Articles | Volume 20, issue 12
https://doi.org/10.5194/nhess-20-3245-2020
© 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-20-3245-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Dec 2020
Research article |
| 01 Dec 2020
| 01 Dec 2020
Comparison of estimates of global flood models for flood hazard and exposed gross domestic product: a China case study
Water Resources Management, Faculty of Civil Engineering and
Geosciences, Delft University of Technology, Delft, the Netherlands
Steffi Uhlemann-Elmer
Aspen Insurance Ltd, Zurich, Switzerland
Dirk Eilander
Institute for Environmental Studies, Vrije Universiteit Amsterdam,
Amsterdam, the Netherlands
Deltares, Delft, the Netherlands
Philip J. Ward
Institute for Environmental Studies, Vrije Universiteit Amsterdam,
Amsterdam, the Netherlands
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Cited
33 citations as recorded by crossref.
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- Urbanizing the floodplain: global changes of imperviousness in flood-prone areas K. Andreadis et al. https://doi.org/10.1088/1748-9326/ac9197
- Human populations in the world’s mountains: Spatio-temporal patterns and potential controls J. Thornton et al. https://doi.org/10.1371/journal.pone.0271466
- The Role of Global Data Sets for Riverine Flood Risk Management at National Scales M. Bernhofen et al. https://doi.org/10.1029/2021WR031555
- Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. https://doi.org/10.1088/1748-9326/abfac4
- Flood Defense Standard Estimation Using Machine Learning and Its Representation in Large‐Scale Flood Hazard Modeling G. Zhao et al. https://doi.org/10.1029/2022WR032395
- A multi-scenario framework for quantifying flood hazard and exposure accounting for runoff-driven uncertainty in global flood models J. Parmar & S. Karmakar https://doi.org/10.1016/j.scitotenv.2025.180381
- Advancing global river hydrodynamics simulations by catchment-based macro-scale floodplain modeling approach D. Yamazaki https://doi.org/10.1186/s40562-025-00452-z
- Comparative Evaluation of Global Flood Hazard Maps and Recommendations for Corporate Practice Y. HIRABAYASHI et al. https://doi.org/10.3178/jjshwr.35.175
- A Review of Flood Risk in China during 1950–2019: Urbanization, Socioeconomic Impact Trends and Flood Risk Management W. Ding et al. https://doi.org/10.3390/w14203246
- CLIM-SEG: A generalizable segmentation model for heat and flood risk mapping A. Ray et al. https://doi.org/10.1016/j.crm.2024.100654
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. https://doi.org/10.1038/s44304-024-00010-1
- Sustainable Risk Mapping of High-Speed Rail Networks Through PS-InSAR and Geospatial Analysis S. Lee et al. https://doi.org/10.3390/su17157064
- Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam L. Hawker et al. https://doi.org/10.5194/nhess-24-539-2024
- Economic growth dominates rising potential flood risk in the Yangtze River and benefits of raising dikes from 1991 to 2015 W. Qi et al. https://doi.org/10.1088/1748-9326/ac5561
- The uncertainty of flood frequency analyses in hydrodynamic model simulations X. Zhou et al. https://doi.org/10.5194/nhess-21-1071-2021
- Global flood exposure from different sized rivers M. Bernhofen et al. https://doi.org/10.5194/nhess-21-2829-2021
- Varying flood exposure due to uncertain data of flood hazard and population distribution W. Shao et al. https://doi.org/10.1088/1748-9326/ae0fae
- Modelling flood losses of micro-businesses in Ho Chi Minh City, Vietnam A. Buch et al. https://doi.org/10.5194/nhess-25-2437-2025
- Natural climate change and social population ageing reconstruct the flood risk gap between inland and coastal cities in China X. Gu et al. https://doi.org/10.1057/s41599-026-06736-9
- A globally applicable framework for compound flood hazard modeling D. Eilander et al. https://doi.org/10.5194/nhess-23-823-2023
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- Mitigating Environmental Impacts of Small Hydropower Plants Through Advanced Hydraulic Modelling O. Halych et al. https://doi.org/10.2478/rtuect-2025-0022
- Flood dynamic monitoring and XGBoost-SHAP based risk assessment: A case study of the 23·7 extreme rainstorm in BTH region, China S. Li et al. https://doi.org/10.1016/j.indic.2025.101020
- A comparison of global flood models using Sentinel-1 and a change detection approach A. Risling et al. https://doi.org/10.1007/s11069-024-06629-7
- Estimating River Channel Bathymetry in Large Scale Flood Inundation Models J. Neal et al. https://doi.org/10.1029/2020WR028301
- Reproducibility and replicability of flood models B. Kar & G. Schumann https://doi.org/10.1002/hyp.14666
- Flood hazard potential reveals global floodplain settlement patterns L. Devitt et al. https://doi.org/10.1038/s41467-023-38297-9
- Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff P. Wiersma et al. https://doi.org/10.5194/hess-26-5971-2022
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- Comprehensive flood vulnerability analysis and mapping for the Awash River Basin, Ethiopia A. Legass et al. https://doi.org/10.1016/j.nhres.2025.01.012
- A semantic notation for comparing global high-resolution coastal flooding studies F. Baart et al. https://doi.org/10.3389/feart.2024.1465040
- Regional Index Insurance Using Satellite‐Based Fractional Flooded Area B. Tellman et al. https://doi.org/10.1029/2021EF002418
33 citations as recorded by crossref.
- Comparative study of various typical hydrological models for flash flood forecasting K. Wen et al. https://doi.org/10.2166/wcc.2026.249
- Urbanizing the floodplain: global changes of imperviousness in flood-prone areas K. Andreadis et al. https://doi.org/10.1088/1748-9326/ac9197
- Human populations in the world’s mountains: Spatio-temporal patterns and potential controls J. Thornton et al. https://doi.org/10.1371/journal.pone.0271466
- The Role of Global Data Sets for Riverine Flood Risk Management at National Scales M. Bernhofen et al. https://doi.org/10.1029/2021WR031555
- Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. https://doi.org/10.1088/1748-9326/abfac4
- Flood Defense Standard Estimation Using Machine Learning and Its Representation in Large‐Scale Flood Hazard Modeling G. Zhao et al. https://doi.org/10.1029/2022WR032395
- A multi-scenario framework for quantifying flood hazard and exposure accounting for runoff-driven uncertainty in global flood models J. Parmar & S. Karmakar https://doi.org/10.1016/j.scitotenv.2025.180381
- Advancing global river hydrodynamics simulations by catchment-based macro-scale floodplain modeling approach D. Yamazaki https://doi.org/10.1186/s40562-025-00452-z
- Comparative Evaluation of Global Flood Hazard Maps and Recommendations for Corporate Practice Y. HIRABAYASHI et al. https://doi.org/10.3178/jjshwr.35.175
- A Review of Flood Risk in China during 1950–2019: Urbanization, Socioeconomic Impact Trends and Flood Risk Management W. Ding et al. https://doi.org/10.3390/w14203246
- CLIM-SEG: A generalizable segmentation model for heat and flood risk mapping A. Ray et al. https://doi.org/10.1016/j.crm.2024.100654
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. https://doi.org/10.1038/s44304-024-00010-1
- Sustainable Risk Mapping of High-Speed Rail Networks Through PS-InSAR and Geospatial Analysis S. Lee et al. https://doi.org/10.3390/su17157064
- Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam L. Hawker et al. https://doi.org/10.5194/nhess-24-539-2024
- Economic growth dominates rising potential flood risk in the Yangtze River and benefits of raising dikes from 1991 to 2015 W. Qi et al. https://doi.org/10.1088/1748-9326/ac5561
- The uncertainty of flood frequency analyses in hydrodynamic model simulations X. Zhou et al. https://doi.org/10.5194/nhess-21-1071-2021
- Global flood exposure from different sized rivers M. Bernhofen et al. https://doi.org/10.5194/nhess-21-2829-2021
- Varying flood exposure due to uncertain data of flood hazard and population distribution W. Shao et al. https://doi.org/10.1088/1748-9326/ae0fae
- Modelling flood losses of micro-businesses in Ho Chi Minh City, Vietnam A. Buch et al. https://doi.org/10.5194/nhess-25-2437-2025
- Natural climate change and social population ageing reconstruct the flood risk gap between inland and coastal cities in China X. Gu et al. https://doi.org/10.1057/s41599-026-06736-9
- A globally applicable framework for compound flood hazard modeling D. Eilander et al. https://doi.org/10.5194/nhess-23-823-2023
- Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps? S. Lindersson et al. https://doi.org/10.5194/nhess-21-2921-2021
- Mitigating Environmental Impacts of Small Hydropower Plants Through Advanced Hydraulic Modelling O. Halych et al. https://doi.org/10.2478/rtuect-2025-0022
- Flood dynamic monitoring and XGBoost-SHAP based risk assessment: A case study of the 23·7 extreme rainstorm in BTH region, China S. Li et al. https://doi.org/10.1016/j.indic.2025.101020
- A comparison of global flood models using Sentinel-1 and a change detection approach A. Risling et al. https://doi.org/10.1007/s11069-024-06629-7
- Estimating River Channel Bathymetry in Large Scale Flood Inundation Models J. Neal et al. https://doi.org/10.1029/2020WR028301
- Reproducibility and replicability of flood models B. Kar & G. Schumann https://doi.org/10.1002/hyp.14666
- Flood hazard potential reveals global floodplain settlement patterns L. Devitt et al. https://doi.org/10.1038/s41467-023-38297-9
- Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff P. Wiersma et al. https://doi.org/10.5194/hess-26-5971-2022
- Are open-source hydrodynamic models efficient in quantifying flood risks over mountainous terrains? An exhaustive analysis over the Hindu-Kush-Himalayan region T. Namgyal et al. https://doi.org/10.1016/j.scitotenv.2023.165357
- Comprehensive flood vulnerability analysis and mapping for the Awash River Basin, Ethiopia A. Legass et al. https://doi.org/10.1016/j.nhres.2025.01.012
- A semantic notation for comparing global high-resolution coastal flooding studies F. Baart et al. https://doi.org/10.3389/feart.2024.1465040
- Regional Index Insurance Using Satellite‐Based Fractional Flooded Area B. Tellman et al. https://doi.org/10.1029/2021EF002418
Saved (final revised paper)
Latest update: 23 Jun 2026
Short summary
We compare and analyse flood hazard maps from eight global flood models that represent the current state of the global flood modelling community. We apply our comparison to China as a case study, and for the first time, we include industry models, pluvial flooding, and flood protection standards. We find substantial variability between the flood hazard maps in the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods and in expected annual exposed GDP.
We compare and analyse flood hazard maps from eight global flood models that represent the...
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