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Flood propagation and duration in large river basins: a data-driven analysis for reinsurance purposes

Author

Listed:
  • Francesco Serinaldi

    (Newcastle University
    Willis Research Network)

  • Florian Loecker

    (Willis Towers Watson
    AIR Worldwide)

  • Chris G. Kilsby

    (Newcastle University
    Willis Research Network)

  • Hubert Bast

    (Willis Towers Watson)

Abstract

Duration is a key characteristic of floods influencing the design of protection infrastructures for prevention, deployment of rescue resources during the emergency, and repartition of damage costs in the aftermath. The latter financial aspect mainly relies on the insurance industry and allows the transfer of damage costs from the public sector to the private capital market. In this context, the cost of catastrophes affecting a large amount of insured properties is partly or totally transferred from insurance companies to reinsurance companies by contracts that define the portion of transferred costs according to the temporal extent of the flood events synthesized in the so-called hours clause. However, hours clauses imply standard flood event durations, such as 168 h (1 week), regardless of the hydrological properties characterizing different areas. In this study, we firstly perform a synoptic-scale exploratory analysis to investigate the duration and magnitude of large flood events that occurred around the world and in Europe between 1985 and 2016, and then we present a data-driven procedure devised to compute flood duration by tracking flood peaks along a river network. The exploratory analysis highlights the link of flood duration and magnitude with flood generation mechanism, thus allowing the identification of regions that are more or less prone to long-lasting events exceeding the standard hours clauses. The flood tracking procedure is applied to seven of the largest river basins in Central and Eastern Europe (Danube, Rhine, Elbe, Weser, Rhone, Loire, and Garonne). It correctly identifies major flood events and enables the definition of the probability distribution of the flood propagation time and its sampling uncertainty. Overall, we provide information and analysis tools readily applicable to improve reinsurance practices with respect to spatiotemporal extent of flooding hazard.

Suggested Citation

  • Francesco Serinaldi & Florian Loecker & Chris G. Kilsby & Hubert Bast, 2018. "Flood propagation and duration in large river basins: a data-driven analysis for reinsurance purposes," 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. 94(1), pages 71-92, October.
  • Handle: RePEc:spr:nathaz:v:94:y:2018:i:1:d:10.1007_s11069-018-3374-0
    DOI: 10.1007/s11069-018-3374-0
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    References listed on IDEAS

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    2. Hossein Bonakdari & Andrew D. Binns & Bahram Gharabaghi, 2020. "A Comparative Study of Linear Stochastic with Nonlinear Daily River Discharge Forecast Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(11), pages 3689-3708, September.
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    4. Jonah S. McLeod & James Wood & Sinéad J. Lyster & Jeffery M. Valenza & Alan R. T. Spencer & Alexander C. Whittaker, 2023. "Quantitative constraints on flood variability in the rock record," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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