Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1437-2022
© Author(s) 2022. 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-22-1437-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Gridded flood depth estimates from satellite-derived inundations
Section 4.4. Hydrology, GFZ German Research Centre for Geosciences,
Potsdam, Germany
Institute for Environmental Sciences and Geography, University of
Potsdam, Potsdam, Germany
Heather McGrath
Canada Centre for Mapping and Earth Observation, Natural Resources
Canada, Ottawa, Canada
Mathieu Boudreault
Department of Mathematics, Université du Québec à
Montréal, Montreal, Canada
Related authors
Aaron Buhrmann, Cecilia I. Nievas, Nivedita Sairam, James E. Daniell, Heidi Kreibich, and Seth Bryant
EGUsphere, https://doi.org/10.5194/egusphere-2025-5172, https://doi.org/10.5194/egusphere-2025-5172, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Our research lays the groundwork for the next generation of disaster risk modelling by improving how building-level value and use are estimated across Germany. By testing multiple data sources and methods, we identify a transparent, adaptable approach that enhances forecasts of damage and recovery—helping protect lives, property, and communities.
Seth Bryant, Heidi Kreibich, and Bruno Merz
Proc. IAHS, 386, 181–187, https://doi.org/10.5194/piahs-386-181-2024, https://doi.org/10.5194/piahs-386-181-2024, 2024
Short summary
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Our study found that simplifying data in flood risk models can introduce errors. We tested 344 damage functions and found errors up to 40 % of the total asset value. This means large-scale flood risk assessments may have significant errors due to the modelling approach. Our research highlights the need for more attention to data aggregation in flood risk models.
Seth Bryant, Guy Schumann, Heiko Apel, Heidi Kreibich, and Bruno Merz
Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
Short summary
Short summary
A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
Benedikt Mester, Thomas Vogt, Seth Bryant, Christian Otto, Katja Frieler, and Jacob Schewe
Nat. Hazards Earth Syst. Sci., 23, 3467–3485, https://doi.org/10.5194/nhess-23-3467-2023, https://doi.org/10.5194/nhess-23-3467-2023, 2023
Short summary
Short summary
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use coastal flood modeling and satellite imagery to construct a counterfactual cyclone event without the effects of climate change. We show that 12 600–14 900 displacements can be attributed to sea level rise and the intensification of storm wind speeds due to global warming. Our impact attribution study is the first one on human displacement and one of very few for a low-income country.
Aaron Buhrmann, Cecilia I. Nievas, Nivedita Sairam, James E. Daniell, Heidi Kreibich, and Seth Bryant
EGUsphere, https://doi.org/10.5194/egusphere-2025-5172, https://doi.org/10.5194/egusphere-2025-5172, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Our research lays the groundwork for the next generation of disaster risk modelling by improving how building-level value and use are estimated across Germany. By testing multiple data sources and methods, we identify a transparent, adaptable approach that enhances forecasts of damage and recovery—helping protect lives, property, and communities.
Aude Garin, Francesco S. R. Pausata, Mathieu Boudreault, and Roberto Ingrosso
Weather Clim. Dynam., 6, 1379–1397, https://doi.org/10.5194/wcd-6-1379-2025, https://doi.org/10.5194/wcd-6-1379-2025, 2025
Short summary
Short summary
As tropical cyclones move poleward, they can transform into extratropical cyclones, a process known as extratropical transition. These storms can pose serious risks to human lives and cause damage to infrastructure along the northeastern coasts of the US and Canada. Our study investigates the impacts of climate change on the frequency, intensity, and location of extratropical transitions, revealing that transitioning storms may become more destructive in the future but may not be more frequent.
Manuel Grenier, Mathieu Boudreault, David A. Carozza, Jérémie Boudreault, and Sébastien Raymond
Nat. Hazards Earth Syst. Sci., 24, 2577–2595, https://doi.org/10.5194/nhess-24-2577-2024, https://doi.org/10.5194/nhess-24-2577-2024, 2024
Short summary
Short summary
Modelling floods at the street level for large countries like Canada and the United States is difficult and very costly. However, many applications do not necessarily require that level of detail. As a result, we present a flood modelling framework built with artificial intelligence for socioeconomic studies like trend and scenarios analyses. We find for example that an increase of 10 % in average precipitation yields an increase in displaced population of 18 % in Canada and 14 % in the US.
Seth Bryant, Heidi Kreibich, and Bruno Merz
Proc. IAHS, 386, 181–187, https://doi.org/10.5194/piahs-386-181-2024, https://doi.org/10.5194/piahs-386-181-2024, 2024
Short summary
Short summary
Our study found that simplifying data in flood risk models can introduce errors. We tested 344 damage functions and found errors up to 40 % of the total asset value. This means large-scale flood risk assessments may have significant errors due to the modelling approach. Our research highlights the need for more attention to data aggregation in flood risk models.
Seth Bryant, Guy Schumann, Heiko Apel, Heidi Kreibich, and Bruno Merz
Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
Short summary
Short summary
A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
Gabriel Morin, Mathieu Boudreault, and Jorge Luis García-Franco
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-460, https://doi.org/10.5194/essd-2023-460, 2023
Revised manuscript not accepted
Short summary
Short summary
The rainfall from tropical cyclones often causes severe impacts due to flooding. Research including flood-risk assessment, vulnerability as well as climate science and meteorology all require estimates of rainfall from tropical cyclones to understand the causes, predictability and mechanisms for the disasters caused by these phenomena. This dataset provides key statistics of tropical cyclone rainfall estimated from global datasets from 1979–2023.
Benedikt Mester, Thomas Vogt, Seth Bryant, Christian Otto, Katja Frieler, and Jacob Schewe
Nat. Hazards Earth Syst. Sci., 23, 3467–3485, https://doi.org/10.5194/nhess-23-3467-2023, https://doi.org/10.5194/nhess-23-3467-2023, 2023
Short summary
Short summary
In 2019, Cyclone Idai displaced more than 478 000 people in Mozambique. In our study, we use coastal flood modeling and satellite imagery to construct a counterfactual cyclone event without the effects of climate change. We show that 12 600–14 900 displacements can be attributed to sea level rise and the intensification of storm wind speeds due to global warming. Our impact attribution study is the first one on human displacement and one of very few for a low-income country.
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Short summary
The advent of new satellite technologies improves our ability to study floods. While the depth of water at flooded buildings is generally the most important variable for flood researchers, extracting this accurately from satellite data is challenging. The software tool presented here accomplishes this, and tests show the tool is more accurate than competing tools. This achievement unlocks more detailed studies of past floods and improves our ability to plan for and mitigate disasters.
The advent of new satellite technologies improves our ability to study floods. While the depth...
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