Dataset for Infrasound Early Warning Detections for Lahars
Boise State ScholarWorks
2022
- 260Usage
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage260
- Abstract Views134
- Downloads126
Dataset Description
Infrasound may be used to detect the approach of hazardous volcanic mudflows, known as lahars, tens of minutes before they arrive at a downstream monitoring station. We have analyzed signals from more than 20 secondary lahars caused by precipitation events at Fuego Volcano during Guatemala’s rainy season in May through October of 2022. We are able to quantify the capabilities of infrasound monitoring through comparison with seismic data, time lapse video footage, and high-resolution video of an event occurring on 17 August 2022. We determine that infrasound sensors, deployed adjacent to the lahar path and in small-aperture (10s of meters) array configurations, are particularly sensitive to remote detection of lahars, including relatively small-sized events, at distances greater than 5 km. At Fuego Volcano early detection can provide timely forecasts of up to 30 minutes before lahars arrive at a monitoring site. Lahars are one of the primary hazards at volcanoes and can occur both during eruption and spontaneously without an eruption. We propose that continuous infrasound monitoring can serve as a valuable tool to minimize impacts to property and people living near volcanoes.
Bibliographic Details
https://scholarworks.boisestate.edu/infrasound_data/10/; http://dx.doi.org/10.18122/infrasound_data.10.boisestate; https://scholarworks.boisestate.edu/infrasound_data/10; https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=1009&context=infrasound_data; https://dx.doi.org/10.18122/infrasound_data.10.boisestate
Boise State University, Albertsons Library
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