Pure and Applied Geophysics

, Volume 174, Issue 6, pp 2411–2426 | Cite as

Test of the Predictability of the PI Method for Recent Large Earthquakes in and near Tibetan Plateau

  • Yongxian Zhang
  • Caiyun Xia
  • Cheng Song
  • Xiaotao Zhang
  • Yongjia Wu
  • Yan Xue


Five large earthquakes of M ≥ 7.0 (based on the magnitude scale of the China Earthquake Networks Center) occurred in and near the Tibetan Plateau during 2008–2014, including the Wenchuan M8.0 earthquake on May 12, 2008 (BJT). In this paper, the Tibetan Plateau was chosen to be the study region, and calculating parameters of pattern informatics (PI) method with grid of 1° × 1° and forecasting time interval of 8 years were employed for the retrospective study according to the previous studies for M7 earthquake forecasting. The sliding step of forecasting interval was 1 year, and the hotspot diagrams of each forecasting interval since 2008 were obtained year by year. The relationships among the hotspots and the M ≥ 7.0 earthquakes that occurred during the forecast intervals were studied. The predictability of PI method was tested by verification of receiver-operating characteristic curve (ROC) and R score. The results show that the successive obvious hotspots occurred during the sliding forecasting intervals before four of the five earthquakes, while hotspots only occurred in one forecasted interval without successive evolution process before one of the five earthquakes, which indicates that four of the five large earthquakes could be forecasted well by PI method. Test results of the predictability of PI method by ROC and R score show that positive prospect of PI method could be expected for long-term earthquake forecast.


PI method Earthquake predictability ROC test R score test Earthquake-forecasting efficacy Tibetan Plateau 



The authors gratefully acknowledge the support from the Chinese Ministry of Science and Technology under Grants No. 2010DFB20190 and No. 2012BAK19B02-05. The authors also thank Prof. J.B. Rundle for certain valuable comments on PI methods and the anonymous reviewers for their constructive comments on the paper. The authors also offer their thanks to CENC (China Earthquake Networks Center) for the earthquake catalogue.


  1. Bufe, C. G., & Varnes, D. J. (1993). Predictive modeling of the seismic cycle of the greater San Francisco Bay region. Journal of Geophysical Research, 98, 9871–9883.CrossRefGoogle Scholar
  2. Chang, L., Chen, C., & Wu, Y. (2013). A study on the pattern informatics and its application to earthquake prediction in Taiwan[C]//AGU Fall. Meeting Abstracts, 1, 2341.Google Scholar
  3. Chen, C. C., Rundle, J. B., Holliday, J. R., Nanjo, K. Z., Turcotte, D. L., Li, S. C., et al. (2005). The 1999 Chi-chi, Taiwan, earthquake as a typical example of seismic activation and quiescence. Geophysical Research Letters, 32, L22315.CrossRefGoogle Scholar
  4. Chen, C. C., Rundle, J. B., Li, H. C., et al. (2006). From tornadoes to earthquakes: forecast verification for binary events applied to the 1999 Chi-Chi, Taiwan, earthquake. Terrestrial Atmospheric and Oceanic Sciences, 17(3), 503–516.Google Scholar
  5. Cho, N. F., & TIAMPO, K. F. (2013). Effects of location errors in pattern informatics[J]. Pure Applied Geophysics, 170(1–2), 185–196.CrossRefGoogle Scholar
  6. Holliday, J. R., Nanjo, K. Z., Tiampo, K. F., Rundle, J. B., & Turcotte, D. L. (2005). Earthquake forecasting and its verification. Nonlinear Processes in Geophysics, 12, 965–977.CrossRefGoogle Scholar
  7. Holliday, J. R., Rundle, J. B., Tiampo, K. F., Klein, W., & Donnellan, A. (2006a). Modification of the pattern informatics method for forecasting large earthquake events using complex eigenfactors. Tectonophysics, 413, 87–91.CrossRefGoogle Scholar
  8. Holliday, J. R., Rundle, J. B., Tiampo, K. F., Klein, W., & Donnellan, A. (2006b). Systematic procedural and sensitivity analysis of the pattern informatics method for forecasting large (M ≥ 5) earthquake events in southern California. Pure Applied Geophysics, 163, 2433–2454.CrossRefGoogle Scholar
  9. Jaume, S. C., & Sykes, L. R. (1999). Evolving towards a critical point: a review of accelerating seismic moment/energy release prior to large and great earthquakes. Pure and Applied Geophysics, 155, 279–306.CrossRefGoogle Scholar
  10. Jiang, C. S., & Wu, Z. L. (2008). Retrospective forecasting test of a statistical physics model for earthquakes in Sichuan-Yunnan region. Science in China, Series D: Earth Sciences, 51(10), 1401–1410. doi: 10.1007/s11430-008-0112-6.CrossRefGoogle Scholar
  11. Jiang, C. S. & Wu, Z. L.(2011). PI forecast with or without de-clustering: an experiment for the Sichuan-Yunnan region. Natural Hazards and Earth System Sciences, 11, 697–706. doi: 10.5194/nhess-11-697-2011.
  12. Kanamori, H., & Anderson, D. L. (1975). Theoretical basis of some empirical relations in seismology. Bulletin of the Seismological Society of America, 65(5), 1073–1095.Google Scholar
  13. Kawamura, M., Wu, Y. H., Kudo, T., & Chen, C. C. (2013). Precursory migration of anomalous seismic activity revealed by the pattern informatics method: a case study of the 2011 Tohoku earthquake, Japan. Bulletin of the Seismological Society of America, 103(2B), 1171–1180.CrossRefGoogle Scholar
  14. Kawamura, M., Wu, Y. H., Kudo, T., & Chen, C. C. (2014). A statistical feature of anomalous seismic activity prior to large shallow earthquakes in Japan revealed by the pattern informatics method. Natural Hazards and Earth System Sciences, 14(4), 849.CrossRefGoogle Scholar
  15. Kossobokov, V. G., Romashkova, L. L., & Keilis-Borok, V. I. (1999). Testing earthquake prediction algorithms: statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992–1997. Physics of the Earth and Planetary Interiors, 111, 187–196.CrossRefGoogle Scholar
  16. Li, B. Y. (1987). On the Extent of the Qinghai-Xizang (Tibet) Plateau. Geographical Research (in Chinese with English abstract), 6(3), 57–64.Google Scholar
  17. Migan, A., & Tiampo, K. F. (2010). Testing the pattern informatics index on synthetic seismicity catalogues based on the non-critical PAST. Tectonophysics, 483, 255–268. doi: 10.1016/j.tecto.2009.10.023.CrossRefGoogle Scholar
  18. Molchang, M. (1997). Earthquake prediction as a decision-making problem. Pure and Applied Geophysics, 149, 233–247.CrossRefGoogle Scholar
  19. Moore, E. F. (1962). Machine models of self reproduction. In Proceedings of the fourteenth symposium on applied mathematics (pp. 17–33). American Mathematical Society.Google Scholar
  20. Nanjo, K. Z., Holliday, J. R., Chen, C. C., Rundle, J. B., & Turcotte, D. L. (2006a). Application of a modified pattern informatics method to forecasting the locations of future large earthquakes in the central Japan. Tectonophysics, 424, 351–366.CrossRefGoogle Scholar
  21. Nanjo, K. Z., Rundle, J. B., Holliday, J. R., et al. (2006b). Pattern informatics and its application for optimal forecasting of large earthquakes in Japan. Pure and Applied Geophysics, 163(11–12), 2417–2432.CrossRefGoogle Scholar
  22. Papazachos, C. B., Karakaisis, G. F., Scordilis, E. M., & Papazachos, B. C. (2005). Global observational properties of the critical earthquake model. Bulletin of the Seismological Society of America, 95, 1841–1855.CrossRefGoogle Scholar
  23. Rundle, J. B., Klein, W., Gross, S. J., & Tiampo, K. F. (2000a). Dynamics of seismicity patterns in systems of earthquake faults. In J. B. Rundle, D. L. Turcotte, & W. Klein (Eds.) Geo-complexity and the Physics of Earthquakes, vol. 120 of Geophysics Monograph Series (pp. 127–146). Washington, D. C: AGU.Google Scholar
  24. Rundle, J. B., Klein, W., Tiampo, K. F., & Gross, S. J. (2000b). Linear pattern dynamics in nonlinear threshold systems. Physical Review E, 61, 2418–2432.CrossRefGoogle Scholar
  25. Rundle, J. B., Klein, W., Turcotte, D. L., et al. (2000c). Precursory seismic activation and critical-point phenomena. Pure and Applied Geophysics, 157, 2165–2182.CrossRefGoogle Scholar
  26. Rundle, J. B., Tiampo, K. F., Klein, W., & Martins, J. S. S. (2002) Self-organization in leaky threshold systems: The influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting. Proceedings of the National Academy of Sciences of the United States of America, 99(Suppl. 1), 2514–2521.Google Scholar
  27. Rundle, J. B., Turcotte, D. L., Shcherbakov, R., Klein, W., & Sammis, C. (2003). Statistical physics approach to understanding the multiscale dynamics of earthquake fault systems. Reviews of Geophysics, 41, 1019–1038.CrossRefGoogle Scholar
  28. Shi, Y. L., Liu, J., & Zhang, G. M. (2000). The evaluation of Chinese annual earthquake prediction in the 90s. J Graduate School Academia Sin (in Chinese with English abstract), 17, 63–69.Google Scholar
  29. Swets, J. A. (1973). The relative operating characteristic in psychology. Science, 182, 990–1000.CrossRefGoogle Scholar
  30. Tiampo, K. F., Bowman, D. D., Colella, H. & Rundle, J. B. (2008). The stress accumulation method and the pattern informatics index: Complementary approaches to earthquake forecasting. Pure Applied. Geophysics, 165, 693–709, 0033–4553/08/030693–17. doi: 10.1007/s00024-008-0329-5.
  31. Tiampo, K. F., Klein, W., Li, H.-C., Migan, A., Toya, Y., Kohen-Kadosh, S. L. Z., et al. (2010). Ergodicity and earthquake catalogs: forecast testing and resulting implications. Pure and Applied Geophysics, 167, 763–782. doi: 10.1007/s00024-010-0076-2.CrossRefGoogle Scholar
  32. Tiampo, K. F., Rundle, J. B., McGinnis, S., Gross, S. J., & Klein, W. (2002a). Eigenpatterns in southern California seismicity. Journal of Geophysical Research, 107, 2354.CrossRefGoogle Scholar
  33. Tiampo, K. F., Rundle, J. B., McGinnis, S., & Klein, W. (2002b). Pattern dynamics and forecast methods in seismically active regions. Pure Applied Geophysics, 159, 2429–2467.CrossRefGoogle Scholar
  34. Tiampo, K. F., Rundle, J. B., McGinniss, S., et al. (2002c). Mean-field threshold systems and phase dynamics: an application to earthquake fault systems. Europhysics Letters, 60, 481–487.CrossRefGoogle Scholar
  35. Tiampo, K. F., & Shcherbakov, R. (2012). Seismicity-based earthquake forecasting techniques: ten years of progress. Tectonophysics, 522–523, 89–121. doi: 10.1016/j.tecto.2011.08.019.CrossRefGoogle Scholar
  36. Tiampo, K. F., & Shcherbakov, R. (2013). Optimization of seismicity-based forecasts. Pure and Applied Geophysics, 170, 139–154. doi: 10.1007/s00024-012-0457-9.CrossRefGoogle Scholar
  37. Wu, Y. H., Chen, C. C. & Rundle, J. B. (2008a) Detecting precursory earthquake migration patterns using the pattern informatics method. Geophysical Research Letters 35 (19) (Art. No. L19304).Google Scholar
  38. Wu, Y. H., Chen, C. C., & Rundle, J. B. (2008b). Precursory Seismic Activation of the Pingtung (Taiwan) Offshore Doublet Earthquakes on 26 December 2006: A Pattern Informatics Analysis. Terrestrial Atmospheric And Oceanic Sciences, 19(6): 743–749.Google Scholar
  39. Xia, C. Y., Zhang, Y. X., Zhang, X. T., & Wu, Y. J. (2014). Test of the predictability of PI method by two Ms7.3 earthquakes in Yutian County, Xinjiang Uygur Autonomous Region. Journal of Seismologica Sinica (In Chinese with English abstract), 37(1), 192–201.Google Scholar
  40. Xu, S. X. (1989). Mark evaluation for earthquake prediction efficacy. In: Department of Science and Technology Monitoring, State Seismological Bureau (Ed.) Collected Papers of Research on Practical Methods of Earthquake Prediction (Volume of Seismology) (in Chinese) (pp. 586–590). Beijing: Academic Books and Periodical Press.Google Scholar
  41. Xu, X. W., Zhang, P. Z., Wen, X. Z., Qin, Z. L., Chen, G. H., & Zhu, A. L. (2005). Features of active tectonics and recurrence behaviours of strong earthquakes in the western Sichuan Province and its adjacent regions[J]. Seismology and Geology, 27(3), 446–461. (in Chinese with English abstract).Google Scholar
  42. Zhang, P. Z. (1999). Late quaternary tectonic deformation and earthquake hazard in continental China[J]. Quaternary Sciences, 19(5), 404–413 (in Chinese with English abstract).Google Scholar
  43. Zhang, Y. L., Li, B. Y., & Zheng, D. (2002). A discussion on the boundary and area of the Tibetan Plateau in China. Geographical Research (in Chinese with English abstract), 21(1), 1–8.Google Scholar
  44. Zhang, Y. X., Zhang, X. T., Wu, Y. J., & Yin, X. C. (2013). Retrospective study on the predictability of pattern informatics to the Wenchuan M8.0 and Yutian M7.3 earthquakes. Pure and Applied Geophysics, 170((1-2)), 197–208. doi: 10.1007/s00024-011-0444-6. (Published online 2012).CrossRefGoogle Scholar
  45. Zhang, X. T., Zhang, Y. X, Xia, C. Y., Wu, Y. J., & Yu H. Z. (2014). A study on the PI anomaly before the Lushan M7.0 earthquake in the Sichuan-Yunnan region and neighboring areas. Journal of Seismologica Sinica (In Chinese with English abstract), 36(5), 780–789.Google Scholar
  46. Zhang, Y. X., Zhang, X. T., Yin, X. C. & Wu, Y. J. (2009). Study on the forecast effects of PI method to the North and Southwest China, Currency and Computation: Practice and Experience. New York: Wiley. doi: 10.1002/cpe.1515 ( (Published online).

Copyright information

© Springer International Publishing 2017

Authors and Affiliations

  1. 1.China Earthquake Networks CenterBeijingChina
  2. 2.Liaoning Earthquake AdministrationShenyangChina
  3. 3.Institute of Earthquake Science, China Earthquake AdministrationBeijingChina

Personalised recommendations