Articles | Volume 18, issue 5
https://doi.org/10.5194/nhess-18-1297-2018
https://doi.org/10.5194/nhess-18-1297-2018
Research article
 | 
03 May 2018
Research article |  | 03 May 2018

Multi-model ensembles for assessment of flood losses and associated uncertainty

Rui Figueiredo, Kai Schröter, Alexander Weiss-Motz, Mario L. V. Martina, and Heidi Kreibich

Related authors

The potential of machine learning for weather index insurance
Luigi Cesarini, Rui Figueiredo, Beatrice Monteleone, and Mario L. V. Martina
Nat. Hazards Earth Syst. Sci., 21, 2379–2405, https://doi.org/10.5194/nhess-21-2379-2021,https://doi.org/10.5194/nhess-21-2379-2021, 2021
Short summary
The whole is greater than the sum of its parts: a holistic graph-based assessment approach for natural hazard risk of complex systems
Marcello Arosio, Mario L. V. Martina, and Rui Figueiredo
Nat. Hazards Earth Syst. Sci., 20, 521–547, https://doi.org/10.5194/nhess-20-521-2020,https://doi.org/10.5194/nhess-20-521-2020, 2020
Short summary
Natural hazard risk of complex systems – the whole is more than the sum of its parts: II. A pilot study in Mexico City
Marcello Arosio, Mario L. V. Martina, and Rui Figueiredo
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-278,https://doi.org/10.5194/nhess-2018-278, 2018
Revised manuscript has not been submitted
Short summary
INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis
Francesco Dottori, Rui Figueiredo, Mario L. V. Martina, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 16, 2577–2591, https://doi.org/10.5194/nhess-16-2577-2016,https://doi.org/10.5194/nhess-16-2577-2016, 2016
Short summary
Using open building data in the development of exposure data sets for catastrophe risk modelling
R. Figueiredo and M. Martina
Nat. Hazards Earth Syst. Sci., 16, 417–429, https://doi.org/10.5194/nhess-16-417-2016,https://doi.org/10.5194/nhess-16-417-2016, 2016
Short summary

Related subject area

Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Identifying the drivers of private flood precautionary measures in Ho Chi Minh City, Vietnam
Thulasi Vishwanath Harish, Nivedita Sairam, Liang Emlyn Yang, Matthias Garschagen, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 23, 1125–1138, https://doi.org/10.5194/nhess-23-1125-2023,https://doi.org/10.5194/nhess-23-1125-2023, 2023
Short summary
Performance of the flood warning system in Germany in July 2021 – insights from affected residents
Annegret H. Thieken, Philip Bubeck, Anna Heidenreich, Jennifer von Keyserlingk, Lisa Dillenardt, and Antje Otto
Nat. Hazards Earth Syst. Sci., 23, 973–990, https://doi.org/10.5194/nhess-23-973-2023,https://doi.org/10.5194/nhess-23-973-2023, 2023
Short summary
Differences in volcanic risk perception among Goma's population before the Nyiragongo eruption of May 2021, Virunga volcanic province (DR Congo)
Blaise Mafuko Nyandwi, Matthieu Kervyn, François Muhashy Habiyaremye, François Kervyn, and Caroline Michellier
Nat. Hazards Earth Syst. Sci., 23, 933–953, https://doi.org/10.5194/nhess-23-933-2023,https://doi.org/10.5194/nhess-23-933-2023, 2023
Short summary
Empirical tsunami fragility modelling for hierarchical damage levels
Fatemeh Jalayer, Hossein Ebrahimian, Konstantinos Trevlopoulos, and Brendon Bradley
Nat. Hazards Earth Syst. Sci., 23, 909–931, https://doi.org/10.5194/nhess-23-909-2023,https://doi.org/10.5194/nhess-23-909-2023, 2023
Short summary
Quantifying the potential benefits of risk-mitigation strategies on future flood losses in Kathmandu Valley, Nepal
Carlos Mesta, Gemma Cremen, and Carmine Galasso
Nat. Hazards Earth Syst. Sci., 23, 711–731, https://doi.org/10.5194/nhess-23-711-2023,https://doi.org/10.5194/nhess-23-711-2023, 2023
Short summary

Cited articles

Apel, H., Aronica, G. T., Kreibich, H., and Thieken, A. H.: Flood risk analyses – how detailed do we need to be?, Nat. Hazards, 49, 79–98, https://doi.org/10.1007/s11069-008-9277-8, 2009.
Bröcker, J.: Evaluating raw ensembles with the continuous ranked probability score, Q. J. Roy. Meteor. Soc., 138, 1611–1617, https://doi.org/10.1002/qj.1891, 2012.
Buck, W. and Merkel, U.: Auswertung der HOWAS-Schadendatenbank, Institut für Wasserwirtschaft und Kulturtechnik der Universität Karlsruhe, 1999.
Budiyono, Y., Aerts, J., Brinkman, J. J., Marfai, M. A., and Ward, P.: Flood risk assessment for delta mega-cities: a case study of Jakarta, Nat. Hazards, 75, 389–413, https://doi.org/10.1007/s11069-014-1327-9, 2015.
Cammerer, H., Thieken, A. H., and Lammel, J.: Adaptability and transferability of flood loss functions in residential areas, Nat. Hazards Earth Syst. Sci., 13, 3063–3081, https://doi.org/10.5194/nhess-13-3063-2013, 2013.
Download
Short summary
Flood loss modelling is subject to large uncertainty that is often neglected. Most models are deterministic, and large disparities exist among them. Adopting a single model may lead to inaccurate loss estimates and sub-optimal decision-making. This paper proposes the use of multi-model ensembles to address such issues. We demonstrate that this can be a simple and pragmatic approach to obtain more accurate loss estimates and reliable probability distributions of model uncertainty.
Altmetrics
Final-revised paper
Preprint