Articles | Volume 24, issue 8
https://doi.org/10.5194/nhess-24-2817-2024
https://doi.org/10.5194/nhess-24-2817-2024
Research article
 | 
22 Aug 2024
Research article |  | 22 Aug 2024

Water depth estimate and flood extent enhancement for satellite-based inundation maps

Andrea Betterle and Peter Salamon

Related authors

Climate change impacts on floods in West Africa: new insight from two large-scale hydrological models
Serigne Bassirou Diop, Job Ekolu, Yves Tramblay, Bastien Dieppois, Stefania Grimaldi, Ansoumana Bodian, Juliette Blanchet, Ponnambalam Rameshwaran, Peter Salamon, and Benjamin Sultan
Nat. Hazards Earth Syst. Sci., 25, 3161–3184, https://doi.org/10.5194/nhess-25-3161-2025,https://doi.org/10.5194/nhess-25-3161-2025, 2025
Short summary
Technical note: Surface fields for global environmental modelling
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 28, 2991–3036, https://doi.org/10.5194/hess-28-2991-2024,https://doi.org/10.5194/hess-28-2991-2024, 2024
Short summary
Sentinel-1-based analysis of the severe flood over Pakistan 2022
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023,https://doi.org/10.5194/nhess-23-3305-2023, 2023
Short summary
Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023,https://doi.org/10.5194/hess-27-1-2023, 2023
Short summary
EMO-5: a high-resolution multi-variable gridded meteorological dataset for Europe
Vera Thiemig, Goncalo N. Gomes, Jon O. Skøien, Markus Ziese, Armin Rauthe-Schöch, Elke Rustemeier, Kira Rehfeldt, Jakub P. Walawender, Christine Kolbe, Damien Pichon, Christoph Schweim, and Peter Salamon
Earth Syst. Sci. Data, 14, 3249–3272, https://doi.org/10.5194/essd-14-3249-2022,https://doi.org/10.5194/essd-14-3249-2022, 2022
Short summary

Cited articles

Bauer-Marschallinger, B., Sabel, D., and Wagner, W.: Optimisation of global grids for high-resolution remote sensing data, Comput. Geosci., 72, 84–93, 2014. a
Betterle, A.: FLEXTH – Flood extent enhancement and water depth estimation tool for satellite-derived inundation maps, EU [code], https://code.europa.eu/floods/floods-river/flexth (last access: 5 August 2024), 2024. a
Bryant, S., McGrath, H., and Boudreault, M.: Gridded flood depth estimates from satellite-derived inundations, Nat. Hazards Earth Syst. Sci., 22, 1437–1450, https://doi.org/10.5194/nhess-22-1437-2022, 2022. a
Chow, V.: Open-channel Hydraulics, McGraw-Hill civil engineering series, Blackburn Press, ISBN 9781932846188, 2009. a
Cian, F., Marconcini, M., Ceccato, P., and Giupponi, C.: Flood depth estimation by means of high-resolution SAR images and lidar data, Nat. Hazards Earth Syst. Sci., 18, 3063–3084, https://doi.org/10.5194/nhess-18-3063-2018, 2018 a
Download
Short summary
The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
Share
Altmetrics
Final-revised paper
Preprint