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S-net is a seafloor observation network for earthquakes and tsunamis around the Japan Trench, comprising 150 observatories with seismometers and pressure gauges. The region has been known to experience massive earthquakes, and several magnitude 6 and 7 class earthquakes have occurred after the network was established in 2016. This study constructed ground motion prediction equations (GMPEs) for horizontal peak ground accelerations (PGAs) and peak ground velocities (PGVs) using the S-net data and revealed that the GMPEs can be used to predict the PGAs and PGVs at the land stations where measured S-wave velocities are available. We used a relatively short time window of the S-net records from the viewpoint of earthquake early warning but included S waves. Data from earthquakes of magnitudes between Mw 5.5 and Mw 7.4 were used. The construction of the GMPEs was achieved in two steps. First, regression analysis was conducted for each event data, and mean site residual was obtained over the available records at each S-net site. Second, the data were adjusted by the mean site residuals, and stratified regression analysis, which decouples the source and path factors, was performed. Finally, we applied the GMPEs to predict PGAs and PGVs at the KiK-net sites on land. We determined that the residuals at the KiK-net sites were systematically biased with Vs30 (average S-wave velocity in the upper 30 m). We obtained correction factors for the bias and demonstrated that the PGAs and PGVs at the KiK-net sites could be predicted reasonably well. [ABSTRACT FROM AUTHOR]

This article describes improvement of the rapid earthquake analysis system, accurate and quick analysis system for source parameters (AQUA), which has automatically determined the location, magnitude, and fault type of M < ∼7 earthquakes with good accuracy by analyzing long-period waveform data, but could not process the 2011 Off Tohoku giant earthquake (M9.0) due to instrumental and program limitations. Here, we address these problems by incorporating strong-motion seismic data and changing processing parameters accordingly, which extends the upper limit of applicable magnitudes to M9. In a simulated process, this earthquake is properly determined as thrust faulting with M8.6 offshore northeast Japan within 431 s of the first phase arrival. We also evaluate its performance. After improvements, four recent large earthquakes (M7.0–7.9) were properly processed in real time. The successful determination ratio is 100% for events with Japanese seismic intensity ≥6 Lower, and 100% for events with M>7 except nearly simultaneous events. Source parameters with and without fixed horizontal locations are provided within 100–250 and 100–600 s of the first P arrival, respectively. This system is valuable for disaster mitigation because it rapidly provides information for use in tsunami warning and early damage assessment. [ABSTRACT FROM AUTHOR]

The use of strongly biased data generally leads to large distortions in a trained machine learning model. We face this problem when constructing a predictor for earthquake-generated ground-motion intensity with machine learning. The machine learning predictor constructed in this study has an underestimation problem for strong motions, although the data fit on relatively weak ground motions is good. This underestimation problem is caused by the strong bias in available ground-motion records; there are few records of strong motions in the dataset. Therefore, we propose a hybrid approach of machine learning and conventional ground-motion prediction equation. This study demonstrates that this hybrid approach machine learning technology and physical model reduces the underestimation of strong motions and leads to better prediction than either of the individual approaches applied alone. [ABSTRACT FROM AUTHOR]

The nationwide strong-motion seismograph network of K-NET and KiK-net in Japan successfully recorded the strong ground motions of the 2016 Kumamoto earthquake sequence, which show the several notable characteristics. For the first large earthquake with a JMA magnitude of 6.5 (21:26, April 14, 2016, JST), the large strong motions are concentrated near the epicenter and the strong-motion attenuations are well predicted by the empirical relation for crustal earthquakes with a moment magnitude of 6.1. For the largest earthquake of the sequence with a JMA magnitude of 7.3 (01:25, April 16, 2016, JST), the large peak ground accelerations and velocities extend from the epicentral area to the northeast direction. The attenuation feature of peak ground accelerations generally follows the empirical relation, whereas that for velocities deviates from the empirical relation for stations with the epicentral distance of greater than 200 km, which can be attributed to the large Love wave having a dominant period around 10 s. The large accelerations were observed at stations even in Oita region, more than 70 km northeast from the epicenter. They are attributed to the local induced earthquake in Oita region, whose moment magnitude is estimated to be 5.5 by matching the amplitudes of the corresponding phases with the empirical attenuation relation. The real-time strong-motion observation has a potential for contributing to the mitigation of the ongoing earthquake disasters. We test a methodology to forecast the regions to be exposed to the large shaking in real time, which has been developed based on the fact that the neighboring stations are already shaken, for the largest event of the Kumamoto earthquakes, and demonstrate that it is simple but effective to quickly make warning. We also shows that the interpolation of the strong motions in real time is feasible, which will be utilized for the real-time forecast of ground motions based on the observed shakings. [ABSTRACT FROM AUTHOR]

In earthquake hazard assessment studies, the focus is usually on horizontal ground motion. However, records from the 14 June 2008 Iwate-Miyagi earthquake in Japan, a crustal event with a moment magnitude of 6.9, revealed an unprecedented vertical surface acceleration of nearly four times gravity, more than twice its horizontal counterpart. The vertical acceleration was distinctly asymmetric; the waveform envelope was about 1.6 times as large in the upward direction us in the downward direction, which is not explained by existing models of the soil response. We present a simple model of a mass bounding on a trampoline to account for this asymmetry and the large vertical amplitude. The finding of a hitherto-unknown mode of strong ground motion may prompt major progress in near-source shaking assessments. [ABSTRACT FROM AUTHOR]

National Research Institute for Earth Science and Disaster Resilience (NIED) integrated the land observation networks established since the 1995 Kobe earthquake with the seafloor observation networks established since the 2011 Tohoku earthquake and tsunami as MOWLAS (Monitoring of Waves on Land and Seafloor) in November 2017. The purpose of MOWLAS is to provide comprehensive, accurate, and rapid observation and monitoring of earthquake, tsunami, and volcano events throughout Japan and its offshore areas. MOWLAS data are widely utilized for long-term earthquake forecasting, the monitoring of current seismic activity, seismic and tsunami hazard assessments, earthquake early warning, tsunami warning, and earthquake engineering, as well as earthquake science. Ocean bottom observations provide an extension of observations to areas where no people are living and have the advantage of increasing lead time of earthquake early warning and tsunami warning. The application of recent technology advancements to real-time observations as well as the processing of MOWLAS data has contributed to the direct disaster mitigation of ongoing earthquakes. These observations are fundamental for both science and disaster resilience, and thus it is necessary to continue ceaseless operation and maintenance. [ABSTRACT FROM AUTHOR]

The observed peak ground accelerations and peak ground velocities (PGVs) of the 2018 Mw 6.6 Hokkaido eastern Iburi earthquake generally followed the median values from ground motion prediction equations with reasonable errors at fault distances ≥ 50 km. However, at smaller distances, the equations significantly underestimated the peak ground motions, and it was eminent for PGVs. A comparison of surface-to-borehole spectral ratios of S-waves during the mainshock and other events revealed that the sites at smaller distances experienced various degrees of nonlinear site response. The two most widely known characteristics of nonlinear site response are the weakening of higher-frequency components and shifting of predominant frequencies to lower ones in comparison with the linear site response. At one of the sites that recorded the largest intensity of 7 in JMA scale of 0–7, the latter nonlinear effect was so dominant that the ground motions around the new predominant frequency got intensified by one order of magnitude in comparison with that during the weak-motions. Two sites, which were closely located, recorded vertical peak ground accelerations exceeding 1 g for the up-going motions. The recordings showed asymmetric waveforms and amplitudes characteristics of the nonlinear site response in extreme vertical ground motions recorded during a few earthquakes in the past. Few sites having lower vertical peak ground accelerations were also suspected of being experienced nonlinear site response on vertical motions. These findings suggest taking a cautious approach to enumerate the reduction in amplification at higher frequencies using the single-station horizontal-to-vertical (H-to-V) spectral ratio technique. However, we found that the H-to-V technique was still useful to detect nonlinearity. Finally, an ad hoc equation was derived to correct the nonlinear site amplification in predicting horizontal PGVs with respect to one of the most widely used attenuation models in Japan. The results indicated that the effect was much stronger for a larger input motion than that for a proportional change in the Vs30 values. [ABSTRACT FROM AUTHOR]

Earthquake ruptures cause mass redistribution, which is expected to induce transient gravity perturbations simultaneously at all distances from the source before the arrival of P-waves. A recent research paper reported the detection of such prompt gravity signals from the 2011 Tohoku-Oki earthquake by comparing observed acceleration waveforms and model simulations. The 11 observed waveforms presented in that paper recorded in East Asia shared a similar trend above the background seismic noise and were in good agreement with the simulations. However, the signal detection was less quantitative because the significance of the observed signals was not discussed and the waveforms at other stations in the region were not shown. In this study, similar trends were not observed in most of the data recorded near the stations used in the aforementioned study, suggesting that the reported signals were only local noises. We thus took a different approach to identify the prompt signals. We optimized the multi-channel data recorded by superconducting gravimeters, broadband seismometers, and tiltmeters. Though no signal was identified in the single-trace records, the stacked trace of the broadband seismometer array data in Japan showed a clear signal above the reduced noise level. The signal amplitude was 0.25 nm/s2 for an average distance of 987 km from the event hypocenter. This detection was confirmed with a statistical significance of 7σ, where σ is the standard deviation of the amplitude of the background noise. This result provided the first constraint on the amplitude of the observed prompt signals and may serve as a reference in the detection of prompt signals in future earthquakes. [ABSTRACT FROM AUTHOR]

We analyzed strong-motion and broadband recordings of two moderate-magnitude earthquakes that occurred in the Nankai Trough. The first event was the 2004 Mw 6.5 southeast off-Kii peninsula earthquake, an aftershock event inside the Philippine Sea Plate near the Nankai Trough axis. The second event was the 2016 Mw 5.8 southeast off-Mie Prefecture earthquake, an independent event in the rupture area of the 1944 Mw ~ 8 Tonankai earthquake. The centroid depths were 11 and 14 km for the 2004 and 2016 events, respectively. Despite a large difference in the moment magnitude between the two events, the JMA magnitude (Mj) was 6.5 for both the events. We found that the short-period ground motions (e.g., response spectra at periods < 1 s) as well as the much longer-period ground motions (> 20 s) for the 2016 event scaled generally well with the moment magnitude of the event. In contrast, the ground motions from the 2016 event were comparable to those for the larger-moment-magnitude 2004 event at equal distances at periods of about 2-20 s in wide areas and the observed acceleration response spectra at those periods were noticeably underestimated for the 2016 event by the ground motion prediction equation (GMPE) that employs Mw. An examination of the existing subsurface velocity model suggested that the difference in the relative location of the two events with respect to the thick accretionary prism of low seismic velocity most probably caused the comparable amplitude of the seismic waves at those periods. As a result, we posit that the values of Mj are equal for the two events because Mj is estimated using the displacement amplitude of ground motions at periods smaller than about 6 s. On the other hand, GMPE employing Mj generally described the observed data well. The results suggested that the plate boundary earthquakes in the Nankai Trough may excite strong long-period ground motions of engineering importance, and these ground motions appear to be better explained by Mj than by Mw in GMPEs for moderate-magnitude earthquakes in the Nankai Trough subduction zone. [ABSTRACT FROM AUTHOR]