Rupture process of the 2016 Kumamoto earthquake in relation to the thermal structure around Aso volcano
© The Author(s) 2016
Received: 5 May 2016
Accepted: 15 June 2016
Published: 14 July 2016
We constructed the rupture process model for the 2016 Kumamoto, Japan, earthquake from broadband teleseismic body waveforms (P-waves) by using a novel waveform inversion method that takes into account the uncertainty of Green’s function. The estimated source parameters are: seismic moment = 5.1 × 1019 Nm (Mw = 7.1), fault length = 40 km, and fault width = 15 km. The mainshock rupture mainly propagated northeastward from the epicenter, for about 30 km, along an active strike-slip fault. The rupture propagation of the mainshock decelerated and terminated near the southwest side of the Aso volcano; the aftershock activity was low around the northeastern edge of the major slip area. Our results suggest that the rupture process of the mainshock and the distribution of aftershocks were influenced by the high-temperature area around the magma chamber of Mt. Aso.
Keywords2016 Kumamoto earthquake Rupture process Foreshocks and aftershocks Mt. Aso Magma chamber
The geologic structure, which includes the Aso volcano, locates in the central part of the OKTL and might have contributed to the complex rupture process during foreshocks, mainshock, and aftershocks. The source model of the mainshock, in particular, may help to understand the seismicity evolution during the 2016 Kumamoto earthquake sequence in its geologic context. Here, we first determine the robust seismic source process of the 2016 Kumamoto earthquake by applying a novel inversion technique (Yagi and Fukahata 2011a) that takes into account the modeling errors due to the uncertainty of Green’s function. Then, we discuss the relationship between the rupture process of the mainshock, seismicity, and the geologic structure around the Aso volcano. Understanding the relationship between seismicity and crustal geophysics (e.g., Hauksson 2011), in particular the crustal thermal structure (Enescu et al. 2009), may help in a better assessment of seismic hazard.
The spatiotemporal slip-rate distributions of large earthquakes have been estimated by waveform inversion since early 1980s (e.g., Hartzell and Heaton 1983). However, the results of inversions conducted for the same earthquake are often different from one another (e.g., Beresnev 2003). The modeling errors originated from the accuracy limitations of Green’s function are a major problem in seismic source inversion studies and may often bias the inversion result.
To obtain a robust seismic source model for the 2016 Kumamoto earthquake, we applied the inversion formulation developed by Yagi and Fukahata (2011a) to teleseismic P-waves. This inversion formulation takes into account the uncertainty of Green’s function and objectively determines the smoothness of the spatiotemporal slip-rate distribution from observed data, using the Akaike’s Bayesian information criterion (e.g., Akaike 1980). Such features of the inversion formulation enable us to estimate the complex and irregular rupture process, including the back rupture propagation; the inversion formulation has been applied, for example, to the 2006 Java, Indonesia, tsunami earthquake (Yagi and Fukahata 2011a), the 2011 Tohoku-oki megathrust earthquake (Yagi and Fukahata 2011b), the 2008 Wenchuan, China, earthquake (Yagi et al. 2012), and the 2015 Illapel, Chile, earthquake (Okuwaki et al. 2016). Yagi and Fukahata (2011a, b) show that if we neglect the data covariance components, the slip-rate distribution is distorted by modeling errors originated from the uncertainty of Green’s function.
We assumed the rupture occurring on a single fault plane of (strike, dip) = (234°, 64°) and the fault area of 58 km length and 20 km width. The geographical coordinates of the initial break point are the same as for the JMA epicenter. The fault plane was slightly modified from that obtained by moment tensor inversion of teleseismic body waves to be consistent with the geometry and location of the Futagawa fault (Headquarters for Earthquake Research Promotion, http://www.jishin.go.jp/main/index‐e.html; last accessed on April 28, 2016). For the same reason, the break point depth (i.e., hypocentral depth) was taken at 9 km. Assumed dip angle was shallower than the estimated value of the regional seismic network (National Research Institute for Earth Science and Disaster Resilience, Japan, http://www.fnet.bosai.go.jp/top.php?LANG=en; last accessed on June 13, 2016). We performed inversions using several dip angles and found that the center of the maximum slip area was stable (Additional file 1: Figure A2). We imposed no specific constraints on the rake angles. As the structure model near the source, we used CRUST 1.0 (Additional file 1: Table A1; Laske et al. 2013). We adopted a slip-rate function represented as linear B-splines with a grid interval of 0.3 s and having a duration of 15 s on each fault patch. The assumed rupture duration was taken as 18 s. The theoretical Green’s functions of each source node were calculated with the method of Kikuchi and Kanamori (1991). The maximum rupture front velocity, which defines the rupture onset time at each spatial node, was set to 2.4 km/s. The center of the maximum slip area was stable even when we have assumed various maximum rupture front velocities (Additional file 1: Figure A3). We also examined two kinds of initial slip model: uniform slip model and vertical striped slip models in the same way as Yagi and Fukahata (2011a), and found that exactly the same solution was obtained for both of the initial slip models.
Results and discussion
The total slip distribution, the moment-rate function, and the focal mechanism are given in Fig. 1a. We found that the rupture mainly propagated toward northeast from the epicenter. The rupture direction is consistent with the characteristics of the mainshock waveforms (Fig. 2b), which are shorter toward northeast and broader toward southwest. The area of large slip, with a maximum of 5.7 m, is centered about 10 km northeast from the epicenter. The effective slip area extends about 40 km long and 15 km wide. The average rake angle was −148°, which is approximately consistent with the fault motion of historical earthquakes estimated by geological surveys (Research Group for Active Faults of Japan 1991). The total seismic moment was 5.1 × 1019 Nm (Mw = 7.0), which is comparable to the Global Centroid Moment Tensor solution of 4.5 × 1019 Nm (http://www.globalcmt.org; last accessed on April 28, 2016).
The slip-rate distribution shows that the rupture propagated to southwest during the first 5 s. At 5 s after the origin time, the main rupture started to propagate toward northeast. The slip rate started decreasing from 15 s and terminated at about 17 s after the initial break. The on-fault aftershocks occurred along the Futagawa fault zone, and the off-fault aftershocks were triggered along the OKTL (Figs. 1a, 3c).
We estimated the robust spatiotemporal slip-rate distribution of the 2016 Kumamoto earthquake using the waveform inversion of teleseismic P-wave data and examined the 2016 Kumamoto earthquake sequence, including the foreshock and aftershock activity. The foreshocks started in the northern part of the Hinagu fault, and the rupture of the mainshock initiated at the junction between the Hinagu and the Futagawa fault zones. The dynamic rupture of the mainshock mainly propagated 30 km northeastward from the epicenter, along the Futagawa fault. The rupture of the mainshock decelerated and terminated near the southwest side of the Aso volcano, and aftershock activity was low around the northeastern edge of the major slip area (where shear stress was increasing due to the coseismic slip of the mainshock). The high-temperature area around the magma chamber of Mt. Aso may contribute to the termination of the rupture during the mainshock and peculiarly low aftershock activity of the 2016 Kumamoto earthquake, around Mt. Aso.
Japan Meteorological Agency
Japan Standard Time
Oita–Kumamoto Tectonic Line
Shuttle Radar Topography Mission
Coordinated Universal Time
YY led and designed the whole research and drafted the manuscript. RO carried out the inversion analysis, generated the figures and Additional file, and contributed to the examination of the results. BE and AK contributed to the discussion of the results. AM contributed to generate the contents of Fig. 1b. AM and MO contributed to the interpretation of the results related to the local and regional geology. All authors discussed the results and commented on the manuscript. All authors read and approved the final manuscript.
Waveform data from Berkeley Digital Seismic Network, Global Seismograph Network, and IRIS/Singapore, Singapore National Network, were accessed through the Incorporated Research Institutions for Seismology—Data Management Center. Figures were generated with the Generic Mapping Tools (Wessel and Smith 1998). We thank Yasukuni Okubo and Yujiro Ogawa for useful information. We also thank Chen Ji, Sebastiano D’Amico, and the Editor Haruo Horikawa and the Chief Editor Yasuo Ogawa for helpful comments and advices. Authors acknowledge support from the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant 16K05529 (to YY) and 26240004 (to BE).
The authors declare that they have no competing interests.
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- Akaike H (1980) Likelihood and the Bayes procedure. In: Bernardo JM, DeGroot MH, Lindley DV, Smith AFM (eds) Bayesian Statistics. University Press, Valencia, pp 143–166Google Scholar
- Beresnev IA (2003) Uncertainties in finite-fault slip inversions: to what extent to believe? (a critical review). Bull Seismol Soc Am 93:2445–2458. doi:10.1785/0120020225 View ArticleGoogle Scholar
- Enescu B, Hainzl S, Ben-Zion Y (2009) Correlations of seismicity patterns in Southern California with surface heat flow data. Bull Seismol Soc Am 99(6):3114–3123. doi:10.1785/0120080038 View ArticleGoogle Scholar
- Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Shaffer S, Shimada J, Umland J, Werner M, Oskin M, Burbank D, Alsdorf D (2007) The shuttle radar topography mission. Rev Geophys 45:RG2004. doi:10.1029/2005RG000183 View ArticleGoogle Scholar
- Hartzell S, Heaton T (1983) Inversion of strong ground motion and teleseismic waveform data for the fault rupture history of the 1979 Imperial Valley, California, earthquake. Bull Seismol Soc Am 73:1553–1583Google Scholar
- Hauksson E (2011) Crustal geophysics and seismicity in southern California. Geophys J Int 186:82–98. doi:10.1111/j.1365-246X.2011.05042.x View ArticleGoogle Scholar
- Kamata H, Kodama K (1994) Tectonics of an arc-arc junction: an example from Kyushu Island at the junction of the Southwest Japan Arc and the Ryukyu Arc. Tectonophysics 233:69–81View ArticleGoogle Scholar
- Kikuchi M, Kanamori H (1991) Inversion of complex body waves—III. Bull Seismol Soc Am 81:2335–2350Google Scholar
- King G, Nabelek J (1985) The role of fault bends in the initiation and termination of earthquake rupture. Science 228:984–987View ArticleGoogle Scholar
- Komazawa M (2013) Gravity grid data of Japan. In: Survey Geological, Geological Survey of Japan (eds) Gravity database of Japan DVD edition Digital Geoscience Map P-2. Geological Survey of Japan, AIST, TsukubaGoogle Scholar
- Laske G, Masters G, Ma Z, Pasyanos M (2013) Update on CRUST1.0—A 1-degree Global Model of Earth’s Crust. Geophys Res Abstracts 15:EGU2013-2658
- Matsumoto S, Nakao S, Ohkura T, Miyazaki M, Shimizu H, Abe Y (2015) Spatial heterogeneities in tectonic stress in Kyushu. Earth Planets Space, Japan and their relation to a major shear zone. doi:10.1186/s40623-015-0342-8 Google Scholar
- Okada Y (1992) Internal deformation due to shear and tensile faults in a half-space. Bull Seism Soc Am 82:1018–1040Google Scholar
- Okubo Y, Shibuya A (1993) Thermal and crustal structure of the Aso volcano and surrounding regions constrained by gravity and magnetic data, Japan. J Volcanol Geotherm Res 55:337–350View ArticleGoogle Scholar
- Okuwaki R, Yagi Y, Aránguiz R, González J, González G (2016) Rupture process during the 2015 Illapel, Chile earthquake: zigzag-along-dip rupture episodes. Pure appl Geophys 173:1011–1020. doi:10.1007/s00024-016-1271-6 View ArticleGoogle Scholar
- Research group for active faults of Japan (1991) Active faults in Japan. Sheet maps and inventories, Revised Edition. University of Tokyo Press, TokyoGoogle Scholar
- Scholz CH (1998) Earthquake and friction laws. Nature 391:37–42. doi:10.1038/34097 View ArticleGoogle Scholar
- Sudo Y, Kong L (2001) Three-dimensional seismic velocity structure beneath Aso Volcano, Kyushu, Japan. Bull Volcanol 63:326–344. doi:10.1007/s004450100145 View ArticleGoogle Scholar
- Wessel P, Smith WHF (1998) New, improved version of generic mapping tools released. EOS Trans Am Geophys Union 79:579. doi:10.1029/98EO00426 View ArticleGoogle Scholar
- Yagi Y, Fukahata Y (2011a) Introduction of uncertainty of Green’s function into waveform inversion for seismic source processes. Geophys J Int 186:711–720. doi:10.1111/j.1365-246X.2011.05043.x View ArticleGoogle Scholar
- Yagi Y, Fukahata Y (2011b) Rupture process of the 2011 Tohoku-oki earthquake and absolute elastic strain release. Geophys Res Lett 38:1–6. doi:10.1029/2011GL048701 View ArticleGoogle Scholar
- Yagi Y, Mikumo T, Pacheco J, Reyes G (2004) Source rupture process of the Tecoman, Colima, Mexico earthquake of January 22, 2003, determined by joint inversion of teleseismic body wave and near source data. Bull Seism Soc Am 94:1795–1807View ArticleGoogle Scholar
- Yagi Y, Naoki N, Kasahara A (2012) Source process of the 12 May 2008 Wenchuan, China, earthquake determined by waveform inversion of teleseismic body waves with a data covariance matrix. Earth Planets Space 64:e13–e16. doi:10.5047/eps.2012.05.006 View ArticleGoogle Scholar