Magma supply from the lower crust is often proposed as a trigger mechanism for volcanic eruptions. The timescales over which magma can be transported from the deepest parts of volcanic systems are, however, poorly constrained. This uncertainty poses problems for the construction of physical models and for assessment of volcanic hazards. Here, we combined geothermobarometry with Bayesian inversion diffusion chronometry on primitive olivine crystals from the Borgarhraun eruption, northern Iceland. We find that magma took about 10 days to ascend from near-Moho storage at 24 km depth before its eruption, and therefore present timescales for transcrustal magma transport on the global spreading ridge system. Our results reveal a rapid connection between the lower and upper crust with melt transport rates of 0.02 to 0.1 m s−1, which are consistent with the propagation rates observed in seismic swarms in the Icelandic lower crust. Monitoring of such events using surface CO2 fluxes may provide one of the earliest indicators that an eruption is imminent. At the high transport rates and low CO2 contents estimated for the Borgarhraun eruption, any effect of rising magma on surface CO2 fluxes is limited to a period of less than two days before eruption.
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The data that support the findings of this study, including Supplementary Datasets 1–3 and Excel spreadsheet versions of Supplementary Tables 1–5, are available from the BGS National Geoscience Data Centre at: https://doi.org/10.5285/0ad0959d-aa0e-4b79-9077-20216a02922a.
We are unable to make the computer code associated with this paper available at this time because it will be the focus of a future methods paper. The diffusion model code and Bayesian inversion in its current format are available on request from the corresponding author.
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This research was funded by a NERC studentship awarded to E.J.F.M (NE/L002507/1). We are grateful to I. Buisman and G. Lampronti for assistance with the EPMA and EBSD analyses, respectively. We would also like to thank C. Richardson for helpful advice on FEniCS.
The authors declare no competing interests.
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Supplementary Figs. 1–46 and Supplementary Tables 1–5.
Olivine EPMA data and model initial conditions.
Olivine diffusion experimental dataset used in this study.
Supplementary inversion results dataset.
Olivine diffusion equation regression parameters.
Covariance matrices for olivine diffusion equations.
Covariance matrices for aSiO2-dependent olivine diffusion equations.
Angles between the EPMA profile and the main crystallographic axes.
Median timescales and 1σ errors.
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