Skip to content
DraconiticResearch
Search Sources API
189,280 studies31 sourcesUpdated 50 min ago
Peer-reviewedCC BYNature Communications

Compounding hazards increase flood economic losses across Europe

  • Michele Ronco1,2
  • Aloïs Tilloy3,4
  • Christina Corbane3,5
  • Damien Delforge6
  • Luc Feyen3,7
  • W. Jäger8,9
  • Alessia Matanó8,10
  • Dominik Paprotny11,12,13,9
  • Andrea Sibilia14,15
  • Timothy Tiggeloven16,8,17
  • Philip J. Ward18,8,19
19 affiliations
  1. 1European Commission, Joint Research Centre, Ispra, Italy. [email protected]
  2. 2European Commission
  3. 3European Commission, Joint Research Centre, Ispra, Italy
  4. 4European Commission Joint Research Centre
  5. 5European Commission, Joint Research Center, Ispra
  6. 6Institute of Health and Society (IRSS), University of Louvain (UCLouvain), Brussels, Belgium
  7. 7Joint Research Centre
  8. 8Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
  9. 9Institute for Environmental Studies, Vrije Universiteit Amsterdam
  10. 10Vrije Universiteit Amsterdam
  11. 11Baltic Climate Centre, University of Szczecin, Szczecin, Poland
  12. 12Institute of Marine and Environmental Sciences, University of Szczecin, Szczecin, Poland
  13. 13Research Department Transformation Pathways, Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
  14. 14Unisystems Luxembourg S.a.r.l. External Service Provider of European Commission Joint Research Centre, Ispra, Italy
  15. 15Vrije Universiteit, Institute for Environmental Studies
  16. 16CMCC Foundation, Euro-Mediterranean Center on Climate Change, Venice, Italy, Venice, Italy
  17. 17Potsdam Institute for Climate Impact Research (PIK)
  18. 18Deltares, Delft, The Netherlands
  19. 196Unisystems Luxembourg S.a.r.l
Open at sourceDOICite

Abstract

Compound events-combinations of multiple hazards contributing to societal or environmental risk-can significantly exacerbate disaster impacts, yet their effect on flood-related losses remains poorly quantified. Using a pan-European multi-hazard dataset spanning 1981-2020 at sub-national resolution, we find that more than 70% of recorded flood events involve compounding hazards, including meteorological extremes such as heatwaves and windstorms, alongside anomalous river discharge, with an increasing trend over time. The top 1% of events by economic losses are all compound, with total losses exceeding 167 billion euros above single-hazard floods. We introduce a compound hazard complexity metric and combine it with regional exposure and vulnerability data. Applying an ensemble machine learning model with explainable AI and a Double Machine Learning Causal Forest, we show that regions with higher complexity experience greater losses, even after controlling for flood magnitude and vulnerability, highlighting the importance of compound hazard information in risk modeling.

Related

  1. Climate change amplified wind-related economic losses during Cyclone Harry (2026)
    Davide Faranda, Marco Zanchi, Tommaso Alberti
    Quarterly Journal of the Royal Meteorological SocietyPeer-reviewedCC BY 4.0Full textAtmospheric science & meteorologyHAL
  2. Sensitivity analysis of annual energy production and associated economic losses due to external wake effects on offshore wind clusters: A case study of the Shinan offshore wind cluster in southwest sea of Korea
    Geonhwa Ryu, Dohee Lee, Jungho Kim +4
    PLOS OnePeer-reviewedCC BY 4.0Full textAtmospheric science & meteorologyFluid dynamicsPLOS
  3. Microplastic contamination in agricultural systems: impacts on plant productivity, economic losses, and supply chain resilience
    Tong Xu
    Frontiers in Plant SciencePeer-reviewedCC BY 4.0Full textEnvironmental science & pollutionCrossrefEurope PMC
  4. Fishery variability across distinct habitat groups in the Indian exclusive economic zone and its teleconnections to large-scale climate drivers
    Faseela Hamza, Vinu Valsala, Hamza Varikoden
    Scientific ReportsPeer-reviewedCC BYFull textClimate scienceDOAJ
  5. Spatially compounding climate extremes and environmental risk: cross-regional synchrony, spatial buffering loss, and systemic consequences
    Aihui Zhu, Dayun Zhu
    Environmental Research LettersPeer-reviewedCC BY 4.0Full textEnvironmental science & pollutionCrossref

Cite

BibTeXRIS
BibTeX
@article{ronco2026compounding,
  title = {{Compounding hazards increase flood economic losses across Europe}},
  author = {Michele Ronco and Aloïs Tilloy and Christina Corbane and Damien Delforge and Luc Feyen and W. Jäger and Alessia Matanó and Dominik Paprotny and Andrea Sibilia and Timothy Tiggeloven and Philip J. Ward},
  journal = {Nature Communications},
  year = {2026},
  month = may,
  doi = {10.1038/s41467-026-73248-0},
  url = {https://doi.org/10.1038/s41467-026-73248-0},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Compounding hazards increase flood economic losses across Europe
AU  - Michele Ronco
AU  - Aloïs Tilloy
AU  - Christina Corbane
AU  - Damien Delforge
AU  - Luc Feyen
AU  - W. Jäger
AU  - Alessia Matanó
AU  - Dominik Paprotny
AU  - Andrea Sibilia
AU  - Timothy Tiggeloven
AU  - Philip J. Ward
PY  - 2026
DA  - 2026/05/19
JO  - Nature Communications
DO  - 10.1038/s41467-026-73248-0
UR  - https://doi.org/10.1038/s41467-026-73248-0
AB  - Compound events-combinations of multiple hazards contributing to societal or environmental risk-can significantly exacerbate disaster impacts, yet their effect on flood-related losses remains poorly quantified. Using a pan-European multi-hazard dataset spanning 1981-2020 at sub-national resolution, we find that more than 70% of recorded flood events involve compounding hazards, including meteorological extremes such as heatwaves and windstorms, alongside anomalous river discharge, with an increasing trend over time. The top 1% of events by economic losses are all compound, with total losses exceeding 167 billion euros above single-hazard floods. We introduce a compound hazard complexity metric and combine it with regional exposure and vulnerability data. Applying an ensemble machine learning model with explainable AI and a Double Machine Learning Causal Forest, we show that regions with higher complexity experience greater losses, even after controlling for flood magnitude and vulnerability, highlighting the importance of compound hazard information in risk modeling.
SN  - 2041-1723
ER  -