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

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

doi:https://doi.org/10.5194/nhess-20-2091-2020

Articles | Volume 20, issue 8

https://doi.org/10.5194/nhess-20-2091-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Advances in extreme value analysis and application to natural...

https://doi.org/10.5194/nhess-20-2091-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 8

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

Supplement

https://doi.org/10.5194/nhess-20-2091-2020-supplement

Data sets

Comparison of bivariate extreme modelling approaches for multi-hazard scenarios Alois Tilloy https://doi.org/10.5281/zenodo.3686962

UERRA Project UERRA http://www.uerra.eu/

ECA&D Project ECA&D https://www.ecad.eu/

Model code and software

Comparison of bivariate extreme modelling approaches for multi-hazard scenarios Alois Tilloy https://doi.org/10.5281/zenodo.3686962

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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.