Joint Inversions of Ground Deformation, Extrusion Flux, and Gas Emissions Using Physics‐Based Models for the Mount St. Helens 2004–2008 Eruption

Abstract

In the past few decades, the expansion of both ground and satellite-based monitoring systems, as well as advances in laboratory techniques to study volcanic products, have increased the quantity and quality of volcanological data. Since these observations are produced by common physical processes, physics-based models can provide a natural and meaningful way to bring together these diverse data, at the same time improving our understanding of volcanic processes.

Contrasting Volcanic Deformation in Arc and Ocean Island Settings Due To Exsolution of Magmatic Water

“…Reconciling observations of volcanic deformation and degassing can help identify the conditions that lead to the lack of observations of ground deformation (Kilbride et al., 2016; Reath et al., 2020). The magmatic processes that drive volcanic deformation and degassing are fundamentally linked: Exsolution of volatiles from silicate melt in crustal magma reservoirs (during isobaric cooling and crystallisation, also termed as “second boiling”, or due to decompression) causes magma to become compressible, thereby allowing it to change its volume in response to pressure perturbations experienced by the magma during eruption and recharge (Kilbride et al., 2016; Wong et al., 2017; Wong & Segall, 2020; Woods & Huppert, 2003). While it is becoming increasingly common to compile multisensor data (e.g., Furtney et al., 2018; Reath et al., 2019, 2020), until recently there has not been a quantitative framework to jointly interpret observations of volcanic deformation and degassing, including CO 2 and SO 2 gas fluxes (Girona et al., 2014; Kilbride et al., 2016; Wong & Segall, 2020).…”

Geodetic Constraints on a 25‐year Magmatic Inflation Episode Near Three Sisters, Central Oregon

“…From a hazards perspective, distinguishing unrest that will lead to eruption from that which will not is critically important. To the extent the difference is ascertainable (the real Earth is complex and small factors might have outsized effects), the way forward is likely to include the following elements: (a) comprehensive, multidisciplinary monitoring, including space‐based observations (Poland, 2015) at as many volcanoes in differing tectonic settings as possible, (b) physics‐based modeling of magmatic systems (e.g., Wong & Segall, 2020); (c) geographically focused experiments at type volcanoes (e.g., Ulberg et al., 2020), and (d) a deep dive into historical records of unrest and its outcomes at volcanoes around the world (Ogburn & VDAP, 2015).…”

Modeling Volcano-Magmatic Systems: Workshop Report for the Modeling Collaboratory for Subduction Research Coordination Network

“…Because magma systems are complex, nonlinear, and observed only indirectly, the future success of magma system modeling hinges on the integration of diverse data types such as geodetic observations with eruption rate and gas emissions data (e.g., Anderson and Segall, 2013;Wong and Segall, 2020). There remains great promise in the combination of new types of observations.…”

“…Subsequently, a vibrant eruption modeling community has produced advances on multiple fronts. Examples, which are by no means comprehensive, include: the conduit model of Dobran and Papale (Dobran and Papale, 1992;Papale and Dobran, 1993), which marked the beginnings of a succession of subsequent generations of conduit models; exploration of the role of conduit wall erosion and collapse (Macedonio et al, 1994;Aravena et al, 2017Aravena et al, , 2018; the loss of magmatic volatiles through conduit walls (Woods and Koyaguchi, 1994;Jaupart, 1998); the incorporation of bubble nucleation (Massol and Koyaguchi, 2005); the inclusion of disequilibrium bubble growth during eruptive magma ascent (Proussevitch and Sahagian, 2005); the coupling of magma chamber and conduit (Bower and Woods, 1998;Huppert and Woods, 2002;Macedonio et al, 2005, Anderson andSegall, 2011), including crystallization and the formation of plugs and domes (Schneider et al, 2012;Kozono andKoyaguchi, 2012, Wong et al, 2017); coupling of dykes and cylindrical geometries together with elastic wall-rock deformation (Costa et al, 2007a); time-dependent eruption models constrained using observations in a Bayesian framework (Anderson and Segall, 2013;Wong and Segall 2020); forays into transient two-phase (gas-melt) flow in one-dimension (Melnik et al, 2005;La Spina et al, 2017); magma flow in dikes (Woods et al, 2006); and dike propagation (Weertman 1971;Rubin, 1995;Mériaux and Jaupart, 1998;Dahm, 2000;Segall et al, 2001). Especially notable in this context are the publicly available user-friendly CONFLOW model of Mastin and Ghiorso (2000) and the conduit model intercomparison workshop discussed in Sahagian (2005).…”

“…In this respect, although there has been undeniable progress in developing models aimed at both simulating the physics of the specific processes and the expected geophysical and geochemical observables, only a small subset of models have achieved robust estimation of eruption source parameters through inversion of observations from eruptions (e.g. Anderson and Segall, 2013;Heimisson et al, 2015;Massaro et al, 2018, Wong andSegall, 2020). Such parameter estimations rely on building blocks to simulate seismicity, deformation, gravity changes, dispersion of eruptive material, and so forth.…”