Articles | Volume 22, issue 3
https://doi.org/10.5194/nhess-22-1109-2022
© Author(s) 2022. 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-22-1109-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Apr 2022
Research article |
| 01 Apr 2022
| 01 Apr 2022
Extreme-coastal-water-level estimation and projection: a comparison of statistical methods
Maria Francesca Caruso
CORRESPONDING AUTHOR
Department of Civil, Architectural, and Environmental Engineering, University of Padua, 35131, Padua, Italy
Marco Marani
Department of Civil, Architectural, and Environmental Engineering, University of Padua, 35131, Padua, Italy
Earth and Climate Sciences Division, Duke University, Durham, NC, USA
Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA
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Cited
16 citations as recorded by crossref.
- Nonstationary hydrological frequency analysis using the Metastatistical extreme value distribution C. Vidrio-Sahagún et al. 10.1016/j.advwatres.2023.104460
- An efficient metamodel to downscale total water level in open beaches M. Zornoza-Aguado et al. 10.1016/j.ecss.2024.108705
- A data-driven framework for enhancing coastal flood resilience in resource-crunched developing nations A. Narendr et al. 10.1080/19475705.2024.2396892
- Warning water level determination and its spatial distribution in coastal areas of China S. Liu et al. 10.5194/nhess-23-127-2023
- Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling K. Jafarzadegan et al. 10.1029/2022RG000788
- Analysis of the vulnerability of the lagoon levees of the Po Delta to coastal flooding in a changing climate C. Favaretto et al. 10.1016/j.ecss.2024.109089
- Importance of non-stationary analysis for assessing extreme sea levels under sea level rise D. Baldan et al. 10.5194/nhess-22-3663-2022
- Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water A. Al-Rammahi & A. Al-Shukur 10.1088/1755-1315/1507/1/012043
- How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? E. Dallan et al. 10.5194/hess-27-1133-2023
- Coevolution of Extreme Sea Levels and Sea‐Level Rise Under Global Warming G. Boumis et al. 10.1029/2023EF003649
- Hydrological frequency analysis under nonstationarity using the Metastatistical approach and its simplified version C. Vidrio-Sahagún & J. He 10.1016/j.advwatres.2022.104244
- Non-asymptotic distributions of water extremes: much ado about what? F. Serinaldi et al. 10.5194/hess-29-1159-2025
- The Role of Different Total Water Level Definitions in Coastal Flood Modelling on a Low-Elevation Dune System P. Cabrita et al. 10.3390/jmse12061003
- Reporting Climate Change Impacts on Coastal Ports (NW Iberian Peninsula): A Review of Flooding Extent A. Ribeiro et al. 10.3390/jmse11030477
- A metastatistical frequency analysis of extreme storm surge hazard along the US coastline G. Boumis et al. 10.1080/21664250.2024.2338323
- Episodic vs. Sea Level Rise Coastal Flooding Scenarios at the Urban Scale: Extreme Event Analysis and Adaptation Strategies S. Spadotto et al. 10.3390/w17131991
16 citations as recorded by crossref.
- Nonstationary hydrological frequency analysis using the Metastatistical extreme value distribution C. Vidrio-Sahagún et al. 10.1016/j.advwatres.2023.104460
- An efficient metamodel to downscale total water level in open beaches M. Zornoza-Aguado et al. 10.1016/j.ecss.2024.108705
- A data-driven framework for enhancing coastal flood resilience in resource-crunched developing nations A. Narendr et al. 10.1080/19475705.2024.2396892
- Warning water level determination and its spatial distribution in coastal areas of China S. Liu et al. 10.5194/nhess-23-127-2023
- Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling K. Jafarzadegan et al. 10.1029/2022RG000788
- Analysis of the vulnerability of the lagoon levees of the Po Delta to coastal flooding in a changing climate C. Favaretto et al. 10.1016/j.ecss.2024.109089
- Importance of non-stationary analysis for assessing extreme sea levels under sea level rise D. Baldan et al. 10.5194/nhess-22-3663-2022
- Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water A. Al-Rammahi & A. Al-Shukur 10.1088/1755-1315/1507/1/012043
- How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? E. Dallan et al. 10.5194/hess-27-1133-2023
- Coevolution of Extreme Sea Levels and Sea‐Level Rise Under Global Warming G. Boumis et al. 10.1029/2023EF003649
- Hydrological frequency analysis under nonstationarity using the Metastatistical approach and its simplified version C. Vidrio-Sahagún & J. He 10.1016/j.advwatres.2022.104244
- Non-asymptotic distributions of water extremes: much ado about what? F. Serinaldi et al. 10.5194/hess-29-1159-2025
- The Role of Different Total Water Level Definitions in Coastal Flood Modelling on a Low-Elevation Dune System P. Cabrita et al. 10.3390/jmse12061003
- Reporting Climate Change Impacts on Coastal Ports (NW Iberian Peninsula): A Review of Flooding Extent A. Ribeiro et al. 10.3390/jmse11030477
- A metastatistical frequency analysis of extreme storm surge hazard along the US coastline G. Boumis et al. 10.1080/21664250.2024.2338323
- Episodic vs. Sea Level Rise Coastal Flooding Scenarios at the Urban Scale: Extreme Event Analysis and Adaptation Strategies S. Spadotto et al. 10.3390/w17131991
Latest update: 15 Jul 2025
Short summary
We comparatively evaluate the predictive performance of traditional and new approaches to estimate the probability distributions of extreme coastal water levels. The metastatistical approach maximizes the use of observational information and provides reliable estimates of high quantiles with respect to traditional methods. Leveraging the increased estimation accuracy afforded by this approach, we investigate future changes in the frequency of extreme total water levels.
We comparatively evaluate the predictive performance of traditional and new approaches to...
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