Estimating the melt fraction and volatile content of regions of partial melt beneath volcanoes has important implications for volcanic hazards since higher melt fraction, volatile-rich magmas are more buoyant and have a lower viscosity, and thus are more susceptible to mobilization and possibly eruption. Magnetotelluric (MT) data can be used to model subsurface bulk resistivity structures through inversion algorithms and can provide information on the distribution and amount of melt and volatiles contained in the residing magma by converting bulk resistivity to estimates of melt fraction, temperature, and water content. These are often treated as independent variables but, in reality, they are thermodynamically correlated. Thermodynamic models such as MELTS can be used to constrain the possible combinations of melt fraction, temperature, and water content such that MT interpretations are petrologically consistent. Probabilistic Bayesian inversion that incorporates these constraints can be used to find a distribution of models and interpretations which fit the MT data and provide a better understanding of the uncertainty in MT-derived estimates of melt fraction. In this study, we apply MELTS-coupled 1-D Bayesian inversions of MT data at Uturuncu Volcano to evaluate the constraints that MT data can provide on melt fraction estimates. Uturuncu Volcano is a large composite volcano in southern Bolivia at the center of the Altiplano Puna Volcanic Complex (APVC), the result of a large ignimbrite flare-up during the past 10 Ma. Previous geophysical studies have shown that the APVC is underlain by the voluminous, laterally-extensive Altiplano Puna Magma Body (APMB) at approximately 15-20 km depth below surface. The APMB has previously been interpreted to have a wide range of melt fractions anywhere from 4% to 45%, but MT results suggest anomalously high water contents of up to 10 wt%. Initial results from petrologically-consistent MT inversion modelling suggests that the resulting low resistivity of the APMB beneath Uturuncu requires high melt fractions (e.g. >90%) in near-saturated conditions. This suggests that either high melt fraction near-saturated magma reservoirs exist at depth or that a significant phase of saline fluids in over-saturated low melt fraction conditions is present.

Estimating the effect of geomagnetic disturbances on infrastructure is an important problem since they can induce damaging currents in electric power transmission lines. In this study, an array of magnetotelluric (MT) impedance measurements in Alberta and southeastern British Columbia are used to estimate the geoelectric field resulting from a magnetic storm on September 8, 2017. The resulting geoelectric field is compared to the geoelectric field calculated using the more common method involving a piecewise-continuous 1-D conductivity model. The 1-D model assumes horizontal layers, which result in orthogonal induced electric fields while the empirical MT impedance data account for fully 3-D electromagnetic induction. The geoelectric field derived from empirical MT impedance data demonstrates a preferential polarization in southern Alberta, and the geoelectric field magnitude is largest in northeastern Alberta where resistive Canadian Shield outcrops. The induced voltage in the Alberta transmission network is estimated to be ~120 V larger in northeastern Alberta when using the empirical MT impedances compared to the piecewise-continuous 1-D model. Transmission lines oriented northwest-southeast in southern Alberta have voltages which are 10-20% larger when using the MT impedances due to the polarized geoelectric field. As shown with forward modelling tests, the polarization is due to the Southern Alberta British Columbia conductor in the lower crust (20-30 km depth) that is associated with a Proterozoic tectonic suture zone. This forms an important link between ancient tectonic processes and modern-day geoelectric hazards that cannot be modelled with a 1-D analysis.