Research Training ProgramSmithsonian
Institution
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 Sara C. James The College of William and Mary Williamsburg, Virginia William G. Melson, Ph.D. "I feel very lucky to have had the opportunity to participate in the program. This has been an outstanding learning experience." |
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Analysis of eruption trends: Arenal Volcano, Costa Rica
ABSTRACT
Believed to be extinct, Arenal Volcano violently awoke in 1968. Since then it has remained active, producing explosions, lava fountains and flows, gas emissions, and pyroclastic flows. This activity has made Arenal a popular tourist destination, making prediction of activity at Arenal especially important. In 1992 an Automatic Data Acquisition System (ADAS), which records sound and seismic signals, was installed to monitor activity. Patterns of activity are revealed by data collected by the ADAS. Data from 1994 -1997 were compared to theoretical earth tide and self organized criticality models. Distortions in the earth's crust caused by tidal forces have been thought to affect eruption frequencies and magnitudes. Data from Arenal shows no correlation between activity levels and earth tides. The theory of self-organized criticality describes the behavior of complex systems that by definition defy prediction of specific future events. However, self-organized critical systems have diagnostic statistics. The magnitude of the events and the number of events of each magnitude follow a power law relationship. The eruption activity at Arenal, for the period 1994 - 97, does show a power law relationship for all but the largest events. One possibility is that the data set does not include a significant number of large events. A further complexity is the number and distance of vents and craters may produce a distortion in the recorded magnitude of events. Despite these problems, it appears that Arenal Volcano is a self-organized critical system. This finding indicates that eruptions can be predicted only by short lived precursors, such as inflation or increased seismicity, but that long term prediction may be impossible.
This research was supported by a grant from the National Science Foundation's Research Experience for Undergraduates Program - award number EAR - 9732416.