GROUND MOTION SPECTRAL INTENSITY PREDICTION WITH STOCHASTIC GREEN S FUNCTION METHOD FOR HYPOTHETICAL GREAT EARTHQUAKES ALONG THE NANKAI TROUGH, JAPAN

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GROUND MOTION SPECTRAL INTENSITY PREDICTION WITH STOCHASTIC GREEN S FUNCTION METHOD FOR HYPOTHETICAL GREAT EARTHQUAKES ALONG THE NANKAI TROUGH, JAPAN Masayuki YOSHIMI 1, Yasuto KUWAHARA 2, Masayuki

1 GROUND MOTION SPECTRAL INTENSITY PREDICTION WITH STOCHASTIC GREEN S FUNCTION METHOD FOR HYPOTHETICAL GREAT EARTHQUAKES ALONG THE NANKAI TROUGH, JAPAN Masayuki YOSHIMI 1, Yasuto KUWAHARA 2, Masayuki YAMADA 3, Tadao SIGARAKI 4 and Koji HADA 5 Introduction Megathrust earthquakes on subduction zone around Japan such as the 2011 Tohoku Earthquake cause serious damage in vast area by strong shaking as well as tsunami. The Nankai trough, a subduction zone off the southern coast of west Japan, is such an area where great subduction earthquake(s) will occur near future. To assess and mitigate damage from those earthquakes, prediction of ground motions and their intensities is of great importance. As the exact source characteristics of the next earthquakes cannot be known in advance, ground motion prediction works must be done considering plausible source variation of the events. We predict spectral intensity of the ground motions during those earthquakes, focusing on Chukyo area, the largest Japanese industrial site where about 15 percent of the total value of shipment of Japan is produced, locating close to the source area of great earthquakes on the Nankai trough. Method Stochastic Green s function method (SGFM: Boore 1983) is applied combined with 1D linear response analysis to calculate synthetic ground motion on the ground surface. Waveforms at the seismic basement are calculated with SGFM applying attenuation Q=114*f 0.92 of eastern Japan (Sato and Tatsumi, 2002). Source model of the hypothetical Nankai earthquake is comprised of tens of strong motion generation areas (SMGA) and background rupture area. Each SMGA has own rupture initiation point, which makes the source model to be multi-hypocenter source model. Setting of spatial variation of the SMGA is shown later in detail. For the 1D response calculation, from the seismic basement to the ground surface, we compile 250 m grid subsurface velocity model from a deep sedimentary basin velocity model made by the Geological Survey of Japan (Horikawa et al., 2008) (Fig.2) and shallow velocity models made by prefectures in Chukyo area, Aichi, Gifu and Mie prefectures (Aichi pref., 2003, Gifu pref., 2013, Mie pref., 2006). Deep and shallow velocity models are combined at a depth where S-wave velocity is 700 m/s or 500 m/s, depending on shallow structure model. Average spectral intensity is calculated from acceleration response spectra (Sa) of the synthetic waveform on the ground surface for four period ranges, , , and sec., by simply averaging Sa values. These period ranges are selected considering dynamic characteristics of structures in Japan. Calculation flow stated above is shown in Fig.1. Note that, 2D or 3D effects are not included in this calculation. 1 Dr. Eng., Geological Survey of Japan, Tsukuba, Japan, yoshimi.m@aist.go.jp 2 Dr. Sci., Geological Survey of Japan, Tsukuba, Japan, y-kuwahara@aist.go.jp 3 Dr. Eng., NEWJEC Inc, Osaka, Japan, yamadams@newjec.co.jp 4 NEWJEC Inc., Osaka, Japan, shigarakitd@newjec.co.jp 5 M. Eng., NEWJEC Inc., Osaka, Japan, hadakj@newjec.co.jp 1

III. Calculate response spectra and its average over a period range. Surface Ave. Sa Response spectra (Sa) Shallow 1D velocity model (by Aichi, Gifu, Mie pref.

2 III. Calculate response spectra and its average over a period range. Surface Ave. Sa Response spectra (Sa) Shallow 1D velocity model (by Aichi, Gifu, Mie pref.) Engineering basement (500 or 700 m/s) Deep velocity model of Chukyo area (Horikawa et al.,2008). (Fig.2) II. Calculate waveform on the ground surface with 1D linear response analysis using combined (deep + shallow) 1D velocity model at every site (250m grid point). Seismic basement (Bedrock) Path effect (attenuation) SMGA SMGA SMGA I. SGFM calculation of the waveform at the seismic basement considering SMGA and multi-hypocenter rupture propagation. Figure 1. Calculation flow Figure 2. Deep velocity structure model of Chukyo area (Horikawa et al., 2008). Distribution of depth to the seismic basement. 2

3) have been calculated with the methodology and the velocity model stated above. Each seismic source is considered as a point source, here.

3 M. Yoshimit, Y. Kuwahara, M. Yamada et al. 3 Point source analysis For validation, ground motions of six earthquakes occurred around the Chukyo area (list is shown in Table 1 and observed PGA distribution is shown in Fig. 3) have been calculated with the methodology and the velocity model stated above. Each seismic source is considered as a point source, here. We found the stress drop should be a value that defined for strong motion generation area, SMGA (Somerville et al., 1999), not for whole source area, in order to reproduce comparable spectral intensities with the observed values (Fig. 4). Otherwise, it results in underestimation. Overall, synthetic spectral intensities match well with the observation even at longer period ranges ( s and ) while 2D/3D effect is not included in the calculation. This may indicate dominance of the body wave in those ground motions, and at the same time, validity of the methodology and the velocity model we employ. Table 1. List of six earthuakes and their source parameters used for validation No. Event date Longitude Latitude Depth [km] Mo [Nm] Mw Source parameters (F-net) Rise time* [s] Stress drop** [MPa] 1 16 Mar E Oct E Sep E Sep E Sep E Aug E *Rise time = 2.03 x 10^-9 x Mo^(1/3), ** Stress drop for strong motion generation area Eq1. 16 Mar Eq2. 31 Oct Eq3. 5 Sep Eq4. 7 Sep Eq5. 8 Sep Eq6. 11 Aug Figure 3. Observed intensity distributions of earthquakes (by NIED) used for validation. Red star in each panel illustrates epicenter.

4 Syn.(cm /s/s) EQ EQ EQ EQ EQ EQ Reg. Syn.(cm /s/s) EQ EQ EQ EQ EQ EQ Reg O bs.(cm /s/s) s b= O bs.(cm /s/s) s b=0.732 Syn.(cm /s/s) EQ EQ EQ EQ EQ EQ Reg. Syn.(cm /s/s) EQ EQ EQ EQ EQ EQ Reg O bs.(cm /s/s) s b= O bs.(cm /s/s) s b=0.694 Figure 4. Comparison of the observed and synthesized averaged spectral intensities of the six earthquakes for four period ranges. Horizontal axes: observed values, vertical axes: values calculated from synthetic waves. Each color corresponds to different event. Seismic source modeling considering spatial variation of SMGA We calculate ground motions in the Chukyo area using source models based on that published by the Cabinet Office of Japanese Government; CAO (2012), shown in Fig. 5, considering additional spatial variation of the SMGA and hypocenter location. Because the source area of the anticipated huge earthquake along the Nankai trough expands over 600-km-wide, and that Chukyo area locates close to Tokai segment - one of the segments of the source area, it is expected that the spatial variation of the SMGA at distant source area can be negligible. We check how much the ground motions vary when spatial distribution of the SMGAs is changed. Fig. 6 shows Sa variation at three sites in the Chukyo area when SMGAs locations other than Tokai segment, namely Suruga, Muroto, Tosa, and Hyuga segments, are moved from the basic model by 20 km westward (W), eastward (E) and inland-ward (L), respectively. As a result, every Sa curve matches well with that of the basic model. This clearly shows that SMGA variation in a segment other than the Tokai segment is negligible for ground motions in Chukyo area. 4

M. Yoshimit, Y. Kuwahara, M. Yamada et al. 5 L E W Figure 5. Nankai megathrust source model ( basic case ) published by Cabinet Office of Japanese Government (2012).

5 M. Yoshimit, Y. Kuwahara, M. Yamada et al. 5 L E W Figure 5. Nankai megathrust source model ( basic case ) published by Cabinet Office of Japanese Government (2012). Green rectangles: SMGA, Red lines: segment boundaries, light-blue contours: depth to the Philippine Sea plate at 10 km interval starting from 10 km. Chukyo area is shown as a rectangle in bold blue boundaries. Acc.ResponseSpectrum (cm /s/s) Acc.ResponseSpectrum (cm /s/s) Period(s) Acc.ResponseSpectrum (cm /s/s) Basic Suruga-W Suruga-E Suruga-L Hyuga-W Hyuga-E Hyuga-L Tosa-W Tosa-E 10.0 Tosa-L Muroto-W Muroto-E Muroto-L Period(s) a) Loc. A. ( Nagoya city) b) Loc. B (Gifu city) Acc.ResponseSpectrum (cm /s/s) Basic Suruga-W Suruga-E Suruga-L Hyuga-W Hyuga-E Hyuga-L Tosa-W Tosa-E Tosa-L Muroto-W Muroto-E Muroto-L Period(s) c) Loc. C (Tsu-city) Period(s) Basic Suruga-W Suruga-E Suruga-L Hyuga-W Hyuga-E Hyuga-L Tosa-W Tosa-E Tosa-L Muroto-W Muroto-E Muroto-L Figure 6. Sa variation of three sites considering SMGA spatial variation other than Tokai segment (shown in Fig.5). Every curve matchs well with each other, showing SMGA variation other than the segment negligible. Basic Suruga-W Suruga-E Suruga-L Hyuga-W Hyuga-E Hyuga-L Tosa-W Tosa-E Tosa-L Muroto-W Muroto-E Muroto-L

6 Ground motion spectral intensity for earthquakes along the Nankai trough Ground motions on the Chukyo area are synthesized at 250 m grid for hypothetical Nankai earthquakes considering SMGA spatial distribution in Tokai segment based on the source model of the Cabinet Office of Japanese government: CAO (2012) (Fig. 5). In total, randomly distributed 100 patterns of SMGAs are created from the basic model, keeping shape and size of the SMGAs. Three cases of rupture propagation are assumed: from the western edge, eastern edge and the center of the whole source area. Spatial distributions of the mean value of the spectral intensities are shown in Fig. 7. Spectral intensities are larger around a bay (Ise Bay), where the seismic basement is deeper (Fig. 2), and along the eastern coast, where closer to the source and seismic basement is relatively deeper. For the period ranges shorter than 1.0 sec., spectral intensity is around or over 1,000 cm/s/s at some areas. In Fig. 8, spatial distribution of the lognormal standard deviation (SD) of the averaged spectral intensity is shown. The lognormal SD is about 0.15 for every period range and spatial variation is not remarkable in this area, indicating that SMGA spatial variation on Tokai segment affects evenly over Chukyo area. CAO (2012) has published seismic intensity (Japan Meteorological Agency; JMA scale) distributions for anticipated huge earthquake (Mw 9.0) along the Nankai trough. Here, we compare our results with those of CAO by means of seismic intensity (Fig. 9). Average value of seismic intensity by this study is larger than that of the basic case of CAO, while it is comparable or slightly smaller to the maximum value among four cases of CAO, where SMGA distribution are uniformly shifted toward eastward, westward, and inland. We also show spatial distribution of the lognormal standard deviation of the JMA seismic intensity. Similar to the case of the spectral intensities, standard deviation of seismic intensity is almost spatially constant (about 0.15). Methodology of strong ground motion calculation of CAO (2012) is similar to ours, while treatment of shallow structure is different: CAO (2012) employed empirical scalar amplification related with AVS30 while we employed 1D linear response analysis even for shallow structure. So, difference seen in Fig. 9 must be analyzed in careful manner. Summary Spectral intensity of strong ground motions have been predicted for Chukyo area during anticipated megathrust earthquake along Nankai trough considering spatial variation of SMGA. Source models are based on published one (CAO, 2012). SGFM is used in synthesizing waveforms at seismic basement. Amplification of the seismic wave is calculated with a 1D linear response analysis. 1D velocity structure model has been compiled using a deep velocity model (Horikawa et al., 2008) and shallow velocity models prepared by prefectures in the area. At first, the methodology and the velocity model are validated by reproducing spectral intensities of ground motions of six earthquakes occurred around the Chukyo area (M=5.5 to 7.2) assuming each seismic source as a point source. Then, effect of spatial variation of SMGA on each segment of the megathrust source model has been checked to be found that SMGA variation in a segment other than the Tokai segment is negligible for ground motions in Chukyo area. Ground motions on the Chukyo area have been synthesized using 100 source models with randomly distributed SMGAs on Tokai segment while shape and size of the SMGAs are kept. Spectral intensities roughly correlate with the depth to the seismic basement. Spatial distribution of the lognormal standard deviation (SD) is spatially constant in the area with a value about 0.15, indicating that SMGA spatial variation on Tokai segment affects evenly over the area. 6

M. Yoshimit, Y. Kuwahara, M. Yamada et al. 7 0.1-0.5s 0.5-1.0s 1.0-2.0s 2.0-5.0s Figure 7.

7 M. Yoshimit, Y. Kuwahara, M. Yamada et al s s s s Figure 7. Spatial distribution of the mean value of the averaged spectral intensity (cm/s/s) for hypothetical Nankai earthquake, the case of rupturing from the center.

0.1-0.5s 0.5-1.0s 1.0-2.0s 2.0-5.0s Figure 8.

8 s s s s Figure 8. Spatial distribution of the standard deviation value of the averaged spectral intensity for hypothetical Nankai earthquake, the case of rupturing from the center. 8

9 M. Yoshimit, Y. Kuwahara, M. Yamada et al. 9 This study (mean value among 100 cases) This study (lognormal standard deviation) Basic case of CAO (2012) Maximum value of CAO (2012) among four cases Figure 9. Comparison of the seismic intensity distribution Acknowledgement Ground motion data are provided by NIED (K-NET, Kik-net), Nagoya University, Aichi prefecture, Mie prefecture, Aichi Institute of Technology, Nagoya City, Toyohashi Institute of Technology. Shallow velocity models are provided by Aichi, Gifu and Mie prefectures. Generic Mapping Tool (GMT, Wessel, P., and W. H. F. Smith, 1998) is used in illustrating figures.

10 REFERENCES Aichi prefecture (2003) Report on damage estimation during Tokai, Tonankai earthquakes on Aichi prefecture - Damage estimation by scenario earthquakes, Earthquake subcommittee of disaster mitigation committee of Aichi prefecture, (in Japanese) Boore DM (1983) Stochastic Simulation of High-frequency Ground Motions Based on Seismological Models of the Radiated Spectra Bull. Seism. Soc. Am. 73, Brune JN (1970) Tectonic Stress and the Spectra of Seismic Shear Waves from Earthquakes J. Geophys. Res. 75, Brune JN (1971) Correction J. Geophys. Res. 76, Cabinet Office of Japanese Government (2012) Report of working group for the source models of Nankai megathrust earthquakes, (in Japanese) Gifu prefecture (2013) Report on damage estimation on Gifu prefecture during huge earthquakes along Nankai trough, (in Japanese) Horikawa H, Yoshimi M, Sekiguchi H, Yoshida K, Sugiyama Y, Satake K, Fukuwa N, Suzuki H, Matsuyama H, Liu Y, Takizawa F (2008) A three-dimensional subsurface structure model of the Chukyo area, central Japan, Annual Report on Active Fault and Paleoearthquake Researches, 8, Mie prefecture (2006) Report on damage estimation for disaster mitigation measures in Mie prefecture (in Japanese) Sato T and Tatsumi Y (2002) Source, Path, and Site Effects for Crustal and Subduction Earthquakes Inferred from Strong Motion Records in Japan, Journal of Structural and Construction Engineering (AIJ) 556, Somerville P.G, Irikura K, Graves R, Sawada S, Wald D, Abrahamson N, Iwasaki Y, Kagawa T, Smith N, Kowada A (1999) Characterizing Crustal Earthquake Slip Models for the Prediction of Strong Ground Motion, Seismological Research Letters, 70, Wessel P and Smith WHF (1998) New Improved version of the Generic Mapping Tools released, EOS Trans. AGU, 79,

Source modeling of hypothetical Tokai-Tonankai-Nankai, Japan, earthquake and strong ground motion simulation using the empirical Green s functions

Source modeling of hypothetical Tokai-Tonankai-Nankai, Japan, earthquake and strong ground motion simulation using the empirical Green s functions Y. Ishii & K. Dan Ohsaki Research Institute, Inc., Tokyo