2005) Use of joint probability methods in flood management—a guide to best practice. Technical report, DEFRA/Environment Agency

  13. Deglaire M (2010) Le havre—etude sur le risque de submersion marine. Technical report, Université Paris 1 Panthéon-Sorbonne/DIRM-CODAH

  14. Dung N, Merz B, Bardossy A, Apel H (2015) Handling uncertainty in bivariate quantile estimation—an application to flood hazard analysis in the Mekong Delta. J Hydrol 527:704–717

  15. Elineau S, Duperret A, Mallet P, Caspar R (2010) Le havre : Une ville cotiere soumise aux submersions marines et aux instabilites de falaises littorales. In: Journées Impacts du changement climatique sur les risques cotiers

  16. Elineau S, Duperret A, Mallet P (2013) Coastal floods along the english channel: the study case of Le Havre town (NW France). Caribbean Waves. (poster)

  17. Gupta I (2002) The state of the art in seismic hazard analysis. ISET J Earthq Technol 9(4):311–346

  18. Gupta I (2007) Probabilistic seismic hazard analysis method for mapping of spectral amplitudes and other design-specific quantities to estimate the earthquake effects on man-made structures. ISET J Earthq Technol 44(1):127–167

  19. Hamdi Y, Bardet L, Duluc CM, Rebour V (2014) Extreme storm surges: a comparative study of frequency analysis approaches. Nat Hazards Earth Syst Sci. https://doi.org/10.5194/nhess-14-2053-2014

  20. Hawkes PJ, Gouldby BP, Tawn JA, Owen MW (2002) The joint probability of waves and water levels in coastal engineering design. J Hydraul Res 40(3):241–251. https://doi.org/10.1080/00221680209499940

  21. Hebert H, Abadie S, Benoit M, Creach R, Duluc CM, Gailler A, Garziglia S, Lemoine A, Loevenbruck A, Macary O, Maspataud A, Marcer R, Morichon D, Pedreros R, Rebour V, Ricchiuto M, Silva Jacinto R, Terrier M, Toucanne S, Hayashi Y (2014) Le projet tandem (tsunamis en atlantique et manche : definition des effets par modelisation) (2014–2017) : enjeux pour les vulnerabilites littorales aux tsunamis

  22. Horrillo-Caraballo J, Reeve D, Simmonds D, Pan S, Fox A, Thompson R, Hoggart S, Kwan SS, Greaves D (2013) Application of a source–pathway–receptor–consequence (SPRC) methodology to the Teign Estuary, UK. J Coastal Res I65:1939–1944. https://doi.org/10.2112/SI65-328.1

  23. IAEA (1993) Probabilistic safety assessment for seismic events. Technical report, International Atomic Energy Agency (IAEA)

  24. IPSN (2000) Rapport sur l’inondation du site du blayais survenue le 27 décembre 1999. Technical report, Institut de Protection et Sûreté Nucléaire (IPSN)

  25. Klugel JU (2013) Probabilistic safety analysis of external floods—method and application. Kerntechnik 78(2):127–136. https://doi.org/10.3139/124.110335

  26. Lang M, Rasmussen P, Oberlin G, Bobée B (1997) Echantillonnage par valeurs supérieures à un seuil: modélisation des occurrences par la méthode du renouvellement. Revue des sciences de l’eau 10(3):279–320. https://doi.org/10.7202/705281ar

  27. Maspataud A, Elineau S, Duperret A, Ruz MH, Mallet P (2016) Impacts de niveaux d’eau extremes sur deux villes portuaires de la manche et mer du nord : Le havre et dunkerque. Journées REFMAR

  28. Mazas F (2017) Extreme meteo-oceanic events. Theses, Université Paris-Est https://pastel.archives-ouvertes.fr/tel-01743728

  29. Mazas F (2019) Extreme events: a framework for assessing natural hazards. Nat Hazards. https://doi.org/10.1007/s11069-019-03581-9

  30. McGuire RK, Arabasz WJ (1990) An introduction to probabilistic seismic hazard analysis. In: Geotechnical and environmental geophysics. Society of Exploration Geophysicists, pp 333–354. https://doi.org/10.1190/1.9781560802785.ch12

  31. Narayan S, Hanson S, Nicholls R, Clarke D (2011) Use of the source–pathway–receptor–consequence model in coastal flood risk assessment. EGU 2011, Vienna, Austria

  32. Norberto CNC, Jeffrey AM, Victor MG, Andrew TC (2015) Coastal storm hazards from Virginia to Maine. Technical report, US Army Corps of Engineers (USACE)

  33. Rebour V, Georgescu G, Leteinturier D, Raimond E, La Rovere S, Bernadara P, Vasseur D, Brinkman H, Groudev P, Ivanov I, Turschmann M, Sperbeck S, Potempski S, Hirata K, Kumar M (2016) Report 2: guidance document on practices to model and implement external flooding hazards in extended PSA. Technical report, IRSN–PSN–RES–SAG–PSN–RES–SAG

  34. Salvadori G, De Michele C (2004) Frequency analysis via copulas: theoretical aspects and applications to hydrological events. Water Resour Res 40

  35. Salvadori G, de Michele C, Durante F (2011) On the return period and design in a multivariate framework. Hydrol Earth Syst Sci 15:3293–3305. https://doi.org/10.5194/hess-15-3293-2011

  36. Sergent P, Prevot G, Mattarolo G, Luck M, Brossard J, Nguyen T, Morel G, Mar NF, Benoit M, Ropert F, Guillou N, Bouttes F, Kergadallan X, Trichet JJ, Delisle JR, Menon JM, Mallet P, Voyneau N, Lam M, Le Banner G (2012) Projet sao polo adaptation des structures cotieres au changement climatique

  37. Serinaldi F, Bardossy A, Kilsby CG (2015) Upper tail dependence in rainfall extremes: would we know it if we saw it? Stoch Environ Res Risk Assess 29(4):1211–1233. https://doi.org/10.1007/s00477-014-0946-8

  38. Sklar M (1959) Fonctions de répartition à n dimensions et leurs marges. Publ Inst Stat Univ Paris 8:229–231

  39. U.S. Nuclear Regulatory Commission (2014) Probabilistic flood hazard assessment research plan, ADAMS accession no. ML14296A442

  40. U.S. Nuclear Regulatory Commission (2015) Workshop on probabilistic flood hazard assessment. Accessed 24 May 2015

  41. Volpi E, Fiori A (2012) Design event selection in bivariate hydrological frequency analysis. Hydrol Sci J 57(8):1506–1515. https://doi.org/10.1080/02626667.2012.726357

  42. Wang J, Wan Tsang W, Marsaglia G (2003) Evaluating kolmogorov’s distribution. J Stat Softw 8:1–4. https://doi.org/10.18637/jss.v008.i18

  43. Yan B, Chen L (2013) Coincidence probability of precipitation for the middle route of South-to-North water transfer project in China. J Hydrol 499:19–26. https://doi.org/10.1016/j.jhydrol.2013.06.040

Download references

Acknowledgements

The authors are grateful to the SHOM (Service Hydrographique et Océanographique de la Marine) and Météo-France for providing data. Thanks to the CODAH for their collaboration and for providing the hydraulic model of Le Havre.

Author information

Correspondence to Amine Ben Daoued.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ben Daoued, A., Mouhous-Voyneau, N., Hamdi, Y. et al. Modelling coincidence and dependence of flood hazard phenomena in a Probabilistic Flood Hazard Assessment (PFHA) framework: case study in Le Havre. Nat Hazards 100, 1059–1088 (2020). https://doi.org/10.1007/s11069-019-03845-4

Download citation

Keywords

  • PFHA
  • Joint probability
  • Dependence
  • Coincidence
  • Hazard curve
  • Aggregation