Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2681-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-2681-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multivariate statistical modelling of the drivers of compound flood events in south Florida
Robert Jane
CORRESPONDING AUTHOR
Civil, Environmental and Construction Engineering and National Center for Integrated Coastal Research, University of Central Florida, 12800 Pegasus Drive, Orlando, FL 32816, USA
Luis Cadavid
Operational Hydraulics Unit – Applied Hydraulics Section, South Florida Water Management District, West Palm Beach, FL 35406, USA
Jayantha Obeysekera
Sea Level Solutions Center, Florida International University, Miami, FL 33199, USA
Thomas Wahl
Civil, Environmental and Construction Engineering and National Center for Integrated Coastal Research, University of Central Florida, 12800 Pegasus Drive, Orlando, FL 32816, USA
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53 citations as recorded by crossref.
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- Compound flood hazard at Lake Como, Italy, is driven by temporal clustering of rainfall events F. Banfi & C. De Michele 10.1038/s43247-022-00557-9
- Assessing the compound flood risk in coastal areas: Framework formulation and demonstration M. Mitu et al. 10.1016/j.jhydrol.2023.130278
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- Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China C. Zhang et al. 10.1007/s11069-021-04993-2
- Uncovering the Dynamics of Multi‐Sector Impacts of Hydrological Extremes: A Methods Overview M. de Brito et al. 10.1029/2023EF003906
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- Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework S. Latif & S. Simonovic 10.3390/hydrology9120221
- Compound flood modeling framework for surface–subsurface water interactions F. Peña et al. 10.5194/nhess-22-775-2022
- Compound flood models in coastal areas: a review of methods and uncertainty analysis K. Xu et al. 10.1007/s11069-022-05683-3
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- Modelling compound flooding: a case study from Jakarta, Indonesia W. Bennett et al. 10.1007/s11069-023-06001-1
- Evolution of Frequency and Intensity of Concurrent Heavy Precipitation and Storm Surge at the Global Scale: Implications for Compound Floods Y. Lai et al. 10.3389/feart.2021.660359
- The timing of decreasing coastal flood protection due to sea-level rise T. Hermans et al. 10.1038/s41558-023-01616-5
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- Investigating compound flooding in a low elevation coastal karst environment using multivariate statistical and 2D hydrodynamic modeling F. Peña et al. 10.1016/j.wace.2022.100534
- Data From the Drain: A Sensor Framework That Captures Multiple Drivers of Chronic Coastal Floods A. Gold et al. 10.1029/2022WR032392
- Compounding joint impact of rainfall, storm surge and river discharge on coastal flood risk: an approach based on 3D fully nested Archimedean copulas S. Latif & S. Simonovic 10.1007/s12665-022-10719-9
- Application of nonstationary extreme value analysis in the coastal environment – A systematic literature review S. Radfar et al. 10.1016/j.wace.2023.100575
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- Estimating the probability of compound floods in estuarine regions W. Wu et al. 10.5194/hess-25-2821-2021
- Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints V. Santos et al. 10.1111/jfr3.12749
- Characterizing compound flooding potential and the corresponding driving mechanisms across coastal environments F. Jalili Pirani & M. Najafi 10.1007/s00477-022-02374-0
- Dune Dynamics Drive Discontinuous Barrier Retreat I. Reeves et al. 10.1029/2021GL092958
- Modes of climate mobility under sea-level rise N. Seeteram et al. 10.1088/1748-9326/acfe22
- Study on multiscale-multivariate prediction and risk assessment of urban flood Y. Wang et al. 10.1016/j.envsoft.2024.105958
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Latest update: 04 Nov 2024
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.
Full dependence is assumed between drivers in flood protection assessments of coastal water...
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