SpringerLink
Log in

Application of New Statistical Methods to Estimation of the Seismicity Field Parameters by an Example of the Japan Region

  • Published:
Izvestiya, Physics of the Solid Earth Aims and scope Submit manuscript

Abstract

This study is devoted to application of some new statistical methods to analysis of the spatial structure of the seismic field in a seismically active region in the neighborhood of Japan bounded by the following coordinates: 28°–50° north latitude, 130°–150° east longitude. The estimates of the seismic flux were obtained by using the k-nearest neighbors method for the magnitude interval m ≥ 5.2. The highest values of seismic flux intensity of about 10–4 \(\frac{1}{{{\text{year}}{\kern 1pt} - {\kern 1pt} {\text{k}}{{{\text{m}}}^{{\text{2}}}}}}\) are located at depths of down to 100 km and manifest themselves in the neighborhood of the Tohoku megathrust earthquake. The spatial resolution of the intensity estimates is ranging from 33–50 km in the regions with a high intensity to 100 km and larger in the zones with a weak intensity. It has been shown that the seismic filed parameters—intensity λ, slope of the magnitude–frequency graph β, maximum possible magnitude m1—have different scales of their spatial variability and, thus, it is necessary to apply different scales of spatial averaging to them. Based on the Gutenberg—Richter truncated distribution model, the estimates are obtained for the slope of the magnitude–frequency graph (b‑value) and the upper boundary of the distribution m1. An original method is proposed for determining the optimal averaging radius for an arbitrary cell of the space grid. The method is based on the use of the statistical coefficient of variation of the corresponding parameter. For the considered region, the estimate of the maximum possible magnitude Мmax = 9.60 \( \pm \) 0.41 was obtained with consideration of the correction for bias.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price includes VAT (Brazil)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.

Similar content being viewed by others

REFERENCES

  1. Aki, K., Maximum likelihood estimate of b in the formula log(N) = a – bM and its confidence limits, Bull. Earthquake Res. Inst. Tokyo Univ., 1965, vol. 43, pp. 237–239.

    Google Scholar 

  2. Beirlant, J., Kijko, A., Reynkens, T., and Einmahl, J., Estimating the maximum possible earthquake magnitude using extreme value methodology: The Groningen case, Nat. Hazards, 2019, vol. 98, pp. 1091–1113. https://doi.org/10.1007/s11069-017-3162-2

    Article  Google Scholar 

  3. Bender, B., Maximum likelihood estimation of b values for magnitude grouped data, Bull. Seismol. Soc. Am., 1983, vol. 73, no. 3, pp. 831–851. https://doi.org/10.1785/BSSA0730030831

    Article  Google Scholar 

  4. Cramer, H., Mathematical Methods of Statistics, Princeton: Princeton Univ. Press, 1940.

    Google Scholar 

  5. Efron, B., Bootstrap methods: Another look at the jackknife, Ann. Stat., 1979, vol. 7, no. 1, pp. 1–26. https://doi.org/10.1214/aos/1176344552

    Article  Google Scholar 

  6. Gutenberg, B. and Richter, C., Seismicity of the Earth, New York: Princeton University Press, 1954.

    Google Scholar 

  7. Holschneider, M., Zöller, G., and Hainzl, S., Estimation of the maximum possible magnitude in the framework of the doubly truncated Gutenberg–Richter model, BSSA, 2011, vol. 101, no. 4, pp. 1649–1659. https://doi.org/10.1785/0120100289

    Article  Google Scholar 

  8. Kanamori, H., The energy release in great earthquakes, J. Geophys. Res., 1977, vol. 82, no. 10, pp. 2981–2987. https://doi.org/10.1029/JB082i020p02981

    Article  Google Scholar 

  9. Khan, P.K., Manoj, G., Chakraborty, P.P., and Mukherjee, D., Seismic b-value and the assessment of ambient stress in Northeast India, Pure Appl. Geophys., 2011, vol. 168, pp. 1693–1706. https://doi.org/10.1007/s00024-010-0194-x

    Article  Google Scholar 

  10. Kijko, A., Estimation of the maximum earthquake magnitude, m max, Pure Appl. Geophys., 2004, vol. 161, pp. 1655–1681. https://doi.org/10.1007/s00024-004-2531-4

    Article  Google Scholar 

  11. Kijko, A. and Singh, M., Statistical tools for maximum possible earthquake estimation, Acta Geophys., 2011, vol. 59, no. 4, pp. 674–700. https://doi.org/10.2478/s11600-011-0012-6

    Article  Google Scholar 

  12. Kolathayar, S., Sitharam, T.G., and Vipin, K.S., Spatial variation of seismicity parameters across India and adjoining areas, Nat. Hazards, 2012, vol. 60, pp. 1365–1379. https://doi.org/10.1007/s11069-011-9898-1

    Article  Google Scholar 

  13. Latchman, J.L., Pisarenko, V., and Rodkin, M. Heavy-Tailed Distributions in Disaster Analysis, Math. Geosci.s, 2010, vol. 43, pp. 501–502. https://doi.org/10.1007/s11004-011-9339-4

    Article  Google Scholar 

  14. Marzocchi, W. and Sandri, L., A review and new insights on the estimation of the b-value and its uncertainty, Ann. Geophys., 2003, vol. 46, no. 6, pp. 1271–1282. http://hdl.handle.net/2122/1017.

    Google Scholar 

  15. Pisarenko, V.F., Statistical evaluation of maximum possible magnitude, Izv., Phys. Solid Earth, 1991, vol. 27, pp. 757–763.

    Google Scholar 

  16. Pisarenko, V.F., Estimating the parameters of truncated Gutenberg–Richter distribution, Izv. Phys. Solid Earth, 2022, vol. 58, no. 1, pp. 80–88. https://doi.org/10.1134/S1069351322010074

    Article  Google Scholar 

  17. Pisarenko, V.F. and Pisarenko, D.V., A modified k-nearest neighbors method and its application to estimation of seismic intensity, Pure Appl. Geophys., 2022, vol. 179, pp. 4025–4036. https://doi.org/10.1007/s00024-021-02717-y

    Article  Google Scholar 

  18. Pisarenko, V.F. and Rodkin, M.V., The maximum earthquake in future T years: Checking by a real catalog, Chaos, Solitons Fractals, 2015, vol. 74, pp. 89–98. https://doi.org/10.1016/j.chaos.2015.01.006

    Article  Google Scholar 

  19. Pisarenko, V.F. and Rodkin, M.V., Declustering of seismicity flow: Statistical analysis, Izv., Phys. Solid Earth, 2019, vol. 55, no. 5, pp. 733–745. https://doi.org/10.1134/S1069351319050082

    Article  Google Scholar 

  20. Pisarenko, V.F. and Rodkin, M.V., Statistics and spatial-temporal structure of ground acceleration caused by earthquakes in the North-Western Pacific, Pure Appl. Geophys, 2020, vol. 177, pp. 2563–2578. https://doi.org/10.1007/s00024-019-02415-w

    Article  Google Scholar 

  21. Pisarenko, V.F. and Rodkin, M.V., Approaches to solving the maximum possible earthquake magnitude (M max) problem, Surv. Geophys., 2022, vol. 43, pp. 561–595. https://doi.org/10.1007/s10712-021-09673-1

    Article  Google Scholar 

  22. Pisarenko, V.F., Lyubushin, A.A., Lysenko, V.B., and Golubeva, T.V., Statistical estimation of seismic hazard parameters: Maximal possible magnitude and related parameters, Bull. Seismol. Soc. Am., 1996, vol. 86, no. 3, pp. 691–700. https://doi.org/10.1785/BSSA0860030691

    Article  Google Scholar 

  23. Pisarenko, V.F., Sornette, A., Sornette, D., and Rodkin, M.V., Characterization of the tail of the distribution of earthquake magnitudes by combining the GEV and GPD descriptions of extreme value theory, Pure Appl. Geophys., 2014, vol. 171, pp. 1599–1624. https://doi.org/10.1007/s00024-014-0882-z

    Article  Google Scholar 

  24. Pisarenko, V.F., Rodkin, M.V., and Rukavishnikova, T.A., Stable modification of frequency–magnitude relation and prospects for its application in seismic zoning, Izv., Phys. Solid Earth, 2020, vol. 56, no. 1, pp. 53–65. https://doi.org/10.1134/S1069351320010103

    Article  Google Scholar 

  25. Pisarenko, V.F., Skorkina, A.A., Ruzhich, V.V., and Levina, E.A., The structure of seismicity field in the Baikal Rift zone, Izv., Phys. Solid Earth, 2022, vol. 58, no. 3, pp. 329–345. https://doi.org/10.1134/S1069351322030053

    Article  Google Scholar 

  26. Pisarenko, V.F., Skorkina, A.A., and Rukavishnikova, T.A., Choosing the magnitude range for estimating the b-value, J. Volcanol. Seismol., 2023, vol. 17, no. 2, pp. 75–82. https://doi.org/10.1134/S0742046323700124

    Article  Google Scholar 

  27. Salahshoor, H., Lyubushin, A., Shabani, E., and Kazemian, J., Comparison of Bayesian estimates of peak ground acceleration (A max) with PSHA in Iran, J. Seismol., 2018, vol. 22, pp. 1515–1527. https://doi.org/10.1007/s10950-018-9782-5

    Article  Google Scholar 

  28. Talukdar, P., Seismic study and spatial variation of b-value in Northeast India, IOSR J. Appl. Phys., 2013, vol. 4, pp. 31–40.

    Google Scholar 

  29. Taroni, M., Zhuang, J., and Marzocchi, W., High-definition map** of the Gutenberg–Richter b-value and its relevance: A case study in Italy, Seismol. Res. Lett., 2021, vol. 92, no. 6, pp. 3778–3784. https://doi.org/10.1785/0220210017

    Article  Google Scholar 

  30. Usami, V., Study of historical earthquakes in Japan, Bull. Earthquake Res., 1979, vol. 54, pp. 399–439.

    Google Scholar 

  31. Utsu, V., Catalog of large earthquakes of Japan from 1885 through 1925, Bull. Earthquake Res., 1982, vol. 57, pp. 401–463.

    Google Scholar 

Download references

ACKNOWLEDGMENTS

The authors thank A.V. Lander for the help in preparing the catalog of earthquakes and D.V. Pisarenko for valuable remarks. The authors are grateful to the revisers of this paper for their comments, which proved to be very useful.

Funding

The work was performed in the framework of the government task of the Institute of Earthquake Prediction Theory and Mathematical Geophysics of the Russian Academy of Sciences.

Author information

Authors and Affiliations

  1. Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, 117997, Moscow, Russia

    V. F. Pisarenko, A. A. Skorkina & T. A. Rukavishnikova

Authors
  1. V. F. Pisarenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. A. Skorkina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T. A. Rukavishnikova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to V. F. Pisarenko, A. A. Skorkina or T. A. Rukavishnikova.

Additional information

Translated by E. Smirnova

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pisarenko, V.F., Skorkina, A.A. & Rukavishnikova, T.A. Application of New Statistical Methods to Estimation of the Seismicity Field Parameters by an Example of the Japan Region. Izv., Phys. Solid Earth 59, 967–978 (2023). https://doi.org/10.1134/S1069351323060162

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1069351323060162

Keywords:

Search

Navigation