Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-823-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-823-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Feb 2023
Research article |
| 27 Feb 2023
| 27 Feb 2023
A globally applicable framework for compound flood hazard modeling
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
Invited contribution by Dirk Eilander, recipient of the EGU Hydrological Sciences Outstanding Student and PhD candidate Presentation (OSPP) Awards 2022.
Anaïs Couasnon
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Tim Leijnse
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
Hiroaki Ikeuchi
Ministry of Land, Infrastructure, Transport and Tourism, Tokyo, Japan
Dai Yamazaki
Institute of Industrial Science, University of Tokyo, Tokyo, Japan
Sanne Muis
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
Job Dullaart
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
Arjen Haag
Deltares, Delft, the Netherlands
Hessel C. Winsemius
Deltares, Delft, the Netherlands
Philip J. Ward
Institute for Environmental Studies (IVM), Vrije Universiteit
Amsterdam, Amsterdam, the Netherlands
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- Understanding the compound flood risk along the coast of the contiguous United States D. Feng et al. 10.5194/hess-27-3911-2023
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- Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach C. Lyddon et al. 10.5194/nhess-24-973-2024
- Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding K. Nederhoff et al. 10.5194/gmd-17-1789-2024
- Investigating the Role of the Key Conditioning Factors in Flood Susceptibility Mapping Through Machine Learning Approaches K. Al-Kindi & Z. Alabri 10.1007/s41748-023-00369-7
- Satellite Video Remote Sensing for Flood Model Validation C. Masafu & R. Williams 10.1029/2023WR034545
- Flood risk assessment of a small river with limited available data N. Szopos et al. 10.1007/s41324-024-00596-8
- Risk of compound flooding substantially increases in the future Mekong River delta M. Wood et al. 10.5194/nhess-24-3627-2024
- A novel conceptual flood inundation model for large scale data-scarce regions S. Unnithan et al. 10.1016/j.envsoft.2023.105863
- Hindcasting compound pluvial, fluvial and coastal flooding during Hurricane Harvey (2017) using Delft3D-FM W. Lee et al. 10.1007/s11069-023-06247-9
- Modelling the combined impact of sea level rise, land subsidence, and tropical cyclones in compound flooding of coastal cities G. Wu et al. 10.1016/j.ocecoaman.2024.107107
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. 10.1038/s44304-024-00010-1
- 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
- HydroMT: Automated and reproducible model building and analysis D. Eilander et al. 10.21105/joss.04897
- Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al. 10.1111/jfr3.12880
- 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
- Estimating nearshore infragravity wave conditions at large spatial scales T. Leijnse et al. 10.3389/fmars.2024.1355095
- Impact of Tides and Surges on Fluvial Floods in Coastal Regions H. Liang & X. Zhou 10.3390/rs14225779
- Towards a global impact-based forecasting model for tropical cyclones M. Kooshki Forooshani et al. 10.5194/nhess-24-309-2024
22 citations as recorded by crossref.
- Human displacements from Tropical Cyclone Idai attributable to climate change B. Mester et al. 10.5194/nhess-23-3467-2023
- Mapping Compound Flooding Risks for Urban Resilience in Coastal Zones: A Comprehensive Methodological Review H. Sun et al. 10.3390/rs16020350
- Fluvial flood inundation and socio-economic impact model based on open data L. Riedel et al. 10.5194/gmd-17-5291-2024
- The developing flood rich period: Science evidence and policy evolution for England. Is it time for place‐based socio‐ecological solutions? M. Newson & J. Lewin 10.1002/rra.4363
- Regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast J. Kiesel et al. 10.5194/nhess-23-2961-2023
- Improved efficient physics-based computational modeling of regional wave-driven coastal flooding for reef-lined coastlines C. Gaido-Lasserre et al. 10.1016/j.ocemod.2024.102358
- Compound effects of sea level and flow on river-induced flooding in coastal areas of southern Sweden F. Inamdeen & M. Larson 10.1016/j.ejrh.2024.102032
- Earth observation technologies, policies and legislation for the coastal flood risk assessment and management: a European perspective A. Velegrakis et al. 10.1007/s44218-024-00037-x
- Estimating a Coastal Compound Flood Standard for the Taehwa River Basin K. Kim et al. 10.9798/KOSHAM.2024.24.4.217
- Understanding the compound flood risk along the coast of the contiguous United States D. Feng et al. 10.5194/hess-27-3911-2023
- Assessing typhoon-induced compound flood drivers: a case study in Ho Chi Minh City, Vietnam F. Rodrigues do Amaral et al. 10.5194/nhess-23-3379-2023
- Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach C. Lyddon et al. 10.5194/nhess-24-973-2024
- Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding K. Nederhoff et al. 10.5194/gmd-17-1789-2024
- Investigating the Role of the Key Conditioning Factors in Flood Susceptibility Mapping Through Machine Learning Approaches K. Al-Kindi & Z. Alabri 10.1007/s41748-023-00369-7
- Satellite Video Remote Sensing for Flood Model Validation C. Masafu & R. Williams 10.1029/2023WR034545
- Flood risk assessment of a small river with limited available data N. Szopos et al. 10.1007/s41324-024-00596-8
- Risk of compound flooding substantially increases in the future Mekong River delta M. Wood et al. 10.5194/nhess-24-3627-2024
- A novel conceptual flood inundation model for large scale data-scarce regions S. Unnithan et al. 10.1016/j.envsoft.2023.105863
- Hindcasting compound pluvial, fluvial and coastal flooding during Hurricane Harvey (2017) using Delft3D-FM W. Lee et al. 10.1007/s11069-023-06247-9
- Modelling the combined impact of sea level rise, land subsidence, and tropical cyclones in compound flooding of coastal cities G. Wu et al. 10.1016/j.ocecoaman.2024.107107
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. 10.1038/s44304-024-00010-1
- 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
6 citations as recorded by crossref.
- HydroMT: Automated and reproducible model building and analysis D. Eilander et al. 10.21105/joss.04897
- Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al. 10.1111/jfr3.12880
- 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
- Estimating nearshore infragravity wave conditions at large spatial scales T. Leijnse et al. 10.3389/fmars.2024.1355095
- Impact of Tides and Surges on Fluvial Floods in Coastal Regions H. Liang & X. Zhou 10.3390/rs14225779
- Towards a global impact-based forecasting model for tropical cyclones M. Kooshki Forooshani et al. 10.5194/nhess-24-309-2024
Latest update: 23 Nov 2024
Short summary
In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial...
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