Journal of Earth Science

, Volume 29, Issue 1, pp 230–236 | Cite as

Short-Impending Earthquake Anomaly Index Extraction of GNSS Continuous Observation Data in Yunnan, Southwestern China

Geodynamics
  • 1 Downloads

Abstract

This paper presents a comprehensive area expansion prediction index method to apply GNSS for short-impending prediction of earthquakes. Based on continuous GNSS observation data from Yunnan Province, a displacement field was detected after data cycle-slip repair using precision data processing software and geophysical field effect model correction. The Yunnan area was divided into 56 grid cells for displacement field interpolation to obtain a more uniform displacement field and a strain field variation time series. The pre-earthquake response of each grid-cell expansion time series was evaluated and synthesized to extract a short-impending earthquake anomaly identification index. The results show that this index indicated occurrence times and hypocenter for earthquakes of magnitude M≥5. Fourteen earthquakes were predicted accurately, and there were five false reports. This index can therefore be used for the short-impending prediction of earthquakes.

Key words

GNSS short-impending earthquake prediction strain anomaly index southwestern China 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

We would like to thank the Crustal Movement Monitoring Engineering Research Center for providing the GNSS continuous observation data. This study was supported by the National 973 Project of China (No. 2013CB733303), the National Natural Science Foundation of China (No. 41474093), the Key Natural Science Foundation of Hubei Province (No. 2014CFA110), the open fund of Key Laboratory of Geospace Environment and Geodesy, Ministry of Education (No. 15-02-07), the China Earthquake Administration’s Earthquake Science and Technology Spark Program (No. XH15037SX), Special fund of earthquake science and technology of Yunnan Earthquake Agency (No. 2017ZX02), and the Jiancheng Li Academician Workstation (No. 2015IC015). The final publication is available at Springer via https://doi.org/10.1007/s12583-018-0826-0.

References Cited

  1. Barzegari, A., Esmaeili, R., Ebrahimi, M., et al., 2016. Evaluation of Slip Rate on Astara Fault System, North Iran. Journal of Earth Science, 27(6): 971–980. https://doi.org/10.1007/s12583-016-0680-xCrossRefGoogle Scholar
  2. Gu, G. H., Wang, W. X., 2013. Advantages of GNSS in Monitoring Crustal Deformation for Detection of Precursors to Strong Earthquakes. Positioning, 4(1): 11–19. https://doi.org/10.4236/pos.2013.41003CrossRefGoogle Scholar
  3. Li, M. K., Zhang, S. X., Zhang, C. Y., et al., 2015. Fault Slip Model of 2013 Lushan Earthquake Retrieved Based on GPS Coseismic Displacements. Journal of Earth Science, 26(4): 537–547. https://doi.org/10.1007/s12583-015-0557-4CrossRefGoogle Scholar
  4. Li, Y. X., Yang, G. H., Li, Z., et al., 2003. Movement and Strain Conditions of Active Blocks in the Chinese Mainland. Science in China Series D: Earth Sciences, 46(2): 82–117. https:/doi.org/10.3321/j.issn:1006-9267.2003.z1.008CrossRefGoogle Scholar
  5. Lin, J. W., 2013. Taiwan’ Chi-Chi Earthquake Precursor Detection Using Nonlinear Principal Component Analysis to Multi-Channel Total Electron Content Records. Journal of Earth Science, 24(2): 244–253. https://doi.org/10.1007/s12583-013-0325-2CrossRefGoogle Scholar
  6. Liu, Y. W., 2006. Review of the Research Progess on the Seismological Science of Underground Fluid in China during Last 40 Years. Earthquake Research in China, 22(3): 222–235 (in Chinese with English Abstract). https:/doi.org/10.3969/j.issn.1001-4683.2006.03.002Google Scholar
  7. Lu, M. Y., Niu, A. F., Bai, C. Q., et al., 2006. Preliminary Study on Relation of Short-Term and Impending-Earthquake Anomalies between Groundwater Level and Crustal Deformation and the Identification Method of Anomalies. Journal of Seismological Research, 29(1): 13–20 (in Chinese with English Abstract). https:/doi.org/10.3969/j.issn.1000-0666.2006.01.003Google Scholar
  8. Lu, Y. Z., 2001. Method for Establishing Dynamic Image of Crustal Strain Field Based on Deformation Observation Data. In: Wu, Y., Wang, W., Li, M. F., et al., eds., Dynamic Image Processing Method of Mid Short Term Earthquake Prediction. Seismological Press, Beijing. 20–21 (in Chinese)Google Scholar
  9. Qian, X. D., Su, Y. J., Fu, H., et al., 2011. Short Term and Impending Prediction of the Mar. 10, 2011, Ms 5.8, Yingjiang, Yunnan Earthquake. Journal of Seismological Research, 34(4): 403–413 (in Chinese with English Abstract). https:/doi.org/10.3969/j.issn.1000-0666.2011.04.001.Google Scholar
  10. Reasenberg, P. A., 1999. Foreshock Occurrence Rates before Large Earthquakes Worldwide. Pure and Applied Geophysics, 155(2/3/4): 355–379. https://doi.org/10.1007/s000240050269CrossRefGoogle Scholar
  11. Sreejith, K. M., Sunil, P. S., Agrawal, R., et al., 2016. Coseismic and Early Postseismic Deformation due to the 25 April 2015, Mw 7.8 Gorkha, Nepal, Earthquake from InSAR and GPS Measurements. Geophysical Research Letters, 43(7): 3160–3168. https://doi.org/10.1002/2016gl067907CrossRefGoogle Scholar
  12. Wang, Q. L., Zhang, X. D., Cui, D. X., et al., 2005. Understanding the Mechanisms of Premonitory Anamolies and Imminent Precursors. Recent Developments in World Seismology, 317(5): 131–144 (in Chinese with English Abstract). https:/doi.org/10.3969/j.issn.0253-4975.2005.05.025Google Scholar
  13. Wang, Q., Zhang, P. Z., Jeffrey, T., et al., 2001. Present-Day Crustal Deformation in China Constrained by Global Positioning System Measurements. Science, 294(5542): 574–577. https://doi.org/10.1126/science.1063647CrossRefGoogle Scholar
  14. Wang, T., Bebbington, M., 2013. Identifying Anomalous Signals in GPS Data Using HMMs: An Increased Likelihood of Earthquakes?. Computational Statistics & Data Analysis, 58: 27–44. https://doi.org/10.1016/j.csda.2011.09.019CrossRefGoogle Scholar
  15. Wang, T., Zhuang, J. C., Kato, T., et al., 2013. Assessing the Potential Improvement in Short-Term Earthquake Forecasts from Incorporation of GPS Data. Geophysical Research Letters, 40(11): 2631–2635. https://doi.org/10.1002/grl.50554CrossRefGoogle Scholar
  16. Wen, X. Z., Fan, J., Yi, G. X., et al., 2008. A Seismic Gap on the Anninghe Fault in Western Sichuan, China. Science in China Series D: Earth Sciences, 51(10): 1375–1387. https://doi.org/10.1007/s11430-008-0114-4CrossRefGoogle Scholar
  17. Wu, T. F., Zhang, S. X., Li, M. K., et al., 2016. Two Crustal Flowing Channels and Volcanic Magma Migration underneath the SE Margin of the Tibetan Plateau as Revealed by Surface Wave Tomography. Journal of Asian Earth Sciences, 132: 25–39. https://doi.org/10.13039/501100001809CrossRefGoogle Scholar
  18. Xu, S. X., 1989. Earthquake Prediction Ability Score. Seismological Press, Beijing. 586–589 (in Chinese)Google Scholar
  19. Yamazaki, K., Sakanaka, S., 2011. Localized Changes in Geomagnetic Total Intensity Values Prior to the 1995 Hyogo-Ken Nanbu (Kobe) Earthquake. Journal of Geodynamics, 51(1): 37–43. https://doi.org/10.1016/j.jog.2010.06.003CrossRefGoogle Scholar
  20. Zhang, Y., Wu, Y., Shi, S. Y., et al., 2005. Preliminary Discussion on GPS Time Series Manifesting Earthquake Precursor. Journal of Geodesy and Geodynamics, 25(3): 96–99 (in Chinese with English Abstract). https:/doi.org/10.3969/j.issn.1671-5942.2005.03.018Google Scholar
  21. Zhang, Z. C., Chen, Q. F., Zheng, D. S., et al., 2013. Seismic Case Studies and Summary (DB/T 24-2007). Seismological Press, Beijing (in Chinsese)Google Scholar

Copyright information

© China University of Geosciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Deformation Survey CenterYunnan Earthquake AgencyKunmingChina
  2. 2.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  3. 3.Key Laboratory of Environment and GeodesyMinistry of EducationWuhanChina

Personalised recommendations