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Uncertainty quantification in volcanology: observations, numerical modelling, and hazard/risk assessment: preface to the special issue

Bulletin of Volcanology, Tadini et al. 2025 -Figura 1
Figure 1 a) Simplified scheme showing the main volcanic phenomena that can be observed during and/or before and/or after a volcanic eruption, including related secondary effects such as water-sediment flows (e.g., lahars), tsunamis or fires. b) Conceptual diagram showing the interconnected fields where uncertainty is present and how it can be quantified: direct (field) or indirect (remote sensing) observations, definition of the eruptive source parameters (through observations and/or via analysis of field data), direct and/or inverse numerical modelling, probabilistic volcanic hazard assessment, including different methodologies (e.g., expert elicitation; event trees; Bayesian Belief Networks; Monte Carlo/Polynomial Chaos methods/statistical emulators)

Tadini A., S. Massaro, A. Bevilacqua, P. Tierz, A. Aravena, (2025).
Bull Volcanol 87, 48. https://doi.org/10.1007/s00445-025-01835-y


Abstract

The observation and modelling of volcanic phenomena are always affected by a certain degree of uncertainty, both epistemic (i.e., related to incomplete knowledge of the phenomena) and aleatory (i.e., representing the physical variability typical of complex natural systems). While uncertainty can be reduced, it can never be fully eliminated. For instance, uncertainty does not necessarily make any model or data invalid; rather, effective assessments should (1) identify limitations; (2) support model calibration, validation, and benchmarking; and (3) provide confidence in measurements and model predictions. In particular, the study of volcanic hazard in a probabilistic framework has become one of the most rapidly developing topics in volcanology, with key applications in decision-making and risk-mitigation actions. A number of numerical tools have been developed to help scientists applying quantitative methods in different volcanic settings. These methods are essential for reproducing pre-, syn-, and post-eruptive volcanic processes under different conditions and over a wide range of spatial and temporal scales. In this Special Issue, we collected 10 contributions about uncertainty quantification of volcanic phenomena, with a specific focus on physical processes and/or hazard/risk assessments and maps, and uncertainty quantification of numerical models and field and laboratory data in volcanology. Examples include model validation and benchmarking studies, multi-model approaches, and the use of physical and statistical models in long and short-term probabilistic volcanic hazard assessments.