In 2018, Kīlauea Volcano experienced its largest lower East Rift Zone (LERZ) eruption and caldera collapse in at least 200 years. After collapse of the Pu‘u ‘Ō‘ō vent on 30 April, magma propagated downrift. Eruptive fissures opened in the LERZ on 3 May, eventually extending ~6.8 kilometers. A 4 May earthquake [moment magnitude (Mw) 6.9] produced ~5 meters of fault slip. Lava erupted at rates exceeding 100 cubic meters per second, eventually covering 35.5 square kilometers. The summit magma system partially drained, producing minor explosions and near-daily collapses releasing energy equivalent toMw4.7 to 5.4 earthquakes. Activity declined rapidly on 4 August. Summit collapse and lava flow volume estimates are roughly equivalent—about 0.8 cubic kilometers. Careful historical observation and monitoring of Kīlauea enabled successful forecasting of hazardous events.
Slow-slip events, or 'silent earthquakes', have recently been discovered in a number of subduction zones including the Nankai trough in Japan, Cascadia, and Guerrero in Mexico, but the depths of these events have been difficult to determine from surface deformation measurements. Although it is assumed that these silent earthquakes are located along the plate megathrust, this has not been proved. Slow slip in some subduction zones is associated with non-volcanic tremor, but tremor is difficult to locate and may be distributed over a broad depth range. Except for some events on the San Andreas fault, slow-slip events have not yet been associated with high-frequency earthquakes, which are easily located. Here we report on swarms of high-frequency earthquakes that accompany otherwise silent slips on Kīlauea volcano, Hawaii. For the most energetic event, in January 2005, the slow slip began before the increase in seismicity. The temporal evolution of earthquakes is well explained by increased stressing caused by slow slip, implying that the earthquakes are triggered. The earthquakes, located at depths of 7-8 km, constrain the slow slip to be at comparable depths, because they must fall in zones of positive Coulomb stress change. Triggered earthquakes accompanying slow-slip events elsewhere might go undetected if background seismicity rates are low. Detection of such events would help constrain the depth of slow slip, and could lead to a method for quantifying the increased hazard during slow-slip events, because triggered events have the potential to grow into destructive earthquakes.
[1] Changes beneath a volcano can be observed through position changes in a GPS network, but distinguishing the source of site motion is not always straightforward. The records of continuous GPS sites provide a favorable data set for tracking magma migration. Dense campaign observations usually provide a better spatial picture of the overall deformation field, at the expense of an episodic temporal record. Combining these observations provides the best of both worlds. A Kalman filter provides a means for integrating discrete and continuous measurements and for interpreting subtle signals. The unscented Kalman filter (UKF) is a nonlinear method for time-dependent observations. We demonstrate the application of this technique to deformation data by applying it to GPS data collected at Okmok volcano. Seven years of GPS observations at Okmok are analyzed using a Mogi source model and the UKF. The deformation source at Okmok is relatively stable at 2.5 km depth below sea level, located beneath the center of the caldera, which means the surface deformation is caused by changes in the strength of the source. During the 7 years of GPS observations more than 0.5 m of uplift has occurred, a majority of that during the time period January 2003 to July 2004. The total volume recovery at Okmok since the last eruption in 1997 is $60-80%. The UKF allows us to solve simultaneously for the time-dependence of the source strength and for the location without a priori information about the source.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.