Articles | Volume 20, issue 8
https://doi.org/10.5194/nhess-20-2091-2020
https://doi.org/10.5194/nhess-20-2091-2020
Research article
 | 
06 Aug 2020
Research article |  | 06 Aug 2020

Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios

Aloïs Tilloy, Bruce D. Malamud, Hugo Winter, and Amélie Joly-Laugel

Related authors

HERA: a high-resolution pan-European hydrological reanalysis (1950–2020)
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, and Luc Feyen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-41,https://doi.org/10.5194/essd-2024-41, 2024
Preprint under review for ESSD
Short summary
Spatial identification of regions at risk to multi-hazards at pan European level: an implemented methodological approach
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-220,https://doi.org/10.5194/nhess-2023-220, 2024
Revised manuscript under review for NHESS
Short summary
A methodology for the spatiotemporal identification of compound hazards: wind and precipitation extremes in Great Britain (1979–2019)
Aloïs Tilloy, Bruce D. Malamud, and Amélie Joly-Laugel
Earth Syst. Dynam., 13, 993–1020, https://doi.org/10.5194/esd-13-993-2022,https://doi.org/10.5194/esd-13-993-2022, 2022
Short summary

Related subject area

Hydrological Hazards
An improved dynamic bidirectional coupled hydrologic–hydrodynamic model for efficient flood inundation prediction
Yanxia Shen, Zhenduo Zhu, Qi Zhou, and Chunbo Jiang
Nat. Hazards Earth Syst. Sci., 24, 2315–2330, https://doi.org/10.5194/nhess-24-2315-2024,https://doi.org/10.5194/nhess-24-2315-2024, 2024
Short summary
Quantifying hazard resilience by modeling infrastructure recovery as a resource-constrained project scheduling problem
Taylor Glen Johnson, Jorge Leandro, and Divine Kwaku Ahadzie
Nat. Hazards Earth Syst. Sci., 24, 2285–2302, https://doi.org/10.5194/nhess-24-2285-2024,https://doi.org/10.5194/nhess-24-2285-2024, 2024
Short summary
Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain
Arnau Amengual, Romu Romero, María Carmen Llasat, Alejandro Hermoso, and Montserrat Llasat-Botija
Nat. Hazards Earth Syst. Sci., 24, 2215–2242, https://doi.org/10.5194/nhess-24-2215-2024,https://doi.org/10.5194/nhess-24-2215-2024, 2024
Short summary
A downward-counterfactual analysis of flash floods in Germany
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 24, 2147–2164, https://doi.org/10.5194/nhess-24-2147-2024,https://doi.org/10.5194/nhess-24-2147-2024, 2024
Short summary
Hyper-resolution flood hazard mapping at the national scale
Günter Blöschl, Andreas Buttinger-Kreuzhuber, Daniel Cornel, Julia Eisl, Michael Hofer, Markus Hollaus, Zsolt Horváth, Jürgen Komma, Artem Konev, Juraj Parajka, Norbert Pfeifer, Andreas Reithofer, José Salinas, Peter Valent, Roman Výleta, Jürgen Waser, Michael H. Wimmer, and Heinz Stiefelmeyer
Nat. Hazards Earth Syst. Sci., 24, 2071–2091, https://doi.org/10.5194/nhess-24-2071-2024,https://doi.org/10.5194/nhess-24-2071-2024, 2024
Short summary

Cited articles

AghaKouchak, A., Huning, L. S., Chiang, F., Sadegh, M., Vahedifard, F., Mazdiyasni, O., Moftakhari, H., and Mallakpour, I.: How do natural hazards cascade to cause disasters?, Nature, 561, 458–460, 2018. 
Aitchison, J.: Lognormal Distribution, Cambridge University Press., Cambridge, UK, 1957. 
Akaike, H.: A new look at the statistical model identification, IEEE Trans. Automat. Contr., 19, 716–723, 1974. 
Anderson, G. and Klugmann, D.: A European lightning density analysis using 5 years of ATDnet data, Nat. Hazards Earth Syst. Sci., 14, 815–829, https://doi.org/10.5194/nhess-14-815-2014, 2014. 
Arnold, T. B. and Emerson, J. W.: Nonparametric goodness-of-fit tests for discrete null distributions, R J., 3, 34–39, 2011. 
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
Estimating risks induced by interacting natural hazards remains a challenge for practitioners. An approach to tackle this challenge is to use multivariate statistical models. Here we evaluate the efficacy of six models. The models are compared against synthetic data which are comparable to time series of environmental variables. We find which models are more appropriate to estimate relations between hazards in a range of cases. We highlight the benefits of this approach with two examples.
Altmetrics
Final-revised paper
Preprint