Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/179843
Title: Forecasting the onset of volcanic eruptions using the increase in seismicity during magma ascent
Authors: Aji, Andika Bayu
Taisne, Benoît
Chardot, Lauriane
Keywords: Earth and Environmental Sciences
Issue Date: 2024
Source: Aji, A. B., Taisne, B. & Chardot, L. (2024). Forecasting the onset of volcanic eruptions using the increase in seismicity during magma ascent. Journal of Volcanology and Geothermal Research, 449, 108053-. https://dx.doi.org/10.1016/j.jvolgeores.2024.108053
Project: NRF-NRFI08-2022-0015 
Journal: Journal of Volcanology and Geothermal Research 
Abstract: The Failure Forecast Method (FFM) has been used to forecast the onset of volcanic eruptions with varying degrees of success. The method involves fitting its empirical equation to precursory observables, e.g., seismic data. Current models explaining the empirical equation assume that the seismic observables used (e.g., seismic event-rate, seismic moment-rate or seismic energy-rate) are related to accelerated fracture growth. In these models, such fracture growth results in an apparent increase in seismic activity. In this study, however, we propose an alternative explanation for the increase in seismicity culminating in volcanic eruptions. We suggest that the increase in seismicity, particularly in the seismic amplitudes, can result from ascending seismic sources towards the surface and that the increase can be used for eruption forecasts using the FFM. Our argument is based on the need for magma to migrate towards the surface to produce an eruption. To test our argument, we used synthetic and field/real data and fitted them with the FFM model. The synthetic data is generated using the body wave attenuation equation, and the real data is from the Piton de la Fournaise eruption on January 2nd, 2010. We used seismic amplitudes and seismic amplitude ratios as the precursory observables and used a combination of Simulated Annealing and Bayesian Inversion algorithms to obtain the best-fit parameters of the FFM model and their posterior distributions. For the synthetic cases, we found that the method gave reasonable estimates of failure or eruption time, suggesting that the seismic amplitudes and the seismic amplitude ratios can be used for forecasting using the FFM. For the field/real cases, the results gave information about the timing of magma chamber failure, magma propagation, and the eruption onset. Our results highlight an example of modelling volcano monitoring data with the FFM that gives reasonable estimates of eruption time even if the data may not fully represent failure processes. We suggest that the result may still be reasonable owing to the empirical and asymptotic nature of the FFM combined with the underlying physics of magma and seismic migrations.
URI: https://hdl.handle.net/10356/179843
ISSN: 0377-0273
DOI: 10.1016/j.jvolgeores.2024.108053
Schools: Asian School of the Environment 
Research Centres: Earth Observatory of Singapore 
Rights: © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ASE Journal Articles

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