Articles | Volume 23, issue 6
https://doi.org/10.5194/nhess-23-2203-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-2203-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Scenario-based multi-risk assessment from existing single-hazard vulnerability models. An application to consecutive earthquakes and tsunamis in Lima, Peru
Juan Camilo Gómez Zapata
CORRESPONDING AUTHOR
Seismic Hazard and Risk Dynamics, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Institute for Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24–25, 14476 Potsdam, Germany
Massimiliano Pittore
Seismic Hazard and Risk Dynamics, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Institute for Earth Observation, EURAC Research, Viale Druso 1, 39100 Bolzano, Italy
Nils Brinckmann
eScience Centre, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Juan Lizarazo-Marriaga
Departamento de Ingeniería Civil y Agrícola, Universidad Nacional de Colombia, 11001 sede Bogotá, Colombia
Sergio Medina
Departamento de Ingeniería Civil y Agrícola, Universidad Nacional de Colombia, 11001 sede Bogotá, Colombia
Nicola Tarque
Gerdis Research Group, Civil Eng. Division, Pontificia Universidad Católica del Perú, Av. Universitaria 1801, Lima 15088, Peru
Department of Continuum Mechanics and Structures, Universidad Politécnica de Madrid, Calle Prof. Aranguren 3, 28040 Madrid, Spain
Fabrice Cotton
Seismic Hazard and Risk Dynamics, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Institute for Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24–25, 14476 Potsdam, Germany
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Cited
12 citations as recorded by crossref.
- Deep multitask learning with label interdependency distillation for multicriteria street-level image classification P. Aravena Pelizari et al. 10.1016/j.isprsjprs.2023.09.001
- Random forest-based multi-hazard loss estimation using hypothetical data at seismic and tsunami monitoring networks Y. Li & K. Goda 10.1080/19475705.2023.2275538
- Preface: Multi-risk assessment in the Andes region E. Schoepfer et al. 10.5194/nhess-25-1163-2025
- Assessment of Building Vulnerability to Tsunami in Ancon Bay, Peru, Using High-Resolution Unmanned Aerial Vehicle Imagery and Numerical Simulation C. Davila et al. 10.3390/drones9060402
- Multi-hazard vulnerability of code non-conforming RC buildings under earthquake followed by cascading landslide A. Kunwar et al. 10.1016/j.nhres.2025.01.013
- From single to multi-risk perspective: How heatwaves risk mitigation solutions can reduce terrorist risk in historic outdoor open areas G. Bernardini et al. 10.1016/j.scs.2025.106412
- Multi-hazard life-cycle consequence analysis of deteriorating engineering systems K. Otárola et al. 10.1016/j.strusafe.2024.102515
- A Bibliographic Analysis of Multi-Risk Assessment Methodologies for Natural Disaster Prevention G. Grandjean 10.3390/geohazards6030041
- Between global risk reduction goals, scientific–technical capabilities and local realities: a modular approach for user-centric multi-risk assessment E. Schoepfer et al. 10.5194/nhess-24-4631-2024
- A Review of Probabilistic Approaches for Assessing the Liquefaction Hazard in Urban Areas A. Cruz et al. 10.1007/s11831-024-10124-4
- High-resolution multi-hazard residential buildings and population exposure model for coastal areas: A case study in northeastern Italy H. Badreldin et al. 10.1016/j.ijdrr.2025.105403
- From repair costs and casualties to human displacements in the aftermath of an earthquake. The case of buildings with and without pre-existing damage exposed to a Mw 7.1 scenario in the Messina Strait, Italy J. Gomez-Zapata et al. 10.1080/19475705.2025.2512357
12 citations as recorded by crossref.
- Deep multitask learning with label interdependency distillation for multicriteria street-level image classification P. Aravena Pelizari et al. 10.1016/j.isprsjprs.2023.09.001
- Random forest-based multi-hazard loss estimation using hypothetical data at seismic and tsunami monitoring networks Y. Li & K. Goda 10.1080/19475705.2023.2275538
- Preface: Multi-risk assessment in the Andes region E. Schoepfer et al. 10.5194/nhess-25-1163-2025
- Assessment of Building Vulnerability to Tsunami in Ancon Bay, Peru, Using High-Resolution Unmanned Aerial Vehicle Imagery and Numerical Simulation C. Davila et al. 10.3390/drones9060402
- Multi-hazard vulnerability of code non-conforming RC buildings under earthquake followed by cascading landslide A. Kunwar et al. 10.1016/j.nhres.2025.01.013
- From single to multi-risk perspective: How heatwaves risk mitigation solutions can reduce terrorist risk in historic outdoor open areas G. Bernardini et al. 10.1016/j.scs.2025.106412
- Multi-hazard life-cycle consequence analysis of deteriorating engineering systems K. Otárola et al. 10.1016/j.strusafe.2024.102515
- A Bibliographic Analysis of Multi-Risk Assessment Methodologies for Natural Disaster Prevention G. Grandjean 10.3390/geohazards6030041
- Between global risk reduction goals, scientific–technical capabilities and local realities: a modular approach for user-centric multi-risk assessment E. Schoepfer et al. 10.5194/nhess-24-4631-2024
- A Review of Probabilistic Approaches for Assessing the Liquefaction Hazard in Urban Areas A. Cruz et al. 10.1007/s11831-024-10124-4
- High-resolution multi-hazard residential buildings and population exposure model for coastal areas: A case study in northeastern Italy H. Badreldin et al. 10.1016/j.ijdrr.2025.105403
- From repair costs and casualties to human displacements in the aftermath of an earthquake. The case of buildings with and without pre-existing damage exposed to a Mw 7.1 scenario in the Messina Strait, Italy J. Gomez-Zapata et al. 10.1080/19475705.2025.2512357
Latest update: 28 Aug 2025
Short summary
To investigate cumulative damage on extended building portfolios, we propose an alternative and modular method to probabilistically integrate sets of single-hazard vulnerability models that are being constantly developed by experts from various research fields to be used within a multi-risk context. We demonstrate its application by assessing the economic losses expected for the residential building stock of Lima, Peru, a megacity commonly exposed to consecutive earthquake and tsunami scenarios.
To investigate cumulative damage on extended building portfolios, we propose an alternative and...
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