A quantitative model for volcanic hazard assessment
Published:January 01, 2006
Volcanic hazard assessment is a basic ingredient for risk-based decision-making in land-use planning and emergency management. Volcanic hazard is defined as the probability of any particular area being affected by a destructive volcanic event within a given period of time (Fournier d'Albe 1979). The probabilistic nature of such an important issue derives from the fact that volcanic activity is a complex process, characterized by several and usually unknown degrees of freedom that are often linked by nonlinear relationships (e.g. Bak et al. 1988). Except in sporadic cases, the result of this complexity is an intrinsic, and perhaps unavoidable, unpredictability of the time evolution of the volcanic system from a deterministic point of view.
In reality, current volcanic hazard assessment is even more entangled by scarce data and relatively poor knowledge of the physical processes. Cumulatively, these difficulties prevent a solution of the hazard or risk problem from a rigorous scientific perspective. Nevertheless, the potential for extreme risk pushes us to be pragmatic and to attempt to solve the problem from an ‘engineering’ point of view. Because of the devastating potential of volcanoes close to urbanized areas, the scientific community must address the issue as accurately and precisely as possible with the currently available methods and based on our current understanding of volcanic systems. This assessment is best done by treating scientific uncertainty in a fully structured manner. In this respect, Bayesian statistics provides a suitable framework for producing a volcanic hazard or risk assessments in
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Statistics in Volcanology
Statistics in Volcanology is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions. Specific topics include the use of expert elicitation and Bayesian methods in eruption forecasting, statistical models of temporal and spatial patterns of volcanic activity, analysis of time series in volcano seismology, probabilistic hazard assessment, and assessment of numerical models using robust statistical methods. Also provided are comprehensive overviews of volcanic phenomena, and a full glossary of both volcanological and statistical terms.
Statistics in Volcanology is essential reading for advanced undergraduates, graduate students, and research scientists interested in this multidisciplinary field.