Temporal models for the occurrence of Etna eruptions and implications for hazard assessment
- 1INGV Sezione di Bologna (Bologna, Italy)
Abstract
Mt. Etna volcanic activity is broadly divided into flank eruptions and summit paroxysms. Here, building on previously-available literature and data on the start time of these events, we collate two separate catalogs of the two activity types. Then we separately model their temporal occurrence. The catalog of flank eruptions, spanning the last 400 years, has been modelled by means of the most widely used renewal models, among which the best one (through Akaike Information Criterion) is the Brownian Passage Time. The catalog of summit paroxysms, covering the period 1986–2022, according to our cluster analysis is best characterized by 12 clusters of paroxysms. We separately analyze the inter-event times between onset times of successive clusters of paroxysms (Inter-Cluster inter-event times) and the inter-event times between successive paroxysms within clusters (Intra-Cluster inter-event times). Again, the Brownian Passage Time is the best-fitting model, obviously with very different parameters in the two cases. We test the best-fitting models by checking their ability to reproduce features of the real catalogs. Finally, we provide an example of how to use in practice such temporal models in the context of probabilistic hazard assessment, showing a possible use in the case of tephra fallout hazard from summit paroxysms. In particular, the proposed temporal model enables the assessment of probabilistic volcanic hazard for tephra fallout over different time windows accounting also for the uncertainty in the temporal occurrence of summit paroxysms.
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BibTeX
@article{sandri2026temporal,
title = {{Temporal models for the occurrence of Etna eruptions and implications for hazard assessment}},
author = {Laura Sandri and Alexander Garcia and Simona Scollo and Luigi Mereu and Michele Prestifilippo},
journal = {Natural Hazards and Earth System Sciences},
year = {2026},
month = oct,
doi = {10.5194/nhess-26-5151-2026},
url = {https://nhess.copernicus.org/articles/26/5151/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Temporal models for the occurrence of Etna eruptions and implications for hazard assessment
AU - Laura Sandri
AU - Alexander Garcia
AU - Simona Scollo
AU - Luigi Mereu
AU - Michele Prestifilippo
PY - 2026
DA - 2026/10/22
JO - Natural Hazards and Earth System Sciences
DO - 10.5194/nhess-26-5151-2026
UR - https://nhess.copernicus.org/articles/26/5151/2026/
AB - Mt. Etna volcanic activity is broadly divided into flank eruptions and summit paroxysms. Here, building on previously-available literature and data on the start time of these events, we collate two separate catalogs of the two activity types. Then we separately model their temporal occurrence. The catalog of flank eruptions, spanning the last 400 years, has been modelled by means of the most widely used renewal models, among which the best one (through Akaike Information Criterion) is the Brownian Passage Time. The catalog of summit paroxysms, covering the period 1986–2022, according to our cluster analysis is best characterized by 12 clusters of paroxysms. We separately analyze the inter-event times between onset times of successive clusters of paroxysms (Inter-Cluster inter-event times) and the inter-event times between successive paroxysms within clusters (Intra-Cluster inter-event times). Again, the Brownian Passage Time is the best-fitting model, obviously with very different parameters in the two cases. We test the best-fitting models by checking their ability to reproduce features of the real catalogs. Finally, we provide an example of how to use in practice such temporal models in the context of probabilistic hazard assessment, showing a possible use in the case of tephra fallout hazard from summit paroxysms. In particular, the proposed temporal model enables the assessment of probabilistic volcanic hazard for tephra fallout over different time windows accounting also for the uncertainty in the temporal occurrence of summit paroxysms.
SN - 1684-9981
ER -