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The Unified Scaling Law for Earthquakes

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Abstract

This paper is a review of a long-continued research by many Russian and foreign scientists in the theory of self-organized criticality (SOC) in application to seismological data. We mean the Unified Scaling Law for Earthquakes (USLE). This law uses the spatial similarity of earthquake epicenters to derive a generalization of the classical Gutenberg–Richter relation. We discuss why this generalization is needed for practical problems that involve space–time parameters of seismicity, and we point out possible restrictions on practical applications. Several different methods are set forth for estimating the constants in USLE with examples of their practical use.

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REFERENCES

  1. Aki, K., A probabilistic synthesis of precursory phenomena, in Earthquake Prediction, Simpson, D.W. and Richards, P.G., Eds., An International Review, Maurice Ewing Ser., 1981, vol. 4, pp. 566‒574.

  2. Baiesi, M. and Paczuski, M., Scale-free networks of earthquakes and aftershocks, Phys. Rev., 2004, E 69. 066106.

    Google Scholar 

  3. Bak, P., Christensen, K., Danon, L., and Scanlon, T., Unified Scaling Law for Earthquakes, Phys. Rev. Lett., 2002, vol. 88, pp. 178 501–178 504.

  4. Ben-Zion, Y., Collective behavior of earthquakes and faults: continuum-discrete transitions, progressive evolutionary changes and different dynamic regimes, Rev. Geophys., 2008, vol. 46, RG4006, pp. 1–70.

    Article  Google Scholar 

  5. Bormann, P., Earthquake, magnitude, in Encyclopedia of Solid Earth Geophysics, Gupta, H., Ed., Heidelberg: Springer, 2011, pp. 207–217.

    Google Scholar 

  6. Castaños, H. and Lomnitz, C., PSHA: is it science?, Eng. Geology, 2002, vol. 66(3/4), pp. 315–318.

    Article  Google Scholar 

  7. Chelidze, T.L., A generalized fractal law of seismicity, Dokl. Akad. Nauk SSSR, 1990, vol. 314, no. 5, pp. 1104‒1105.

    Google Scholar 

  8. Christensen, K., Danon, L., Scanlon, T., and Bak, P., Unified scaling law for earthquakes, Proc. Nat. Acad. Sci., 2002, vol. 99, Suppl 1, pp. 2509–2513. https://doi.org/10.1073/pnas.012581099 ISSN: 0027-8424;

  9. Corral, A., Local distribution and rate fluctuation in unified scaling law for earthquakes, Phys. Rev. E, 2003, vol. 68, 035102[R]. https://doi.org/10.1103/PhysRevE.68.035102

  10. Corral, A., Universal local versus unified global scaling laws in the statistics of seismicity, Physica A, 2004, vol. 340, pp. 590–597.

    Article  Google Scholar 

  11. Dolgosrochnyi prognoz zemletryasenii. Metodicheskie rekomendatsii (Long-Term Earthquake Prediction. Recommended Procedures), Sadovskii, M.A., Ed., Moscow: IFZ AN SSSR, 1986.

    Google Scholar 

  12. Earthquake Research and Analysis: Seismology, Seismotectonic and Earthquake, Phys. Earth and Planet. Inter., 2001, vol. 125, pp. 65–83.

  13. Falconer, K., Fractal Geometry: Mathematical Foundations and Applications, Chichester etc.: John Wiley, Sons [ISBN 0-471-92287-0], 1990. XXII. 288 p.

  14. Feder, J., Fractals, N. Y.: Plenum Press, 1988.

    Book  Google Scholar 

  15. Gelfand, I., Guberman, Sh., Keilis-Borok, V., Knopoff, L., Press, F., Rantsman, E., Rotwain, I., and Sadovsky, A., Pattern recognition applied to earthquakes epicenters in California, Phys. Earth and Planet. Inter., 1976, vol. 11, pp. 227‒283.

    Article  Google Scholar 

  16. GHDB, Global Hypocenters Data Base CD-ROM, NEIC/USGS, Denver, CO, 1989 and its updates through December 2015.

  17. Giardini, D., Grünthal, G., Shedlock, K.M., and Zhang, P., The GSHAP Global Seismic Hazard Map, Annali di Geofisica, 1999, vol. 42[6], pp. 1225‒1230. https://doi.org/10.4401/ag-3784

    Article  Google Scholar 

  18. Gorshkov, A., Kossobokov, V., and Soloviev, A., Recognition of earthquake-prone areas, in Nonlinear Dynamics of the Lithosphere and Earthquake Prediction, Keilis-Borok, V. and Soloviev, A., Eds., Heidelberg: Springer, 2003. P. 239‒310.

    Google Scholar 

  19. Gospodinov, D., Marekova, E., and Marinov, Al., Verifying the dependence of fractal coefficients on different spatial distributions, AIP Conference Proceedings 1203, Melville, NY: AIP Publishing, 2010, vol. 3, pp. 731. https://doi.org/10.1063/1.3322545.

  20. Grassberger, P. and Procaccia, I., Characterization of strange attractors, Phys. Rev. Lett., 1983, vol. 50, pp. 346.

    Article  Google Scholar 

  21. Gutenberg, B. and Richter, C.F., Frequency of earthquakes in California, Bull. Seismol. Soc. Am., 1944, vol. 34, pp. 185‒188.

    Google Scholar 

  22. Gutenberg, B. and Richter, C.F., Seismicity of the Earth, Princeton, N. J.: Princeton University Press, 1954.

    Google Scholar 

  23. Kagan, Y.Y. and Knopoff, L., Spatial distribution of earthquakes: the two-point correlation function, Geophys. J. R., Astr. Soc., 1980, vol. 62, no. 2, pp. 303‒320. https://doi.org/10.1111/j.1365-246X.1980.tb04857.x

    Article  Google Scholar 

  24. Keilis-Borok, V.I., The lithosphere of the Earth as a nonlinear system with implications for earthquake prediction, Rev. Geophys., 1990, vol. 28, pp. 19–34.

    Article  Google Scholar 

  25. Keilis-Borok, V.I. and Kossobokov, V.G., A set of long-term precursor for world great earthquakes, in Zemletryaseniya i preduprezhdenie stikhinykh bedstvii (Earthquakes and Prevention of Natural Disasters), 27th Geological Congress, August 4–14, 1984, Moscow, Colloquium C6, vol. 61, Moscow: Nauka, 1984, pp. 56–66.

  26. Keilis-Borok, V.I., Kossobokov, V.G., and Mazhkenov, S.A., On self-similarity in the spatial distribution of seismicity, in Teoriya i algoritmy interpretatsii geofizicheskikh dannykh (Theory and Algorithms for Interpretation of Geophysical Data), Vychisl. Seismol., 22, Moscow: Nauka, 1989, pp. 28–40.

  27. Kocharyan, G.G., Geomekhanika razlomov (Fault Geomechanics), Moscow: GEOS, 2016.

  28. Körting, G.C.O., Lateinisch-romanisches Wörterbuch, 1891–1907: [LRW: (Etymologisches Wörterbuch der romanischen Hauptsprachen)]. Paderborn: F. Schöningh, 1891; 2.e, vermehrte u. verbess. Aufl.: 1901 (LRW); 3.e, vermehrte u. verbess. Aufl.: 1907 (LRW).

  29. Kossobokov, V.G., Prognoz zemletryasenii i geodinamicheskie protsessy (Earthquake Prediction and Geodynamic Processes), Part I, Prognoz zemlenii: osnovy, realizatsiya, perspektivy (Earthquake Prediction: Pronciples, Implementation, Prospects), Vychisl. Seismol. 36, Moscow: GEOS, 2005.

  30. Kossobokov, V.G., Testing an earthquake prediction algorithm: The 2016 New Zealand and Chile earthquakes, Pure Appl. Geophys., 2017, vol. 174, no. 5, pp. 1845‒1854. https://doi.org/10.1007/s00024-017-1543-9

    Article  Google Scholar 

  31. Kossobokov, V., Unified Scaling Law for Earthquakes that generalizes the fundamental Gutenberg-Richter relationship, Encyclopedia of Solid Earth Geophysics, Gupta, H., Ed., Encyclopedia of Earth Sciences Series, 2nd Edition, 2020. https://doi.org/10.1007/978-3-030-10475-7_257-1

    Book  Google Scholar 

  32. Kossobokov, V.G. and Mazhkenov, S.A., Spatial Characteristics of Similarity for Earthquake Sequences: Fractality of Seismicity, in Lecture Notes of the Workshop on Global Geophysical Informatics with Applications to Research in Earthquake Prediction and Reduction of Seismic Risk, 15 Nov.–16 Dec., 1988, ICTP, Trieste, 1988.

  33. Kosobokov, V.G. and Mazhkenov, S.A., On similarity in the spatial distribution of seismicity, in Computational Seismology and Geodynamics, Chowdhury, D.K., Ed.,Am. Geophys. Un., 1, Washington, D.C.: The Union, 1994. pp. 6‒15.

  34. Kossobokov, V. and Nekrasova, A., Generalized Gutenberg-Richter recurrence law, in Geophysical Research Abstracts, 5, Abstracts of the Contributions of the EGS-AGU-EGU Joint Assembly, Nice, France, 06‒11 April, 2003 [CD-ROM]: EAE03-A-06597.

  35. Kossobokov, V.G. and Nekrasova, A.K., A general self-similarity law for earthquakes: A global map of parameters, in Analiz geodinamicheskikh i seismicheskikh protsessov (The Analysis of Geodynamic and Seismic Processes), Vychisl. Seismol., 35, Moscow: GEOS, 2004, pp. 160–175.

  36. Kossobokov, V.G. and Nekrasova, A.K., The maps of the global seismic hazard assessment program (GSHAP) are in error, Voprosy Inzhenern. Seismol., (ISSN 0132-2826), 2011, no. 38(1), pp. 65‒76.

  37. Kossobokov, V.G. and Nekrasova, A.K., Characterizing aftershock sequences of the recent strong earthquakes in Central Italy, Pure Appl. Geophys., 2017, vol. 174, no. 10, pp. 3713‒3723. https://doi.org/10.1007/s00024-017-1624-9

    Article  Google Scholar 

  38. Kossobokov, V.G. and Nekrasova, A., Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: Greater Caucasus and Crimea, J. Seismology, 2018a, vol. 22, pp. 1157–1169. https://doi.org/10.1007/s10950-018-9759-4

    Article  Google Scholar 

  39. Kossobokov, V.G. and Nekrasova, A., Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: Altai–Sayan region, Natural Hazards, 2018b, vol. 93(3), pp. 1435–1449. https://doi.org/10.1007/s11069-018-3359-z

    Article  Google Scholar 

  40. Kossobokov, V.G. and Nekrasova, A.K., Aftershock sequences of the recent major earthquakes in New Zealand, Pure and Applied Geophysics, 2019, vol. 176, no. 1, pp. 1‒23. https://doi.org/10.1007/s00024-018-2071-y

    Article  Google Scholar 

  41. Kossobokov, V.G., Keilis-Borok, V.I., Turcotte, D.L., and Malamud, B.D., Implications of a statistical physics approach for earthquake hazard assessment and forecasting, Pure Appl. Geophys., 2000, vol. 157, pp. 2323‒2349.

    Article  Google Scholar 

  42. Kossobokov, V., Peresan, A., and Panza, G.F., Reality check: Seismic hazard models you can trust, EOS Earth & Space Sci. News, 2015, vol. 96, no. 13, pp. 9‒11. https://doi.org/10.1029/2015EO031919

    Article  Google Scholar 

  43. Mandelbrot, B.B., How long is the coast of Britain? Statistical self-similarity and fractional dimension, Science, 1967, vol. 156, pp. 636–638.

    Article  Google Scholar 

  44. Mandelbrot, B.B., Fractals: Form, Chance and Dimension, N.Y.: W.H. Freeman & Company, 1977.

    Google Scholar 

  45. Mandelbrot, B.B., The Fractal Geometry of Nature, New York: Times Books, 1982.

    Google Scholar 

  46. Mandelbrot, B.B., Multifractal measures, especially for the geophysicist, Pure Appl. Geophys., 1989, vol. 131, pp. 5–42.

    Article  Google Scholar 

  47. Molchan, G.M., Interevent time distribution of seismicity: a theoretical approach, Pure Appl. Geophys., 2005, vol. 162, pp. 1135‒1150.

    Article  Google Scholar 

  48. Molchan, G.M., Fractal seismicity and seismic risk, Izvestiya, Physics of the Solid Earth, 2020, vol. 56, no. 1, pp. 66‒73. https://doi.org/10.1134/S1069351320010073

    Article  Google Scholar 

  49. Molchan, G. and Kronrod, T., Seismic interevent time: A spatial scaling and multifractality, Pure Appl. Geophys., 2007, vol. 164, no. 1, pp. 75–96.

    Article  Google Scholar 

  50. Molchan, G. and Kronrod, T., The fractal description of seismicity, Geophys. J. International, 2009, vol. 179, no. 3, pp. 1787‒1799.

    Article  Google Scholar 

  51. Molchan, G.M., Kronrod, T.L., Dmitrieva, O.E., and Nekrasova, A.K., A multiscale model of seismicity in seismic risk problems: Italy, in Sovremennye problemy seismichnosti i dinamiki Zemli (Contemporary Problems in Seismicity and Geodynamics), Vychisl. Seismol. 28, Moscow: Nauka, 1996, pp. 193–224.

  52. Molchan, G., Kronrod, T., and Panza, G.F., Multi-scale seismicity model for seismic risk, Bull. Seism. Soc. Am., 1997, vol. 87, no. 5, pp. 1220‒1229.

    Google Scholar 

  53. Nekrasova, A. and Kossobokov, V., Generalizing the Gutenberg-Richter scaling law, EOS Trans. AGU, 2002, vol. 83(47), Fall Meet. Suppl., Abstract NG62B-0958.

  54. Nekrasova, A. and Kossobokov, V., Generalized Gutenberg-Richter recurrence law: Global map of parameters, in Geophysical Research Abstracts, 5, Abstracts of the Contributions of the EGS-AGU-EGU Joint Assembly, Nice, France, 06‒11 April, 2003 [CD-ROM]: EAE03-A-03801.

  55. Nekrasova, A. and Kossobokov, V., Unified Scaling Law for Earthquakes: Mega-cities and urban agglomerations, in Eos Trans AGU, 2005, vol. 86(52), Fall Meet Suppl., Abstract S23A-0229.

  56. Nekrasova, A.K. and Kossobokov, V.G., The unified scaling law for earthquakes: The Crimea and the North Caucasus, Dokl. Akad. Nauk, 2016, vol. 470, no. 4, pp. 468–470.

    Google Scholar 

  57. Nekrasova, Anastasia K. and Kossobokov, Vladimir G., Unified Scaling Law for Earthquakes: Global map of parameters, in ISC’s Seismological Dataset Repository, 2019. https://doi.org/10.31905/XT753V44 http://www.isc.ac.uk/dataset_repository/recent_submissions.php

  58. Nekrasova, A., Kossobokov, V., Aoudia, A., Peresan, A., and Panza, G.F., A multiscale application of the Unified Scaling Law for Earthquakes in the central Mediterranean area and Alpine region, Pure Appl. Geophys., 2011, vol. 168, pp. 297‒327. Springer Basel AG. ;https://doi.org/10.1007/s00024-010-0163-4

  59. Nekrasova, A.K., Kossobokov, V.G., and Parvez, I.A., Assessment of seismic hazard and seismic risk using the Unified Scaling Law for earthquakes: The Himalaya and adjacent regions, Fizika Zemli, 2015a, no. 2, pp. 116–125.

  60. Nekrasova, A., Kossobokov, V., Parvez, I.A., and Tao, X., Seismic hazard and risk assessment based on the unified scaling law for earthquakes, Acta Geod. Geophys., ISSN 2213-5812, 2015b, vol. 50, no. 1, pp. 21‒37. https://doi.org/10.1007/s40328-014-0082-4

  61. Nekrasova, A.K., Kossobokov, V.G., Parvez, I.A., and Tao, H., The unified scaling law for earthquakes in application to the assessment of sesmic hazard and associated risks, Fizika Zemli, 2020, no. 1, pp. 96‒108. https://doi.org/10.31857/S0002333720010093

  62. Okubo, P.G. and Aki, K., Fractal geometry in the San Andreas Fault system, J. Geophys. Res., 1987, vol. 92(B1), pp. 345‒356.

    Article  Google Scholar 

  63. Öncel, A.I., Wilson, T.H., and Nishizawa, O., Size scaling relationships in the active fault networks of Japan and their correlation with Gutenberg-Richter b-values, J. of Geophys. Res., 2001, vol. 106, pp. 21827‒21841. https://doi.org/10.1029/2000JB900408

    Article  Google Scholar 

  64. Pagani, M., Garcia-Pelaez, J., Gee, R., Johnson, K., Poggi, V., Styron, R., Weatherill, G., Simionato, M., Viganò, D., Danciu, L., and Monelli, D., Global Earthquake Model [GEM] Seismic Hazard Map [version 2018.1—December 2018]. 2018. https://doi.org/10.13117/GEM-GLOBAL-SEISMIC-HAZARD-MAP-2018.1

    Book  Google Scholar 

  65. Panza, G. F. and Bela, J., NDSHA: A new paradigm for reliable seismic hazard assessment, Engineering Geology, 2020, https://doi.org/10.1016/j.enggeo.2019.105403

  66. Panza, G. F., Vaccari, F., Costa, G., Suhadolc, P., and Faeh, D., Seismic input modelling for zoning and microzoning, Earthquake Spectra, 1996, vol. 12(3), pp. 529–566. https://doi.org/10.1193/1.1585896

    Article  Google Scholar 

  67. Panza, G.F., La Mura, C., Peresan, A., Romanelli, F., and Vaccari, F., Chapter three ‒ Seismic hazard scenarios as preventive tools for a disaster resilient society, Advances in Geophysics, 2012, vol. 53, pp. 93–165. https://doi.org/10.1016/B978-0-12-380938-4.00003-3

    Article  Google Scholar 

  68. Panza, G.F., Romanelli, F., and Vaccari, F., Seismic wave propagation in laterally heterogeneous anelastic media: theory and applications to seismic zonation, Adv. Geophys., 2001, vol. 43, pp. 1–95.

    Article  Google Scholar 

  69. Parvez, I., Nekrasova, A.K., and Kossobokov, V.G., Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: State of Gujarat, India, Pure Appl. Geophys., 2017, vol. 174, pp. 1441‒1452. Springer International Publishing. https://doi.org/10.1007/s00024-017-1475-4

  70. Parvez, I.A., Magrin, A., Vaccari, F., Ashish, Mir R.R., Peresan, A., and Panza, G.F., Neo-deterministic seismic hazard scenarios for India—a preventive tool for disaster mitigation, Journal of Seismology, 2017, vol. 21, no. 6, pp. 1559–1575. https://doi.org/10.1007/s10950-017-9682-0

    Article  Google Scholar 

  71. Parvez, I.A., Nekrasova, A., and Kossobokov, V., Estimation of seismic hazard and risks for the Himalayas and surrounding regions based on Unified Scaling Law for Earthquakes, Natural Hazards, 2014, vol. 71(1), pp. 549–562.

    Article  Google Scholar 

  72. Peresan, A. and Gentili, S., Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach, Phys. of the Earth and Planet. Interiors, 2018, vol. 274, pp. 87–104.

    Article  Google Scholar 

  73. Peresan, A. and Gentili, S., Identification and characterisation of earthquake clusters: a comparative analysis for selected sequences in Italy and adjacent regions, Bollettino di Geofisica Teorica ed Applicata, 2020, vol. 61, no. 1, pp. 57‒80. https://doi.org/10.4430/bgta0249

    Article  Google Scholar 

  74. Pisarenko, V. and Golubeva, T., The use of stable laws in seismicity models, in Sovremennye problemy seismichnosti i dinamiki Zemli (Contemporary Problems in Seismicity and Geodynamics), Vychisl. Seismol. 28, Moscow: Nauka, 1996, pp. 153–174.

  75. Richter, C. F., An instrumental earthquake magnitude scale, Bull. Seismol. Soc. Am., 1935, vol. 25(1), pp. 1–32.

    Google Scholar 

  76. Riznichenko, Yu.V., On the study of seismicity, Izv. AN SSSR, Ser. Geofiz., 1958, no. 9, pp. 1057‒1074.

  77. Sadovskii, M.A., The Natural Lumpiness of Rocks, Dokl. Akad. Nauk SSSR, 1979, vol. 247, no. 4, pp. 829–831.

    Google Scholar 

  78. Sadovsky, M.A., The self-similarity of seismic processes, in Fizicheskie osnovy prognozirovaniya razrusheniya gornykh porod pri zemletryaseniyakh (The Physical Principles of Rock Failure during Earthquakes), Moscow: Nauka, 1987, pp. 6-12.

  79. Sadovsky, M.A., Nersesov, I.L., and Pisarenko, V.F., The hierarchical discrete structure of the lithosphere and the seismic process, in Sovremennaya tektonicheskaya aktivnost Zemli i seismichnost (Present-Day Tectonic Activity of the Earth and Seismicity), Moscow: Nauka, 1987, pp. 182‒191.

  80. Sadovsky, M.A. and Pisarenko, V.F., Self-similarity in geophysics, Priroda, 1991, no. 1, pp. 13‒23.

  81. Schwartz, D.P. and Coppersmith, K.J., Fault behavior and characteristic earthquake: Example from the Wasatch and San-Andreas fault zones, J. Geophys. Res., 1984, vol. 89(B7), pp. 5681‒5698.

    Article  Google Scholar 

  82. Smirnov, V.B., The occurrence of earthquakes and seismicity parameters, Vulkanol. Seismol., 1995, no. 3, pp. 59‒70.

  83. Smirnov, V.B., Estimating the duration of the lithospheric failure cycle from earthquake catalogs, Izvestiya, Physics of the Solid Earth, 2003, vol. 39, no. 10, pp. 794–811.

    Google Scholar 

  84. Smirnov, V.B., Ommid, 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, Izvestiya, Physics of the Solid Earth, 2019, vol. 55, no. 5, pp. 701–718.

    Article  Google Scholar 

  85. Stakhovsky, I.R., Scale invariance of crustal seismicity and predictive signs of approaching earthquakes, UFN, 2017, vol. 187, no. 5, pp. 505‒524.

    Article  Google Scholar 

  86. Turcotte, D.L., Fractals and Chaos in Geology and Geophysics, Cambridge, U.K.: Cambridge Univ. Press, 1997. https://doi.org/10.1017/CBO9781139174695

    Book  Google Scholar 

  87. Wyss, M., Nekrasova, A., and Kossobokov, V., Errors in expected human losses due to incorrect seismic hazard estimates, Nat. Hazards, 2012, vol. 62(3), pp. 927–935.

    Article  Google Scholar 

  88. Zaliapin, I. and Ben-Zion, Y., Earthquake clusters in southern California: Identification and stability, Geophys. Res., 2013, vol. 118[6], pp. 847–2864. https://doi.org/10.1002/jgrb.50179

    Article  Google Scholar 

  89. Zaliapin, I. and Ben-Zion, Y., A global classification and characterization of earthquake clusters, Geophysical Journal International, 2016, vol. 207, no. 1, pp. 608–634. https://doi.org/10.1093/gji/ggw300

    Article  Google Scholar 

  90. Zaliapin, I., Gabrielov, A., Keilis-Borok, V., and Wong, H., Clustering analysis of seismicity and aftershock identification, Phys. Rev. Lett., 2008, vol. 101(1), pp. 018501. https://doi.org/10.1103/PhysRevLett.101.018501

    Article  Google Scholar 

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Funding

We thank the Russian Foundation for Basic Research (RFBR) for the financial support of this paper, project no. 19-15-50252.

Our own research reviewed in this paper was carried out for the State Assignment of the Institute of Earthquake Prediction Theory for 2019‒2021.

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  1. Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, ul. Profsoyuznaya, 84/32, 117997, Moscow, Russia

    A. K. Nekrasova & V. G. Kossobokov

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Nekrasova, A.K., Kossobokov, V.G. The Unified Scaling Law for Earthquakes. J. Volcanolog. Seismol. 14, 353–372 (2020). https://doi.org/10.1134/S0742046320060056

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