Japan Geoscience Union Meeting 2022

Presentation information

[J] Poster

S (Solid Earth Sciences ) » S-VC Volcanology

[S-VC31] Active Volcanism

Thu. Jun 2, 2022 11:00 AM - 1:00 PM Online Poster Zoom Room (25) (Ch.25)

convener:Yuta Maeda(Nagoya University), convener:Fukashi Maeno(Earthquake Research Institute, University of Tokyo), Takeshi Matsushima(Institute of Seismology and Volcanology, Faculty of Science, Kyushu University)

11:00 AM - 1:00 PM

[SVC31-P15] Distribution of subsurface resistivity before the Aso 2021 magmatic eruption

*Sakura Ishibashi1, Mitsuru Utsugi1, Takuto Minami2 (1.Graduate School of Science, Kyoto University, 2.Graduate School of Science, Kobe University)


Keywords:Aso Volcano, phreatic eruption, resistivity structure, temporary change, ACTIVE survey

1. Background
The information about the subsurface hydrothermal system of volcanoes is important for understanding the mechanism of phreatomagmatic explosions. At Aso volcano, the magmatic eruptions with ash plume started in April 2019 and continued intermittently until June 2020. These activities were once quiescent, but two phreatic eruptions occurred in October 2021. In Sep.2021, a sinkhole was formed in the crater floor, and it was filled with hydrothermal fluids, resulting in continuous small-scale eruptions, which suggests the distribution of the subsurface volcanic fluids were changed prior to the eruptions in October. To monitor the subsurface resistivity structure of Aso volcano, Kyoto University has conducted ACTIVE observation, an electromagnetic survey method, around the Nakadake crater. In this study, we estimated the resistivity beneath the crater to know the state change of the hydrothermal system in the period from May to September 2021, just before the eruption.
2. Data
In this study, we used the data of ACTIVE observations in May, August, and September 2021, the period before the phreatic eruption (October 14 and 20), and tried to investigate the subsurface resistivity structure on these periods. In the ACTIVE observation, a rectangular artificial current is transmitted into the ground, and the induced magnetic field is observed to obtain information of the subsurface resistivity. In this study, we set up a current transmitting point at Sunasenrigahama, located southeast of the Nakadake 1st crater, and set up receiving points around the crater. In the previous study, four receiving points were set up on the western side of the crater (Fig.1), but we added two additional receiving points on the eastern side to improve the resolution and reliability of the inversion model (Fig.2).
As a result of these observations, it was found that the response of the induced magnetic field had changed before the eruptions in Oct.2021. Fig.3 shows the observation data obtained at a receiving point of A03 (Fig.2). This figure shows the amplitude of the induced magnetic field in the frequency domain. From the results of Fig.3, it can be seen that this amplitude changed significantly in time from May to September, suggesting that the subsurface resistivity had been changed before the 2021 phreatic eruption.
3. Method
In this study, we used the data obtained from the above three observations with the inversion code of Minami et al.(2018) to estimate the three-dimensional subsurface resistivity structure. In this inversion analysis, the subsurface space was divided by a fine tetrahedral mesh to consider the topography. Then, the subsurface area was divided into the blocks and it is assumed that that the tetrahedral mesh contain in each block have same resistivity in order to balance the number of the data and that of the unknown variables. In other words, the subsurface space was divided into blocks coarser than the tetrahedral meshes. In addition, the outer region, which is more than 2 km away from the crater, was assumed to be an integrated block with constant resistivity. In the inversion calculation, the sum of the misfit term and the roughness term, which represents the roughness of the model, was set as the objective function, and it was minimized by iterative calculations. The resistivity model derived by the 3D inversion using AMT data (Kanda et al., 2018) was used as the initial value of the resistivity structure. The resistivity value of the outer block was also varied and their optimum values were also obtained by the iteration.
In our presentation, we show the data obtained from the three observations before the 2021 phreatic eruption and snapshots of the subsurface structure at each observation period. From the temporal variation of subsurface resistivity during this period, we plan to discuss the state change of the onset site of the 2021 phreatic eruption.