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Investigating the development of eruption source parameters probability density functions

Engwell, Samantha; de' Michieli Vitturi, Mattia; Pardini, Federica; Di Vito, Mauro; Scollo, Simona. 2023 Investigating the development of eruption source parameters probability density functions. [Poster] In: IAVCEI 2023, Rotorua, New Zealand, 29 Jan - 3 Feb 2023. British Geological Survey. (Unpublished)

Abstract
Eruption source parameters are required for the initiation of numerical models, and significant work has gone into their estimation for volcanic ash transport and dispersal models. In application of these models, typically a given scenario or range of scenarios is used to inform source parameters and modelling approach. However, increasing computational competencies allow for more complex input parameters to be used with a look towards probabilistic model outputs. Here, we investigate the potential for developing probability density functions for inputs, in particular plume height, for ash-dispersal models using Etna volcano, Italy as a case study. We brought together information from the published record, from eruption databases, and from volcanic ash advisories (VAAs), to inform eruption source parameters. Despite being one of the most well studied and monitored volcanoes in the world, difficulties arose around data availability and bias. Published records tend to have a low temporal resolution and, through analysis of deposits, focus on larger eruptions, while the VAAs capture more recent activity at high temporal resolutions, but which has tended to be at lower levels. Distributions of plume height produced from combining information from these different datasets had long tails to large plume heights, which were difficult to confidently fit with commonly used distributions. Our analysis shows that producing probability density functions of eruption source parameters for a given volcano is nontrivial and limited by uncertainties and bias within eruption data.
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BGS Programmes 2020 > Multihazards & resilience
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