Insights into Episodic Caldera Collapse and Magmatic Systems from the 2018 Eruption of Kilauea Volcano

Volcanic caldera collapse occurs when large volumes of magma erupt rapidly, causing the overlying the crust to founder into the subterranean magma chamber. Caldera collapse occurs during both explosive and lava flow forming eruptions; both are fortunately relatively rare. The 2018 eruption of Kīlauea volcano in Hawai‘i destroyed 700 homes and led to $800 million in damage.

The associated caldera collapse was by far the best monitored in history. In 2.5 months, the floor of the centuries-old caldera, within Hawai‘i Volcanoes National Park, dropped up to 500 meters and increased in volume by 0.8 km3. It is crucial to understand the collapse process because the weight of the overlying crust acts to sustain these eruptions.

While the basics of caldera collapse are understood, the unprecedented data collected in 2018 will allow us to address first order questions, including: What are the crustal stress and magma pressure conditions necessary for collapse? What is the sub-surface geometry of the ring fault system bounding the collapse? Why did collapse occur in discrete events, and what physical properties controlled the character of these events?

What is the nature of sub-caldera magma storage systems and how do they connect to the eruptive vents? Modeling of these unique data will lead to a quantitative leap in our understanding of caldera collapse. The project will support a graduate student to understand volcanic hazards in the U.S.

The 2018 collapse of occurred in 62 discrete events in which the caldera dropped from several to nearly 10 meters, accompanied by magnitude 5.2 to 5.4 earthquakes. Collapses were accompanied by remarkable, inflationary deformation offsets followed by decelerating deflations, similar to behavior at other basaltic caldera collapses. There has been considerable debate as to whether caldera ring-faults are inward or outward dipping.

This project will use finite element (FEM) modeling combined with inversion of high-rate GPS data to constrain the ring-fault dip and the compressibility, and hence vesicularity, of the underlying magma. The research will further use pre- co-, and in particular post-collapse GPS and InSAR data to constrain the geometry, size and connectivity of the enigmatic summit magma system.

The dynamics of collapse are analyzed with a model in which the weight of the caldera block is balanced by magma pressure at its base and rate-and-state dependent friction on its sides. Flow of magma is driven by the pressure difference between the magma chamber and the eruption site. Model predictions of repeated collapse events are compared to the time between events, their duration, displacement, and magma chamber pressure increase.

The model elucidates the conditions for caldera collapse, and how collapse sustains eruptions that would otherwise cease. The measured surges in eruptive flux will be used to further constrain pressures within the magma system. Our analysis of co-collapse deformation leads naturally to a model for the VLP earthquakes.

Synthetic waveforms will be computed that can be compared to low-pass filtered seismic observations. A striking correlation of cumulative VT seismicity with inter-collapse subsidence strongly suggests fault creep on the ring-fault prior to collapse, providing insights into fault development and chamber pressure history.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.