Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2821-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-2821-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 May 2021
Research article |
| 26 May 2021
| 26 May 2021
Estimating the probability of compound floods in estuarine regions
Department of Infrastructure Engineering, The University of
Melbourne, Melbourne, 3010, Australia
School of Civil, Environmental and Mining Engineering, The
University of Adelaide, Adelaide, 5005, Australia
Seth Westra
School of Civil, Environmental and Mining Engineering, The
University of Adelaide, Adelaide, 5005, Australia
Michael Leonard
School of Civil, Environmental and Mining Engineering, The
University of Adelaide, Adelaide, 5005, Australia
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Cited
28 citations as recorded by crossref.
- System comprehensive risk assessment of urban rainstorm–induced flood-water pollution disasters S. Huang et al. 10.1007/s11356-023-26762-3
- Compound Continental Risk of Multiple Extreme Floods in the United States N. Najibi et al. 10.1029/2023GL105297
- Research progresses and prospects of multi-sphere compound extremes from the Earth System perspective Z. Hao & Y. Chen 10.1007/s11430-023-1201-y
- Assessing the Potential for Compound Storm Surge and Extreme River Discharge Events at the Catchment Scale with Statistical Models: Sensitivity Analysis and Recommendations for Best Practice R. Jane et al. 10.1061/(ASCE)HE.1943-5584.0002154
- On the generation of high‐resolution probabilistic design events capturing the joint occurrence of rainfall and storm surge in coastal basins H. Kim et al. 10.1002/joc.7825
- Sea Level Rise Impact on Compound Coastal River Flood Risk in Klaipėda City (Baltic Coast, Lithuania) E. Čepienė et al. 10.3390/w14030414
- Flood Risk in Urban Areas: Modelling, Management and Adaptation to Climate Change. A Review L. Cea & P. Costabile 10.3390/hydrology9030050
- Nonstationary multi-site design flood estimation and application to design flood regional composition analysis Y. Hu et al. 10.1016/j.jhydrol.2024.131538
- A Hybrid Framework for Rapidly Locating Transition Zones: A Comparison of Event‐ and Response‐Based Return Water Levels in the Suwannee River FL R. Jane et al. 10.1029/2022WR032481
- Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment M. Song et al. 10.1111/jfr3.13032
- Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
- Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique D. Eilander et al. 10.5194/nhess-23-2251-2023
- A practical method for developing future joint probabilities of riverine and coastal flood risk in complex tidal river systems – a case study M. Maimone et al. 10.2166/wcc.2025.653
- A nonstationary bivariate design flood estimation approach coupled with the most likely and expectation combination strategies Y. Hu et al. 10.1016/j.jhydrol.2021.127325
- Review article: A comprehensive review of compound flooding literature with a focus on coastal and estuarine regions J. Green et al. 10.5194/nhess-25-747-2025
- Uncertainties in Riverine and Coastal Flood Impacts under Climate Change S. Wang et al. 10.3390/w13131774
- Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach C. Lyddon et al. 10.5194/nhess-24-973-2024
- Improving Estuarine Flood Risk Knowledge through Documentary Data Using Multiple Correspondence Analysis A. Rilo et al. 10.3390/w14193161
- In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections G. Boumis et al. 10.1016/j.advwatres.2024.104858
- Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta I. Pelckmans et al. 10.5194/hess-28-1463-2024
- Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh D. Feng et al. 10.5194/hess-26-5473-2022
- Understanding the compound flood risk along the coast of the contiguous United States D. Feng et al. 10.5194/hess-27-3911-2023
- Mapping Dependence between Extreme Skew-Surge, Rainfall, and River-Flow S. Stephens & W. Wu 10.3390/jmse10121818
- Perspectives on Compound Flooding in Chinese Estuary Regions H. Xu et al. 10.1007/s13753-023-00482-1
- Characterizing future changes in compound flood risk by capturing the dependence between rainfall and river flow: An application to the Yangtze River Basin, China J. Yu et al. 10.1016/j.jhydrol.2024.131175
- Recent advances and future challenges in urban pluvial flood modelling L. Cea et al. 10.1080/1573062X.2024.2446528
- Dealing with Multisource Information for Estuarine Flood Risk Appraisal in Two Western European Coastal Areas A. Rodrigues Rilo et al. 10.1007/s13753-022-00403-8
- Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) L. Terlinden-Ruhl et al. 10.5194/nhess-25-1353-2025
28 citations as recorded by crossref.
- System comprehensive risk assessment of urban rainstorm–induced flood-water pollution disasters S. Huang et al. 10.1007/s11356-023-26762-3
- Compound Continental Risk of Multiple Extreme Floods in the United States N. Najibi et al. 10.1029/2023GL105297
- Research progresses and prospects of multi-sphere compound extremes from the Earth System perspective Z. Hao & Y. Chen 10.1007/s11430-023-1201-y
- Assessing the Potential for Compound Storm Surge and Extreme River Discharge Events at the Catchment Scale with Statistical Models: Sensitivity Analysis and Recommendations for Best Practice R. Jane et al. 10.1061/(ASCE)HE.1943-5584.0002154
- On the generation of high‐resolution probabilistic design events capturing the joint occurrence of rainfall and storm surge in coastal basins H. Kim et al. 10.1002/joc.7825
- Sea Level Rise Impact on Compound Coastal River Flood Risk in Klaipėda City (Baltic Coast, Lithuania) E. Čepienė et al. 10.3390/w14030414
- Flood Risk in Urban Areas: Modelling, Management and Adaptation to Climate Change. A Review L. Cea & P. Costabile 10.3390/hydrology9030050
- Nonstationary multi-site design flood estimation and application to design flood regional composition analysis Y. Hu et al. 10.1016/j.jhydrol.2024.131538
- A Hybrid Framework for Rapidly Locating Transition Zones: A Comparison of Event‐ and Response‐Based Return Water Levels in the Suwannee River FL R. Jane et al. 10.1029/2022WR032481
- Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment M. Song et al. 10.1111/jfr3.13032
- Guidelines for Studying Diverse Types of Compound Weather and Climate Events E. Bevacqua et al. 10.1029/2021EF002340
- Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique D. Eilander et al. 10.5194/nhess-23-2251-2023
- A practical method for developing future joint probabilities of riverine and coastal flood risk in complex tidal river systems – a case study M. Maimone et al. 10.2166/wcc.2025.653
- A nonstationary bivariate design flood estimation approach coupled with the most likely and expectation combination strategies Y. Hu et al. 10.1016/j.jhydrol.2021.127325
- Review article: A comprehensive review of compound flooding literature with a focus on coastal and estuarine regions J. Green et al. 10.5194/nhess-25-747-2025
- Uncertainties in Riverine and Coastal Flood Impacts under Climate Change S. Wang et al. 10.3390/w13131774
- Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach C. Lyddon et al. 10.5194/nhess-24-973-2024
- Improving Estuarine Flood Risk Knowledge through Documentary Data Using Multiple Correspondence Analysis A. Rilo et al. 10.3390/w14193161
- In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections G. Boumis et al. 10.1016/j.advwatres.2024.104858
- Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta I. Pelckmans et al. 10.5194/hess-28-1463-2024
- Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh D. Feng et al. 10.5194/hess-26-5473-2022
- Understanding the compound flood risk along the coast of the contiguous United States D. Feng et al. 10.5194/hess-27-3911-2023
- Mapping Dependence between Extreme Skew-Surge, Rainfall, and River-Flow S. Stephens & W. Wu 10.3390/jmse10121818
- Perspectives on Compound Flooding in Chinese Estuary Regions H. Xu et al. 10.1007/s13753-023-00482-1
- Characterizing future changes in compound flood risk by capturing the dependence between rainfall and river flow: An application to the Yangtze River Basin, China J. Yu et al. 10.1016/j.jhydrol.2024.131175
- Recent advances and future challenges in urban pluvial flood modelling L. Cea et al. 10.1080/1573062X.2024.2446528
- Dealing with Multisource Information for Estuarine Flood Risk Appraisal in Two Western European Coastal Areas A. Rodrigues Rilo et al. 10.1007/s13753-022-00403-8
- Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) L. Terlinden-Ruhl et al. 10.5194/nhess-25-1353-2025
Latest update: 23 Apr 2025
Short summary
Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based on analysis of a real-world river system, guidance on method selection is provided.
Flood probability estimation is important for applications such as land use planning, reservoir...
