Frontiers in Earth Science (Sep 2017)

Assessing Earthquake Early Warning Using Sparse Networks in Developing Countries: Case Study of the Kyrgyz Republic

  • Stefano Parolai,
  • Tobias Boxberger,
  • Marco Pilz,
  • Kevin Fleming,
  • Michael Haas,
  • Massimiliano Pittore,
  • Bojana Petrovic,
  • Bolot Moldobekov,
  • Alexander Zubovich,
  • Joern Lauterjung,
  • Joern Lauterjung

DOI
https://doi.org/10.3389/feart.2017.00074
Journal volume & issue
Vol. 5

Abstract

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The first real-time digital strong-motion network in Central Asia has been installed in the Kyrgyz Republic since 2014. Although this network consists of only 19 strong-motion stations, they are located in near-optimal locations for earthquake early warning and rapid response purposes. In fact, it is expected that this network, which utilizes the GFZ-Sentry software, allowing decentralized event assessment calculations, not only will provide useful strong motion data useful for improving future seismic hazard and risk assessment, but will serve as the backbone for regional and on-site earthquake early warning operations. Based on the location of these stations, and travel-time estimates for P- and S-waves, we have determined potential lead times for several major urban areas in Kyrgyzstan (i.e., Bishkek, Osh, and Karakol) and Kazakhstan (Almaty), where we find the implementation of an efficient earthquake early warning system would provide lead times outside the blind zone ranging from several seconds up to several tens of seconds. This was confirmed by the simulation of the possible shaking (and intensity) that would arise considering a series of scenarios based on historical and expected events, and how they affect the major urban centers. Such lead times would allow the instigation of automatic mitigation procedures, while the system as a whole would support prompt and efficient actions to be undertaken over large areas.

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