A framework to quantify the impacts of multi-hazard interactions

Hazards do not always occur in isolation. They often interact in space and time, triggering, compounding, or amplifying each other, resulting in complex, cascading impacts. Recent decades have seen a rise in the frequency, intensity, and complexity of such events. Understanding how one hazard can trigger or increase the likelihood of another is essential for realistic risk assessment <br/>and effective decision-making. Recognising this, the Sendai Framework for Disaster Risk Reduction have called for integrated, multi-hazard approaches to risk assessment and management. However, despite advances in multi-hazard risk analysis, existing methods still fall short in quantifying the dynamic and interconnected nature of multi-hazards. Traditional approaches have typically focused on single hazards or considered multiple hazards independently, neglecting the ways in which hazards can interact over space and time. This can lead to underestimation of risk.<br/><br/>To address these, the study introduces a structured, five-step framework designed to quantify and visualize multi-hazard interactions. The framework begins with the identification of relevant hazards and their potential interrelations, such as triggering, cascading, conditioning and independent. Spatially, the hazards can be overlapping, source and spread or not overlapping and temporal interrelations include simultaneous, consecutive and events after a long time. In the third step, hazard modelling approaches are applied to reflect these interactions. Step four incorporates evolving exposure and vulnerability, accounting for dynamic changes. This emphasizes that disaster impacts are not static, and assets can become vulnerable as events occur. The final step is the impact assessment that accounts for interrelations.<br/><br/>The final step is impact assessment that accounts for interrelations. The study also presents a novel visual method that organizes multi-hazard events along a temporal axis and categorical sections for triggers, hazards, and impacts. This framework and visualisation help stakeholders grasp the sequence and interdependence of events, supporting both retrospective analysis and forward-looking perspectives. To demonstrate the framework’s applicability, three real-world case studies are analyzed: the 2023 Kahramanmaraş earthquakes in <br/>Turkey, the 2021 La Soufrière volcanic eruption in Saint Vincent and a case study of Dominica. The results highlight how multi-hazard interactions can have non-linear, compounding effects and alter exposure and vulnerability conditions. By systematically capturing these patterns, the framework not only reconstructs past event sequences but also aids in anticipating future scenarios under evolving conditions.

Authors

Publication Details

Journal
University of Twente Research Information
Published
2025-10-01
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A framework to quantify the impacts of multi-hazard interactions

Mariya Sunil, F.; id_orcid 0000-0002-6222-8049 Atun, C.; id_orcid 0000-0002-2992-902X van Westen, I.; id_orcid 0000-0001-7518-819X Manzella
University of Twente Research Information
Disaster Management and Resilience
article

A framework to quantify the impacts of multi-hazard interactions

Mariya Sunil, F.; id_orcid 0000-0002-6222-8049 Atun, C.; id_orcid 0000-0002-2992-902X van Westen, I.; id_orcid 0000-0001-7518-819X Manzella
article en

Abstract

Hazards do not always occur in isolation. They often interact in space and time, triggering, compounding, or amplifying each other, resulting in complex, cascading impacts. Recent decades have seen a rise in the frequency, intensity, and complexity of such events. Understanding how one hazard can trigger or increase the likelihood of another is essential for realistic risk assessment <br/>and effective decision-making. Recognising this, the Sendai Framework for Disaster Risk Reduction have called for integrated, multi-hazard approaches to risk assessment and management. However, despite advances in multi-hazard risk analysis, existing methods still fall short in quantifying the dynamic and interconnected nature of multi-hazards. Traditional approaches have typically focused on single hazards or considered multiple hazards independently, neglecting the ways in which hazards can interact over space and time. This can lead to underestimation of risk.<br/><br/>To address these, the study introduces a structured, five-step framework designed to quantify and visualize multi-hazard interactions. The framework begins with the identification of relevant hazards and their potential interrelations, such as triggering, cascading, conditioning and independent. Spatially, the hazards can be overlapping, source and spread or not overlapping and temporal interrelations include simultaneous, consecutive and events after a long time. In the third step, hazard modelling approaches are applied to reflect these interactions. Step four incorporates evolving exposure and vulnerability, accounting for dynamic changes. This emphasizes that disaster impacts are not static, and assets can become vulnerable as events occur. The final step is the impact assessment that accounts for interrelations.<br/><br/>The final step is impact assessment that accounts for interrelations. The study also presents a novel visual method that organizes multi-hazard events along a temporal axis and categorical sections for triggers, hazards, and impacts. This framework and visualisation help stakeholders grasp the sequence and interdependence of events, supporting both retrospective analysis and forward-looking perspectives. To demonstrate the framework’s applicability, three real-world case studies are analyzed: the 2023 Kahramanmaraş earthquakes in <br/>Turkey, the 2021 La Soufrière volcanic eruption in Saint Vincent and a case study of Dominica. The results highlight how multi-hazard interactions can have non-linear, compounding effects and alter exposure and vulnerability conditions. By systematically capturing these patterns, the framework not only reconstructs past event sequences but also aids in anticipating future scenarios under evolving conditions.

University of Twente Research Information
Climate action
Openalex Percentile: Top 11%
Disaster Management and Resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.