EGU26-14573, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-14573
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 05 May, 15:00–15:10 (CEST)
 
Room N2
An extended hazard interaction matrix for analysing multi-hazard complexity in data-scarce regions: An application to Kerala, India
Anisha Desai1, Marlies Barendrecht1, Fatemeh Jalayer2, and Faith Taylor1
Anisha Desai et al.
  • 1King's College London, Department of Geography, United Kingdom (anisha.desai@kcl.ac.uk)
  • 2University College London, Institute or Risk and Disaster Reduction, United Kingdom

This paper develops an evidence-based database of multi-hazard interrelationships in a data-scarce context that extends beyond the primary focus on cascading and amplifying interaction mechanisms. The methodology is applied to Kerala, India. Drawing on academic literature, grey literature, and media sources, the database captures both well-documented and underreported hazards and their interactions, whether historically observed or theoretically possible. The final database contains evidence of 22 distinct hazard types across six hazard groups and 137 potential hazard interrelationships. To support interpretation, an adapted hazard interaction matrix was developed that extends existing frameworks by (i) incorporating a broader range of interaction mechanisms beyond traditional cascading and amplifying effects, and (ii) enabling representation of three-way hazard interactions, advancing beyond conventional pairwise models. Results indicate that while cascading and disposition alteration mechanisms dominate the interrelationships observed in Kerala, 26% of identified interactions arise from other mechanisms. This demonstrates that restricting analyses to a limited subset of interaction types does not fully capture the region’s multi-hazard complexity. The matrix was further enhanced to capture seasonal variation in interaction potential throughout the year. Incorporating seasonality reveals distinct temporal windows of elevated interaction potential shaped by monsoon rainfall and temperature variability. When applying seasonal filters, the number of potential interrelationships identified was reduced by approximately 10%. This study demonstrates that interaction-focused, seasonally informed frameworks can reveal multi-hazard dynamics that may otherwise be overlooked when analysing only a subset of hazard types and interaction mechanisms.

How to cite: Desai, A., Barendrecht, M., Jalayer, F., and Taylor, F.: An extended hazard interaction matrix for analysing multi-hazard complexity in data-scarce regions: An application to Kerala, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14573, https://doi.org/10.5194/egusphere-egu26-14573, 2026.