Abstract
Typically surface displacements, as a consequence of magmatic movements, are calculated by implementing either a data inversion model or an analytical model comprising of loosely constrained, generalised rock properties and simplified source geometries. In fact, these analytical models are commonly characterised by a pressurised point source embedded within a homogeneous, isotopic, flat, elastic half space (i.e. the Mogi-McTigue Models). The Mogi model, in particular, provides a quick and relatively accurate estimation of the symmetric, radial displacement patterns from a predefined pressure source. However, limitations arise from the assumptions behind the parameterisation of the model (Masterlark, 2007), namely defining the elastic moduli of the matrix and failing to account for the influence that the topography exerts on the volcanic system. This work seeks to address these limitations by employing GALES (GAlerkin LEast Squares), a Multiphysics finite element software (FEM) that was developed by INGV, Sezione di Pisa. GALES consists of various geophysical solvers, including, but not limited to: computational fluid dynamics, computational solid dynamics and fluid solid interaction (Garg & Papale, 2022). The GALES software is tailored towards high performance computing (HPC), on cluster machines, and has been used regularly since its inception; contributing to several significant studies pertaining to magma transport and rock deformation. Thus, GALES is seen as the ideal software platform to introduce geophysical and spatial heterogeneities to these established analytical models - this time with the topography of the volcano at the forefront of its consideration. As 3D simulations of this extent are computationally expensive, the open-source softwares MESHER (Marsh et. al., 2018) and GMSH were used to generate a dynamic computational mesh, of variable resolution, for the simulations by deriving a triangulated irregular network (TIN) from the Tinitaly Digital Elevation (~10 m resolution - see Tarquini et. al., 2007) and GEBCO (2022) Bathymetry datasets (~500 m resolution). Significantly, it was also possible to avail of the INGV’s extensive monitoring network by including the positions of the signal receivers stationed across a vast computational domain of 100 km x 100 km x -50 km. The integration of these receiver stations not only allows for a direct and comprehensive comparative analysis of the modelled synthetic deformation signals against the catalogues of empirical data, but also significantly, the extent of its coverage is beneficial as we can obtain deformation patterns from a variety of different source locations, both in the near-field and far-field ranges. Therefore, whilst recording volcanic deformation signals and distinguishing its sources at significant depths within the Earth’s crust can prove to be complex, challenging and even elusive, the combination of these numerical models, high-resolution datasets along with continuous monitoring, simulations such as these have the potential to provide new insights into the existence, behaviour and evolution of deep magmatic bodies (Dzurisin, 2003), as well as, constraining the geophysical characteristics of the medium by which they are emplaced. 
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