Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2681-2020
https://doi.org/10.5194/nhess-20-2681-2020
Research article
 | 
10 Oct 2020
Research article |  | 10 Oct 2020

Multivariate statistical modelling of the drivers of compound flood events in south Florida

Robert Jane, Luis Cadavid, Jayantha Obeysekera, and Thomas Wahl

Related authors

A multivariate statistical framework for mixed populations in compound flood analysis
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Andrew Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
EGUsphere, https://doi.org/10.5194/egusphere-2024-1122,https://doi.org/10.5194/egusphere-2024-1122, 2024
Short summary

Related subject area

Hydrological Hazards
Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024,https://doi.org/10.5194/nhess-24-2215-2024, 2024
Short summary
A downward-counterfactual analysis of flash floods in Germany
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024,https://doi.org/10.5194/nhess-24-2147-2024, 2024
Short summary
Hyper-resolution flood hazard mapping at the national scale
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024,https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary
Compound droughts under climate change in Switzerland
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024,https://doi.org/10.5194/nhess-24-1975-2024, 2024
Short summary
Brief communication: SWM – stochastic weather model for precipitation-related hazard assessments using ERA5-Land data
Melody Gwyneth Whitehead and Mark Stephen Bebbington
Nat. Hazards Earth Syst. Sci., 24, 1929–1935, https://doi.org/10.5194/nhess-24-1929-2024,https://doi.org/10.5194/nhess-24-1929-2024, 2024
Short summary

Cited articles

Aas, K. and Berg, D.: Models for construction of multivariate dependence – a comparison study, Eur. J. Financ., 15, 639–659, 2009. 
Aas, K., Czado, C., Frigessi, A., and Bakken, H.: Pair copula constructions of multiple dependence, Insurance: Math. Econ., 44, 182–198, 2009. 
Arns, A., Wahl, T., Haigh, I. D., Jensen, J., and Pattiaratchi, C.: Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise, Coast. Eng., 81, 51–66, 2013. 
Bedford, T. and Cooke, R. M.: Probability density decomposition for conditionally dependent random variables modeled by vines, Ann. Math. Artif. Intel., 32, 245–268, 2001. 
Bedford, T. and Cooke, R. M.: Vines – a new graphical model for dependent random variables, Ann. Stat., 30, 1031–1068, 2002. 
Download
Short summary
Full dependence is assumed between drivers in flood protection assessments of coastal water control structures in south Florida. A 2-D analysis of rainfall and coastal water level showed that the magnitude of the conservative assumption in the original design is highly sensitive to the regional sea level rise projection considered. The vine copula and HT04 model outperformed five higher-dimensional copulas in capturing the dependence between rainfall, coastal water level, and groundwater level.
Altmetrics
Final-revised paper
Preprint