The University of Reading, Environmental Systems Science Centre

Tea 3:30, Meeting ends 5:00pm

Ian Main (The University of Edinburgh)
**Earthquake Statistics and Predictability**

The mitigation of earthquake hazard depends on a quantification of
the point process of earthquake recurrence in space and time.
Combined with wave propagation information, and the seismic
response of local building sites, this information can be used to
produce seismic hazard maps that can be used for land use
planning and building design codes. Current practice centres on
time-independent (Poisson) hazard calculations that are stationary
in time, although non-stationarly processes such as earthquake
foreshocks and aftershocks are known to occur. Here I consider
the population dynamics of earthquakes, and test hypotheses of
earthquake occurrence against natural data. First I briefly describe
the statistical mechanics of earthquakes, and show cellular
automaton models that predict (a) quasi-stationary Boltmann
fluctuations in total system energy about a steady-state and (b) a
gamma form for the probability density function for the earthquake
energy. The results map to those expected at the critical
branching model in statistics, the percolation threshold in
stochastic flow problems, or the critical point in second-order
phase transitions. These predictions are compared to data from
the global frequency-energy catalogue, and confirmed using a
Bayesian Information Criterion which tests alternative hypotheses
with varying numbers of model parameters. In order to test the
time-dependent component, we examine the global catalogue for
triggered event pairs, compared to a Poisson background process.
the results show a trigerring correlation length of 10-20 km or so,
similar to the brittle thiockness of the crust, and 'anomalous'
diffusion <x>~t**H, with an exponent H<<0.5. Some 3% of these
potentially damaging earthquakes (magnitude>5.5) are triggered,
showing that the time-dependent component (for large events) is
significant compared to the background, but small in an absolute
sense. Prospects for tuning seismic hazard with a conditional
probability to reflect this amplification would be straightforward to
implement. Such methods apply to time-dependent hazard based
on a population. The prospects for predicting individual events
(place, magnitude and time, above chance) remain beyond reach
with current understanding.

Adrian Matthews (University of East Anglia)
**Predicting Volcanic Activity with Rainfall**

Dome-forming volcanic eruptions cyclically extrude bodies of lava over
several months, which then become gravitationally unstable and
collapse, generating pyroclastic flows. On 29 July 2001 extreme
rainfall over Montserrat coincided with a major collapse of the
Soufriere Hills lava dome. We present rainfall and seismic records
that demonstrate, for the first time, a relationship between intense
rainfall and lava dome collapse, with associated pyroclastic flow
generation. After seven months of little rain and a period of
sustained dome growth, the onset of intense rain was followed within
hours by dome collapse and pyroclastic flows. The large-scale weather
system responsible for the rain was identifiable in satellite images
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Louise Burt (RUWPA, University of St Andrews)
**Mapping volcanic flow deposits from stratigraphic records**

The stratigraphic record of deposits from volcanic eruptions is incomplete, due to,
among other things, erosion. Thus, maps based on this record alone, will underestimate
the likelihood that an area may be affected during future eruptions.
A statistical algorithm will be presented which can be used to compensate for the
incompleteness of the stratigraphic record. Cartographic functions can then be
applied to produce various types of hazard map.
The method is illustrated using the eruption history of Montagne Pelée.

Willy Aspinall (Aspinall and Associates)
**Statistics and subjective probabilities: inputs to real-time management of the Montserrat volcanic eruption crisis**

Howard Grubb: envstat-request@jiscmail.ac.uk

envstat list page: http://www.jiscmail.ac.uk/files/envstat

Updated: January 27, 2003