UC Santa Barbara

The majority of potentially active volcanoes worldwide are not well monitored. Eruptions and surficial mass wasting activity can go entirely undetected. Low-frequency acoustic waves known as infrasound can provide valuable information for remotely detecting, locating, and modeling these hazardous volcanic processes. Infrasound is produced by sources coupled to the atmosphere, with signals often able to propagate further than seismicity in the solid earth, and without need for line of sight (e.g., cloud cover).The overall aim and contribution of this dissertation is toward improving volcanic event detection and localization workflows at local (< 15 km), regional (15–250 km), and remote (> 250 km) distances from the source, using a variety of sensor network configurations. These topics include effective use of dense regional infrasound networks, the impact of pre- and post-recording data noise-reduction, and the role of local infrasound monitoring in surficial mass wasting observations. Together, three principal projects demonstrate some of the benefits and limitations of various signal processing and detection techniques, site selections, and station hardware designs. Dense infrasound sensor deployments on a regional scale, such as the EarthScope Transportable Array (TA) in Alaska, can fill the observational gap between local and global scale volcano monitoring. The rolling TA uses ~80 km spaced single-sensor stations. In comparison, several small infrasound arrays (< 1 km), each with multiple sensors, already populate the area. Volcanic explosion detection and location using a backprojection (delay and stack) scheme achieves relatively limited success solely using TA-type sensors. Backprojection with the small arrays offers greater performance in terms of the number of events detected, and location accuracy. This is due to their shorter source-station distances, lower interstation spacing, higher azimuthal coverage, and more efficient wind-noise reduction hardware. Traditional array processing with the small arrays typically offers higher event detection rates than backprojection. Improvements can be made to the aforementioned detection and location schemes by using signal processing techniques to first isolate volcanic events from background noise sources. Such sources include incoherent wind noise, and pervasive ambient infrasound, primarily microbaroms (ocean wave-wave interaction source). Microbarom reduction typically improves array processing and enhances detection of weak events. Wind-noise reduction does not affect such detection rates, indicating sufficient turbulence can make coherent signal information unrecoverable. This approach does, however, improve the signal-to-noise ratios of isolated or stacked waveforms. At local infrasound monitoring scales relevant to relatively low-amplitude mass wasting signal detection, an additional ambient infrasound noise source with critical influence on detection capability arises from waterfalls, and other fluvial turbulence (river noise). At structurally unstable locations such as Mount Adams, Washington, large mass wasting events (e.g., lahars) are expected to propagate down the same fluvial channels responsible for this clutter. In addition to wind and microbaroms, this temporally and spatially varying fluvial infrasound can significantly affect detection thresholds. Wind noise precluded detection of several witnessed small debris flows below the summit. Conversely, such flows were not visually observed for a range of signals that are characteristic of mass wasting. A well-constrained glacial avalanche provides an exception, permitting assessment of detection and location schemes, and other techniques.