Depending on their magnitude and location, volcanic eruptions have the potential to become major social and economic disasters (e.g. Tambora, Indonesia, 1815; Vesuvius, Italy, AD 79; Soufriere Hills Volcano, Montserrat, 1995-present).One of the challenges for the volcanology community is to improve our understanding of volcanic processes so as to achieve successful assessments and mitigation of volcanic hazards, which are traditionally based on volcano monitoring and geological records. Geological records are crucial to our understanding of eruptive activity and history of a volcano, but often do not provide a comprehensive picture of the variation of volcanic processes and their effects on the surrounding area. The geological record is also typically biased towards the largest events, as deposits from smaller eruptions are often removed by erosion. Numerical modelling and probability analysis can be used to complement direct observations and to explore a much wider range of possible scenarios. As a result, numerical modelling and probabilistic analysis have become increasingly important in hazard assessment of volcanic hazards (e.g. Barberi et al. 1990; Heffter & Stunder 1993; Wadge et al. 1994, 1998; Hill et al. 1998; Iverson et al. 1998; Searcy et al. 1998; Canuti et al. 2002).
Reliable and comprehensive hazard assessments of volcanic This paper offers a detailed review of common approaches for hazard assessments of tephra dispersion. First, the main characteristics of tephra dispersion and tephra hazards are recounted. A critical use of field data for a
Figures & Tables
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.