Volcanic eruptions and the human hazards associated with them are challenging to predict because they involve highly unsteady motions of magma hidden below Earth’s surface. Although observations critical for inferring subsurface magma motions, such as seismicity and infrasound, are being collected more and more often, we lack a theoretical framework for understanding the physical processes that give rise to such signals. This work will be a study of magma flow within volcanic conduits on short timescales, in order to understand the physical processes that give rise to a variety of eruptive phenomena. The first goal is to study volcanic activity at Kilauea volcano, Hawai’i’, associated with rocks falling onto an active lava lake, which cause resonant oscillations of magma within the conduit and sometimes small but hazardous explosions at the surface. These well-documented natural experiments provide a unique test for models of the shallow conduit and magma reservoir geometry as well as multiphase magma fluid properties. The second goal is to develop a high performance computing-enabled modeling framework to predict transient motions of magma in volcanic conduits under a range of flow conditions, including during explosive eruptions. This work will help bridge the gap between geophysical observations, volcano physics, and advanced computing. The project will support graduate students in interdisciplinary scientific research, and contribute to ongoing development of “The Volcano Listening Projectâ€, an outreach effort dedicated to representing volcano data as sound and animations.
This proposal describes a study of small amplitude oscillatory magma flow in volcanic conduits. The first goal is to study short term (tens of minutes) unrest episodes at Kilauea volcano, Hawai’i’, associated with rock falls onto an active lava lake and from rising gas slugs. These disturbances cause ‘very long period’ (VLP, 5−40 s) oscillations of the multi-phase magma within the conduit, explosions, unsteady surface gas flux, and lava lake height variations, recorded on a nearby network of geophysical instruments. These well-documented natural experiments provide a unique test for unsteady conduit flow models, which will be used to invert for subsurface conduit and reservoir geometry as well as magma rheology and primary volatile content. Previous NSF-funded work developed a preliminary framework for modeling and inverting VLP seismic data in terms of the resonant eigenmodes of coupled conduit-reservoir systems, where fluid pressure changes cause elastic deformations of the surrounding solid Earth that are recorded instrumentally. This framework will be applied to thousands of events spanning the ten-year lifespan of the Halema’uma’u vent on Kilauea. Bayesian Markov-Chain Monte Carlo inversions will incorporate constraints from seismicity, ground deformation, continuous gravity, petrologically-determined melt viscosity and volatile content, and lava lake geometry. The second goal is to generate a forward modeling framework to predict wave motion in complex states of magma flow. Modeling relative motion between gas and liquid will predict surface gas flux data during transient unrest events, as well as transient explosions triggered by rockfalls. Wave-like disturbances will also be studied in the context of explosive eruptions, where such oscillatory fluid motions may play a key role in state shifts during eruptions such as the onset of fragmentation and explosive behavior. Flow in volcanic systems is typically not studied at the short timescales proposed here. Explicit consideration of non-equilibrium bubble growth and resorption, complex conduit geometry that includes branching cracks, and stratified, multiphase fluid flow with strong interfaces (such as bubble exsolution or magma fragmentation) is necessary to achieve consistency between multiple geophysical datasets. This approach also permits a critical examination of quasi-steady conduit flow models, which can be shown to be conditionally linearly unstable to perturbations. This suggests a new approach to studying transitions in eruption style. Finally, the study of unstable wave motions in strongly stratified multiphase systems will contribute to numerical method developments with applications beyond volcanology. Numerically resolving flow instabilities using recent developments in provably stable high-order finite difference methods provides a unique opportunity to advance models of volcanic conduit flow, discover new eruptive phenomenology, and connect with volcano monitoring efforts. The project will involve two PhD students at the University of Oregon across Earth Science and Computer Science. Software will be open-source and available to the community. The project team will visit and collaborate with the USGS (Hawaiian Volcano Observatory) to study Kilauea. Ongoing results of modeling and seismic data analysis will be incorporated into public presentations and to “Volcano Listening Project†outreach effort dedicated to representing volcano data as sound and animations.
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.
