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Multiobjective genetic algorithm inversion of ground deformation and gravity changes spanning the 1981 eruption of Etna volcano
Language
English
Obiettivo Specifico
2.6. TTC - Laboratorio di gravimetria, magnetismo ed elettromagnetismo in aree attive
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Title of the book
Issue/vol(year)
/113 (2008)
Publisher
Americal Geophysical Union
Pages (printed)
B07406
Issued date
2008
Keywords
Abstract
During the last few decades, joint investigations of microgravity and surface
deformation measurements have played an increasingly important role in studying the
internal dynamics of active volcanoes. Deformation and microgravity observations have
been accomplished at Mt Etna since the eighties. Past data sets collected during
important paroxysmal events can be utilized as case-studies to both (1) test the
possibilities of nowadays more powerful inversion tools and improved analytical
formulations to model the source-mechanisms of volcano-related deformation and gravity
changes and (2) in turn obtain new insights into the functioning of the plumbing system of
the volcano. Here we analyze a data set spanning the March 1981 eruption of Mt.
Etna. Large horizontal displacements were evidenced on the NE and SW flanks of the
volcano through electrooptical distance measurements (EDM) during two 20-month
periods, both encompassing the March 1981 eruption. Elevation changes, evidenced
through leveling measurements, during a 12-month period spanning the eruption, were in
general smaller than horizontal displacements with important amplitudes only close to
the eruptive fissure. Gravity measurements, carried out together with leveling
measurements, evidenced positive changes, spatially well correlated with elevation
changes, but having a larger wavelength. The joint inversion of the multimethod
geophysical data is regarded as a multiobjective optimization problem and solved through
a Genetic Algorithm technique of the nondominated type. We conclude that a composite
intrusive mechanism with two tensile cracks, each associated to a zone where
preexisting microfractures were filled with new magma, leaded to the 1981 eruption. The
results of the present study highlight the advantages of multiobjective evolutionary
algorithms, as a powerful tool to jointly invert multimethod geophysical data, and pose
important issues on the subject of volcano-monitoring.
deformation measurements have played an increasingly important role in studying the
internal dynamics of active volcanoes. Deformation and microgravity observations have
been accomplished at Mt Etna since the eighties. Past data sets collected during
important paroxysmal events can be utilized as case-studies to both (1) test the
possibilities of nowadays more powerful inversion tools and improved analytical
formulations to model the source-mechanisms of volcano-related deformation and gravity
changes and (2) in turn obtain new insights into the functioning of the plumbing system of
the volcano. Here we analyze a data set spanning the March 1981 eruption of Mt.
Etna. Large horizontal displacements were evidenced on the NE and SW flanks of the
volcano through electrooptical distance measurements (EDM) during two 20-month
periods, both encompassing the March 1981 eruption. Elevation changes, evidenced
through leveling measurements, during a 12-month period spanning the eruption, were in
general smaller than horizontal displacements with important amplitudes only close to
the eruptive fissure. Gravity measurements, carried out together with leveling
measurements, evidenced positive changes, spatially well correlated with elevation
changes, but having a larger wavelength. The joint inversion of the multimethod
geophysical data is regarded as a multiobjective optimization problem and solved through
a Genetic Algorithm technique of the nondominated type. We conclude that a composite
intrusive mechanism with two tensile cracks, each associated to a zone where
preexisting microfractures were filled with new magma, leaded to the 1981 eruption. The
results of the present study highlight the advantages of multiobjective evolutionary
algorithms, as a powerful tool to jointly invert multimethod geophysical data, and pose
important issues on the subject of volcano-monitoring.
Type
article
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