A Prototype of Strong Ground Motion Prediction
Procedure for Intraslab Earthquake based on
the Characterized Source Model
T. Iwata, K. Asano & H. Sekiguchi
Disaster Prevention Research Institute, Kyoto University, JapanSUMMARY:
Strong motion predictions for anticipated earthquakes are important for seismic disaster evaluation and planningof disaster management. We proposed a prototype of the procedure to construct source models of intraslab
earthquakes for strong motion prediction based on the concept of the characterized source model (Irikura andMiyake, 2011). Iwata and Asano (2011) characterized the heterogeneous source model for intraslab earthquakes
based on the empirical scaling relationships between the asperity and the total rupture areas and thecorrespondence between the SMGA (strong motion generation area, Miyake et al., 2003) and the asperity (large
slip area). We proposed ta procedure to construct a source model or a intraslab earthquake to be used for strong
ground motion prediction based on the characterized intraslab-earthquake source model by Iwata and Asano(2011). We applied this procedure to several observed events occurred in Japan and simulated ground motions inorder to validate the procedure. Through those validation tests, we found that some source parameters show
regional dependency and that appropriate choice for the target source region is crucial.
Keywords: Strong ground motion prediction, Intraslab earthquake, characterized source model

1. INTRODUCTION
Along the Pacific Rim, large intraslab earthquakes have caused disasters (e.g., the 1993 Kushiro-oki,
Japan, the 2001 Nisqually, USA, and the 2008 Iwate-Engan-Hokubu, Japan, earthquakes). Generally,
high-frequency-rich ground motion characteristics are pointed out for intraslab earthquakes. Studies on
PGA attenuation relationships (e.g. Youngs et al., 1997; Si and Midorikawa, 1999) have shown thatdeeper events cause larger PGA.
Strong motion prediction based on scenario earthquakes are recently carried out for earthquake
disaster mitigation of urbanized societies and source modelling methodologies have been developed.
For inland crustal earthquakes, Somerville et al. (1999) compiled the kinematic source models andproposed a set of empirical scaling relationships for inland crustal earthquakes. They showed that thearea ratio of the asperities to the rupture area is constant in the moment magnitude ranging from 5.7 to
7.2. Miyake et al. (2003) showed that strong motion generation area (SMGA), defined as a restricted
area with higher slip velocity and/or higher stress drop on the source fault, which mainly generates
broad-band strong ground motions, coincides with the asperity area by strong motion simulation using
the empirical Green’s function method. From those results, Irikura and Miyake (2001, 2011) proposeda manual so-called ‘recipe’ of strong ground motion prediction including an idea of characterized
source model. The characterized source model is defined by the finite source model consisting of theasperity area and the background area. The asperity area has larger stress drop than the backgroundarea following the asperity model proposed by Boatwright (1988).
Iwata and Asano (2011) compiled kinematic heterogeneous source models of intraslab earthquakes tocompare source scaling properties with those of inland crustal (Somerville et al., 1999) and
subduction-zone plate-boundary earthquakes (Murotani et al., 2008). Characterization of

heterogeneous slip distributions to extract rupture area, asperity, and average slip was done following
the procedure proposed by Somerville et al. (1999). They also compared SMGAs for intraslab events,and found that the asperity area coincides with the SMGA area, which assures direct usage of thischaracterize source models in broadband ground motion simulation by the empirical Green’s function
method or by the stochastic Green’s function method. Iwata et al. (2011) proposed a procedure forconstructing the source model of intraslab earthquakes for strong motion prediction, and applied it to
the past events to check the applicability of the procedure by comparing ground motion records andseismic intensity distributions. This paper will summarize the procedure shown in Iwata et al. (2011),
apply it to the 2011 Miyagi-Oki intraslab earthquake, and discuss on applicability of the procedure.

2. SCALING RELATIONSHIPS OF HETELOGENEOUS INTRASLAB EARTHQUAKESOURCE MODEL AND CHARACTERIZED SOURCE MODEL
Iwata and Asano (2011) collected twelve source models for eleven intraslab events of MW 6.6–8.3.
Using final slip models, they estimated the rupture area, the asperity area, the average slip amounts forthe rupture area, and the average slip amounts for asperity area following to the criterion proposed bySomerville et al. (1999). Their definition of the rupture area is a rectangle one consisting subfaults
whose slips are more than 0.3 times of the average slip. That of the asperity area is the one in therupture area consisting subfaults whose slips are more than 1.5 times of the average slip. If there areplural asperity areas in the rupture area, total asperity area is obtained. They obtained scaling
relationship for rupture area (S), total asperity area (Sa), and average slip (D) by the lest-squares fit.
They assumed the power coefficient of M0 as 2/3 for S and Sa and 1/3 for D by the constraint of theself-similarity (Somerville et al., 1999).
The empirical relationships are as follows,

S = 6.57 ×10 −11 M 02 / 3−11

S a = 1.04 ×10 M 02 / 3
D = 2.25 × 10 −5 M 01 / 3

(2.1)
(2.2)
(2.3)

The units of area, slip, and seismic moment are km2, m, and Nm, respectively.
The relationships of the rupture area and the asperity area versus the seismic moment are shown in Fig.
2.1. Closed circles represent the intraslab earthquakes collected in this study. The inland crustal
earthquakes (Somerville et al., 1999) and the plate-boundary earthquakes (Murotani et al., 2008) arealso shown in the same figure. The empirical relationships of three categorized events are indicated by
the lines. The assumption of self-similarity is quite reasonable because there is no systematic trend for
intraslab earthquakes. Under the same seismic moment, a plate-boundary earthquake has the largest
rupture area and the intraslab earthquake has a smallest rupture area. The empirical relationship forinland crustal and plate-boundary earthquakes seems to be similar and the total asperity area for
intraslab earthquakes is approximately the half of other groups under the same seismic moment.
Following those empirical relationships, Iwata and Asano (2011) obtained stress parameters of thesource model for intraslab earthquakes. Stress drops on the rupture area and the asperity are given by
the following equations (Boatwright, 1988).
7 M0
16 R 3
7 M0
Δσ a =
16 Rr 2

Δσ =

(2.4)
(2.5)

R and r are the equivalent radius of total rupture area and asperity area, respectively. From the Eqns.
2.1 and 2.2, they obtained those stress drops are 4.6 MPa for total rupture area and 28.9 MPa forasperity (c.f. 2.3 MPa and 10.5 MPa for crustal earthquakes).

Figure 2.1. (Left) Empirical scaling relationships of rupture area and seismic moment. Intraslab events collectedby Iwata and Asano (2011) are shown in solid circles, whereas inland crustal events (Somerville et al., 1999) are
shown in grey squares and plate-boundary events (Murotani et al., 2008) are shown in grey triangles. Solid line
indicates the empirical formulation for intraslab earthquakes obtained by Iwata and Asano (2011). Grey lines
indicate those for inland crustal earthquakes (Somerville et al., 1999) and for plate-boundary earthquakes(Murotani et al., 2008). (Right) Those of asperity area and seismic moment.

SMGA for intraslab events are estimated by broadband strong motion waveform modelling (e.g.
Asano et al., 2003, 2004) using the empirical Green’s function method (e.g. Irikura, 1986). Iwata andAsano (2011) collected the SMGA modelling results for intraslab earthquakes, and compared the sizes
and the locations of the SMGA and the asperity area. In Fig. 2.2, the scaling relationship of SMGAs toseismic moment for intraslab earthquakes is shown. For comparison, the SMGAs for inland crustal
earthquakes discussed by Miyake et al. (2003) are also shown. Comparing to the empirical
relationship of combined asperity area and seismic moment obtained by Somerville et al. (1999), theSMGAs of intraslab earthquakes are obviously smaller than the combined asperity area of inland
crustal earthquake. The solid line indicates the empirical relationship of intraslab earthquake for theasperity and the seismic moment (Eqn. 2.2). The SMGA size is mostly following this empirical
relationship. Using those characteristics of SMGA, the characterized source model of intraslab
earthquakes can be modelled in the similar manner for inland crustal earthquakes, that is, thecharacterized source model composed of the asperity area and background area whose area ratio andstress drop parameters are different from inland crustal earthquakes. For inland crustal earthquakes,
Sa/S (the ratio of asperity and total area) is about 0.22, whereas that for intraslab earthquakes is 0.16.

Figure 2.2. Scaling relationship of strong motion generation area to seismic moment for intraslab earthquakes.
Circles show the strong motion generation areas for intraslab earthquakes studied in Asano et al. (2003, 2004)
and Asano and Iwata (2009). Hexagons show the SMGAs studied by Morikawa and Fujiwara (2002), Morikawa

and Sasatani (2004), and Sasatani et al. (2006). Squares show the SMGAs for inland crustal earthquakes
analysed by Miyake et al. (2003). The line indicates the empirical relationship of combined asperity area andseismic moment obtained by Somerville et al. (1999).

3. PROCEDURE FOR SOURCE MODEL CONSTRUCTION
EARTHQUAKES FOR STRONG MOTION PREDICTIONOFINTRASLAB

As mentioned above, Iwata and Asano (2011) obtained the empirical relationships of the rupture size
and the asperity size of the intraslab events. Following to those relationships, we give a procedure forconstructing source models of intraslab earthquakes for strong motion prediction.
[1] Give the seismic moment, M0.
[2] Obtain the total rupture area and the total asperity area according to the empirical scaling
relationships between S, Sa, and M0 given by Eqns. (2.1) and (2.2)[3] Square rupture area and asperities are assumed.
[4] The source mechanism is assumed to be the same as that of small events in the source region.
[5] Plural scenarios including variety of the number of asperities and rupture starting points areprepared.
Iwata et al. (2011) tested this procedure by simulating strong ground motions for several pastearthquakes such as the 2001 Geiyo (MW 6.8, hypocentral depth = 46 km, the Philippine-Sea plate),the 2003 Miyagi-Oki (MW 7.0, 72 km, Pacific plate), and the 1987 Chiba-Ken-Toho-Oki (MW 6.7, 47
km, Pacific plate) earthquakes. The simulated ground motions reproduced observations fairly well forthe 2001 Geiyo and the 1987 Chiba earthquakes. On the contrary, the simulated ground motions forthe 2003 Miyagi-Oki from the average empirical relationships are underestimated compared to theobservations. They simulated the ground motions with the average – S.D. source model for total andasperity area sizes, which means higher stress drop source model than the average, and reproduced
observations well. Here we will show the simulation results for the 7 April 2011 Miyagi-Oki intraslab
earthquake.
3.1 Simulation for the 2011 Miyagi-Oki earthquake

The 2011 Miyagi-Oki earthquake occurred on 7 April 2011 (JST = UT + 9) in the subducting Pacificplate. This event is referred as an induced earthquake by the 2011 Great Tohoku earthquake. The
hypocentral depth and MW are 66 km and 7.1, respectively. The source mechanism is reverse fault type.
Aftershock distribution shows the fault plane is down to East with the WNW-ESE direction.
Following the procedure, we assumed the source model. The EGFM ground motion modelling is used
for the forward simulation. We used records of an MW 5.4 aftershock occurred at 18:42 on 9 April
2011 (JST) as an empirical Green’s function. Target sites are K-NET and KiK-net strong motion
stations. The simulated results using the average parameters, that means that the characterized source
model parameters from the empirical relationships (2.1) and (2.2), show underestimation of PGA,PGV and JMA seismic intensity. Therefore, we demonstrate the average minus one-standard deviation
model, which gives the smaller total fault size and the asperity size for the given seismic momentusing one standard deviation relationships of (2.1) and (2.2). In other words, the average – one S.D.
model gives small total size and asperity size, and higher stress drops for the asperity and total area, 58,
and 6 MPa, respectively. The simulated PGA, PGV and JMA seismic intensities using the average –S.D. model are compared to the observation in Fig. 3.1. Reasonable reproduction is observed in thismodel simulation. For the case of the 2011 Miyagi-Oki earthquake, the average – one S.D. model isnecessary for reasonable simulation, which is similar to the case of the 2003 Miyagi-Oki earthquake in
Iwata et al. (2011).

Figure 3.1. Comparison of PGA, PGV, and JMA seismic intensities of simulated ground motions by the average– one S.D. model (smaller fault and asperity size, i.e. larger stress drop model) to the observations.

4. DISCUSSION AND CONCLUSIONS

Following the empirical relationships of the total rupture area and the asperity area of the intraslab
earthquakes (Iwata and Asano, 2011), we constructed the procedure of the characterized source
models for strong motion prediction of intraslab earthquakes. In order to validate this procedure, weapplied it to simulate strong ground motions for several observed events in Iwata et al. (2011) and thispaper. Table 4.1 summarizes the application results. The simulated ground motions reproduced
observations fairly well for the 2001 Geiyo and the 1987 Chiba earthquakes. On the contrary, thesimulated ground motions for the 2003 and the 2001 Miyagi-Oki from the average empirical
relationships are underestimated compared to the observations. We simulated the ground motions withthe average – one S.D. source model that reproduced observations well. Going back to each source
model in Iwata and Asano (2011), the source models of the 2001 Geiyo and the 2003 Miyagi-Oki
events are used. There, the stress drop on the asperity is similar to the average one for the 2001 Geiyo
earthquake and that is larger than the average one for the 2003 Miyagi-Oki earthquake. In Fig. 4.1,
stress drops on asperities in the data-base of intraslab events are plotted against its hypocentral depth
summarized in Iwata and Asano (2011). The asperity stress drop parameters of the 2001 Geiyo
earthquake is almost same as the average values (28.9 MPa) in their database, whereas that of the 2003
Miyagi-Oki earthquake is about the stress drop from the average – S.D. model.
Table 4.1 Summary of the validation results
Event
MW
The 1987 Chiba-Ken-Toho-Oki
The 2001 Geiyo
The May 2003 Miyagi-Oki
The April 2011 Miyagi-Oki

6.7
6.8
7.0
7.1

Plate
Pacific Plate
Philippine Sea Plate
Pacific Plate
Pacific Plate

Hypocentral
depth
58 km
51 km
71 km
66 km

Preferred Modelaverage model
average model
ave. – one S.D.model
ave. – one S.D.model

The source models of the 1987 Chiba and the 2011 Miyagi-Oki events are not included in theheterogeneous source slip model data base in Iwata and Asano (2011). The strong motions of the 1987
Chiba event, whose focal depth is 47km, are well represented by the average model. In Fig. 4.1, there
is a systematic change of stress drops on asperity between 30 and 70 km of the hypocentral depth. We
could introduce depth dependency of stress drop values in this modelling. As a point of strong motion
prediction model, we could recommend simulations by not only the average model but the average –one S.D. model (higher stress drop model) and recognize those ground motion characteristics.

Figure 4.1. Stress drops on asperity for events in Iwata and Asano (2011). Stress drop values are plotted on the
hypocentral depth for each event. * denotes the 2001 Geiyo, and ** denotes the 2003 Miyagi-Oki earthquakes.
Thick and broken lines show the stress drop parameters of the average and average – S.D. characterized source
model, respectively.

ACKNOWLEDGEMENTS
We used K-NET and KiK-net data of NIED. JMA unified hypocentre catalogue was used. We also thank Mr. K.
Somei for the analysis. This study is partially supported by the Special Project for Earthquake Disaster
Mitigation in Tokyo Metropolitan Area from the Ministry of Education, Culture, Sports, Science andTechnology (MEXT) of Japan (The authors are collaborative members). Figures are drawn using the Generic
Mapping Tools (Wessel and Smith, 1998).

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