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

Assessing the spatial correlation of potential compound flooding in the United States
Huazhi Li, Robert A. Jane, Dirk Eilander, Alejandra R. Enríquez, Toon Haer, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2993,https://doi.org/10.5194/egusphere-2025-2993, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Generating Boundary Conditions for Compound Flood Modeling in a Probabilistic Framework
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, Sönke Dangendorf, Hanbeen Kim, and Gabriele Villarini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1557,https://doi.org/10.5194/egusphere-2025-1557, 2025
Short summary
A multivariate statistical framework for mixed storm types in compound flood analysis
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, James F. Booth, Hanbeen Kim, and Gabriele Villarini
Nat. Hazards Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/nhess-24-4091-2024,https://doi.org/10.5194/nhess-24-4091-2024, 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.
Share
Altmetrics
Final-revised paper
Preprint