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.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-2091-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Aug 2020
Research article |
| 06 Aug 2020
| 06 Aug 2020
Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios
Department of Geography, King's College London, London, WC2B 4BG,
United Kingdom
Bruce D. Malamud
Department of Geography, King's College London, London, WC2B 4BG,
United Kingdom
Hugo Winter
EDF Energy R&D UK Centre, Croydon, CR0 2AJ, United Kingdom
Amélie Joly-Laugel
EDF Energy R&D UK Centre, Croydon, CR0 2AJ, United Kingdom
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18 citations as recorded by crossref.
- Invited perspectives: An insurer's perspective on the knowns and unknowns in natural hazard risk modelling M. Déroche 10.5194/nhess-23-251-2023
- Extremal Dependence Modelling of Global Horizontal Irradiance with Temperature and Humidity: An Application Using South African Data C. Sigauke et al. 10.3390/en15165965
- Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach D. Maposa et al. 10.1007/s11069-021-04608-w
- Revealing alarming changes in spatial coverage of joint hot and wet extremes across India S. Dash & R. Maity 10.1038/s41598-021-97601-z
- A Framework for Effective Multi-Hazard Risk Assessment in Post-Mining Areas D. Nalmpant-Sarikaki et al. 10.3390/safety11010018
- Increasing dam failure risk in the USA due to compound rainfall clusters as climate changes J. Hwang & U. Lall 10.1038/s44304-024-00027-6
- Preface: Advances in extreme value analysis and application to natural hazards Y. Hamdi et al. 10.5194/nhess-21-1461-2021
- Quantifying the joint distribution of drought indicators in Borneo fire-prone area M. Najib et al. 10.1088/1755-1315/880/1/012002
- A copula-based assessment of renewable energy droughts across Europe N. Otero et al. 10.1016/j.renene.2022.10.091
- New estimation methods for extremal bivariate return curves C. Murphy‐Barltrop et al. 10.1002/env.2797
- A comparative analysis of semi-quantitative multi-hazard methodologies with an application to a post-mining area D. Nalmpant-Sarikaki et al. 10.1007/s11069-025-07282-4
- Flash flood susceptibility mapping of north-east depression of Bangladesh using different GIS based bivariate statistical models M. Chowdhury 10.1016/j.wsee.2023.12.002
- Analysis of the simultaneous actions of vertical and horizontal temperature differences in transverse direction of concrete bridge box girders D. Ngo et al. 10.1016/j.cscm.2024.e03732
- Compound droughts and hot extremes: Characteristics, drivers, changes, and impacts Z. Hao et al. 10.1016/j.earscirev.2022.104241
- Trivariate copula to design coastal structures O. Orcel et al. 10.5194/nhess-21-239-2021
- An Integrated Trivariate-Dimensional Statistical and Hydrodynamic Modeling Method for Compound Flood Hazard Assessment in a Coastal City W. Wang et al. 10.3390/land14040816
- A Copula-Based Assessment of Renewable Energy Droughts Across Europe N. Otero Felipe et al. 10.2139/ssrn.3980444
- Multi-hazard risk characterization and collaborative control oriented to space in non-coal underground mines M. Wu et al. 10.1038/s41598-022-20437-8
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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.
Estimating risks induced by interacting natural hazards remains a challenge for practitioners....
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