Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

Home , Matsuyama

Paper: Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

Shigeki Senna∗,†, Atsushi Wakai∗, Haruhiko Suzuki∗∗, Atsushi Yatagai∗∗, Hisanori Matsuyama∗∗, and Hiroyuki Fujiwara∗

∗National Research Institute for Earth Science and Disaster Resilience 3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan †Corresponding author, E-mail: [email protected] ∗∗OYO Corporation, Ibaraki, Japan [Received April 2, 2018; accepted August 6, 2018]

During the 2016 Kumamoto earthquakes, two earth- lization System Development” of “Strengthening of Re- quakes of seismic intensity 7 were observed in Mashiki silient Disaster Prevention and Disaster Mitigation Func- Town, the foreshock (MJMA 6.5) of April 14 and the tion,” the Cross-ministerial Strategic Innovation Promo- main shock (MJMA 7.3) of April 16, resulting in sig- tion Program (SIP) of the Council for Science, Technol- nificant damage to structures near the fault. The dis- ogy and Innovation. Using a similar creation method, we tribution of damage of houses and other buildings [1] have been developing an integrated ground model from showed a tendency in which damage was concentrated the seismic bedrock to the surface of the ground of the in areas near the surface earthquake fault where the Kanto and Tokai regions [2]. This article reports the cre- main shock presumably occurred. However, there ation state and its verification result of a shallow and deep were locations with slight damage even though they integrated ground model of the affected area, additionally were immediately above the fault and locations with conducted as part of a SIP project in response to the 2016 a relatively significant damage even though they were Kumamoto earthquakes. far from the fault. These phenomena are highly likely to be a result of soil structure. First, we built an initial geologic model by collecting boring data in areas 2. Data Collection and Analysis of the Kumamoto plain near the fault where damage was severe. Next, we observed microtremors, collected We collected boring and other geological survey data earthquake observational records, and adjusted the as well as microtremor observation and previous data of layer thickness and S-wave velocity of the initial geo- mainly minimal and irregular microtremor arrays. We logic model. Finally, we built a shallow and deep in- collected approximately 5900 boring data points from tegrated ground model, compared it to the building the Kyushu Geotechnical Information Shared Database damage distribution, and discussed the implications. (First and Second editions) [3, 4]; Kumamoto Prefecture, Cities, Towns, and Villages; Geotechnical Engineering Map around Kumamoto City [5]; and Urgent Open Web- site on Boring Log for Reconstruction Assistance from Keywords: S-wave velocity structure model, mi- the 2016 Kumamoto Earthquake [6]. For the earthquake crotremor, strong motion evaluation, active fault, Ku- observational record, we collected seismic waveform data mamoto plain from seismic intensity meters of the Kumamoto Prefec- ture. For microtremor observations, we conducted minimal array observation mainly up to engineering bedrock 1. Introduction (approximately Vs400) and four-point arrays of a radius of 800 m (400 m, 200 m, 100 m, 50 m, and 25 m) up to the The National Research Institute for Earth Science and seismic bedrock (approximately Vs3000). For the mini- Disaster Resilience of Japan (NIED) has continuously mal array observation, we conducted a combination of a developed a soil structure model for strong motion pre- “four-point minimal array” of the array radius of 60 cm diction using geological structure data extracted from and a “three-point irregular array” of a side of from 4 m boring data and S-wave velocity structure data obtained to 10 m or more (refer to Fig. 1). mainly from microtremor observations. We created a Those observations were conducted near earthquake ground model in Section 5. “Real-Time Damage Esti- observational points (K-NET, KiK-net, local government mation, Disaster Information Collection, Analysis, Uti- seismic intensity meters, and the Japan Meteorological Agency) and on public roads. We conducted observations

Journal of Disaster Research Vol.13 No.5, 2018 917 Senna, S. et al.

Fig. 3. Distribution map of the microtremor observational Fig. 1. Conceptual diagram of the miniature and irregular points. seismic arrays.

Table 1. Physical parameters of initial model.

Vp [m/s] Vs [m/s] ρ [g/cm3] 1 300 100 1.40 2 500 150 1.50 3 800 200 1.60 4 1200 250 1.70 5 1400 300 1.80 6 1600 400 1.85 7 1700 500 1.90 8 2100 600 1.90 9 2400 900 2.05 10 2600 1100 2.15 11 4000 2100 2.40 12 5000 2700 2.50 Fig. 2. Distribution map of the miniature array observational points (•). depth conversion (SPM) [11] of the dispersion curve and an inverse analysis ([12, 13]). However, we conducted an analysis of mainly the deep soil structure. As an in- at 26 points using arrays within intervals of approximately verse analysis method, we executed a simultaneous in- 5 km for 1 to 2 h at each of the points. We conducted verse analysis of the phase velocity dispersion curve ob- observations of a minimal array with intervals of approx- tained from the analysis and the H/V spectral ratio of imately 1 km (within intervals of 100 to 500 m around the microtremor. There was not a large difference from Mashiki Town) at approximately 500 points (please refer the R/V spectral ratio of the local government seismo- to Figs. 2 and 3). graph and the strong motion observational points, and the The observational devices used were an integrated type H/V spectral ratio of the microtremor was stably calcu- of constant microtremor observational device JU410 [7] lated. Hence, the H/V spectral ratio of the microtremor for the minimal array and a JU410 and VSE15D6 (ve- was used for the inverse analysis. We used the genetic locity meter, Tokyo Sokushin Co., Ltd.) for the ar- algorithm of [14]. The velocity value was fixed with re- ray. The sampling frequency was 200 Hz. For the mi- spect to the physical properties (Table 1) of the velocity crotremor analysis of this discussion, we evaluated a one- layer of the initial model described later in this article, dimensional S-wave velocity structure using a shallow and the layer thickness varied. The inverse analysis spec- ground survey method and similar approaches (for exam- ifications are listed in Table 2. Considering the analysis ple, [8] and [9]) that have been proposed and refined in results of the surrounding observational points and the ge- recent research. For analysis of the minimal and irregular ological state of the observational points, we changed the array, we calculated the horizontal/vertical (H/V) spectral setting of the layer thickness to the result obtained via the ratio and the phase velocity using a “cloud microtremor inverse analysis. Then, we conducted an inverse analy- observation system” [10] and similar approaches, and cal- sis again, and adopted a one-dimensional structure model culated the S-wave velocity structure by conducting a with a minimum residual. As an example of the adopted

918 Journal of Disaster Research Vol.13 No.5, 2018 Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain City and its surrounding area (an area of approximately Table 2. Inversion parameters. 20 km north–south and approximately 30 km east–west). In addition, to examine in further detail the area near the Inverion parameter Thickness (Vs of layers are fixed) center of Mashiki Town, in which the earthquake-caused Phasevelocity (Fundamental damage was concentrated, (an area approximately 5 km × Thinthetic mode) calcuclation H/V ratio (Superposed Rayleigh approximately 2 km), we created a detailed ground model wave mode [ 0 to 4 th order]) of grid of approximately 50 m on each side by dividing × Inverion algorithm Genetic algorithm the 250-m grid into 5 5 squares. Population 100 Generation 100 3.1. Modeling of Initial Shallow Subsurface Struc- Crossover probability 0.7 tures Mutation probability 0.01 Number of initial ran- The Aso-4 pyroclastic flow deposit (pumiceous pyro- 12 dom values clastic flow) erupted from the Aso Caldera some 90 thou- sand years ago and is distributed in a wide area from the plateau area to the plain area around Kumamoto City. (a)㻌 (c) This deposit is widespread as a layer in the geological structure. Our survey found that it also shows a stable value (Vs250 to 400 m/s) in its elastic wave velocity structure. In light of this finding, we classified the layer structure as the following from 1 to 4 (described from the upper to lower) at the boring points of the plain area and the plateau area, also with reference to the standard geologic stratigraphy [15] of the previous data based on facies and N value. This classification generally corresponds well to the S-wave velocity structure of the microtremor exploration: 1. Alluvium: Comprises a fluvial sand layer / Ariake clay layer (marine deposit): The N value is mostly 5 or less, (b)㻌 and is high in sandy areas. The Vs is approximately 100 to 200 m/s.

2. Shimabara Bay Layer: Comprises a sand gravel layer, Fig. 4. Comparison between observed and synthetic data at silt layer, and peat layer. The Vs is approximately 200 KMMA015. (a) Phase velocity of Rayleigh waves for mi- to 300 m/s. crotremoros. Circle and red line indicate synthetic data and observed data, respectively. (b) H/V spectral ratio for mi- 3. Terrace gravel layer: Comprises a terrace surface crotremoros. Circle and red line indicate synthetic data and termed the Hotakubo Surface and Takuma Surface. observed data, respectively. (c) S-wave velocity proﬁle esti- The N value is mostly 50 or more. The Vs is approxi- mated by joint inversion. mately 250 to 300 m/s.

4. Aso-4 pyroclastic flow deposit: The N value is 50 or model, the result of the observation point (KMMA015) more in a fresh area. A layer lower than the Aso-4 with its array center on the premises of the Kumamoto pyroclastic flow deposit has a Vs of approximately Prefectural Government is shown in Fig. 4.Asshown, 500 m/s or more. This layer or the deeper later was because we conducted the simultaneous inverse analysis modeled as deep ground. of the phase velocity and the H/V spectra, there may be a case in which the observational value and a theoretical As for data interpolation, regarding the plain, plateau, value of the phase velocity are not necessarily consistent and pyroclastic flow plateau, we modified the previous with each other when the peak periods of the H/V spectra microtopographic classification [16] in such a manner that are brought together. the deposit surface of the Aso-4 pyroclastic flow, in particular, is clarified in accordance with the actual geologic distribution, interpolating the layer structure of the bor- 3. Modeling Method of Subsurface Velocity ing point for each of the microtopographic regions using Structures a Kriging method [17] and creating a surface elastic wave velocity structure. For layer structure classification of the The ground model was created in units of a 250-m grid mountain, hill, and volcano, we classified a weathered (one-fourth regional grid: The Statistics Bureau, Ministry area with an N value of less than 50 based on boring data. of Internal Affairs and Communications) for Kumamoto Because the number of data is small, we uniformly set the

Journal of Disaster Research Vol.13 No.5, 2018 919 Senna, S. et al.

thickness of a weathered area, and also set Vs to a constant value (200 to 250 m/s) for each geographic classiﬁ- cation. The upper Vs350 m/s layer of the velocity structure of the shallow ground created in this manner is set as a boundary surface and is joined with the deep ground model described later in this article into an “initial shallow and deep integrated ground model.” As presented in Section 2, simultaneous inverse analysis was conducted with the S-wave velocity of each layer being ﬁxed. In the initial model, a 12-layer structure was assumed; however, there is a case in which the layer thickness becomes nearly 0 m via the inverse analysis as the layer has been annihilated. Because the deep ground model was created in a 1-km grid, we downsized it to a grid size of the shallow ground model (250-m grid) by interpolation before joining. In addition, we built a ground model of a 50-m grid in further detail around Mashiki Town. Because the number of the previous boring data is small and the excavation length is not particularly long, we modeled using data of the microtremor exploration (minimal and irregular array) conducted at intervals of a few hundred meters and boring data [18, 19] that were newly excavated following the earthquake and for which a PS well logging was conducted. The creation method was the same as the 250-m grid model but we also used microtremor observational data obtained for the volcano (refer to Fig. 5).

3.2. Modeling of Deep Subsurface Structures For the main area of Kumamoto City and its neighboring area, to use ground motion calculation via a finite difference method, based on the previous ground model (J-SHIS model) of the NIED, we created a deep soil structure model (0.25-km grid) from the seismic bedrock to the engineering bedrock. Outside of the created range, the model was joined to the J-SHIS model. At that time, we provided a buffer zone to adjust the created model. Fig. 5. Estimated structures as a key layer for Vs200, Vs350 The data we used were the microtremor observational data and Vs500 layer on surface boundary of pyroclastic flow de- obtained as described in Sections 2 and 3, the minimal posits such as Aso-4 and Aso-2 to Aso-3. array microtremor observational data that was separately recorded, and the previous gravity data (data of the “gravity database (GALILEO)” of the National Institute of Ad- vanced Industrial Science and Technology). The creation vational value of the extraction gravity of the resid- procedure of the soil structure model is as follows: ual gravity value, a band pass filter was applied to Bouguer anomaly data with an assumed density of 1. Creation of a velocity structure using the microtremor ρ = 2.3g/cm3. During the processing of this time, we exploration result created residual gravity data by subtracting from the For the observational range of a microtremor array, us- Bouguer anomaly data a gravity value upwardly con- ing a one-dimensional velocity structure immediately nected at a connection altitude of 1 km and a gravity below each observation point obtained by the analysis value upwardly connected at a connection altitude of of the observational result, we interpolated the bound- 3km. ary surface depth of each velocity layer in a planar 3. Examination of the correlation between the residual manner, and created the surface structure of the ve- gravity and velocity layer upper depth locity layer. We employed the Kriging method as an Using the analysis result from 1, we examined the interpolation method. correlation between the upward connection residual 2. Creation of residual gravity data of gravity under the observational point and the up- To extract the structure of the sedimentary layer shal- per depth of each velocity layer of the observational lower than the seismic bedrock included in the obser- point in the plain area. As a result, we found a cor-

920 Journal of Disaster Research Vol.13 No.5, 2018 Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

Alldata DataintheKumamotoplain UpperdepthestimatedinKumamotoBay RegressionEq.byexponentialfunc. 1200 y=181.49eͲ0.436x

layer[m] 1000 R²=0.7836 800

600 Vs1100m/s of 400 depth 200

Upper 0 Ͳ4 Ͳ20 2 Residualgravity[mGal] Fig. 6. Correlation between residual gravity and upper depth 'HSWK P of Vs1100-m/s layer. Blue and red circles indicate data in the Kumamoto plain and all data, respectively. Black and orange Fig. 7. Contour map of upper depth of Vs1100-m/s layer. line indicate regression equation by exponential function and The outside of the dotted line is the area using the initial estimated depth used in Kumamoto Bay area, respectively. model (J-SHIS Model). The inside of the dotted line is the area using microtremor array measurement results.

relation between the upward connection residual value of gravity and the upper depth of each of the velocity layers of Vs900 m/s, Vs1100 m/s, and Vs2100 m/s, respectively The upper depth of the three layers that have the correlation was estimated using an exponential function from the distribution of the residual gravity and modeled. During this operation, we estimated the area of the residual gravity of −2 mGal or less. As an example, a correlation between residual gravity and the upper depth of the Vs1100-m/s layer is shown in Fig. 6. In addition, at the upper depth of the Vs500-m/s, Vs650-m/s, and Vs2700-m/s layers, which all have a low correlation, we provided a depth estimated from observation by 0.5 mGal for the area of −2 mGal or less.

4. Connection of the smoothing and the ground model of the neighboring area × We provided a movement average ﬁlter of 4 km 4km Fig. 8. Upper elevation of Vs350-m/s layer (•: Distribution to the created soil structure model. The outside of the map of miniature array observation points). range of the created model was provided with a buffer zone approximately 3 km in width. In this portion, the depth of the velocity layer boundary was adjusted and joined to the outside J-SHIS model. Tsuboi River. The deepest part of the upper Vs2700-m/s layer in the plain area is at a depth of 1500 m or more, and the deepest part of the upper Vs2100-m/s layer cor- 4. Characteristics of Subsurface Velocity responding to the upper Cretaceous Mifune Group is at a Structure Models depth of approximately 1000 m. For the shallow ground model, the velocity layers Among the shallow and deep integrated ground models (Fig. 8) are set; for example, each show a structure of created, for the deep soil structure, the Vs1100-m/s layer deepening towards the Ariake Sea from the Aso Caldera. upper depth is shown in Fig. 7 as an example. Either ve- In the plateau area, there is a strong tendency for the dis- locity layer shows a structure of deepening in the plain tribution to reach a generally stable depth and deepen to- area, and deepens in the shape of a graben in a northeast wards the sea side in the plain area. This is thought to direction along the Kiyama River and northward along the be a structure regulated by the distribution of the deposit

Journal of Disaster Research Vol.13 No.5, 2018 921 Senna, S. et al.

created ground model indicates that in the structural damage concentration area nearly immediately above the fault of Mashiki Town in particular, the proportion of “totally collapsed” structures is large in an area that shows 1.75 Hz to 3 Hz and there is a relatively small number of damage in an area of less than 1.75 Hz. In addition, the AVS30 is from 100 to 180 m/s in the area of less than 1.75 Hz, and it is 180 to 270 m/s in the area that is equal to or greater than 1.75 Hz and less than 3.0 Hz. This indicates that while the linear amplification factor increase in the former, actual building damage increases in the latter (please refer to Figs. 11 and 12). This result suggests the possibility that on the soft ground of the former, at the time of the strong motion of the foreshock and the main shock that recorded a seismic intensity of 7, non-linear behavior increased, the dominant period lengthened, and the amplitude decreased. The amplification factor for each period from the engi- Fig. 9. AVS30 m/s of velocity structure model (•: Distribu- tion map of miniature array observation points). neering bedrock (Vs400 m/s) using the one-dimensional multi-reflection method by the ground model shows a similar tendency toward a dominant frequency (period characteristics) found in the H/V spectral ratio, and appro- priate modeling was confirmed (please refer to Figs. 13 and 14).

5. Validation of S-wave Velocity Models

Figure 15 shows a comparison between the observational site amplification characteristics to the theoretical amplification characteristics obtained using the estimated S-wave velocity structure. In KMM006 and TOMIAI, the theoretical amplification characteristics are underes- timated compared to the observational site amplification characteristics but the peak frequencies are well in accordance with each other. However, in MIFUNE, both the amplitudes and the peak frequencies are well in accordance. The three aforementioned points occur at the end part of the plain. However, because of the differ- Fig. 10. Upper elevation of Vs350-m/s layer at Mashiki ence in the structure immediately below the observational with detailed velocity structure model (•: Distribution map point and the soil structure of the neighboring areas, they of miniature array observation points). were thought to have been divided into points that can be explained by the one-dimensional structure and points difficult to explain unless a three-dimension structure is surface of the Aso-4 pyroclastic flow. In addition, it deep- considered. In the future, it is necessary to verify the ens in from the northeast to the west along the Kiyama validity of the ground model using small- and medium- River, expressing the structure of “the Kiyama-Kashima sized earthquakes using the finite difference method with graben” [15]. The AVS30 m/s distribution created from a three-dimensional structure. We extracted the ground the velocity structure model is shown in Fig. 9. model at the strong motion observational point from In addition, in a detailed model (engineering bedrock the aforementioned three-dimensional ground model and upper depth as shown in Fig. 10) around Mashiki Town, compared the observational S-wave amplification charac- the graben-like structure along the Kiyama River is teristics to the theoretical amplification characteristics via clearer. The central area of Mashiki Town in which dam- the one-dimensional structure. To set a constraint con- age was concentrated constitutes a gentle slope that gen- dition in the spectral inversion at the time of estimating tly extends downward from the primary deposit surface of the observational S-wave amplification characteristics, we the Aso-4 pyroclastic flow of north side to a lowland along conducted an identification analysis of the soil structure the Kiyama River. For this area, it is clear that the veloc- using the spectral ratio of the ground motion of the sur- ity upper layer corresponding to the engineering bedrock face of the ground and the borehole at the KiK-net obser- deepens. In addition, a response analysis result using the vational point where a velocity layer corresponding to the

922 Journal of Disaster Research Vol.13 No.5, 2018 Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

Mashiki town office

Surface fault trace (Shirahama et al.(2016))

Fig. 11. Distribution map of peak frequencies at Mashiki Fig. 13. One-dimensional S-wave ampliﬁcation factor from and building damage [1] (the dotted line indicates the con- basement (Vs400 m/s) to surface at period 0.5 s (the dotted nection of assumed fault positions in Shirahama et al. [20]). line indicates the connection of assumed fault positions in Shirahama et al. [20]).

Fig. 11. Distribution map of peak frequencies at Mashiki and building damage [1].㸦The dotted line indicates the connection of assumed fault positions in Shirahama et al.(2016)[19]㸧㻌

Fig. 12. Distribution map of AVS30 m/s of velocity structure model at Mashiki and building damage [1] (the dotted Fig. 14. One-dimensional S-wave ampliﬁcation factor from line indicates the connection of assumed fault positions in basement(Vs400 m/s) to surface at period 1 s (the dotted line Shirahama et al. [20]). indicates the connection of assumed fault positions in Shira- hama et al. [20]).

seismic bedrock was conﬁrmed. The observational points used for the spectral inver- earthquakes of Mj4.0 or greater and that occurred at 10 km sion analysis are K-NET points in the Kyushu region, or deeper (Fig. 16). KiK-net observational points, and Kumamoto Prefecture To separate the source, propagation path, and site char- seismic intensity meter observational points. The earth- acteristics, the ampliﬁcation characteristics of the points quakes used for the analysis were the subduction zone where layers of approximately 3 km/s of the S-wave ve- earthquakes of Mj4.0 or greater and 40 km or more in locity are found at the KiK-net observational points were depth that occurred prior to March 2016 and the inland set as a constraint condition (red circles in Fig. 16). We

Journal of Disaster Research Vol.13 No.5, 2018 923 Senna, S. et al.

Fig. 16. Location of epicenters (starts) and strong motion observation points (circles) used for spectral inversion method. Colored circles indicate reference site for spectral inversion method. KMM006㻌

䡏䠅 Vs(km/ MIFUNE㻌 01234 0 100 20 SAGH04 TOMIAI㻌 Bor SAGH04 10 40

Spectral Rao 1 Fig. 15. 80 Comparison between observed (black) and syn- obs Depth(m) thetic (red) site ampliﬁcation. cal 100 0.1 0.1 1 10 120 Frequency(Hz) 䡏䠅 140

calculated the spectral ratio of the borehole and the sur- 160 face of the ground of the KiK-net observational points, conducted an identification analysis of the S-wave veloc- Fig. 17. Comparison between observed (black) and syn- ity structure, and set it as a constraint condition. Fig. 17 thetic (red) spectral ratio at SAGH04. shows a comparison of the observational record of the spectral ratio of the S-wave part of the surface of the ground and the borehole record at SAGH04 as well as the theoretical calculation result. For the spectral inversion, light blue represent the site amplification characteristics we referred to [21]. Propagation path characteristics P( f ) by [22]. Because [22] used the surface wave part of the were expressed as follows in terms of inland earthquakes observational data, the amplitude increases on the low- and subduction zone earthquakes: frequency side in particular but the peak frequencies are well in accordance with each other. −π fX P( f )= 1 X exp Qβ (Subduction zone) (1) 1 −π fX 6. Issues and Plans = exp (Inland), (2) min(80,X)∗ X Qβ For structural damage at the time of the earthquake in where f is the frequency [Hz]; X is the source distance Kumamoto City and Mashiki Town, in addition to the [km]; and β is the S-wave velocity of the propagation ground model (250-m grid and 50-m grid) created for path, which was set to 3.4 km/s for the inland and 4.0 km/s this study, we are planning to also examine the seismic for the subduction zone earthquakes [21]. source in consideration of an active fault that is assumed Figure 18 shows the site amplification characteristics to lie immediately below the damage concentration area separated from the observational record. The lines in of Mashiki Town, and attempt to reproduce the damage

924 Journal of Disaster Research Vol.13 No.5, 2018 Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

[8] I. Cho, S. Senna, and H. Fujiwara, “Miniature array analysis of microtremors,” Geophysics, Vol.78, KS13–KS23, 6. Issues and plans doi:10.1190/geo2012-0248.1, 2013. For structural damage at the time of the earthquake [9] S. Senna,“A Method for Setting Engineering Bedrock Using Records of Miniature Array Microtremor Observation,” 16th Eu- in Kumamoto City and Mashiki Town, in addition to ropean Conf. on Earthquake Engineering, No.678, 2018. the ground model (250-m grid and 50-m grid) created [10] I. Cho and S. Senna, “Constructing a system to explore shallow velocity structures using a miniature microtremor array – Accumu- for this study, we are planning to also examine the lating and utilizing large microtremor datasets –,” Synthesiology, Vol.9, No.2, pp. 86-96, 2016. 䡏䠅 seismic source in consideration of an active fault that is assumed to lie immediately below the damage [11] T. Satoh, C. J. Poran, K. Yamagata, and J. A. Rodriguez, “Soil pro- filing by spectral analysis of surface waves,” Proc. 2nd Int. Conf. concentration area of Mashiki Town, and attempt to on Recent Advances in Geotechnical Earth-quake Engineering and reproduce the damage aspect. In addition, in future Soil Dynamics, Vol.2, pp. 1429-1434, 1991. [12] P. C. Pelekis and G. A. Athanasopoulos, “An overview of surface countermeasures against earthquake disasters, strong wave methods and a reliabil-ity study of a simplified inversion tech- motion prediction very near an inland active fault will nique,” Soil Dyn. Earthquake Eng., Vol.31, pp. 1654-1668, 2011. [13] H. Arai and K. Tokimatsu, “S-Wave velocity pro-filing by inversion be an essential request, and the examination and the of microtremor H/V Spectrum,” Bull. Seismol. Soc. Am., Vol.94, creation method of the ground model conducted for pp. 53-63, 2004. [14] H. Yamanaka and H. Ishida, “Application of genetic algorithms to Fig. 18. an inversion of surface-wave dispersion data,” Bulletin of the Seis- Site amplification spectrum (black lines). Blue mological Society of America, Vol.86, No.2, pp. 436-444, 1996. lines indicate site amplification spectrum [21]. [15] K. Watanabe, “Geology in the western area of Aso Caldera,” Bul- letin of Facalty of Education, Kumamoto University, 1972. [16] K. Wakamatsu and M. Matsuoka, “Development a Geomorphologic-based 7.5-second Site-condition Map for aspect. In addition, in future countermeasures against Nationwide Hazard Zon-ings,” Bulletin of Institute of Science and Technology, Kanto Gakuin University, No.40, pp. 31-42, 2012. earthquake disasters, strong motion prediction very near [17] N. A. C. Cressie, “Statistics for Spatial Data,” John Wiley and Sons an inland active fault will be an essential request, and the Inc., New York, p. 928, 1993. examination and the creation method of the ground model [18] M. Yoshimi et al., “Borehole exploration in heavily damaged area of the 2016 Kumamoto Earthquake, Mashiki town, Kumamoto,” JSAF conducted for this study will be a prototype. We are plan- Annual Meeting Proc., 2016 (in Japanese). ning in the future to make a similar attempt for other ac- [19] City Bureau of MLIT, “Interim report on safety measures for the ur- ban area reconstruction in Mashiki town from the 2016 Kumamoto tive fault areas, accumulate data, and verify the validity of earthquake,” Dec. 22, 2016 (in Japanese). the ground model created in this manner. [20] Y. Shirahama, et al, “Characteristics of the sur-face ruptures as- sociated with the 2016 Kumamoto earthquake sequence,” Cen- tral Kyushu, Japan, Earth Planets Space, Vol.68, No.191, doi:10.1186/s40623-016-0559-1, 2016. Acknowledgements [21] S. Kataoka et al., “Attnuation relationships of ground motion inten- This research was supported by the “Strengthening of Resilient sity using short period level as variable,” J. JSCE A, Vol.62, No.4, pp. 740-757, 2006 (in Japanese). Disaster Prevention and Disaster Mitigation Function” (Manage- [22] A. Nozu and T. Nagao, “Site amplification factors for strong-motion ment Entity: The Japan Science and Technology Agency), the SIP sites in JAPAN based on spectral inversion technique,” Technical of the Council for Science, Technology and Innovation. During note of the port and airport presearch institute, Vol.1112, p. 56, 2005 (in Japanese). our microtremor observational survey of the Kumamoto plain, we received cooperation from Mr. Nobuyuki Morikawa, Mr. Takahiro Maeda, Mr. Shohei Naito, Ms. Asako Iwaki, Mr. Shinichi Kawai, Mr. Hiroki Azuma, and Mr. Ryuji Yamada of the National Re- search Institute for Earth Science and Disaster Resilience of Japan; Ms. Kaoru Jin of the Oyo Corporation; and Mr. Ikuo Cho of the National Institute of Advanced Industrial Science and Tech- nology. We express our gratitude to all of them.

References: [1] N. Monma, et al., “Relation between Japanese intensity factor and building damage in Mashiki town due to the 2016 Kumamoto earthquake,” Proc. of JAEE Annual Meeting, O1-2, 2016 (in Japanese). [2] S. Senna, A. Wakai, K. Jin, T. Maeda, K. Kimura, H. Matsuyama, and H. Fujiwara, “Modeling of the subsurface structure from the seismic bedrock to the ground surface for a broadband strong motion evaluation in Kanto area,” JpGU2016 SSS25-12, 2016. [3] Kyushu Branch of Japanese Geotechnical Society, “Kyushu geotechnical information shared database,” 1st edition, 2005 (in Japanese). [4] Kyushu Branch of Japanese Geotechnical Society, “Kyushu geotechnical information shared database,” 2nd edition, 2013 (in Japanese). [5] Kumamoto Geological Survey Association, “Geotechnical engineering map around Kumamoto city,” 2003 (in Japanese). [6] Kumamoto Geological Survey Association, “Urgent open website on boring log for reconstruction assistance from the 2016 Ku- mamoto Earthquake,” 2016 (in Japanese). [7] Hakusan Corporation, Microtremor observation device JU410, https://www.hakusan.co.jp/products/keisoku/ju410.html (in Japanese) [accessed April 1, 2017]

Journal of Disaster Research Vol.13 No.5, 2018 925 Senna, S. et al.

Name: Name: Shigeki Senna Haruhiko Suzuki

Afﬁliation: Afﬁliation: Principal Research Fellow, Department of In- Group Manager, Department of Earthquake Re- tegrated Research on Disaster Prevention, Na- search on Disaster Prevention, Earthquake Engi- tional Research Institute for Science and Disaster neering Center, OYO Corporation Resilience (NIED)

Address: Address: 3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan 43 Miyukigaoka, Tsukuba, Ibaraki 305-0841, Japan Brief Career: Brief Career: 1994-2001 Chef Engineer, Dia Consultants Corporation 1997-2002 Exploration Engineering Center, OYO Corporation 2001-2003 Chef Engineer, Mitsubishi Space Software Corporation 2002- Earthquake Engineering Center, OYO Corporation 2003-2014 Researcher, National Research Institute for Earth Science and Selected Publications: Disaster Prevention (NIED) • K. Hayashi and H. Suzuki, “CMP cross-correlation analysis of 2014- Principal Research Fellow, National Research Institute for Earth multi-channel surface-wave data,” Exploration Geophysics, Vol.35, Science and Disaster Resilience (NIED) pp. 7-13, 2004. Selected Publications: Academic Societies & Scientiﬁc Organizations: • “Liquefaction during the Kumamoto Earthquakes on April 14and 16, • Seismological Society of Japan (SSJ) 2016,” Lowland Technology Int., Vol.19, No.3, pp. 177-188, 2017. • Architectural Institute of Japan (AIJ) • “Liquefaction Occurrence Ratio Estimation Considering Strong • Society of Exploration Geophysicists of Japan (SEGJ) GroundMotion Duration and Regional Characteristics,” J. of Japan Association for Earthquake Engineering, Vol.18, No.2, pp. 82-94, 2018 (in Japanese). Academic Societies & Scientiﬁc Organizations: • Seismological Society of Japan (SSJ) • Japan Association for Earthquake Engineering (JAEE) Name: • Society of Exploration Geophysicists of Japan (SEGJ) Atsushi Yatagai

Afﬁliation: Department of Earthquake Research on Disas- ter Prevention, Earthquake Engineering Center, OYO Corporation Name: Atsushi Wakai

Affiliation: Address: Researcher, Department of Integrated Research 43 Miyukigaoka, Tsukuba, Ibaraki 305-0841, Japane on Disaster Prevention, National Research Insti- tute for Science and Disaster Resilience (NIED) Brief Career: 2015- Earthquake Engineering Center, OYO Corporation Selected Publications: • A. Yatagai, T. Hida, S. Tamura, and M. Nagano, “Effects of pile damage and seismic property on response of base-isolated structure during soil Address: liquefaction,” AIJ J. Technol. Des., Vol.21, No.49, pp. 995-1000, 2015. 3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan Academic Societies & Scientific Organizations: Brief Career: • Japan Geoscience Union (JpGU) 2008-2014 Researcher, Port and Airport Research Institute (PARI) • Architectural Institute of Japan (AIJ) 2014-2015 Newjec Inc. 2015- Researcher, National Research Institute for Earth Science and Disaster Resilience (NIED) Selected Publications: • “Simulation of Strong Ground Motion in Kanto Plain during the 2011 Off the Pacific Coast of Tohoku Earthquake, Japan / Application of Pseudo Point-Source Model,” J. of JAEE, Vol.16, No.11, pp. 41-61, 2016. Academic Societies & Scientific Organizations: • Seismological Society of Japan (SSJ) • Japan Society of Civil Engineering (JSCE) • Japanese Geotechnical Society (JGS)

926 Journal of Disaster Research Vol.13 No.5, 2018 Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain

Name: Hisanori Matsuyama

Afﬁliation: Professional Engineer, Engineering Headquar- ter, OYO Corporation

Address: 43 Miyukigaoka, Tsukuba, Ibaraki 305-0841, Japan Brief Career: 1982-2005 Engineering Geologist, OYO Corporation 2005-2016 Earthquake Engineering Center, OYO Corporation 2016- Engineering Headquarter, OYO Corporation Selected Publications: • “Creation of elastic wave velocity structure model and by Boring Data and Microtremor Exploration Data for strong ground motion prediction at Kumamoto Plain and the center of Masashiro-machi,” Abstract, 0881, 53rd Japan National Conf. on Geotechnical Engineering, 2017. • “Typing of ground by Phase velocity curve of microtremor survey for strong ground motion prediction,” Abstract, 0995, 54th Japan National Conf. on Geotechnical Engineering, 2018. Academic Societies & Scientiﬁc Organizations: • Japanese Geotechnical Society (JGS) • Japan Society of Engineering Geology (JSEG)

Name: Hiroyuki Fujiwara

Afﬁliation: Director, Research Center for Reinforcement of Resilient Function, National Research Institute for Earth Science and Disaster Resilience

Address: 3-1 Tennodai, Tsukuba, ibaraki 305-0006, Japan Brief Career: 1989- Researcher, NIED 2001- Head of Strong Motion Observation Network Laboratory, NIED 2006- Project Director, Disaster Prevention System Research Center, NIED 2011- Director, Social System Research Department, NIED 2014- Director, Research Center for Reinforcement of Resilient Function Academic Societies & Scientiﬁc Organizations: • Seismological Society of Japan (SSJ) • Japan Association for Earthquake Engineering (JAEE)

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