Stress Inversion and Forecast of Future Vent Locations in Calderas: Combining a Monte Carlo Algorithm with a Physics-based Model of Dike Propagation.

Abstract

Forecast of vent opening locations in volcanic regions is typically performed on the basis of the spatial density of past eruptive vents, without accounting for the physics of magma propagation. As sophisticated as the statistical analysis can be, such methods are difficult to apply to settings with scarce and spatially sparse data. An alternative approach has been recently proposed that combines a two-dimensional mechanical model of stress-driven dike pathways in the subsurface with a Monte Carlo stress optimization method. Here, we extend that strategy to three dimensions. We present a model of crustal stress in calderas accounting for tectonic processes and gravitational loading/unloading associated to topography. Then, we introduce a model of dike propagation that is able to capture the complexity of three-dimensional magma trajectories with low run times and may also backtrack dikes from a vent to the magma storage region. We test these models on synthetic scenarios inspired by real calderas, producing sets of dikes and vents for a given stress field and magma reservoir. Then, we use such scenarios to test a stress inversion strategy such that dike trajectories backtracked from the known vents are consistent with the assumed location of a magma reservoir. We eventually exploit the results from the stress inversions to produce probability maps of future vent locations.