Publication Date:
2017-04-04
Description:
The statistical modeling of the time-size distribution
of volcanic eruptions is a fundamental tool to understand
better the physics of the eruptive process, and to make
reliable forecasts [Newhall and Hoblitt, 2002; Connor et al.,
2003; Marzocchi et al., 2004a; Sparks and Aspinall, 2004].
Eruption forecasting is commonly associated to different
timescales (short-, intermediate-, and long-term; see definition
by Newhall and Hoblitt [2002]). Regardless of the time
frame, the statistical modeling of the past behavior of a
volcano is a key ingredient for quantitative forecasting
(usually, but not necessarily, over long time intervals) when
the volcano has an almost stationary state (for instance, it is
dormant). In this case, monitoring data are not particularly
informative of the future evolution of the system, at least
until the volcano becomes restless and/or changes its
stationary state. Hereinafter, the terms ‘‘eruption forecasting’’
and ‘‘volcanic hazard’’ refer to this stationary case.
[3] The main difficulties in providing a general model of
eruptive activity are linked to the existence of different
types of volcanic activity, to the paucity of eruptive data for
most volcanoes, and to the intrinsic complexity of eruptive
processes. As a consequence, most of the past papers
devoted to this issue are focused on single (or very few)
volcanoes [e.g., Wickman, 1976; Klein, 1982; Burt et al.,
1994; Bebbington and Lai, 1996; Marzocchi, 1996; Connor
et al., 2003; Gusev et al., 2003; Sandri et al., 2005] where
detailed eruptive catalogs exist. This approach limits the
generality of the results. We cannot know if the behavior of
the volcano analyzed represents a generic feature of a
specific type of volcanism, or if it is peculiar of the volcano
itself. Under this perspective, part of the different statistical
distributions found by analyzing single eruptive catalogs
can be explained by the existence of some peculiarities in
volcanic activity.
[4] One way to overcome this drawback, which we use
here, is to perform a common analysis on data from several
volcanoes. In particular, we test the Poisson hypothesis in
the time domain, and the reliability of time-size distributions
such as the time predictable model and size predictable
model. The results obtained are then used to build a
quantitative model of the statistical time-size distribution
for some classes of volcanic activities that can be used for
volcanic hazard assessment.
Description:
Published
Description:
B04204
Description:
JCR Journal
Description:
reserved
Keywords:
quantitative model
;
eruptions
;
04. Solid Earth::04.08. Volcanology::04.08.08. Volcanic risk
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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