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Staging of Occurrence of Seismicity Anomalies before Earthquakes in Kamchatka, Japan and Iceland

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Abstract—The paper presents the results of a study showing that anomalies in the seismic regime parameters before earthquakes of various magnitudes occur in stages. The occurrence in stages means the correlation between the times of formation and development of anomalies in various seismic regime parameters. Earthquakes in regions with two general types of tectonics are selected for analysis: in the subduction zone (Kamchatka and Japan) and in the rift zone (Iceland). The selection of regions is primarily based on the availability and quality of regional seismic catalogs. GR b-value and the composite parameter known as the RTL are used as the seismic regime parameters. The detection of spatiotemporal anomalies before the selected earthquakes is based on the known “precursory patterns” of the seismic regime parameters. Comparing the durations of the detected anomalies shows that the anomalies of b-value generally occur earlier than the RTL anomalies. Possible reasons why the anomalies occur in stages are suggested. In the vicinity of the studied earthquakes, a change in the seismogenic rupture concentration parameter within the corresponding seismic cycles is also estimated. Comparing the times at which the detected seismic regime anomalies occur with the values of the seismogenic rupture concentration parameter corresponding to these times shows that the formation of seismic regime anomalies occurs at a stage when the system of seismogenic ruptures accumulated during the seismic cycle has almost reached its critical value.

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Notes

  1. https://cloud.mail.ru/public/rfq3/CNDPQRZ7r

  2. https://gitlab.com/Mr.Brain/PyRTL

  3. https://sdis.emsd.ru/info/earthquakes/catalogue.php

  4. https://sdis.emsd.ru/info/earthquakes/catalogue.php?out=info

  5. ftp://isc-mirror.iris.washington.edu/pub/

  6. http://hraun.vedur.is/ja/viku/

  7. https://sdis.emsd.ru/info/earthquakes/catalogue.php?out=info&informationShow=show#Mw=f(Ml)

REFERENCES

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

    Google Scholar 

  2. Chebrov, V.N., Droznin, D.V., Kugaenko, Yu.A., Levina, V.I., Senyukov, S.L., Sergeev, V.A., Shevchenko, Yu.V., and Yashchuk, V.V., The system of detailed seismological observations in Kamchatka in 2011, J. Volcanol. Seismol., 2013, vol. 7, no. 1, pp. 16–36. https://doi.org/10.1134/S0742046313010028

    Article  Google Scholar 

  3. Chebrova, A.Yu., Chemarev, A.S., Matveenko, E.A., and Chebrov, D.V., Unified Seismological Data Information System of the Kamchatka Branch of the Federal Research Center “Unified Geophysical Survey of the Russian Academy of Sciences”: organization principles, main elements and key functions, Geofiz. Issled., 2020, vol. 21, no. 3, pp. 66–91. https://doi.org/10.21455/gr2020.3-5

    Article  Google Scholar 

  4. Kail, R., Zaytsev, A., and Burnaev, E., Recurrent convolutional neural networks help to predict location of earthquakes, IEEE Geosci. Remote Sens. Lett., 2021, vol. 19, Article ID 8019005.

    Google Scholar 

  5. Kendall, M.D. and Stuart, A., The Advanced Theory of Statistics, Vol. 2: Inference and Relationship, London: Griffin, 1961.

    Google Scholar 

  6. Mikhailov, V.O., Nazaryan, A.N., Smirnov, V.B., Diament, M., Shapiro, N., Kiseleva, E.A., Tikhotskii, S.A., Polyakov, S.A., Smol’yaninova, E.I., and Timoshkina, E.P., Joint inversion of the differential satellite interferometry and GPS data: a case study of Altai (Chuia) earthquake of September 27, 2003, Izv., Phys. Solid Earth, 2010, vol. 46, no. 2, pp. 91–103.

    Article  Google Scholar 

  7. Myachkin, V.I., Sobolev, G.A., Dolbilkina, N.A., Morozow, V.N., and Preobrazensky, V.B., The study of variations in geophysical fields near focal zones of Kamchatka, Tectonophysics, 1972, vol. 14, no. 3, pp. 287–293.

    Article  Google Scholar 

  8. Mjachkin, V.I., Brace, W.F., Sobolev, G.A., and Dietrich, J.H., Two models for earthquake forerunners, Pure Appl. Geophys., 1975, vol. 113, pp. 169–181.

    Article  Google Scholar 

  9. Myachkin, V.I., Kostrov, B.V., Sobolev, G.A., and Shamina, O.G., Fundamentals of source physics and earthquake precursors, in Fizika ochaga zemletryaseniya (Physics of the Earthquake Source). Moscow: Nauka, 1975, pp. 6–29.

  10. Nagao, T., Takeuchi, A., and Nakamura, K., A new algorithm for the detection of seismic quiescence: Introduction of the RTM algorithm, a modified RTL algorithm, Earth, Planets Space, 2011, vol. 63, pp. 315–324. https://doi.org/10.5047/eps.2010.12.007

    Article  Google Scholar 

  11. Earthquakes and Sustainable Infrastructure, Panza, G.F., Kossobokov, V.G., Laor, E., and De Vivo, B., Eds., Amsterdam: Elsevier, 2021.

  12. Petrushov, A.A. and Smirnov, V.B., Svidetel’stvo o gosudarstvennoi registratsii programmy dlya EVM (Computer Software State Registration Certificate), no. 2022611056, 2022.

  13. Proskura, P., Zaytsev, A., Braslavsky, I., Egorov, E., and Burnaev, E., Usage of multiple RTL features for earthquakes prediction, in Computational Science and Its Applications, ICCSA 2019, Lecture Notes in Computer Science, vol. 11619, Cham: Springer, pp. 556–565. https://doi.org/10.1007/978-3-030-24289-3_41

  14. Sadovsky, M. A., Pisarenko, V.F., and Steinberg, V.V., On the dependence of earthquake energy on the seismic focus volume, Dokl. Akad. Nauk SSSR, 1983, vol. 271, no. 3, pp. 598–602.

    Google Scholar 

  15. Saltykov, V.A. and Konovalova, A.A., Monitoring variations in the slope of the Kamchatka earthquake recurrence schedule: methods and examples, in Problemy kompleksnogo geofizicheskogo monitorings Dal’nego Vostoka Rossii: Trudy Vtoroi regional’noi nauchno-tekhnicheskoi konf. (Problems of Comprehensive Geophysical Monitoring in the Far East of Russia: Proc. 2nd Regional Scientific and Technical Conf.), Chebrov, V.N., Ed., Petropavlovsk-Kamchatskii, 2009, Petropavlovsk-Kamchatskii: GS RAN, 2010, pp. 235–238.

  16. Saltykov, V.A., Kugaenko, Yu.A., Kravchenko, N.M., and Konovalova, A.A., A parametric representation of Kamchatka seismicity over time, J. Volcanol. Seismol., 2013, vol. 7, no. 1, pp. 58–75.

    Article  Google Scholar 

  17. Scholz, C.H., Sykes, L.R., and Aggarwal, Y.P., Earthquake prediction: a physical basis, Science, 1973, vol. 181, no. 4102, pp. 803–810.

    Article  Google Scholar 

  18. Sidorin, A.Ya., Predvestniki zemletryasenii (Earthquake Peecursors), Moscow: Nauka, 1992.

  19. Smirnov, V.B. and Ponomarev, A.V., Fizika perekhodnykh rezhimov seismichnosti (Physics of Seismicity Transient Modes), Moscow: RAN, 2020.

  20. Smirnov, V.B. and Zavyalov, A.D., Incorporating the fractal distribution of faults as a measure of failure concentration, J. Volcanol. Seismol., 1997, vol. 18, no. 4, pp. 447–452.

    Google Scholar 

  21. Smirnov, V.B. and Zavyalov, A.D., Seismic response to electromagnetic sounding of the Earth’s lithosphere, Izv., Phys. Solid Earth, 2012, vol. 48, no. 7–8, pp. 615–639.

    Article  Google Scholar 

  22. Smirnov, V.B., Ommi, S., Potanina, M.G., Mikhailov, V.O., Petrov, A.G., Shapiro, N.M., and Ponomarev, A.V., Estimates of lithospheric failure cycle parameters from regional earthquake catalogues, Izv., Phys. Solid Earth, 2019, vol. 55, no. 5, pp. 701–718.

    Article  Google Scholar 

  23. Sobolev, G.A., Fizicheskie osnovy prognoza zemletryasenii (Physical Basis for Earthquake Prediction), Moscow: Nauka, 1993.

  24. Sobolev, G.A., Kontseptsiya predskazuemosti zemletryasenii na osnove dinamiki seismichnosti pri triggernom vozdeistvii (The Concept of Earthquake Predictability Based on the Dynamics of Seismicity under Trigger Effect), Moscow: IFZ RAN, 2011.

  25. Sobolev, G.A., Avalanche unstable fracturing formation model, Izv., Phys. Solid Earth, 2019, vol. 55 no. 1, pp. 138–151.

    Article  Google Scholar 

  26. Sobolev, G.A. and Ponomarev, A.V., Fizika zemletryasenii i predvestniki (Earthquake Physics and Precursors), Moscow: Nauka, 2003.

  27. Sobolev, G.A. and Zavyalov, A.D., A concentration criterion for seismically active faults, Dokl. Akad. Nauk SSSR, 1980, vol. 252, no. 1, pp. 69–71.

    Google Scholar 

  28. Sobolev, G.A., Tyupkin, Yu.S., Smirnov, V.B., and Zavyalov, A.D., Method of medium–term earthquake prediction, Dokl. Akad. Nauk, 1996, vol. 347, no. 3, pp. 405–407.

    Google Scholar 

  29. Stefánsson, R., Advances in Earthquake Prediction, Berlin: Springer, 2011.

    Book  Google Scholar 

  30. Zavyalov, A.D., Srednesrochnyi prognoz zemletryasenii: osnovy, metodika, realizatsiya (Medium-Term Earthquake Forecasting: Basic Principles, Methods, Implementation), Moscow: Nauka, 2006.

  31. Zhang, Y. and Huang, Q., Seismicity changes before major earthquakes in Sichuan, China, revealed by a combination of the RTL algorithm and ETAS model, Seismol. Res. Lett., 2023, vol. 94, no. 2A, pp. 844–851. https://doi.org/10.1785/0220220282

    Article  Google Scholar 

  32. Zhurkov, S.N., Kuksenko, V.S., Petrov, V.A., Savel’ev, V.N., and Sultonov, U.S., On prediction of rock failure, Izv. Akad. Nauk SSSR, Fiz. Zemli, 1977, no. 6, pp. 11–18.

  33. Zhurkov, S.N., Kuksenko, V.S., Petrov, V.A., Savel’ev, V.N., and Sultanov, U.S., Concentration criterion for volumetric fracture of solids, in Fizicheskie protsessy v ochagakh zemletryasenii (Physical Processes in Earthquake Sources), Sadovskii, M.A. and Myachkin, V.I., Eds., Moscow: Nauka, 1980, pp. 78–86.

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ACKNOWLEDGMENTS

This study is based on the data (regional catalog of Kamchatka earthquakes) obtained at the unique research facilities “Seismic infrasound array for monitoring Arctic cryolithozone and continuous seismic monitoring of the Russian Federation, neighboring territories and the world” (https://ckp-rf.ru/usu/507436/).

Funding

This study was funded by the Russian Science Foundation, Grant No. 23-27-00067 “Staging of seismicity anomalies manifestation before strong earthquakes ”.

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Correspondence to V. B. Smirnov.

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Smirnov, V.B., Petrushov, A.A. Staging of Occurrence of Seismicity Anomalies before Earthquakes in Kamchatka, Japan and Iceland. Izv., Phys. Solid Earth 59, 717–732 (2023). https://doi.org/10.1134/S1069351323050129

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