Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries

Journal Article (2018)
Authors

P. J. Ward (Vrije Universiteit Amsterdam)

Anais Couasnon (Vrije Universiteit Amsterdam)

D. Eilander (Deltares, Vrije Universiteit Amsterdam)

Ivan D Haigh (University of Southampton)

Alistair Hendry (University of Southampton)

Sanne Muis (Deltares, Vrije Universiteit Amsterdam)

Ted I.E. Veldkamp (Vrije Universiteit Amsterdam, International Institute for Applied Systems Analysis)

Hessel Winsemius (Vrije Universiteit Amsterdam, Deltares, TU Delft - Water Resources)

Thomas Wahl (University of Central Florida)

Research Group
Water Resources
Copyright
© 2018 Philip J. Ward, Anais Couasnon, Dirk Eilander, Ivan D Haigh, Alistair Hendry, Sanne Muis, Ted I.E. Veldkamp, H.C. Winsemius, Thomas Wahl
To reference this document use:
https://doi.org/10.1088/1748-9326/aad400
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Philip J. Ward, Anais Couasnon, Dirk Eilander, Ivan D Haigh, Alistair Hendry, Sanne Muis, Ted I.E. Veldkamp, H.C. Winsemius, Thomas Wahl
Research Group
Water Resources
Volume number
13
DOI:
https://doi.org/10.1088/1748-9326/aad400
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Abstract

When river and coastal floods coincide, their impacts are often worse than when they occur in isolation; such floods are examples of ‘compound events’. To better understand the impacts of these compound events, we require an improved understanding of the dependence between coastal and river flooding on a global scale. Therefore, in this letter, we: provide the first assessment and mapping of the dependence between observed high sea-levels and high river discharge for deltas and estuaries around the globe; and demonstrate how this dependencemay influence the joint probability of floods exceeding both the design discharge and design sea-level. The research was carried out by analysing
the statistical dependence between observed sea-levels (and skew surge) from the GESLA-2 dataset, and river discharge using gauged data from the Global Runoff Data Centre, for 187 combinations of stations across the globe. Dependence was assessed using Kendall’s rank correlation coefficient (휏)
and copula models. We find significant dependence for skew surge conditional on annual maximum discharge at 22% of the stations studied, and for discharge conditional on annual maximum skew surge at 36% of the stations studied. Allowing a time-lag between the two variables up to 5 days, we find significant dependence for skew surge conditional on annual maximum discharge at 56% of stations, and for discharge conditional on annual maximum skew surge at 54% of stations. Using copula models, we show that the joint exceedance probability of events in which both the design discharge and design sea-level are exceeded can be several magnitudes higher when the dependence is considered, compared to when independence is assumed. We discuss several implications, showing that flood risk assessments in these regions should correctly account for these joint exceedance probabilities.