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Peng Chaoyong, Yang Jiansi. 2019: Real-time estimation of potentially damaged zone for earthquake early warning based on thresholds of P-wave parameters. Acta Seismologica Sinica, 41(3): 354-365. DOI: 10.11939/jass.20190140
Citation: Peng Chaoyong, Yang Jiansi. 2019: Real-time estimation of potentially damaged zone for earthquake early warning based on thresholds of P-wave parameters. Acta Seismologica Sinica, 41(3): 354-365. DOI: 10.11939/jass.20190140
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Real-time estimation of potentially damaged zone for earthquake early warning based on thresholds of P-wave parameters

  • Institute of Geophysics，China Earthquake Administration，Beijing 100081，China

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  • Received Date: November 30, 2018
  • Revised Date: February 19, 2019
  • Available Online: May 21, 2019
  • Published Date: April 30, 2019
    Graphical Abstract
    • Abstract
  • Conventional methods used for potentially damaged zone （PDZ） estimation usually take several minutes to produce the results, which are generated only after the epicenter of an earthquake has been acquired and the seismic event has ended, its real-time performance cannot meet the requirements of earthquake early warning （EEW）. Therefore, to rapidly produce the estimated range of PDZ for EEW, in this paper, we adopted a real-time method to estimate the PDZ range. The method is an integrated on-site and regional early-warning method based on the predefined thresholds of two early-warning parameters, the peak displacement （Pd） and characteristic period （τc）. Firstly, we used seismic events records with MS between 4.0 and 8.0 from the China Strong Motion Networks Center and strong-motion records with MJ between 6.5 and 8.0 downloaded from the Japanese National Research Institute for Earth Science and Disaster Resilience to linearly fit relationships of early-warning parameters, including τc versus M, Pd versus PGV, and Pd as a function of τc and hypocentral distance R. We then defined two early-warning parameters thresholds which are set for a minimum magnitude MS6.0 and instrumental intensity Ⅶ, according to the empirical regression analyses of the applied data. At each recording site, the alert level is assigned based on a decisional table with four alert levels defined upon critical values of the parameters Pd and τc. These two threshold values are Pd＝0.1 cm and τc＝1.1 s. Given a real-time, evolutionary estimation of earthquake location from first P arrivals, the method furnishes an estimation of the extent of PDZ as inferred from continuously updated averages of the period parameter and from mapping of the alert levels determined at the near-source seismic stations. Finally, to test the method’s efficiency and rapidity on mapping the damage zone in a few seconds after an earthquake occurrence, we offline applied the methodology to the strong-motion records of three destructive seismic events. The results show that a robust estimation of the PDZ range for moderate-to-large earthquakes like the 2013 MS7.0 Lushan and 2014 MS6.6 Ludian events can be obtained at about 10 s after the earthquake occurrence. And for the Wenchuan giant earthquake, as the case of low density of recording stations, the prediction of the PDZ becomes stable about 40 s after its occurred time.
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