Pure and Applied Geophysics

, Volume 168, Issue 1–2, pp 105–116 | Cite as

Characterization of Stress Drops on Asperities Estimated from the Heterogeneous Kinematic Slip Model for Strong Motion Prediction for Inland Crustal Earthquakes in Japan

  • Kimiyuki AsanoEmail author
  • Tomotaka Iwata


Dense strong motion observation networks provided us with valuable data for studying strong motion generation from large earthquakes. From kinematic waveform inversion of seismic data, the slip distribution on the fault surface of large earthquakes is known to be spatially heterogeneous. Because heterogeneities in the slip and stress drop distributions control the generation of near-source ground motion, it is important to characterize these heterogeneities for past earthquakes in constructing a source model for reliable prediction of strong ground motion. The stress changes during large earthquakes on the faults recently occurring in Japan are estimated from the detailed slip models obtained by the kinematic waveform inversion. The stress drops on and off asperities are summarized on the basis of the stress change distributions obtained here. In this paper, we define the asperity to be a rectangular area whose slip is 1.5 or more times larger than the average slip over the fault according to the previous study for inland crustal earthquakes. The average static stress drops on the asperities of the earthquakes studied here are in the range 6–23 MPa, whereas those off the asperities are below 3 MPa. We compiled the stress drop on the asperities together with a data set from previous studies of other inland earthquakes in Japan and elsewhere. The static stress drop on the asperity depends on its depth, and we obtained an empirical relationship between the static stress drop and the asperity’s depth. Moreover, surface-breaking asperities seemed to have smaller stress drops than buried asperities. Simple ground motion simulations using the characterized asperity source models reveal that deep asperities generate larger ground motion than shallow asperities, because of the different stress drops of the asperities. These characteristics can be used for advanced source modeling in strong ground motion prediction for inland crustal earthquakes.


Stress drop asperity inland crustal earthquake source model strong motion prediction 



The authors are grateful to Professor Wenbo Zhang for the dynamic source parameters from previous studies. We thank the anonymous reviewers for their helpful comments which improved this manuscript. This study is partially supported by the JSPS Grant-in-Aid for Young Scientists (start-up) No. 19810008 (PI K. Asano), the JSPS Grant-in-Aid for Scientific Research (B) No. 20310105 (PI T. Iwata), and the Research Project for Intensive Survey and Study on the Concentrated Strain Zone from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. Figures are drawn using the Generic Mapping Tools (Wessel and Smith 1998).


  1. Andrews, D.J. (1980), A stochastic fault model: 1. Static case, J. Geophys. Res. 85, 3867–3877.Google Scholar
  2. Asano, K., and Iwata, T. (2006), Source process and near-source ground motions of the 2005 west off Fukuoka prefecture earthquake, Earth Planets Space 58, 93–98.Google Scholar
  3. Asano, K., and Iwata, T. (2007), Source rupture process of the 2007 Noto Hanto earthquake, Japan, obtained from strong ground motion and GPS data, EOS Trans. Am. Geophys. Union 88, Fall meet. Suppl., Abstract S51B-0512.Google Scholar
  4. Asano, K., and Iwata, T. (2008), Kinematic source rupture process of the 2008 Iwate-Miyagi Nairiku earthquake, a MW6.9 thrust earthquake in northeast Japan, using strong motion data, EOS Trans. Am. Geophys. Union 89, Fall meet. Suppl., Abstract S23B-1890.Google Scholar
  5. Asano, K., and Iwata, T. (2009), Source rupture process of the 2004 Chuetsu, mid-Niigata prefecture, Japan, earthquake inferred from the waveform inversion with dense strong-motion data, Bull. Seismol. Soc. Am. 99, 123–140.Google Scholar
  6. Boatwright, J. (1988), The seismic radiation from composite model of faulting, Bull. Seismol. Soc. Am. 78, 489–598.Google Scholar
  7. Bouchon, M. (1997), The state of stress on some faults of the San Andreas system as inferred from near-field strong motion data, J. Geophys. Res. 102, 11731–11744.Google Scholar
  8. Dalguer, L.A., Miyake, H., Day, S.M. and Irikura, K. (2008), Surface rupturing and buried dynamic-rupture models calibrated statistical observations of past earthquakes, Bull. Seismol. Soc. Am. 98, 1147–1161.Google Scholar
  9. Das, S., and Kostrov, B.V., Fracture of a single asperity on a finite fault: a model for weak earthquakes? In Earthquake source mechanics (eds. Das, S., Boatwright, J., and Scholz, C.H.) (American Geophysical Union, Geophysical Monograph Series 37, Washington D.C., 1986) pp. 91–96.Google Scholar
  10. Day, S.M. (1982), Three-dimensional simulation of spontaneous rupture: the effect of nonuniform prestress, Bull. Seismol. Soc. Am. 72, 512–522.Google Scholar
  11. Eshelby, J.D. (1957), The determination of the elastic field of an ellipsoidal inclusion, and related problems, Proc. Roy. Soc. A 241, 376–396.Google Scholar
  12. Fujiwara, H., Kawai, S., Aoi, S., Morikawa, N., Senna, S., Kobayashi, K., Ishii, T., Okumura, T., and Hayakawa, Y. (2006), National seismic hazard maps of Japan, Bull. Earthq. Res. Inst. Univ. Tokyo 81, 221–232.Google Scholar
  13. Fukuyama, E., Ishida, M., Dreger, D.S., and Kawai, H. (1998), Automated seismic moment tensor determination using on-line broadband seismic waveforms, Zisin 2 (J. Seismol. Soc. Jpn.) 51, 149–156 (in Japanese with English abstract).Google Scholar
  14. Hartzell, S.H., and Heaton, T.H. (1983), Inversion of strong ground motion and teleseismic waveform data for the fault rupture history of the 1979 Imperial Valley, California, earthquake, Bull. Seismol. Soc. Am. 73, 1553–1583.Google Scholar
  15. Ide, S. and Takeo, M. (1997), Determination of constitutive relations of fault slip based on seismic wave analysis, J. Geophys. Res. 102, 27379–27391.Google Scholar
  16. Irikura, K. (2006), Predicting strong ground motions with a “recipe”, Bull. Earthq. Res. Inst. Univ. Tokyo 81, 342–351.Google Scholar
  17. Irikura, K., and Miyake, H. (2010), Recipe for predicting strong ground motion from crustal earthquake scenarios, Pure Appl. Geophys., this topical volume, in revise.Google Scholar
  18. Irikura, K., Miyake, H., Iwata, T., Kamae, K., and Kawabe, H. (2002), Revised recipe for predicting strong ground motion and its validation, Proc. 11th Japan Earthq. Eng. Symp., 567–572 (in Japanese with English abstract).Google Scholar
  19. Iwata, T., and Sekiguchi, H. (2002), Rupture process and near-source ground motions of the 2000 Tottoriken-Seibu earthquake, Proc. 11th Japan Symp. Earthq. Eng., 121–125 (in Japanese with English abstract).Google Scholar
  20. Iwata, T., Sekiguchi, H., Miyake, H., Zhang, W., and Miyakoshi, K. (2005), Dynamic source parameters for characterized source model for strong motion prediction, Proc. Int. Symp. Earthq. Eng. Commem. Tenth Anniv. 1995 Kobe Earthq., A159–A164.Google Scholar
  21. Kagawa, T., Irikura, K., and Somerville, P.G. (2004), Differences in ground motion and fault rupture process between the surface and buried rupture earthquake, Earth Planets Space 56, 3–14.Google Scholar
  22. Kamae, K., and Irikura, K. (1998), Source model of the 1995 Hyogo-ken Nanbu earthquake and simulation of near-source ground motion, Bull. Seismol. Soc. Am. 88, 400–412.Google Scholar
  23. Madariaga, R. (1977), High-frequency radiation from crack (stress drop) models of earthquake faulting, Geophys. J. Roy. Astr. Soc. 51, 625–651.Google Scholar
  24. Madariaga, R (1979), On the relation between seismic moment and stress drop in the presence of stress and strength heterogeneity, J. Geophys. Res. 84, 2243–2250.Google Scholar
  25. Mai, P.M., and G.C. Beroza (2000), Source scaling properties from finite-fault-rupture models, Bull. Seismol. Soc. Am. 90, 604–615.Google Scholar
  26. Mikumo, T., and Miyatake, T. (1993), Dynamic rupture processes on a dipping fault, and estimates of stress drop and strength excess from the results of waveform inversion, Geophys. J. Int. 112, 481–496.Google Scholar
  27. Miyake, H., Iwata, T., and Irikura, K. (2003), Source characterization for broadband ground-motion simulation: kinematic heterogeneous source model and strong motion generation area, Bull. Seismol. Soc. Am. 93, 2531–2545.Google Scholar
  28. Miyakoshi, K., Kagawa, T., Sekiguchi, H., Iwata, T., and Irikura, K. (2000), Source characterization of inland earthquakes in Japan using source inversion results, Proc. 12th World Conf. Earthq. Eng., paper no. 1850.Google Scholar
  29. Morikawa, N., Senna, S., Hayakawa, Y., and Fujiwara, H. (2008), Application and verification of the ‘recipe’ to strong-motion evaluation for the 2005 west off Fukuoka earthquake (MW = 6.6), Proc. 14th World Conf. Earthq. Eng., paper no. 02-0039 (DVD-ROM).Google Scholar
  30. Nakamura, H., and Miyatake, T. (2000), An approximate expression of slip velocity time function for simulation of near-field strong ground motion, Zisin 2 (J. Seismol. Soc. Jpn.) 53, 1–9 (in Japanese with English abstract).Google Scholar
  31. Pitarka, A. (1999), 3D elastic finite-difference modeling of seismic motion using staggered grids with nonuniform spacing, Bull. Seismol. Soc. Am. 89, 54–68.Google Scholar
  32. Ripperger, J., and Mai, P.M. (2004), Fast computation of static stress changes on 2D faults from final slip distributions, Geophys. Res. Lett. 31, L18610, doi: 10.1029/2004GL020594.
  33. Scholz, C.H., The Mechanics of Earthquakes and Faulting (Cambridge University Press, New York, 1990).Google Scholar
  34. Sekiguchi, H., and Iwata, T. (2002), Rupture process of the 1999 Kocaeli, Turkey, earthquake using strong motion waveforms, Bull. Seismol. Soc. Am. 92, 300–312.Google Scholar
  35. Sekiguchi, H., Iwata, T., and Irikura, K. (2002), Source inversion for estimating continuous slip distribution on the faultintroduction of Green’s functions convolved with a correction function to give moving dislocation effects in subfaults, Geophys. J. Int. 150, 377–391.Google Scholar
  36. Somerville, P. G. (2003), Magnitude scaling of the near fault rupture directivity pulse, Phys. Earth Planet. Int. 137, 201–212.Google Scholar
  37. Somerville, P., Irikura, K., Graves, R., Sawada, S., Wald, D., Abrahamson, N., Iwasaki, Y., Kagawa, T., Smith, N., and Kowada, A. (1999), Characterizing crustal earthquake slip models for the prediction of strong ground motion, Seism. Res. Lett. 70, 59–80.Google Scholar
  38. Watanabe, M., Sato, T., and Dan, K. (1998), Scaling relations of fault parameters for inland earthquakes, Proc. 10th Jpn. Earthq. Eng. Symp., 583–588.Google Scholar
  39. Wessel, P., and Smith, W.H.F. (1998), New, improved version of Generic Mapping Tools released, Eos Trans. AGU 79, 579.Google Scholar
  40. Zhang, W., Iwata, T., Irikura, K., Sekiguchi, M., and Bouchon, M. (2003), Heterogeneous distribution of the dynamic source parameters of the 1999 Chi-Chi, Taiwan, earthquake, J. Geophys. Res. 108, 2232, doi: 10.1029/2002JB001889.

Copyright information

© Birkhäuser / Springer Basel AG 2010

Authors and Affiliations

  1. 1.Disaster Prevention Research InstituteKyoto UniversityUjiJapan

Personalised recommendations