Modeling of the Subsurface Structure from the Seismic Bedrock to the Ground Surface for a Broadband Strong Motion Evaluation in Kumamoto Plain 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 ini- tial 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 mini- mal 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 observa- tional 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 struc- ture. In light of this finding, we classified the layer struc- ture as the following from 1 to 4 (described from the up- per 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 explo- ration: 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.