Crustal deformation associated with the 2016 Kumamoto Earthquake and its effect on the magma system of Aso volcano
© The Author(s) 2016
Received: 22 June 2016
Accepted: 5 November 2016
Published: 22 November 2016
Aso volcano has a large caldera with a size of 25 km from north to south and 18 km from east to west, and its central cones are aligned east–west in the center of the caldera (e.g., Ono and Watanabe 1985). The most violent eruption occurred about 90,000 years ago (VEI 7), and the caldera was formed in this eruption (Aso-4) (Matsumoto 1996; Aoki 2008). Nakadake, which is a central cone, is an active volcano where eruptions have occurred frequently. NIED operates a volcano observation network named V-net in several Japanese volcanoes, including the Aso volcano (Ueda et al. 2013). High activity of volcanic tremor has been observed before the Kumamoto Earthquake, but further activation or inactivation has not been observed at present (September 2016). However, the relationship between a large earthquake and volcanic activity has been discussed in many previous studies (e.g., Bautisa et al. 1996; Manga and Broadsky 2006; Lara et al. 2004; Walter 2007; Walter and Amelung 2007; Ebmeier et al. 2016). One of possible triggering mechanisms is deformation of magma system due to the earthquake. Since seismic area is close to the Aso volcano, there is a possibility that the magma system has been deformed significantly. Such deformation may cause further activation of volcanic activity in the future. Therefore, it is important to estimate how much influence the earthquake had on the Aso magma system.
In this paper, we detected crustal deformation associated with the 2016 Kumamoto Earthquake using synthetic aperture radar interferometry (InSAR) and a GNSS analysis and estimated a fault model from the obtained crustal deformations. Based on the estimated fault model, we evaluated the effect of the earthquake on the Aso magma system.
Detection of crustal deformation
SAR data pairs analyzed in this study
Estimation of the fault model
We estimated fault models for this earthquake from InSAR and GNSS results. In this estimation, we used theoretical crustal deformation due to dislocation of a rectangular fault in an elastic half-space (Okada 1985) and estimated fault parameters that well explained the observed crustal deformations. Since the number of InSAR data exceeds 5 million, using all InSAR data in this estimation is inefficient. For efficiency of estimation, the slant-range change, based on the stripmap mode data, was picked up every 20 s (approximately 500 m) in areas where a large change was observed and every 80 s (approximately 2 km) in other areas. Slant-range changes from the ScanSAR mode were picked up every 40 s (approximately 1 km) in areas where a large change was observed and every 160 s (approximately 4 km) in other areas. 24,306 slant-range changes from InSAR and three components of the GNSS displacement vectors for 13 sites were used in this estimation. We set a 100-fold weight on GNSS displacements relative to the InSAR slant-range change. In this fault model estimation, we considered four fault segments (F1–F4) that were suggested from interferograms. The F1 segment is along the Futagawa Fault, and the F2 segment is the northeast extension part from its east end. The F3 segment is located alongside the Hinagu Fault. The F4 segment is located alongside the F1 segment. Since the strike directions for the F1 and F3 segments could be identified clearly from interferograms, we fixed them to N240°E (F1) and N216°E (F3). Furthermore, the decorrelation line along the Futagawa Fault and the steep gradient line along the Hinagu Fault correspond to the upper margins of faults or the intersection line of a fault extension and land surface, and we constrained the fault locations so that a fault extension was consistent with that. Although the decorrelation line and steep gradient of the slant-range change were also seen around the F2 segment, we did not constrain the location of the F2 segment because the distribution might be distorted by local deformation as mentioned in the previous chapter. We then estimated all parameters for the F2 segment. Concerning the F4 segment, we assumed its strike direction to be the same as that of the F1 segment. In the fault model estimation, we first searched the presumed parameters for fault locations, sizes, dips, and strike by the trial-and-error method, and then improved the solution using the Levenberg–Marquardt (LM) method (Marquardt 1963). Generally, a non-deformation component with a long wavelength due to orbital errors and ionospheric effect remains in an InSAR result. We assumed their components to be a uniformly inclined plane and estimated them (three components for each InSAR result) with fault parameters simultaneously. Slip vectors for the four segments and non-deformation components for the six interferograms were estimated in each iteration using the linear least-square method.
Parameters for the estimated fault model
As revealed in our previous study (Ozawa and Fujita 2013) and other studies (Takada and Fukushima 2013; Pritchard et al. 2013), local deformation associated with large earthquake was detected around volcanoes. We expected that such deformation might have found above the magma chamber in residual distributions, but such local deformation was not detected in this analysis (Fig. 4). We suspect that its reason is related to the size of the affected magma chamber. In the case that the size of magma chamber is small, surface deformation due to deformation of the magma chamber is small. Provably, larger magma chamber will exist in deeper area. However, rupture in this earthquake occurred in shallow depth and typical fault dislocation was lateral slip. Therefore, crustal deformation around the deep large magma chamber must have been small. From this reason, we suspect that crustal deformation due to deformation of the magma chamber might have not been detected.
Effect of crustal deformation on the magma system
In this section, we model the crustal structure and magma system using the finite-element method (FEM) and calculate the displacement and stress fields caused by the earthquake. The target area was set to 130.5°E–131.5°E, 32.5°N–33.3°N, and 0–40 km, and was divided into 112 × 112 × 50 elements. In addition, we re-mesh Aso volcanic area of 0.04° latitude × 0.09° longitude × 15 km depth to 112 × 112 × 50 meshes for more detailed analysis. In the elements generation for the FEM analysis, we considered topography by using a digital elevation model published by GSI. Elastic parameters at each element were derived based on Vp and Vs structures estimated by seismic tomography (Matsubara et al. 2008). We estimated the density via an empirical equation; the elastic moduli and Poisson ratios can then be obtained (Birch 1961). For a magma system, we assumed a spherical structure filled with the soft elastic; the bulk modulus was 10 GPa, and the Poisson ratio was 0.49. Sudo and Kong (2001) applied seismic tomography and detected a low velocity region about 6 km beneath an area south of the Kusasenri region. A leveling survey suggested a deflation source around the same area (Sudo et al. 2006). Considering their results, we placed a spherical soft structure with a 1-km radius 6 km deep beneath the area south of the Kusasenri region. To remove the artificial reflection from the finite boundaries, we applied “infinite elements” at the horizontal and bottom boundaries. Applying slips on the four fault segments estimated in this study, we calculated the displacement and stress fields around the Aso magma system.
Confidence of the estimated fault model
The F3 segment corresponds to the Hinagu Fault. As mentioned before, high gradient line of crustal deformation was obtained alongside the Hinagu Fault, and the strike direction and the location of the upper margin are obvious from its feature. The rake angle of the fault slip was estimated to 180°, and it is consistent with the right-lateral offset of the Hinagu Fault revealed from geological investigations (e.g., Chida 1979). According to the F-net catalogue, the strike-slip type focal mechanism was dominant around the F3 segment, and strike directions for MJMA5 earthquakes were N211°E–N216°E, corresponding to that of the F3 segment. Dip angles were 74°–89°, and it roughly corresponds to that of the F3 segment. Figure 11b shows the relation between the location of the F3 segment and the aftershock distribution. Seismicity is low around the upper- and mid-parts of the segment, and that is high around the bottom part. However, it seems that the location of the F3 segment and the alignment line of aftershock distribution are slightly different. Additionally, high gradient line of crustal deformation was not consistent with the Hinagu Fault as mentioned before. It suggests that multiple fault segments may have been ruptured around this area. However, as a simple model for rough estimation of the effect on the magma system of the Aso volcano, this model must be acceptable.
The F4 segment is located alongside the east part of the Futagawa Fault and intersects the F1 segment at a shallow depth. We assumed this segment for explaining crustal deformation obtained from InSAR pair 1 (Figs. 2, 4), slant-range extension which was obtained in both sides of the Futagawa Fault. The F4 segment has a low dip angle of 38°. The rake angle of the F4 segment was estimated to be 237° including large normal-slip component, though pure right-lateral slips were estimated for other segments. Around the F4 segment, several shallow aftershocks with a normal-slip mechanism occurred, and two earthquakes in them exceeded MJMA5. Their strike directions were N238°E and N286°E, and dip angles were 35° and 38°, corresponding to that of the F4 segment. Furthermore, the shallower extension of the F4 segment is roughly consistent with another parallel fault line of the Futagawa Fault.
Kubo et al. (2016) estimated source rupture process from strong motion waveforms, and large right-lateral slips were obtained near the F1–F4 segments. Its amount was 2 m or larger, roughly corresponding to our model. In particular, fault slips around the F1, F2, and F3 segments were large. Furthermore, large normal-slip component was estimated around the F4 segment. Such features are consistent with those of the fault model in this study.
As mentioned above, the estimated fault model is mostly consistent with results from seismic observation data and geological surveys. Then, we think that the estimated fault model must be acceptable for estimating the effect of crustal deformation on the magma system of the Aso volcano. Although we aimed at estimating the simple fault model in this study, a more accurate fault model could be estimated by considering the heterogeneity of the fault slip distribution. It is one of the issues for future research.
We detected crustal deformation associated with the 2016 Kumamoto Earthquake using InSAR and GNSS and found a decorrelation line and a steep gradient line of slant-range change along the Futagawa Fault, along the northeast extension of the Futagawa Fault, and alongside the Hinagu Fault. Additionally, we found a complex fringe pattern west of the Aso caldera, suggesting that shallow fault slips occurred in many known and unknown faults associated with the earthquake. Most of the crustal deformation could be explained reasonably by four rectangle faults located along the Futagawa Fault (F1), in the northeast extension of the Futagawa fault (F2), alongside the Hinagu Fault (F3), and in the eastern part of the Futagawa Fault (F4). The first-mentioned three faults have high dip angles and right-lateral slip, and the last fault has a low dip angle and normal-dip right-lateral slip. The estimated fault model is consistent with the aftershock distribution and seismic mechanisms.
Based on the estimated fault model, we estimated the effect of crustal deformation on the Aso magma system using FEM. Our calculation suggests the following two points. (1) Deformation and stress perturbations were very complicated, since the assumed location of the magma system was close to a seismic fault, especially the F2 fault segment. In general, the spherical magma system deformed slightly to an ellipsoid, and the total volume increased. In this case, the magma in the reservoir can be depressurized, and this may lead to degassing from the magma. (2) The differential stress around the northeastern portion of the magma system was as large as 3.5 MPa. It is on the order of stress disturbances that could trigger an opening of a pre-existing fracture around the magma reservoir and the intrusion of magma.
We are monitoring volcanic activity using V-net observation, and no obvious increase or decrease in activity has been observed through the time of this paper submission (September 2016). However, we have shown that this earthquake could have effected the shape of the magma reservoir and local stress field, thereby possibly triggering processes that lead to enhanced volcanic activity. Hence, more detailed monitoring of the Aso volcano is important.
TO performed InSAR analysis and fault modeling. He also wrote the manuscript. EF modeled the crustal structure and magma system using FEM and calculated the displacement and stress fields caused by the earthquake. HO performed GNSS analysis. All authors read and approved the final manuscript.
We are grateful to two anonymous reviewers and Prof. Nishimura for their valuable comments. We analyzed ALOS-2/PALSAR-2 data that are shared within the PALSAR Interferometry Consortium to Study our Evolving Land Surface (PIXEL) in this study. The data were provided by the Japan Aerospace Exploration Agency (JAXA) under a cooperative research contract with the Earthquake Research Institute (ERI) at the University of Tokyo. This study was supported in part by the ERI cooperative research program. PALSAR-2 observations after the earthquake were carried out based on the Earthquake Working Group, a special project for evaluating ALOS for disaster mitigation, coordinated by the Geospatial Information Authority of Japan (GSI) and JAXA. The original PALSAR-2 data are owned by JAXA. GEONET data and the 10-m-mesh DEM published by GSI were used in this study. We used the unified hypocenter catalog processed in collaboration with the Japan Meteorological Agency (JMA) and the Ministry of Education, Culture, Sports, Science and Technology (MEXT). We used the Generic Mapping Tools (Wessel and Smith 1998) for drawing the figures.
The authors declare that they have no competing interests.
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