Towards a background probability map for vent opening position in a future Plinian-subPlinian eruption of Somma-Vesuvius, with structured uncertainty assessment

Abstract

In this study we combine detailed reconstructions of volcanological datasets and inputs from structured expert judgement (SEJ) to produce a first background (i.e. long-term or base-rate) probability map for vent opening location in the next Plinian or Sub-Plinian eruption of Somma-Vesuvius (SV). The SV volcano has, over its history, exhibited large variability in eruptive styles, and moderate spatial variability in vent locations. In particular, the vent positions associated with large explosive eruptions, i.e. Plinian and Sub-Plinian, have shown shifts within the present SV caldera. Notwithstanding this moderate shift, the location of a new active vent will have a major effect on the run-out and dispersal of pyroclastic density currents mainly due to the presence of the Mt Somma barrier, as also evidenced by past deposit patterns and illustrated by numerical simulations, and therefore will have important implications for hazard mitigation. Thus far, we have focused on three main objectives: i) the collection and critical review of key volcanological features (position of past vents, distribution of faults, etc.) that could influence the spatial distribution of future vent locations; ii) developing spatial probability density maps with Gaussian kernel function modelling to use with our different volcanological and geophysical datasets, and iii) the production of a background probability map for vent opening position, using weighted linear combination of spatial density maps for the identified volcanological and geophysical parameters, with uncertainties explicitly included from structured expert elicitation. Preliminary outcomes obtained by a first elicitation session involving about 17 experts are reported for three expert judgement weighting and pooling models: (a) the Classical Model (CM) of Cooke (1991); (b) the Expected Relative Frequency (ERF) model of Flandoli et al. (2011), and (c) an Equal Weights (EW) combination. The results of combining expert judgements with our spatial modelling illustrate the influence of uncertainties in the various variables on the spatial probability content of the final maps, depicting areas at higher and lower probability of vent opening; second order effects of alternative methods for pooling judgements for quantifying uncertainty sources are discussed.