Disasters classification in a compound event perspective: insights from existing databases

Natural disasters often result from compound event dynamics, in which multiple interacting drivers converge across spatial and temporal scales, significantly amplifying their impacts. The concept of compound events has gained increasing attention in recent literature, offering opportunities to enhan...

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Main Authors: Carlo De Michele, Fabiola Banfi, Maria Pia Russomando
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Letters
Subjects:
Online Access:https://doi.org/10.1088/1748-9326/ade72d
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author Carlo De Michele
Fabiola Banfi
Maria Pia Russomando
author_facet Carlo De Michele
Fabiola Banfi
Maria Pia Russomando
author_sort Carlo De Michele
collection DOAJ
description Natural disasters often result from compound event dynamics, in which multiple interacting drivers converge across spatial and temporal scales, significantly amplifying their impacts. The concept of compound events has gained increasing attention in recent literature, offering opportunities to enhance disaster understanding, while also presenting challenges and open issues for modern risk assessment frameworks. This study investigates the capability of existing disasters/extreme events databases (Emergency Events Database EM-DAT, Severe Weather Data Inventory SWDI, and Canadian Disaster Database CDD) to capture compound event dynamics, and assess the accuracy of reported impacts. We found that SWDI, a national dataset for the USA, reports a high number of compound events versus single events, always higher than 50%, except for wildfires, and its structure allows for accurately identify spatially compounding events. This percentage in EM-DAT, a global dataset, is always lower than 50%, except for storms. A good match in events occurrences can be observed between the three databases, however the agreement in terms of deaths and injures varies depending on the databases compared. Finally, the work highlights the limitations of existing databases in representing the multidimensional nature of risks, and the cascading impacts that emerge from compound hazards. Reclassifying disasters from a compound event perspective not only enriches our knowledge of hazard dynamics, but also provides actionable pathways for improving risk assessment, informing adaptive policies, and enhancing resilience to the growing complexity of environmental challenges.
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spelling doaj-art-23d8fc5d1d144e5aa44f26409c68e3742025-08-20T03:50:16ZengIOP PublishingEnvironmental Research Letters1748-93262025-01-0120808405410.1088/1748-9326/ade72dDisasters classification in a compound event perspective: insights from existing databasesCarlo De Michele0https://orcid.org/0000-0002-7098-4725Fabiola Banfi1https://orcid.org/0000-0002-9774-9071Maria Pia Russomando2https://orcid.org/0009-0007-0780-5556Department of Civil and Environmental Engineering, Politecnico di Milano , 20133 Milano, ItalyDepartment of Civil and Environmental Engineering, Politecnico di Milano , 20133 Milano, ItalyDepartment of Civil and Environmental Engineering, Politecnico di Milano , 20133 Milano, ItalyNatural disasters often result from compound event dynamics, in which multiple interacting drivers converge across spatial and temporal scales, significantly amplifying their impacts. The concept of compound events has gained increasing attention in recent literature, offering opportunities to enhance disaster understanding, while also presenting challenges and open issues for modern risk assessment frameworks. This study investigates the capability of existing disasters/extreme events databases (Emergency Events Database EM-DAT, Severe Weather Data Inventory SWDI, and Canadian Disaster Database CDD) to capture compound event dynamics, and assess the accuracy of reported impacts. We found that SWDI, a national dataset for the USA, reports a high number of compound events versus single events, always higher than 50%, except for wildfires, and its structure allows for accurately identify spatially compounding events. This percentage in EM-DAT, a global dataset, is always lower than 50%, except for storms. A good match in events occurrences can be observed between the three databases, however the agreement in terms of deaths and injures varies depending on the databases compared. Finally, the work highlights the limitations of existing databases in representing the multidimensional nature of risks, and the cascading impacts that emerge from compound hazards. Reclassifying disasters from a compound event perspective not only enriches our knowledge of hazard dynamics, but also provides actionable pathways for improving risk assessment, informing adaptive policies, and enhancing resilience to the growing complexity of environmental challenges.https://doi.org/10.1088/1748-9326/ade72dreclassifyingdisasterscompoundeventperspective
spellingShingle Carlo De Michele
Fabiola Banfi
Maria Pia Russomando
Disasters classification in a compound event perspective: insights from existing databases
Environmental Research Letters
reclassifying
disasters
compound
event
perspective
title Disasters classification in a compound event perspective: insights from existing databases
title_full Disasters classification in a compound event perspective: insights from existing databases
title_fullStr Disasters classification in a compound event perspective: insights from existing databases
title_full_unstemmed Disasters classification in a compound event perspective: insights from existing databases
title_short Disasters classification in a compound event perspective: insights from existing databases
title_sort disasters classification in a compound event perspective insights from existing databases
topic reclassifying
disasters
compound
event
perspective
url https://doi.org/10.1088/1748-9326/ade72d
work_keys_str_mv AT carlodemichele disastersclassificationinacompoundeventperspectiveinsightsfromexistingdatabases
AT fabiolabanfi disastersclassificationinacompoundeventperspectiveinsightsfromexistingdatabases
AT mariapiarussomando disastersclassificationinacompoundeventperspectiveinsightsfromexistingdatabases