Articles | Volume 24, issue 11
https://doi.org/10.5194/nhess-24-4091-2024
© Author(s) 2024. 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-24-4091-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Nov 2024
Research article |
| 27 Nov 2024
| 27 Nov 2024
A multivariate statistical framework for mixed storm types in compound flood analysis
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA
Thomas Wahl
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA
Sara Santamaria-Aguilar
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA
Robert Jane
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL 32816, USA
James F. Booth
Department of Earth and Atmospheric Sciences, City University of New York, City College, New York, NY 10031, USA
Hanbeen Kim
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA
High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
Gabriele Villarini
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA
High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
Viewed
Total article views: 5,999 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 May 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,845 | 1,955 | 199 | 5,999 | 348 | 230 | 316 |
- HTML: 3,845
- PDF: 1,955
- XML: 199
- Total: 5,999
- Supplement: 348
- BibTeX: 230
- EndNote: 316
Total article views: 2,193 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Nov 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,712 | 417 | 64 | 2,193 | 122 | 76 | 105 |
- HTML: 1,712
- PDF: 417
- XML: 64
- Total: 2,193
- Supplement: 122
- BibTeX: 76
- EndNote: 105
Total article views: 3,806 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 May 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 2,133 | 1,538 | 135 | 3,806 | 226 | 154 | 211 |
- HTML: 2,133
- PDF: 1,538
- XML: 135
- Total: 3,806
- Supplement: 226
- BibTeX: 154
- EndNote: 211
Viewed (geographical distribution)
Total article views: 5,999 (including HTML, PDF, and XML)
Thereof 5,943 with geography defined
and 56 with unknown origin.
Total article views: 2,193 (including HTML, PDF, and XML)
Thereof 2,153 with geography defined
and 40 with unknown origin.
Total article views: 3,806 (including HTML, PDF, and XML)
Thereof 3,790 with geography defined
and 16 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
12 citations as recorded by crossref.
- MultiHazard: Copula-based Joint Probability Analysis in R R. Jane et al. https://doi.org/10.21105/joss.08350
- A cluster-based temporal attention approach for predicting cyclone-induced compound flood dynamics S. Daramola et al. https://doi.org/10.1016/j.envsoft.2025.106499
- Establishing coastal water level magnitude-duration-frequency curves for infrastructure design M. Sohrabi et al. https://doi.org/10.1016/j.advwatres.2025.105179
- Unlocking the benefits of transparent and reusable science for climate risk management A. Pollack et al. https://doi.org/10.1073/pnas.2422157123
- Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut R. Glas et al. https://doi.org/10.5194/nhess-26-2169-2026
- Large discrepancies between event- and response-based compound flood hazard estimates S. Santamaria-Aguilar et al. https://doi.org/10.5194/nhess-26-571-2026
- Inundación compuesta en el estuario de Santoña: umbrales bivariados y su aplicación en alertas tempranas D. Gómez-Rave et al. https://doi.org/10.4995/ia.2025.23025
- Multivariate design events for compound flooding analysis in estuaries D. Gomez Rave et al. https://doi.org/10.1016/j.coastaleng.2025.104850
- Teleconnection driven drought to flood sequences and spatially compound events in urban water systems for resilient cities K. Haddad https://doi.org/10.1007/s44327-026-00333-w
- Generating Boundary Conditions for Compound Flood Modeling in a Probabilistic Framework P. Maduwantha et al. https://doi.org/10.5194/hess-30-401-2026
- Assessing the spatial correlation of potential compound flooding in the United States H. Li et al. https://doi.org/10.5194/nhess-26-391-2026
- Unraveling uncertainty in compound flood modeling: sensitivity of simulations to forcings and model parameters C. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135424
12 citations as recorded by crossref.
- MultiHazard: Copula-based Joint Probability Analysis in R R. Jane et al. https://doi.org/10.21105/joss.08350
- A cluster-based temporal attention approach for predicting cyclone-induced compound flood dynamics S. Daramola et al. https://doi.org/10.1016/j.envsoft.2025.106499
- Establishing coastal water level magnitude-duration-frequency curves for infrastructure design M. Sohrabi et al. https://doi.org/10.1016/j.advwatres.2025.105179
- Unlocking the benefits of transparent and reusable science for climate risk management A. Pollack et al. https://doi.org/10.1073/pnas.2422157123
- Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut R. Glas et al. https://doi.org/10.5194/nhess-26-2169-2026
- Large discrepancies between event- and response-based compound flood hazard estimates S. Santamaria-Aguilar et al. https://doi.org/10.5194/nhess-26-571-2026
- Inundación compuesta en el estuario de Santoña: umbrales bivariados y su aplicación en alertas tempranas D. Gómez-Rave et al. https://doi.org/10.4995/ia.2025.23025
- Multivariate design events for compound flooding analysis in estuaries D. Gomez Rave et al. https://doi.org/10.1016/j.coastaleng.2025.104850
- Teleconnection driven drought to flood sequences and spatially compound events in urban water systems for resilient cities K. Haddad https://doi.org/10.1007/s44327-026-00333-w
- Generating Boundary Conditions for Compound Flood Modeling in a Probabilistic Framework P. Maduwantha et al. https://doi.org/10.5194/hess-30-401-2026
- Assessing the spatial correlation of potential compound flooding in the United States H. Li et al. https://doi.org/10.5194/nhess-26-391-2026
- Unraveling uncertainty in compound flood modeling: sensitivity of simulations to forcings and model parameters C. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135424
Saved (final revised paper)
Latest update: 03 Aug 2026
Short summary
When assessing the likelihood of compound flooding, most studies ignore that it can arise from different storm types with distinct statistical characteristics. Here, we present a new statistical framework that accounts for these differences and shows how neglecting these can impact the likelihood of compound flood potential.
When assessing the likelihood of compound flooding, most studies ignore that it can arise from...
Altmetrics
Final-revised paper
Preprint