Suitability of energy cone for probabilistic volcanic hazard assessment: validation tests at Somma-Vesuvius and Campi Flegrei (Italy)

Pyroclastic density currents (PDCs) are gravity-driven hot mixtures of gas and volcanic particles which can propagate at high speed and cover distances up to several tens of kilometers around a given volcano. Therefore, they pose a severe hazard to the surroundings of explosive volcanoes able to produce such phenomena. Despite this threat, probabilistic volcanic hazard assessment (PVHA) of PDCs is still in an early stage of development. PVHA is rooted in the quantification of the large uncertainties (aleatory and epistemic) which characterize volcanic hazard analyses. This quantification typically requires a big dataset of hazard footprints obtained from numerical simulations of the physical process. For PDCs, numerical models range from very sophisticated (not useful for PVHA because of their very long runtimes) to very simple models (criticized because of their highly simplified physics). We present here a systematic and robust validation testing of a simple PDC model, the energy cone (EC), to unravel whether it can be applied to PVHA of PDCs. Using past PDC deposits at Somma-Vesuvius and Campi Flegrei (Italy), we assess the ability of EC to capture the values and variability in some relevant variables for hazard assessment, i.e., area of PDC invasion and maximum runout. In terms of area of invasion, the highest Jaccard coefficients range from 0.33 to 0.86 which indicates an equal or better performance compared to other volcanic mass-flow models. The p values for the observed maximum runouts vary from 0.003 to 0.44. Finally, the frequencies of PDC arrival computed from the EC are similar to those determined from the spatial distribution of past PDC deposits, with high PDC-arrival frequencies over an ∼8-km radius from the crater area at Somma-Vesuvius and around the Astroni crater at Campi Flegrei. The insights derived from our validation tests seem to indicate that the EC is a suitable candidate to compute PVHA of PDCs. © 2016, Springer-Verlag Berlin Heidelberg.