Linking thermomechanical models with geodetic observations to assess magma reservoir evolution and stability

Abstract:

A classic paradigm in volcanology is that eruption occurs when the pressure within a magma reservoir exceeds the strength of the host rock surrounding it. Referred to as “overpressure”, magma chamber pressurization is thought to be generated by rapid volume changes resulting from the injection of new material or the exsolution of volatile phases. While overpressure is often considered the primary catalyst for eruption, the stress evolution of the host rock plays an important role in determining whether magma remains in stable storage conditions or erupts. For example, the evolution of the host rock stress state is particularly critical in large magma systems with long thermal histories where the rheology of the crust may buffer overpressurization. Advancements in thermomechanical finite element models (FEM) provide new opportunities to estimate stress evolution and investigate magma reservoir stability. Simultaneously, data collection efforts provide critical observations necessary to constrain model predictions. The challenge is building a model-data fusion framework to take full advantage of observational data and modeling approaches to estimate the state of a volcanic system through time. Here we present new advances in volcano data assimilation that link geodetic observations with thermomechanical models to assess magma chamber evolution and stability. The Ensemble Kalman Filter (EnKF), a Monte Carlo based Kalman filtering approach, is used to assimilate geodetic data into temperature-dependent viscoelastic FEMs and provide time-varying estimates of overpressure and stress. Magma reservoir stability is investigated through time by calculating failure in the brittle and ductile portions of the model space, using a Mohr-Coulomb and von Mises failure criterion respectively, and tensile stress and failure along the inferred magma reservoir boundary. Finally, application to active systems (e.g., Okmok, Kerinci, and Laguna del Maule) demonstrates the potential for utilizing the EnKF to investigate eruption potential and triggering mechanisms at restless volcanoes worldwide.