Articles | Volume 24, issue 2
https://doi.org/10.5194/nhess-24-539-2024
https://doi.org/10.5194/nhess-24-539-2024
Research article
 | 
15 Feb 2024
Research article |  | 15 Feb 2024

Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam

Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Pham Khanh Nam

Related authors

Global-scale evaluation of precipitation datasets for hydrological modelling
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024,https://doi.org/10.5194/hess-28-3099-2024, 2024
Short summary

Related subject area

Hydrological Hazards
Post-wildfire sediment source and transport modeling, empirical observations, and applied mitigation: an Arizona, USA, case study
Edward R. Schenk, Alex Wood, Allen Haden, Gabriel Baca, Jake Fleishman, and Joe Loverich
Nat. Hazards Earth Syst. Sci., 25, 727–745, https://doi.org/10.5194/nhess-25-727-2025,https://doi.org/10.5194/nhess-25-727-2025, 2025
Short summary
Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood
Belinda Rhein and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 25, 581–589, https://doi.org/10.5194/nhess-25-581-2025,https://doi.org/10.5194/nhess-25-581-2025, 2025
Short summary
Large-scale flood risk assessment in data-scarce areas: an application to Central Asia
Paola Ceresa, Gianbattista Bussi, Simona Denaro, Gabriele Coccia, Paolo Bazzurro, Mario Martina, Ettore Fagà, Carlos Avelar, Mario Ordaz, Benjamin Huerta, Osvaldo Garay, Zhanar Raimbekova, Kanatbek Abdrakhmatov, Sitora Mirzokhonova, Vakhitkhan Ismailov, and Vladimir Belikov
Nat. Hazards Earth Syst. Sci., 25, 403–428, https://doi.org/10.5194/nhess-25-403-2025,https://doi.org/10.5194/nhess-25-403-2025, 2025
Short summary
Multi-scale hydraulic graph neural networks for flood modelling
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Nat. Hazards Earth Syst. Sci., 25, 335–351, https://doi.org/10.5194/nhess-25-335-2025,https://doi.org/10.5194/nhess-25-335-2025, 2025
Short summary
The role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context
Maria Staudinger, Martina Kauzlaric, Alexandre Mas, Guillaume Evin, Benoit Hingray, and Daniel Viviroli
Nat. Hazards Earth Syst. Sci., 25, 247–265, https://doi.org/10.5194/nhess-25-247-2025,https://doi.org/10.5194/nhess-25-247-2025, 2025
Short summary

Cited articles

Aerts, J. P. M., Uhlemann-Elmer, S., Eilander, D., and Ward, P. J.: Comparison of estimates of global flood models for flood hazard and exposed gross domestic product: a China case study, Nat. Hazards Earth Syst. Sci., 20, 3245–3260, https://doi.org/10.5194/nhess-20-3245-2020, 2020. 
Airbus: Copernicus DEM: Copernicus Digital Elevation Model Product Handbook, https://doi.org/10.5270/ESA-c5d3d65, 2020. 
Alemu, A. N., Haile, A. T., Carr, A. B., Trigg, M. A., Mengistie, G. K., and Walsh, C. L.: Filling data gaps using citizen science for flood modeling in urbanized catchment of akaki, Nat. Hazards Res., 3, 395–407, https://doi.org/10.1016/j.nhres.2023.05.002, 2023. 
Apel, H., Martínez Trepat, O., Hung, N. N., Chinh, D. T., Merz, B., and Dung, N. V.: Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam, Nat. Hazards Earth Syst. Sci., 16, 941–961, https://doi.org/10.5194/nhess-16-941-2016, 2016. 
Archer, L., Neal, J., Bates, P., and House, J.: Comparing TanDEM-X Data with Frequently Used DEMs for Flood Inundation Modelling, Water Resour. Res., 54, 10205–10222, https://doi.org/10.1029/2018WR023688, 2018. 
Download
Short summary
We present a global flood model built using a new terrain data set and evaluated in the Central Highlands of Vietnam.
Share
Altmetrics
Final-revised paper
Preprint