Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2647-2020
https://doi.org/10.5194/nhess-20-2647-2020
Research article
 | 
06 Oct 2020
Research article |  | 06 Oct 2020

Building hazard maps with differentiated risk perception for flood impact assessment

Punit K. Bhola, Jorge Leandro, and Markus Disse

Related authors

Reducing uncertainties in flood inundation outputs of a two-dimensional hydrodynamic model by constraining roughness
Punit Kumar Bhola, Jorge Leandro, and Markus Disse
Nat. Hazards Earth Syst. Sci., 19, 1445–1457, https://doi.org/10.5194/nhess-19-1445-2019,https://doi.org/10.5194/nhess-19-1445-2019, 2019
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

Alfieri, L., Feyen, L., Salamon, P., Thielen, J., Bianchi, A., Dottori, F., and Burek, P.: Modelling the socio-economic impact of river floods in Europe, Nat. Hazards Earth Syst. Sci., 16, 1401–1411, https://doi.org/10.5194/nhess-16-1401-2016, 2016. 
Bartels, J., Seidel, J., Bardossy, A., Bliefernicht, J., Kunstmann, H., Kunstmann, H., Johst, M., and Demuth, N.: Bewertung von Ensemble-Abflussvorhersagen für die operationelle Hochwasserwarnung, Hydrol. Wasserbewirts., 61, 297–310, https://doi.org/10.5675/HyWa_2017,5_1, 2017. 
Bates, P. D., Pappenberger, F., and Romanowicz, R. J.: Uncertainty in Flood Inundation Modelling, in: Applied Uncertainty Analysis for Flood Risk Management, edited by: Beven, K., and Hall, J., Imperial College Press, London, UK, 232–269, ISBN 978-1-78326-312-7, 2014. 
Beg, M. N. A., Leandro, J., Bhola, P., Konnerth, I., Amin, K., Koeck, F., Carvalho, R. F., and Disse, M.: Flood Forecasting with Uncertainty Using a Fully Automated Flood Model Chain: A Case Study for the City of Kulmbach, HIC 2018, in: 13th International Conference on Hydroinformatics, 1–5 July 2018, Palermo, Italy, 2018. 
Bermúdez, M. and Zischg, A. P.: Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling, Nat. Hazards, 92, 1633–1648. https://doi.org/10.1007/s11069-018-3270-7, 2018. 
Download
Short summary
In operational flood risk management, a single best model is used to assess the impact of flooding, which might misrepresent uncertainties in the modelling process. We have used quantified uncertainties in flood forecasting to generate flood hazard maps that were combined based on different exceedance probability scenarios with the purpose to differentiate impacts of flooding and to account for uncertainties in flood hazard maps that can be used by decision makers.
Share
Altmetrics
Final-revised paper
Preprint