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

Serinaldi, F; Loecker, F; Kilsby, CG; Bast, H

doi:10.1007/s11069-018-3374-0

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

Lookup NU author(s): Dr Francesco Serinaldi, Professor Chris Kilsby

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This is the final published version of an article that has been published in its final definitive form by Springer, 2018.

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Abstract

Duration is a key characteristic of floods influencing 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 hours (one week), regardless of the hydrological properties characterizing different areas. In this study, we firstly perform a synoptic-scale exploratory analysis to investigate duration and magnitude of large flood events 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 macro-areas that are more/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 spatio-temporal extent of flooding hazard.