Abstract Data Method Results Conclusions References

Empirical characterization of ground motion processes in Japan, and comparison to other regions Department of Earth Sciences

Ruins of San Francisco after earthquake and fire, April 18 - 21, 1906, view from Stanford Mansion site Photo by Lester C. Guernsey Via Library of Congress Panoramic collection (http://lcweb2.loc.gov/pp/panabt.html) Digital ID: ppmsca 05595; digital file from original print,Library of Congress Prints and Photographs Division Washington, D.C. 20540 USA

Abstract

Data

Method

Results

We use a large database (>10,000 records) of ground motions in Japan to explore earthquake processes including attenuation, magnitude scaling, site effects and other factors such as event type and focal depth, for events with moment magnitude M ≥ 5.5. Regression analysis and statistical analysis are implemented to characterize, and distinguish between, different types of earthquake ground motion processes including those for crustal, in-slab and interface events (for both source characterization and attenuation). We explore site effects, and their nonlinearity, by implementing Vs30 directly into ground motion prediction equations (GMPEs) as a predictive variable.

The strong motion data were collected from the National Research Institute for Earth Science and Disaster Prevention (NIED) networks of Japan.  K-NET (Kyoshin network)

Ground Motion Prediction Equation (GMPE):

Linear site effect

 No. Events: 211, No. Records: 11993, Horizontal components  Normal (892), Reverse (7936), Strike Slip (1862), Unknown (1303)  Crustal (4055), Interface (4500), In-Slab (3206), Off-Shore (232)

Figure 3. Simplification to Zoback’s classification scheme (1992) recommended in Boore-Atkinson NGA PEER Report, 2008 (http://peer.berkeley.edu/products/Boore-Atkinson-NGA.html)

Figure 1. Japanese ground motion data from 1996 to 2009

Figure 2. Distribution of events (M  5.0)

Normal Reverse Strike-slip Undefined

pl > 40° pl ≤ 40° pl ≤ 40° pl > 40°

pl ≤ 40° pl > 40° pl ≤ 40° pl > 40°

Figure 4. Distribution of Catalogue M versus hypocentral distance of all K-NET data from 1996 to 2009. The red dashed line representing the cut-off distance for different magnitude ranges due to “non-triggered” events. Figure5. Distribution of events based on different focal-mechanism (normal, reverse, strike-slip, and unknown)

log μij = b1 + b2(M – Mref) + b3(M – Mref)2 + b4 Rij + b5log Rij+ b6log(Vs30/Vref) μij amplitude from earthquake i at station j Mref reference magnitude (Mref = 6) R = (Rcd2 + h2)0.5 where Rcd is the closest distance to the rupture and h is a fictitious depth bi’s (i = 1-6) are regression coefficients Assume linear site response initially, as most motions are relatively weak.

Random-Effects Algorithm

ni

(Brillinger and Preisler, 1984, 1985; Abrahamson and Youngs, 1992)

logYij = logμij + i + εij

Figure 10. Average residuals (1 standard deviation of the mean) for each site category. The residuals are plotted corresponding to NEHRP B/C boundary site conditions (Vs = 760 m/s). The dashed line is the predicted residual (b6log(Vs30/Vref))

i 

 2  rij j 1 2

ni   2

i is the inter-event term for the ith event and εij represents the intra-event variability. i ~ N(0,τ2), εij ~ N(0,σ2)

PGA

0.3-sec SA

1.0-sec SA

Event type Figure 6. For Crustal and Interface events the attenuation model we used is about right. For the In-slab events it might be a slight increase in amplitude for PGA because of high frequency content of those events.

Non-Linear site effect Figure 11 The total amplification (residual) as a function of predicted peak ground acceleration at a reference site (PHAr) for different site classes. The nonlinear term can result in a significant reduction of motions on sites with relatively low velocities (Boore and Atkinson 2005; Choi and Stewart 2005). Fij(T) = Sij/(Sr)ij

Crustal

Interface

In-Slab

Off-Shore

(Sr)ij is the median spectral acceleration for rock site corrected for event terms

Figure 7. The average response spectral ratio (H/V) for different site classes.

Figure 8. Comparing the average values within the period range of ~0.7-9 sec. The numbers after site class labels are the total number of events which are used in calculating the average. Figure 9. Observed H/V ratios as a function of distance, for frequencies of 1 and 2Hz.

http://geoinfo.amu.edu.pl/wpk/pe/a/harbbook/c_iii/Earthquakes/realquakes/Lga/Lga0004.JPG

Conclusions  Preliminary findings suggest that there are not large differences in ground motions between the different classes of events (crustal, in-slab, interface).  The overall agreement between the average inter-event corrected residuals for each site class, relative to the predictions for NEHRP B/C boundary site class and the trend predicted by the model is very good.  The non-linear soil response is modeled by ln(Fij) = ai + biln(PHAr) where Fij is the amplification factor for ground motion j within site category i and PHAr is the expected peak acceleration on rock (g).

References Abrahamson, N.A., and R.R. Youngs (1992). A stable algorithm for regression analysis using the random effects model, Bull. Seism. Soc. Am. 82, 505-510 Boore, D. M. and G. M. Atkinson (2007). Boore-Atkinson NGA Ground Motion Relations for the Geometric Mean Horizontal Component of Peak and Spectral Ground Motion Parameters, PEER 2007/01, Pacific Earthquake Engineering Research Center, Berkeley, California Brillinger, D. R., and H. K. Preisler (1984). An exploratory analysis of the Joyner–Boore attenuation data, Bull. Seism. Soc. Am. 74, 1441–1450. Brillinger, D. R., and H. K. Preisler (1985). Further analysis of the Joyner–Boore attenuation data, Bull. Seism. Soc. Am. 75, 611–614. Choi, Y., and J. P. Stewart (2005). Nonlinear site amplification as function of 30 m shear wave velocity. Earthquake Spectra (21: 1-30.) Zoback, M.L. (1992). First- and second-order patterns of stress in the lithosphere: The World Stress Map Project. J. Geophysical Research 97: 11,703-28.