Skip to main content
Log in

Stable Modification of Frequency–Magnitude Relation and Prospects for Its Application in Seismic Zoning

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

Abstract

A new composite model is suggested for the frequency–magnitude relation of the earthquakes. The new model statistically reasonably describes the distribution in the range of weak and moderate events (the Gutenberg–Richter law) and in the range of strongest events (generalized Pareto law—one of the limiting laws in the extreme value theory). By the example of Japan and Kuriles, based on the GCMT catalog, it is shown that the model fairly adequately describes the seismicity in the circles containing at least 80 main shocks in the range of the reliably detected events m ≥ 5.3. The restriction on the number of the events imposes a statistical limitation on the resolution of the proposed model. In the case of the studied regions, this limitation allows reliable estimation of seismicity parameters for the areas with a radius of 300 km on a 2° × 2° grid. The use of this model in our previously designed statistical method for seismic risk assessment (Pisarenko and Rodkin, 2007; 2010; 2013) provides a theoretical basis for developing this technique towards more robust results and a better spatial resolution approaching the scale of the general seismic zoning maps.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.

Similar content being viewed by others

REFERENCES

  1. Baiesi, M. and Paczuski, M., Scale-free networks of earthquakes and aftershocks, Phys. Rev. E., 2004, vol. 69, pp. 66–106.

    Article  Google Scholar 

  2. Cosentino, P., Ficara, V., and Luzio, D., Truncated exponential frequency-magnitude relationship in the earthquake statistics, Bull. Seismol. Soc. Am., 1977, vol. 67, pp. 1615–1623.

    Google Scholar 

  3. Czechowski, Z., The privilege as the cause of power distribution in geophysics, Geophys J. Int., 2003, vol. 154, pp. 754–766.

    Article  Google Scholar 

  4. Dargahi-Noubary, G.R., A procedure for estimation of the upper bound for earthquake magnitudes, Phys. Earth Planet Inter., 1983, vol. 33, pp. 91–93.

    Article  Google Scholar 

  5. Dargahi-Noubary, G.R., Statistical Methods for Earthquake Hazard Assessment and Risk Analysis, Huntington: Nova Science, 2000.

  6. Efron, B., Bootstrap methods: Another look at the jackknife, Ann. Statist., 1979, no 7. pp. 1–26.

  7. Embrechts, P., Kluppelberg, C., and Mikosch, T., Modelling Extremal Events, Berlin: Springer, 1997a.

    Book  Google Scholar 

  8. Epstein, B.C. and Lomnitz, C., A model for the occurrence of large earthquakes, Nature, 1966, vol. 211, pp. 954–956.

    Article  Google Scholar 

  9. Godano, C. and Pingue, F., Is the seismic moment-frequency relation universal? Geophys J. Int., 2000, vol. 142, pp. 193–198.

    Article  Google Scholar 

  10. Golitsyn, G.S., The place of the Gutenberg-Richter law among other statistical laws of nature, Comput Seismol., 2001, vol. 32, pp. 138–161.

    Google Scholar 

  11. Grachev, A.F., Magnitsky, V.A., Mukhamediev, Sh.A., and Yunga, S.L., Determination of Possible Maximum Magnitudes of Earthquakes in the East European Platform, Izv.,Phys. Solid Earth, 1996, vol. 32, no. 7, pp. 559–574.

    Google Scholar 

  12. Gutenberg, B. and Richter, C., Earthquake magnitude, intensity, energy and acceleration, Bull. Seismol. Soc. Am., 1942, vol. 32, pp. 163–191.

    Google Scholar 

  13. Gutenberg, B. and Richter, C., Seismicity of the Earth and Associated Phenomena, Princeton: Princeton Univ., 1949.

    Google Scholar 

  14. Gutenberg, B. and Richter, C., Earthquake magnitude, intensity, energy, and acceleration, part II, Bull. Seismol. Soc. Am., 1956, vol. 46, pp. 105–145.

    Google Scholar 

  15. Jarrard, R.D., Relations among subduction parameters, Rev. Geophys., 1986, vol. 24, no. 2, pp. 217–284.

    Article  Google Scholar 

  16. Kagan, Y.Y., Statistics of characteristic earthquakes, Bull. Seismol. Soc. Am., 1993, vol. 83, no. 1. pp. 7–24.

    Google Scholar 

  17. Kagan, Y.Y., Observational evidence for earthquakes as a non-linear dynamic process, Physica D., 1994, vol. 77, pp. 160–192.

    Article  Google Scholar 

  18. Kagan, Y.Y., Seismic moment-frequency relation for shallow earthquakes: Regional comparison, J. Geophys Res., 1997a, vol. 102, pp. 2835–2852.

    Article  Google Scholar 

  19. Kagan, Y.Y., Earthquake size distribution and earthquake insurance, Commun. Statist. Stochastic Models, 1997b, vol. 13, no. 4, pp. 775–797.

    Article  Google Scholar 

  20. Kagan, Y.Y., Universality of the seismic moment-frequency relation, Pure Appl. Geophys., 1999, vol. 155, pp. 537–573.

    Article  Google Scholar 

  21. Kagan, Y.Y., Seismic moment distribution revisited: I. Statistical results, Geophys J. Int., 2002a, vol. 148, pp. 520–541.

    Article  Google Scholar 

  22. Kagan, Y.Y., Seismic moment distribution revisited: II. Moment conservation principle, Geophys J. Int., 2002b, vol. 149, pp. 731–754.

    Article  Google Scholar 

  23. Kagan, Y.Y. and Schoenberg, F., Estimation of the upper cutoff parameter for the tapered distribution, J. Appl. Probab., 2001, vol. 38A, pp. 901–918.

    Google Scholar 

  24. Kijko, A., Estimation of the maximum earthquake magnitude, Mmax,Pure Appl Geophys., 2004, vol. 161, pp. 1–27.

    Article  Google Scholar 

  25. Kijko, A. and Graham, G., Parametric-historic procedure for probabilistic seismic hazard analysis, Part I, Estimation of maximum regional magnitude Mmax, Pure Appl Geophys., 1998, vol. 152, pp. 413–442.

    Article  Google Scholar 

  26. Kijko, A. and Sellevol, M.A., Estimation of earthquake hazard parameters from incomplete data files. Part I, Utilization of extreme and complete catalogues with different threshold magnitudes, Bull. Seismol. Soc. Am., 1989, vol. 79, pp. 645–654.

    Google Scholar 

  27. Kijko, A. and Sellevol, M.A., Estimation of earthquake hazard parameters from incomplete data files. Part II. Incorporation of magnitude heterogeneity, Bull. Seismol. Soc. Am., 1992, vol. 82, pp. 120–134.

    Google Scholar 

  28. Molchan, G.M. and Podgaetskaya, V.M., Parameters of global seismicity, in Vychislitel’naya seysmologiya, Vyp. 6, Vychislitel’nyye i statisticheskiye metody interpretatsii seysmicheskikh dannykh (Computational and Statistical Methods for the Interpretation of Seismic Data, vol. 6 of Computational Seismology), 1973, pp. 44–66.

  29. Molchan, G., Kronrod, T., Dmitrieva, O., and Nekrasova, A., Multiscale model of seismicity in seismic risk problems: Italy, in Vychisl. Seismologiya, Vyp. 27, Sovremennyye problemy seysmichnosti (Modern Problems of Seismicity, Vol. 27 of Computational Seismology), Keilis-Borok, V.I., Ed., Moscow: Nauka, 1996, pp. 193–224.

  30. Molchan, G., Kronrod, T., and Panza, G.F., Multi-scale seismicity model for seismic risk, Bull Seismol. Soc. Am., 1997, vol. 87, pp. 1220–1229.

    Google Scholar 

  31. Okal, E.A. and Romanowicz, B.A., On variation of b-values with earthquake size, Phys. Earth Planet Interior., 1994, vol. 87, pp. 55–76.

    Article  Google Scholar 

  32. Pacheco, J.F., Scholz, C., and Sykes, L., Changes in frequency-size relationship from small to large earthquakes, Nature, 1992, vol. 355, pp. 71–73.

    Article  Google Scholar 

  33. Pisarenko, V.F., On the law of recurrence of earthquakes, in Diskretnyye svoystva geofizicheskoy sredy (Discrete Properties of the Geophysical Environment) Moscow: Nauka. 1989, pp. 47–60.

  34. Pisarenko, V.F., On the best statistical estimation of the maximum possible earthquake magnitude, Dokl. Ross. Akad. Nauk, 1995, vol. 344, no. 2, pp. 237–239.

    Google Scholar 

  35. Pisarenko,V.F., Statistical estimation of the maximum possible earthquakes, Phys. Solid Earth., 2009, no. 9, pp. 38–46.

  36. Pisarenko, V.F. and Lysenko, V.B., The probability distribution of the maximum earthquake that can occur in a given period of time, Dokl. Ross. Akad. Nauk, 1997, vol. 347, no. 2, pp. 399–401.

    Google Scholar 

  37. Pisarenko, V. and Rodkin, M., Heavy-Tailed Distributions in Disaster Analysis, inAdvances in Natural and Technological Hazards Research, Dordrecht: Springer, 2010, vol. 30.

    Google Scholar 

  38. Pisarenko, V. and Rodkin, M., Statistical Analysis of Natural Disasters and Related Losses. Springer Briefs in Earth Sciences. Dordrecht: Springer, 2013.

    Google Scholar 

  39. Pisarenko, V.F. and Rodkin, M.V., Raspredeleniya s tyazhelymi khvostami: prilozheniya k analizu katastrof, Vyp. 38, Vychislitel’naya seysmologiya (Heavy-Tailed Distributions: Applications for Catastrophe Analysis, vol. 38 of Computational Seismology), 2007, Moscow: GEOS.

  40. Pisarenko, V.F. and Rodkin, M.V., The instability of the Mmax parameter and an alternative to its using, Izv.,Phys. Solid Earth, 2009, vol. 45, no. 12, pp. 1081–1092.

    Article  Google Scholar 

  41. Pisarenko, V.F. and Sornette, D, Characterization of the Frequency of Extreme Earthquake Events by the Generalized Pareto Distribution, Pure Appl. Geophys., 2003, vol. 160, pp. 2343–2364.

    Article  Google Scholar 

  42. Pisarenko, V.F., Sornette, D., Statistical detection and characterization of a deviation from the Gutenberg–Richter distribution above magnitude 8, Pure Appl. Geophys., 2004, vol. 161, pp. 839–864.

    Article  Google Scholar 

  43. Pisarenko, V.F., Lyubushin, A.A., Lysenko, V.B., and Golubeva, T.V., Statistical estimation of seismic hazard parameters: maximum possible magnitude and related parameters, Bull. Seismol. Soc. Am., 1996, vol. 86, no. 3, pp. 691–700.

    Google Scholar 

  44. Pisarenko, V.F., Rodkin, M.V., and Rukavishnikova, T. A., Estimation of the probability of strongest seismic disasters based on the extreme value theory, Izv.,Phys. Solid Earth,2014, vol. 50, no. 3, pp. 311–324.

    Article  Google Scholar 

  45. 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.

    Article  Google Scholar 

  46. Pisarenko, V.F., Sornette, A., Sornette, D., and Rodkin, M.V., New approach to the characterization of Mmax and of the tail of the distribution of earthquake magnitudes, Pure Appl. Geophys., 2008, vol. 165, pp. 1–42.

    Article  Google Scholar 

  47. Pisarenko, V.F., Sornette, D., and Rodkin, M.V., Distribution of maximum earthquake magnitudes in future time intervals: application to the seismicity of Japan (1923–2007), Earth Planets Space, 2010, vol. 62, pp. 567–578.

    Article  Google Scholar 

  48. Romanovicz, B. and Rundle, J.B., On scaling relation for large earthquakes, Bull. Seismol. Soc. Am., 1993, vol. 83, no. 4, pp. 1294–1297.

    Google Scholar 

  49. Stephens, M.A., EDF statistics for goodness of fit and some comparisons, J. Am. Statist. Ass., 1974, vol. 68, no. 347. pp. 730–737.

    Article  Google Scholar 

  50. Utsu, T., Representation and analysis of the earthquake size distribution: A historical review and some new approaches, Pure Appl. Geophys., 1999, vol. 155, pp. 509–535.

    Article  Google Scholar 

  51. Ward, S.N., More on Mmax, Bull. Seismol. Soc. Am., 1997, vol. 87, no. 5, pp. 1199–1208.

    Google Scholar 

  52. Wesnousky, S.G., The Gutenberg-Richter or characteristic earthquake distribution, which is it? Bull. Seismol. Soc. Am., 1994, vol. 84, pp. 1940–1959.

    Google Scholar 

  53. Wu, Z.L., Frequency-size distribution of global seismicity seen from broad-band radiated energy, Geophys J. Int., 2000, vol. 142, pp. 59–66.

    Article  Google Scholar 

  54. Zalyapin, I. and Ben-Zion, Y., Earthquake clusters in Southern California I: Identification and stability, J. Geophys. Res., 2013, vol. 118, pp. 2847–2864.

    Article  Google Scholar 

  55. Zhuang, J., Werner, M.J, Hainzl S, Harte, D., and Zhou, S., Basic models of seismicity: spatiotemporal models, Community Online Resource for Statistical Seismicity Analysis, 2011. https://doi.org/10.5078/corssa-07487583

    Google Scholar 

  56. Zoller, G., Holschneider, V., and Hainzl, H., The maximum earthquake magnitude in a time horizon: theory and case studies, Bull. Seismol. Soc. Am., 2013, vol. 103, no. 2A, pp. 860–875.

    Article  Google Scholar 

Download references

Funding

The work was carried out as part of the state registration task AAAA-A19-119011490129-0 and supported by the Russian Foundation for Basic Research under project no. 17-05-00351.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. V. Rodkin.

Additional information

Translated by M. Nazarenko

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pisarenko, V.F., Rodkin, M.V. & Rukavishnikova, T.A. Stable Modification of Frequency–Magnitude Relation and Prospects for Its Application in Seismic Zoning. Izv., Phys. Solid Earth 56, 53–65 (2020). https://doi.org/10.1134/S1069351320010103

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1069351320010103

Keywords:

Navigation