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Bayesian inversion of 1994–1998 vertical displacements at Mt Etna: evidence for magma intrusion
Author(s) -
Obrizzo F.,
Pingue F.,
Troise C.,
De Natale G.
Publication year - 2004
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2004.02160.x
Subject(s) - geology , seismology , volcano , geodesy , magma , isotropy , earthquake swarm , inversion (geology) , tectonics , induced seismicity , physics , quantum mechanics
SUMMARY We have developed a Bayesian method for the inversion of static ground deformations at volcanic areas. The method allows inference of the conditional probability density on the location and mechanism of point sources representing volcanic phenomena (isotropic strain nuclei, tensile faults) embedded in homogeneous, elastic media. The method has been tested with simulated and real data from volcanic areas. We have then analysed vertical displacements recorded at Mt Etna (southern Italy) from 1994 to 1998, by high precision levelling. Measurements in this period had been carried out yearly, so resulting displacements have been analysed both in consecutive periods and in the cumulative one. Measurement periods 1994–1995 and 1997–1998 show significant uplift, of several centimetres. The maximum cumulative displacement amounts to 6.5 cm., with a trend similar to each of the two periods 1994–1995 and 1997–1998. The shape of displacement is well approximated by a circular symmetry, thus allowing one to hypothesize an isotropic overpressure model as the source, simulating magma intrusion at shallow depth. The application of the inverse method gives the most probable location at about 4.5 km of depth (b.s.l.) at about 1.5 km north of the central craters. The 95 per cent of probability density is concentrated within a radius of about 0.5 km on the horizontal, 1 km on depth. The obtained results give important insight on the interpretation of recent eruptive episodes.

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