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
Viewed
Total article views: 3,713 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Jan 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 2,499 | 1,154 | 60 | 3,713 | 315 | 58 | 60 |
- HTML: 2,499
- PDF: 1,154
- XML: 60
- Total: 3,713
- Supplement: 315
- BibTeX: 58
- EndNote: 60
Total article views: 2,662 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Dec 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,937 | 680 | 45 | 2,662 | 197 | 43 | 40 |
- HTML: 1,937
- PDF: 680
- XML: 45
- Total: 2,662
- Supplement: 197
- BibTeX: 43
- EndNote: 40
Total article views: 1,051 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Jan 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 562 | 474 | 15 | 1,051 | 118 | 15 | 20 |
- HTML: 562
- PDF: 474
- XML: 15
- Total: 1,051
- Supplement: 118
- BibTeX: 15
- EndNote: 20
Viewed (geographical distribution)
Total article views: 3,713 (including HTML, PDF, and XML)
Thereof 3,437 with geography defined
and 276 with unknown origin.
Total article views: 2,662 (including HTML, PDF, and XML)
Thereof 2,510 with geography defined
and 152 with unknown origin.
Total article views: 1,051 (including HTML, PDF, and XML)
Thereof 927 with geography defined
and 124 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
22 citations as recorded by crossref.
- Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps? S. Lindersson et al. 10.5194/nhess-21-2921-2021
- Urbanizing the floodplain: global changes of imperviousness in flood-prone areas K. Andreadis et al. 10.1088/1748-9326/ac9197
- Human populations in the world’s mountains: Spatio-temporal patterns and potential controls J. Thornton et al. 10.1371/journal.pone.0271466
- The Role of Global Data Sets for Riverine Flood Risk Management at National Scales M. Bernhofen et al. 10.1029/2021WR031555
- Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. 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. 10.1029/2022WR032395
- Comparative Evaluation of Global Flood Hazard Maps and Recommendations for Corporate Practice Y. HIRABAYASHI et al. 10.3178/jjshwr.35.175
- Estimating River Channel Bathymetry in Large Scale Flood Inundation Models J. Neal et al. 10.1029/2020WR028301
- Reproducibility and replicability of flood models B. Kar & G. Schumann 10.1002/hyp.14666
- A Review of Flood Risk in China during 1950–2019: Urbanization, Socioeconomic Impact Trends and Flood Risk Management W. Ding et al. 10.3390/w14203246
- Flood hazard potential reveals global floodplain settlement patterns L. Devitt et al. 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. 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. 10.1016/j.scitotenv.2023.165357
- 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. 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. 10.1088/1748-9326/ac5561
- The uncertainty of flood frequency analyses in hydrodynamic model simulations X. Zhou et al. 10.5194/nhess-21-1071-2021
- Global flood exposure from different sized rivers M. Bernhofen et al. 10.5194/nhess-21-2829-2021
- Regional Index Insurance Using Satellite‐Based Fractional Flooded Area B. Tellman et al. 10.1029/2021EF002418
- A globally applicable framework for compound flood hazard modeling D. Eilander et al. 10.5194/nhess-23-823-2023
- Multi-hazard risk to global port infrastructure and resulting trade and logistics losses J. Verschuur et al. 10.1038/s43247-022-00656-7
- Comparing earth observation and inundation models to map flood hazards L. Hawker et al. 10.1088/1748-9326/abc216
- Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards G. Boni et al. 10.3390/rs12233943
19 citations as recorded by crossref.
- Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps? S. Lindersson et al. 10.5194/nhess-21-2921-2021
- Urbanizing the floodplain: global changes of imperviousness in flood-prone areas K. Andreadis et al. 10.1088/1748-9326/ac9197
- Human populations in the world’s mountains: Spatio-temporal patterns and potential controls J. Thornton et al. 10.1371/journal.pone.0271466
- The Role of Global Data Sets for Riverine Flood Risk Management at National Scales M. Bernhofen et al. 10.1029/2021WR031555
- Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. 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. 10.1029/2022WR032395
- Comparative Evaluation of Global Flood Hazard Maps and Recommendations for Corporate Practice Y. HIRABAYASHI et al. 10.3178/jjshwr.35.175
- Estimating River Channel Bathymetry in Large Scale Flood Inundation Models J. Neal et al. 10.1029/2020WR028301
- Reproducibility and replicability of flood models B. Kar & G. Schumann 10.1002/hyp.14666
- A Review of Flood Risk in China during 1950–2019: Urbanization, Socioeconomic Impact Trends and Flood Risk Management W. Ding et al. 10.3390/w14203246
- Flood hazard potential reveals global floodplain settlement patterns L. Devitt et al. 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. 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. 10.1016/j.scitotenv.2023.165357
- 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. 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. 10.1088/1748-9326/ac5561
- The uncertainty of flood frequency analyses in hydrodynamic model simulations X. Zhou et al. 10.5194/nhess-21-1071-2021
- Global flood exposure from different sized rivers M. Bernhofen et al. 10.5194/nhess-21-2829-2021
- Regional Index Insurance Using Satellite‐Based Fractional Flooded Area B. Tellman et al. 10.1029/2021EF002418
- A globally applicable framework for compound flood hazard modeling D. Eilander et al. 10.5194/nhess-23-823-2023
3 citations as recorded by crossref.
- Multi-hazard risk to global port infrastructure and resulting trade and logistics losses J. Verschuur et al. 10.1038/s43247-022-00656-7
- Comparing earth observation and inundation models to map flood hazards L. Hawker et al. 10.1088/1748-9326/abc216
- Remote Sensing-Based Methodology for the Quick Update of the Assessment of the Population Exposed to Natural Hazards G. Boni et al. 10.3390/rs12233943
Latest update: 18 Apr 2024
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...
Altmetrics
Final-revised paper
Preprint