Measuring compound flood potential from river discharge and storm surge extremes at the global scale
Measuring compound flood potential from river discharge and storm surge extremes at the global scale
The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.
489-504
Couasnon, Anais
3cd73383-6489-4baa-914f-1fd4ff4da620
Eilander, Dirk
01cd09ca-8639-4cd2-9acd-67c874298a0e
Muis, Sanne
d73531db-78f1-4f65-b1a0-f96ae1c46377
Veldkamp, Ted I.E.
644baba8-7d4c-4847-8ef5-71703e8c0b0a
Haigh, Ivan D.
945ff20a-589c-47b7-b06f-61804367eb2d
Wahl, Thomas
6506794a-1f35-4803-b7f7-98702e57e667
Winsemius, Hessel C.
0934e633-e76e-4dfa-ad4a-2839fbe60f3a
Ward, Philip J.
ff039336-2f71-44da-b28f-feab4875a944
21 February 2020
Couasnon, Anais
3cd73383-6489-4baa-914f-1fd4ff4da620
Eilander, Dirk
01cd09ca-8639-4cd2-9acd-67c874298a0e
Muis, Sanne
d73531db-78f1-4f65-b1a0-f96ae1c46377
Veldkamp, Ted I.E.
644baba8-7d4c-4847-8ef5-71703e8c0b0a
Haigh, Ivan D.
945ff20a-589c-47b7-b06f-61804367eb2d
Wahl, Thomas
6506794a-1f35-4803-b7f7-98702e57e667
Winsemius, Hessel C.
0934e633-e76e-4dfa-ad4a-2839fbe60f3a
Ward, Philip J.
ff039336-2f71-44da-b28f-feab4875a944
Couasnon, Anais, Eilander, Dirk, Muis, Sanne, Veldkamp, Ted I.E., Haigh, Ivan D., Wahl, Thomas, Winsemius, Hessel C. and Ward, Philip J.
(2020)
Measuring compound flood potential from river discharge and storm surge extremes at the global scale.
Natural Hazards and Earth System Sciences, 20 (2), .
(doi:10.5194/nhess-20-489-2020).
Abstract
The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.
Text
Couasnon_al_2019_CompoundFloodPotential_final
- Author's Original
Text
nhess-20-489-2020
- Version of Record
More information
Accepted/In Press date: 16 November 2019
Published date: 21 February 2020
Identifiers
Local EPrints ID: 438937
URI: http://eprints.soton.ac.uk/id/eprint/438937
ISSN: 1684-9981
PURE UUID: f841f6f2-65f1-489c-82f9-c1eec6da9110
Catalogue record
Date deposited: 27 Mar 2020 17:30
Last modified: 06 Jun 2024 01:44
Export record
Altmetrics
Contributors
Author:
Anais Couasnon
Author:
Dirk Eilander
Author:
Sanne Muis
Author:
Ted I.E. Veldkamp
Author:
Hessel C. Winsemius
Author:
Philip J. Ward
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics