Identifying bubble collapse in a hydrothermal system using hiddden Markov models

Phillip B. Dawson; M.C. Benitez; Jacob B. Lowenstern; Bernard A. Chouet

doi:10.1029/2011gl049901

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Identifying bubble collapse in a hydrothermal system using hiddden Markov models

Phillip B. Dawson·M.C. Benitez·Jacob B. Lowenstern·Bernard A. Chouet

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Abstract

Beginning in July 2003 and lasting through September 2003, the Norris Geyser Basin in Yellowstone National Park exhibited an unusual increase in ground temperature and hydrothermal activity. Using hidden Markov model theory, we identify over five million high-frequency (>15 Hz) seismic events observed at a temporary seismic station deployed in the basin in response to the increase in hydrothermal activity. The source of these seismic events is constrained to within ~100 m of the station, and produced ~3500–5500 events per hour with mean durations of ~0.35–0.45 s. The seismic event rate, air temperature, hydrologic temperatures, and surficial water flow of the geyser basin exhibited a marked diurnal pattern that was closely associated with solar thermal radiance. We interpret the source of the seismicity to be due to the collapse of small steam bubbles in the hydrothermal system, with the rate of collapse being controlled by surficial temperatures and daytime evaporation rates.

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Geophysical Research Letters Article

Source-reported bounding extent: 44.69611500685269° to 44.757582949615994° latitude; -110.75180053710938° to -110.65292358398438° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeX RIS

Phillip B. Dawson, M.C. Benitez, Jacob B. Lowenstern, Bernard A. Chouet. 2012-01-06. Identifying bubble collapse in a hydrothermal system using hiddden Markov models. https://doi.org/10.1029/2011gl049901

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