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Preliminary estimation of high-frequency (4–20 Hz) energy released from the 2016 Kumamoto, Japan, earthquake sequence
© The Author(s) 2016
- Received: 25 July 2016
- Accepted: 29 October 2016
- Published: 23 November 2016
- 2016 Kumamoto earthquake sequence
- High-frequency energy release
- Normalized cumulative energy release
At 21:26 (JST) on April 14, 2016, an M JMA6.5 earthquake (hereafter, April 14 event) occurred in Kumamoto district, center of Kyushu Island, Japan, and was followed by a significant number of earthquakes including the M JMA6.4 event at 00:03 on April 15. Twenty-eight hours after the April 14 event, an M JMA7.3 earthquake (hereafter, April 16 event) occurred in the same district at 01:25 on April 16. This event triggered widespread seismicity not only in Kumamoto district but also in northeastern distant areas like Aso district and Oita prefecture, and was also followed by large amount of earthquakes. Through this earthquake sequence, in total 50 people were directly killed due to collapse of buildings, mudflows or landslides, and so on (Cabinet Office, Government of Japan 2016).
One of the most important information for the public after a large earthquake is fast and accurate aftershock forecasting; particularly, people worry about whether comparable or even larger earthquakes would follow in the near future or not. For the Kumamoto earthquake sequence, the April 14 M JMA6.5 event had been considered to be the “mainshock” until the larger one (M JMA7.3) occurred on April 16: The original expectation was eventually wrong. In Japan, specific aftershock forecasting is usually announced at least 1 day after the occurrence of a large earthquake because it takes usually more than 1 day before catalog of the aftershocks becomes available for the forecast. Detection of earthquakes occurring within early lapse times (within a few hours in general) after a large event is generally very difficult because waveforms of many earthquakes occurring within a short time interval tend to overlap in seismograms, and conventional detection techniques using P- and/or S-wave picking become unavailable. Lack of the early earthquake catalog is one reason why the aftershock forecasting takes long time before it is announced.
To overcome this defect, some studies use an incomplete early aftershock catalog to estimate the parameter that represents the catalog’s incompleteness at the same time with other parameters that control the Omori–Utsu (Utsu 1961) and the Gutenberg–Richter (Gutenberg and Richter 1944) laws (e.g., Omi et al. 2015). More recently, Omi et al. (2016) pointed out that even automatically determined earthquake catalog (thus incompleteness and uncertainty are much serious than final catalog) is available for the aftershock forecasting with a performance comparable to the case of using the final catalog. Another strategy that can improve the early aftershock forecasting is to utilize continuous seismograms directly (e.g., Sawazaki and Enescu 2014; Lippiello et al. 2016). Since this technique can detect energy release from all earthquakes occurring in each consequent time interval, the misdetection should not be a problem in theory.
In this study, we apply the method by Sawazaki and Enescu (2014) with moderate correction to the Hi-net (operated by National Research Institute for Earth Science and Disaster Resilience, NIED) continuous seismograms and estimate high-frequency (4–20 Hz) energy release from the Kumamoto earthquake sequence. Particularly, we focus on how the energy release in pre-April 16 period (21:26, April 14–01:25, April 16) differs from that in post-April 16 period (01:25, April 16–01:25, April 26) and discuss the possibility of forecasting the April 16 event before it occurred.
After removing average and linear trend of the Hi-net seismogram, we apply the 4- to 20-Hz Butterworth band-pass filter to the original velocity seismogram and compute squared sum of the three components. The 4–20 Hz is selected because the signal-to-noise ratio of the seismograms is high at this frequency range. Then we multiply mass density 2800 kg/m3 to the record and compute average energy density every 1 s. The obtained seismogram envelope trace at each station is normalized by each local site amplification factor estimated by the coda-normalization method (Philips and Aki 1986), where the station N.KHKH is selected as the reference station because this site is characterized by relatively high V P and V S (V P = 4.2 km/s and V S = 1.9 km/s at 100 m depth) according to the well-logging data provided by NIED. Then, we divide the envelope by the global site amplification factor (Sawazaki and Enescu 2014) of 3.7 considering reflection of incident wave on the ground surface and difference of V S at the source (3.5 km/s) and that at the reference station (1.9 km/s). See Sawazaki and Enescu (2014) for detail of correction of the site amplification factor.
At some Hi-net stations, amplitude of the original velocity seismogram is saturated due to strong ground motion. Shiomi et al. (2005) pointed out that the Hi-net record is overlapped by high-frequency pulse noise when the stroke amplitude of the pendulum exceeds a threshold value (0.09 and 0.15 cm for horizontal and vertical components, respectively) and moving direction of the pendulum is changed suddenly. By comparing the Hi-net records and the colocated KiK-net strong motion records, we found that the contamination of the high-frequency noise is not negligible for six earthquakes with the magnitude larger than 5.8. For these events, we replace the saturated Hi-net records by the KiK-net records obtained at the same location. For the replacement, we first integrate the KiK-net accelerogram to velocity after applying the 0.1-Hz high-pass filter. Then we apply the same data processing as that applied to the Hi-net records and obtain the non-saturated envelope trace.
The original scheme of Sawazaki and Enescu (2014) is moderately corrected as follows. First, we use the hybrid synthetic envelope as the envelope Green’s function, where direct and coda parts of the envelope are synthesized on the basis of the forward scattering approximation (Shishov 1974) and the multiple isotropic scattering model (Paasschens 1997), respectively. This hybrid envelope better describes the whole envelope shape than the isotropic scattering model-based envelope used in Sawazaki and Enescu (2014) does. The synthesis of the hybrid envelope is summarized in Appendix 1. We synthesize not only S-wave but also P-wave envelope because amplitude of P-wave is not negligible in logarithmic scale. Second, we determine the energy release location using the theoretical S-wave peak arrival times. This strategy is different from that adopted by Sawazaki and Enescu (2014) who used theoretical peak amplitudes for estimation of the energy release location. The difference between the previous and the newly developed schemes for the location determination is explained in Appendix 2. Through these corrections, accuracy of the energy release location is considerably improved (Sawazaki 2016).
We determine the parameters that characterize the subsurface structure as follows: V P = 6.1 km/s V S = 3.5 km/s, ε (RMS fractional velocity fluctuation for a 3-D Gaussian-type random inhomogeneous media) = 0.12, a (correlation length) = 5 km, g 0 (scattering coefficient) = 1.0 × 10−2 km−1, and Q i −1 (intrinsic absorption factor) = 1.2 × 10−3. These values are determined from inspection of small earthquake records and previous studies by Carcole and Sato (2010), Sato et al. (2012), and so on. We use the theoretical envelopes synthesized using these parameters as the envelope Green’s function.
Figure 2 shows the comparison between the observed (black) and the best-fit (red) envelopes for the first 1000 s after the April 14 event. The fitness is generally good except for a few overestimated (e.g., N.YMGH) and underestimated (e.g., N.YABH) stations. These misfits are probably due to local difference in the scattering and intrinsic absorption factors and/or directionality due to radiation pattern, which are not reflected in the used envelope Green’s function.
Figure 3b demonstrates the zoomed energy release rate around the origin time (0 s) of the April 14 (black) and the April 16 events (red). Integrating the energy release rate from −5 to 25 s, we estimate the cumulative energy release from the April 14 and the April 16 events as 2.7 × 1012 J and 2.1 × 1013 J, respectively, in 4–20 Hz: The latter released eight times larger energy than the former.
Figure 3b shows a secondary peak at the lapse time of 34 s after the April 16 event, which corresponds to the energy release from the earthquake triggered at Oita prefecture (close to the number 12 source-grid in Fig. 1). Magnitude of this earthquake is estimated to be 5.6 from Eq. (3) using α = 3.4 and β = 1.4. This magnitude is similar to M JMA5.7, which had not been reported until a careful survey completes: Detection of this earthquake took a long time because seismograms are partially overlapped by coda wave of the April 16 event. Our envelope inversion technique can determine magnitude of this earthquake correctly in quasi real-time without disturbance by the coda wave.
Consistency between the estimated energy release rate and the aftershock catalog
Normalized cumulative energy release
Monitoring of NCER would provide information that contributes to judge the ongoing seismicity pattern after the large earthquake. The seismicity pattern would be categorized to mainshock–aftershock type if NCER is below a certain threshold value, while it could be categorized as foreshock–mainshock–aftershock type or swarm type if NCER is above the threshold value. It is interesting to examine the threshold value of NCER that distinguishes the mainshock–aftershock type and other types.
Importantly, the proposed envelope inversion analysis is available in quasi real-time once continuous seismograms are provided, which may be especially useful at regions covered by dense real-time seismograph networks. Through this method, we are able to obtain the p E value, which is related to b and p values that characterize activity of aftershocks without disturbance by the detection threshold. The NCER value is also important to understand how the energy release process varies depending on seismicity patterns such as mainshock–aftershock, foreshock–mainshock–aftershock, and swarm types. It is important to accumulate case studies by applying the envelope inversion analysis to various large earthquakes, especially to those accompanied by large foreshocks.
So far, we do not have any definite reasons that can explain why the aftershock productivity is so different for the April 14 and the April 16 events. Because the main ruptures of these two earthquakes occurred along the different faults (Hinagu and Futagawa faults, respectively) and the faulting processes are also largely different (e.g., Asano and Iwata 2016), the observed different behavior in the aftershock activities is not surprising. It is also important to examine how the aftershock productivity is related to rupture process of the mainshock, geological structure such as fault segmentation, small-scale velocity heterogeneity, intrinsic absorption, and so on.
In this study, we apply the envelope inversion scheme to the Hi-net continuous records to estimate spatiotemporal high-frequency (4–20 Hz) energy release associated with the 2016 Kumamoto earthquake sequence. The applied method is useful to estimate a gross feature of the earthquake sequence occurring immediately after a large earthquake, for which conventional earthquake relocation technique based on the phase picking does not work well. We especially focus on the difference in the energy releases after the April 14 M JMA6.5 and the April 16 M JMA7.3 earthquakes. There is a log-linear relationship between M JMA and the 4- to 20-Hz energy release when M JMA is smaller than about 4.5, while the relationship does not describe well for larger events probably because M JMA is determined using lower frequencies. The location of energy release expands to the northeast regions (Aso district and Oita prefecture) after the April 16 event, which includes an M5.6 earthquake triggered in Oita prefecture 34 s after the April 16 earthquake. The time-lapse decay of the energy release rate obeys a power-law function, where the exponent p E of the power-law decay is estimated to be 1.7–2.1. From combination of the Omori–Utsu law, the Gutenberg–Richter law, and the magnitude–energy release relationship, we derive the equality given by p E = βp/b. The β, p, and b values obtained by the analysis of aftershock catalog match the estimated p E values well. The normalized cumulative energy releases (NCERs) in the pre- and post-April 16 periods reach 60 and 11%, respectively, by the lapse time of 27 h. This discrepancy in NCER indicates that the April 14 M JMA6.5 event was followed by much larger relative energy release for its magnitude than the April 16 M JMA7.3 event. Thus, NCER would reflect the relative productivity of aftershocks and provide information of the ongoing seismicity pattern: mainshock–aftershock type, foreshock–mainshock–aftershock type, and swarm type, where the latter may give higher NCER.
KS analyzed the data and drafted the manuscript. HN and KS provided many comments and suggestions to improve the manuscript. All authors read and approved the final manuscript.
We thank Japan Meteorological Agency (JMA) and corresponding universities and institutes that contribute to compiling the JMA unified hypocenter catalog. We also thank Dr. M. Hashimoto, editor of Earth Planets and Space, two anonymous reviewers, and one guest editor for their thoughtful comments to improve our manuscript. Seismic Analysis Code (SAC) and Generic Mapping Tools (GMT) were used for signal processing and figure plotting, respectively. This work was partly supported by the Earthquake Research Institute Cooperative Research Program (2015-B-01).
The authors declare that they have no competing interests.
The Hi-net and KiK-net records are available through the webpage of NIED (http://www.hinet.bosai.go.jp/?LANG=en and http://www.kyoshin.bosai.go.jp/, respectively). The JMA unified hypocenter catalog is available from http://www.data.jma.go.jp/svd/eqev/data/bulletin/hypo.html.
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