Articles | Volume 21, issue 10
https://doi.org/10.5194/nhess-21-2921-2021
© 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/nhess-21-2921-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Sep 2021
Research article |
| 30 Sep 2021
| 30 Sep 2021
Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?
Sara Lindersson
CORRESPONDING AUTHOR
Department of Earth Sciences, Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
Luigia Brandimarte
Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
Johanna Mård
Department of Earth Sciences, Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
Giuliano Di Baldassarre
Department of Earth Sciences, Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
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Cited
16 citations as recorded by crossref.
- SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains K. Zheng et al. 10.5194/essd-16-3873-2024
- Flood occurrence and impact models for socioeconomic applications over Canada and the United States M. Grenier et al. 10.5194/nhess-24-2577-2024
- Evaluating topography-based approaches for fast floodplain mapping in data-scarce complex-terrain regions: Findings from a Himalayan basin P. Dhote et al. 10.1016/j.jhydrol.2023.129309
- Geomorphic flood hazard mapping: from floodplain delineation to flood hazard characterization A. Magnini et al. 10.1080/02626667.2023.2269909
- Global population datasets overestimate flood exposure in Sweden K. Karagiorgos et al. 10.1038/s41598-024-71330-5
- Optimizing Height Above Nearest Drainage parameters to enable rapid flood mapping in North Carolina C. Richardson & R. Beighley 10.3389/frwa.2023.1296434
- A first-order approximation of floodplain soil organic carbon stocks in a river network: The South Platte River, Colorado, USA as a case study E. Wohl & R. Knox 10.1016/j.scitotenv.2022.158507
- Human alterations of the global floodplains 1992–2019 A. Rajib et al. 10.1038/s41597-023-02382-x
- Fluvial and pluvial flood hazard mapping: combining basin and municipal scale assessment M. Vojtek et al. 10.1080/19475705.2024.2432377
- A comparison of global flood models using Sentinel-1 and a change detection approach A. Risling et al. 10.1007/s11069-024-06629-7
- Satellite flood detection integrating hydrogeomorphic and spectral indices C. Samela et al. 10.1080/15481603.2022.2143670
- Floods: Emerging concepts and persisting challenges O. Bonacci et al. 10.15292/acta.hydro.2024.07
- A river ran through it: Floodplains as America’s newest relict landform R. Knox et al. 10.1126/sciadv.abo1082
- Understanding flood risk in urban environments: spatial analysis of building vulnerability and hazard areas in the Lisbon metropolitan area P. Santos et al. 10.1007/s11069-024-06731-w
- Evaluating the impact of gridded population datasets variability on flood exposure estimates across South Asia J. Zhang et al. 10.1080/19475705.2025.2481996
- A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau Y. Guo et al. 10.5194/essd-16-1651-2024
16 citations as recorded by crossref.
- SHIFT: a spatial-heterogeneity improvement in DEM-based mapping of global geomorphic floodplains K. Zheng et al. 10.5194/essd-16-3873-2024
- Flood occurrence and impact models for socioeconomic applications over Canada and the United States M. Grenier et al. 10.5194/nhess-24-2577-2024
- Evaluating topography-based approaches for fast floodplain mapping in data-scarce complex-terrain regions: Findings from a Himalayan basin P. Dhote et al. 10.1016/j.jhydrol.2023.129309
- Geomorphic flood hazard mapping: from floodplain delineation to flood hazard characterization A. Magnini et al. 10.1080/02626667.2023.2269909
- Global population datasets overestimate flood exposure in Sweden K. Karagiorgos et al. 10.1038/s41598-024-71330-5
- Optimizing Height Above Nearest Drainage parameters to enable rapid flood mapping in North Carolina C. Richardson & R. Beighley 10.3389/frwa.2023.1296434
- A first-order approximation of floodplain soil organic carbon stocks in a river network: The South Platte River, Colorado, USA as a case study E. Wohl & R. Knox 10.1016/j.scitotenv.2022.158507
- Human alterations of the global floodplains 1992–2019 A. Rajib et al. 10.1038/s41597-023-02382-x
- Fluvial and pluvial flood hazard mapping: combining basin and municipal scale assessment M. Vojtek et al. 10.1080/19475705.2024.2432377
- A comparison of global flood models using Sentinel-1 and a change detection approach A. Risling et al. 10.1007/s11069-024-06629-7
- Satellite flood detection integrating hydrogeomorphic and spectral indices C. Samela et al. 10.1080/15481603.2022.2143670
- Floods: Emerging concepts and persisting challenges O. Bonacci et al. 10.15292/acta.hydro.2024.07
- A river ran through it: Floodplains as America’s newest relict landform R. Knox et al. 10.1126/sciadv.abo1082
- Understanding flood risk in urban environments: spatial analysis of building vulnerability and hazard areas in the Lisbon metropolitan area P. Santos et al. 10.1007/s11069-024-06731-w
- Evaluating the impact of gridded population datasets variability on flood exposure estimates across South Asia J. Zhang et al. 10.1080/19475705.2025.2481996
- A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau Y. Guo et al. 10.5194/essd-16-1651-2024
Latest update: 30 May 2025
Short summary
Riverine flood risk assessments require the identification of areas prone to potential flooding. We find that (topography-based) hydrogeomorphic floodplain maps can in many cases be useful for riverine flood risk assessments, particularly where hydrologic data are scarce. For 26 countries across the global south, we also demonstrate how dataset choice influences the estimated number of people living within flood-prone zones.
Riverine flood risk assessments require the identification of areas prone to potential flooding....
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