| dc.description.abstract | Our understanding of the subsurface processes that cause volcanic unrest is currently incomplete, impacting our ability to predict eruptive episodes and protect communities at risk from volcanic hazards. Monitoring and modelling of ground deformation has become one of the main methods for evaluating the potential for volcanic unrest, however basic modelling techniques usually require too many assumptions to be realistic. In this thesis, volcano deformation has been assessed and modelled using Finite Element Analysis (FEA), to increase the accuracy of identifying the origins of observable surface deformation. Simplified modelling of a vertically stacked, double reservoir magmatic system showed that major magmatic reservoirs can dominate surface displacement fields during deformation episodes. Displacement contributions from shallower, smaller storage regions can be obscured from modern geodetic monitoring equipment, hiding their presence within the magmatic system, and impacting eruption forecasts and hazard assessments. Understanding how individual parameters behave in a 2D environment set a benchmark for more realistic 3D modelling. This framework was then applied to assess Aira caldera in Japan, to re-examine a period of deformation around the caldera and Sakurajima volcano utilizing FEA, assuming a multiple pressure source magmatic system. With the inclusion of topography and subsurface heterogeneities, modelling identified a shallow magmatic reservoir that may account for uncertainties in earlier models, which assumed a single magmatic source. Additional models analysed Bouguer gravity data to scrutinize shallow reservoir parameters, which highlighted the potential of combining deformation and gravity modelling approaches to produce higher accuracy magmatic storage estimates for Aira caldera, as well as other volcanic systems worldwide. Uncertainties remain in fully representing crustal characteristics, which will continue to restrict the potential of future geodetic modelling. However, the FEA work presented in this thesis gives a framework for improved interpretation of deformation events. | en_GB |
