Research Activities
1. Laboratory determination of single-phase and multiphase magma-rock properties
Work package 1 will conduct a range of laboratory investigations on natural volcanic rocks or melts and relate these to theoretical and computational approaches, as well as results from analogue experiments. The following main tasks are necessary to implement WP1: (1) identify sets of properties most crucial to the behaviour of magma and rock within different scenarios of volcanic systems, (2) design laboratory test series and modify existing set-ups to accomplish the tests (3) conduct laboratory experiments and parameterize the identified properties for a range of conditions, (4) investigate the dependency of these properties on the physical and chemical conditions of natural systems, (5) develop empirical and theoretical models for the analysed properties and their dependencies amongst each other and on the conditions in natural systems, and finally (6) provide the resultant insights as well as validation data to WPs 2-6.
2. Analogue modeling
Work package 2 will undertake a range of laboratory investigations and relate these to theoretical and computational approaches. The work will be developed through the following steps: (1) design of analogous experimental approaches through the use of scaling arguments to identify fluid properties and apparatus dimensions, (2) identify the most suitable measurable parameters that relate to both numerical simulation and field measurement of volcanic processes, (3) use of high-temperature high-pressure (HT-HP) methods to explore the behaviour of volcanic materials at an analogue scale, (4) use of both analogue fluids and analogue scale to explore volcanic processes occurring over larger spatial ranges, (5) in parallel with WP1, provision of resultant insights and validation data to modelling WP3 and hence onward to WP7.
3. Numerical simulation of magma and eruption dynamics
Numerical modelling is key to understanding volcanic eruptions because magmatic systems are complex and involve scales and conditions that are often not realizable in the laboratory. A cross-comparison benchmark test will be conducted for the existing codes that are used by the Partners. To unify results and aid comparisons, the Partners will use common test cases and common constitutive equations from laboratory results. These constitutive equations will also be used for models in WP4 and WP5, and will be updated by results of WP1 and WP2 in month 28. Codes will be validated through comparison with analogue laboratory experiments and with analytical solutions of simplified scenarios. The codes will then be employed for more complex scenarios that can only be studied numerically, from eruption dynamics, magma-aquifer interactions, and ash and aerosol transport. Results will be compared to existing datasets for particular volcanoes where appropriate and will contribute to hazard assessment (WP7).
4. Fluid-Rock interaction dynamics and rock transfer functions
A range of numerical tools will be developed in this WP with a focus on the geophysical signals generated by rock-rock & fluid-rock static and dynamic signal generation. Synthetic data from these tools will be used to test inversion procedures/codes by comparing solutions to known input sources. Volcano sources can often by ’hidden’ by strong path effects hence tools developed in this WP will be capable of handling the response of mechanically heterogeneous edifices to input sources. The simulation tools will be tested by comparison with physical laboratory experiments, be used to upscale the physical experiments to field scale, and will be applied to real data – including tremor and LP data from high density networks.
5. Source models and inversion procedures
Numerical forward models for different sources using codes available within the consortium will produce synthetic seismological, gravity, deformation, and thermal data sets. In conjunction with WP6, analyses will be conducted to test the sensitivity of these models to structural features such as density, seismic velocity, thermal and electromagnetic conductivities. Further analyses will then be aimed at understanding the effects of simplified source models on the inversion results. For seismic modelling, several sources mechanism (like point pressure sources, double-couple, full moment or finite sources having different shapes, e.g., cylinder, dykes) will be tested; for deformation and gravity, analytic modelling of sources will be used and possibly compared with results from more advanced forward models accounting for multiple sources of arbitrary shapes; gravity modelling will be used to constraint gravity sources and density structure; thermal modelling will help constrain conductivities for different geological structures and fluids. In a second step, different inversion techniques based on both stochastic and systematic exploration of the model space will be defined and applied to synthetic data sets to understand their ability to correctly discriminate the input source mechanism and/or structures defined in the first step. Inversion codes will be validated through comparison with analytical solutions and with respect to the particular geological context. This validation stage will help understand similarities and differences between individual inversion codes, and assess the importance of boundary conditions in the production of forward models. Where appropriate, Results will be used for the analysis of existing, observational datasets at particular volcanoes and will eventually contribute to hazard assessment.
6. Mixed deterministic/stochastic approach for the simulation of volcanic processes
The first step consists in the physical-mathematical description of the volcanic process of interest, mainly based on coupled systems of partial differential equations (PDEs). This specific project deals with segments of the volcanic process which involve randomness, which may be either the intrinsic randomness of certain phenomena or our lack of knowledge of details or value of certain quantities. Thus, particular attention will be paid to the modelling of these sources of randomness, including PDEs with random parameters and time-dependent stochasticity leading to stochastic partial differential equations (SPDEs) driven by white noise. The second step consists in the mathematical investigation of the properties of the (S)PDE obtained above. Foundational questions of existence, uniqueness and regularity of solutions will be addressed. Special properties like the emergence of singularities, discontinuities or blow-up of some quantity, may reflect physical mechanisms of main interest, and their knowledge is essential. The third step consists in the numerical solution. Particular attention will be paid to the specific computational problems caused by randomness. In general, if the underlying PDE is complex, Monte Carlo simulations are expensive; this requires the development of techniques like the so called stochastic quantization to keep under control the computational costs. The last step consists in the analysis of the numerical outputs, in terms of geophysical consequences and inputs for new theoretical investigation.
7. Volcanic hazard assessment
The work will be developed in the following steps: 1) Development of theoretical basis for probabilistic volcanic hazard assessment on different time scales and implementation of software codes. Bayesian procedures will be explored in order to properly describe epistemic and aleatory uncertainties. 2) Comparison of different techniques to account for expert opinion in volcanic hazard assessment. In particular, different expert elicitation techniques will be compared, and merging of expert elicitations with more classical probabilistic evaluations based on observed data will be investigated. 3) Empirical analysis and theoretical studies of monitoring parameters that characterize magmatic or hydrothermal episodes of unrest, the precursory phase of an impending eruption, and possibly the size of the event. This work involves quite different techniques, ranging from multivariate statistical analysis (like pattern recognition) of the available data to a physical description of the monitoring parameters that should be observed according to a modelling of the processes that stand behind the reactivation of magmatic system. 4) Development of hybrid deterministic-probabilistic models for volcanic hazard assessment. The aim is to merge the deterministic description of some specific hazards, like those due to ash fall and pyroclastic flows, with stochasticity introduced by the unknown source (e.g., the intensity, volume and the specific nature of the volcanic eruption) as well as other aleatory and epistemic uncertainties.
