Pure and Applied Geophysics

, Volume 176, Issue 4, pp 1417–1432 | Cite as

Nowcasting Earthquakes in the Bay of Bengal Region

  • Sumanta PasariEmail author


Statistical quantification of observed seismicity is important for understanding earthquake dynamics and future risk in any seismic-prone region. In this paper, we implement the idea of nowcasting (Rundle et al. in Earth and Space Science 3:480–486, 2016) to examine the current uncertain state of earthquake hazard assessment in the seismically active Bay of Bengal (BoB) and adjacent regions. First, we utilize the concept of “natural time” (Varostos et al. in Physical Review E 71:032102, 2005), rather than clock time, to develop a statistical distribution of inter-event counts of “small” earthquakes occurring between “large” earthquakes. Using relevant statistics of natural time, we then calculate the earthquake potential score (EPS) as the cumulative number of small earthquakes since the last large event in the selected region. The EPS, which provides the nowcast value for a region, reveals the current state of earthquake hazard in that region. Therefore, by indirect means, the EPS provides us with a simple yet transparent estimation of the current level of seismic progress through the regional earthquake cycle of recurring events in a geographical area. To illustrate the nowcasting approach in the study region, we computed EPS values for the two most seismically exposed megacities, Dhaka and Kolkata, considering events of \(M \ge 4\) within a radius of 250 km around their respective city centers. We found that the current EPS values corresponding to M ≥ 6  events in Dhaka and Kolkata were approximately 0.72 and 0.40, respectively. The practical applicability of these values is discussed in conjunction with sensitivity analysis of the threshold magnitudes.


Bay of Bengal nowcast earthquake statistics 



Valuable comments and constructive suggestions of two anonymous reviewers are highly appreciated. The Generic Mapping Tool (GMT) developed by Wessel and Smith (1995) was used for preparing some figures. Earthquake data for the nowcasting analysis was obtained from the ANSS global composite catalog and ISC Bulletin catalog. This research was supported in part through an Additional Competitive Research Grant (ACRG) from BITS Pilani provided to the author.

Compliance with ethical standards

Conflict of interest

The authors report no potential conflict of interest.


  1. ANSS Earthquake catalog search. (2018) Accessed 22 Sept 2018
  2. Chen, K. H., & Burgmann, R. (2017). Creeping faults: Good news, bad news? Reviews of Geophysics, 55, 282–286.CrossRefGoogle Scholar
  3. Harris, R. A. (2017). Large earthquakes and creeping faults. Reviews of Geophysics, 55, 169–198.CrossRefGoogle Scholar
  4. Hogg, R. V., Mckean, J. W., & Craig, A. T. (2005). Introduction to mathematical statistics. New Delhi: PRC Press.Google Scholar
  5. Holliday, J. R., Graves, W. R., Rundle, J. B., & Turcotte, D. (2016). Computing earthquake probabilities on global scales. Pure and Applied Geophysics, 173, 739–748.CrossRefGoogle Scholar
  6. ISC Bulletin: event catalog search. (2018). Accessed 22 Sept 2018
  7. Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995). Continuous univariate distributions. New York: Wiley-Interscience.Google Scholar
  8. Lee, Y. T., Turcotte, D. L., Holliday, J. R., Sachs, M. K., Rundle, J. B., Chen, C. C., et al. (2011). Results of the regional earthquake likelihood models (RELM) test of earthquake forecasts in California. Proceedings of the National Academy of Sciences, 108(40), 16533–16538.CrossRefGoogle Scholar
  9. Liang, W. T., Lee, J. C., Chen, K. H., & Hsiao, N. C. (2017). Citizen earthquake science in Taiwan: from science to hazard mitigation. Journal of Disaster Advances, 12(6), 1174–1181.CrossRefGoogle Scholar
  10. Luginbuhl, M., Rundle, J. B., Hawkins, A., & Turcotte, D. L. (2018a). Nowcasting earthquakes: a comparison of induced earthquakes in Oklahoma and at the Geysers, California. Pure and Applied Geophysics, 175, 49–65.CrossRefGoogle Scholar
  11. Luginbuhl, M., Rundle, J. B., & Turcotte, D. L. (2018b). Natural time and nowcasting earthquakes: are large global earthquakes temporally clustered? Pure and Applied Geophysics, 175, 661–670.CrossRefGoogle Scholar
  12. Nandy, D. R. (2001). Geodynamics of north eastern India and the adjoining region. Kolkata: ACB Publications.Google Scholar
  13. Pasari, S. (2015). Understanding Himalayan tectonics from geodetic and stochastic modeling. PhD Thesis, Indian Institute of Technology Kanpur, IndiaGoogle Scholar
  14. Pasari, S. (2018a). Seismotectonic modeling in the Bay-of-Bengal region. New Dimensions for Natural Hazards in Asia: An AOGS-EGU Joint Conference, in Tagaytay, Philippines, 4–8 February, 2018Google Scholar
  15. Pasari, S. (2018b). Stochastic modelling of earthquake interoccurrence times in northwest Himalaya and adjoining regions. Geomatics, Natural Hazards and Risk, 9(1), 568–588.CrossRefGoogle Scholar
  16. Pasari, S., & Dikshit, O. (2014a). Impact of three-parameter Weibull models in probabilistic assessment of earthquake hazards. Pure and Applied Geophysics, 171(7), 1251–1281.CrossRefGoogle Scholar
  17. Pasari, S., & Dikshit, O. (2014b). Three-parameter generalized exponential distribution in earthquake recurrence interval estimation. Natural Hazards, 73, 639–656.CrossRefGoogle Scholar
  18. Pasari, S., & Dikshit, O. (2015a). Distribution of earthquake interevent times in northeast India and adjoining regions. Pure and Applied Geophysics, 172(10), 2533–2544.CrossRefGoogle Scholar
  19. Pasari, S., & Dikshit, O. (2015b). Earthquake interevent time distribution in Kachchh, northwestern India. Earth, Planets and Space, 67, 129.CrossRefGoogle Scholar
  20. Pasari, S., & Dikshit, O. (2018). Stochastic earthquake interevent time modelling from exponentiated Weibull distributions. Natural Hazards, 90(2), 823–842.CrossRefGoogle Scholar
  21. Rai, A. K., Tripathy, S., & Sahu, S. C. (2015). The May 21st, 2014 Bay of Bengal earthquake: Implications for intraplate stress regime. Current Science, 108(9), 1706–1712.Google Scholar
  22. Rao, G. S., Radhakrishna, M., & Murthy, K. S. R. (2015). A seismotectonic study of the 21 May 2014 Bay of Bengal intraplate earthquake: Evidence of onshore-offshore tectonic linkage and fracture zone reactivation in the northern Bay of Bengal. Natural Hazards, 78, 895–913.CrossRefGoogle Scholar
  23. Rundle, J. B., Luginbuhl, M., Giguere, A., & Turcotte, D. L. (2018). Natural time, nowcasting and the physics of earthquakes: estimation of seismic risk to global megacities. Pure and Applied Geophysics, 175, 647–660.CrossRefGoogle Scholar
  24. Rundle, J. B., Turcotte, D. L., Donnellan, A., Grant-Ludwig, L., Luginbuhl, M., & Gong, G. (2016). Nowcasting earthquakes. Earth and Space Science, 3, 480–486.CrossRefGoogle Scholar
  25. Scholz, C. H. (1990). The mechanics of earthquakes and faulting. Cambridge: Cambridge University.Google Scholar
  26. Tiampo, K. F., Rundle, J. B., Klein, W., Martins, J. S. S., & Ferguson, C. D. (2003). Ergodic dynamics in a natural threshold system. Physical Review Letters, 91(1–4), 238501.CrossRefGoogle Scholar
  27. Utsu, T. (1984). Estimation of parameters for recurrence models of earthquakes. Bulletin of Earthquake Research Institute, University of Tokyo, 59, 53–66.Google Scholar
  28. Varostos, P. A., Sarlis, N. V., & Skordas, E. S. (2011). Natural time analysis: the new view of time. Berlin: Springer.Google Scholar
  29. Varostos, P. A., Sarlis, N. V., Tanaka, H. K., & Skordas, E. S. (2005). Some properties of the entropy in natural time. Physical Review E, 71, 032102.Google Scholar
  30. Wald, D. J., Quitoriano, V., Worden, B., Hopper, M., & Dewey, J. W. (2011). USGS “Did you feel it?” Internet based macroseismic intensity maps. Annals of Geophysics, 54(6), 688–707.Google Scholar
  31. Wessel, P., & Smith, W. H. F. (1995). New version of the generic mapping tools released (p. 76). Transactions American Geophysical Union: EOS.Google Scholar
  32. Working Group. (2013). Working Group on California Earthquake Probabilities: The Uniform California Earthquake Rupture Forecast Version 3 (UCERF 3), USGS Open File Report 2013–1165 and California Geological Survey Special Report 228. Accessed 22 Sept 2018
  33. Yin, A. (2006). Cenozoic tectonic evolution of the Himalayan orogen as constrained by along-strike variation of structural geometry, exhumation history, and foreland sedimentation. Earth Science Review, 76, 1–31.CrossRefGoogle Scholar
  34. Young, J. C., Wald, D. J., Earle, P. S., & Shanley, L. A. (2013). Transforming earthquake detection and science through citizen seismology. Washington, DC: Woodrow Wilson International Center for Scholars.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of MathematicsBirla Institute of Technology and SciencePilaniIndia

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