Probabilistic Volcanic Hazard Assessment
Document Type
Book Chapter
Publication Date
2015
Keywords
Bayesian event tree, Eruption forecast, Eruption frequency, Eruption recurrence rate, Hazard curve, Hazard map, Probabilistic volcanic hazard, Vent distribution
Digital Object Identifier (DOI)
https://doi.org/10.1016/B978-0-12-385938-9.00051-1
Abstract
This chapter provides an introduction to a wide range of methods volcanologists may use to forecast eruptions and their potential effects. Eruption forecasts are expressed in terms of probability of the timing of volcanic eruptions, their likely locations, magnitudes and products. Prior to observing volcanic unrest, forecasts are often articulated in terms of long-term volcanic hazard assessments that rely primarily on the distribution and nature of past volcanic events. Methods are presented to assess recurrence rates of volcanic eruptions, especially using steady-state Poisson and non-Poissonian renewal models. Tests are provided for steady-state eruption recurrence rate and model comparison methods using the Akaike Information Criterion. Potential locations of new volcanic vents may be estimated using nonparametric kernel density methods and combined with numerical simulations of volcanic processes, such as the dispersion of tephra and lava flowemplacement, to create hazard curves for specific locations and hazard maps for specific areas. These tools are incorporated into a Bayesian framework for estimating volcanic hazards using event trees, with the important result that a wide range of potential eruption consequences may be visualized and evaluated.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Probabilistic Volcanic Hazard Assessment, in H. Sigurdsson (Ed.), The Encyclopedia of Volcanoes (Second Edition), Academic Press, p. 897-910
Scholar Commons Citation
Connor, Charles; Bebbington, Mark S.; and Marzocchi, Warner, "Probabilistic Volcanic Hazard Assessment" (2015). School of Geosciences Faculty and Staff Publications. 1681.
https://digitalcommons.usf.edu/geo_facpub/1681
