Multivariate approaches to infer volcanic system parameters, timing, and size of explosive eruptions

• Main Author: Manta, Fabio
• Other Authors: Benoit Taisne
• Format: Theses and Dissertations
• Language: English
• Published: 2019
• Subjects: Science::Geology::Volcanoes and earthquakes
• Online Access: https://hdl.handle.net/10356/107577; http://hdl.handle.net/10220/50337
• Institution: Nanyang Technological University

Volcanoes can exhibit a wide range of activities: from effusive eruptions, low-energy bursts, and mild explosive Strombolian eruptions that can cause minor localized effects on human populations, to more severe Plinian eruptions, which are characterized by large emission of ash in the atmosphere with consequent regional to global impacts on human life. To monitor the associated risk, volcanologists apply several ground-based and satellite techniques to analyse geophysical signals associated with the mechanisms happening deep inside the earth that can lead to an eruption. These techniques allow, with the appropriate instruments in place, to estimate the time and intensity of coming events and, in case a large eruption is ongoing, can provide information on ash ejection rates and column heights. Despite technological advancements, many active volcanoes still lack an adequate permanent monitoring network; moreover, harsh climatic conditions can complicate the application of the existing remote sensing techniques. Therefore, there is the need for complementing volcano monitoring with new supportive tools to enhance the current systems. Accordingly, in this thesis we propose two different methods based on volcano tilt observations and ionospheric sounding, respectively for close field and remote sensing applications, to detect and characterize eruptions prior, and during the event. We propose a method to exploit the time series of tilt signals recorded by a single station during Strombolian explosions to forecast the time and magnitude of a coming event. This is achieved by estimating, by mean of the Bayesian statistics and a physics‐based model, the range of controlling parameters. To validate the proposed model and test its uncertainties we performed analogue experiments in a controlled environment. To date, analogue experiments in controlled environments have been focused on the uncertainties related to the dynamics of slugs inside rigid conduits, but little is known about how the slug dynamics changes in the elastic conduit, and how the slug ascent affects surface deformation. We finally focused on the development of a new tool that can support remote sensing techniques to detect and assess the intensity of eruptions. We tested whether the analysis of ionospheric Total Electron Content (TEC) can provide additional information to complement the existing monitoring system. To this end, we mined GNSS data recorded during 22 volcanic eruptions to measure the ionospheric TEC perturbation associated with the acoustic-gravity waves generated by volcanic explosions. We evaluated the relationship between a metric related to the energy of atmospheric disturbances, called TEC Intensity Index (TECII), and several well-known metrics obtained by seismology, and satellite remote sensing. The results presented in this thesis support the use of techniques based on the analysis of tilt observations and ionospheric sounding as complementary methods for volcano monitoring. The synergy of these new techniques and the classic ones will augment the possibility of preventing losses of life and mitigating damages by providing useful information for volcano observatories and alert systems.