4.6 Article

An empirical attenuation model of the peak ground acceleration (PGA) in the near field of a strong earthquake

Journal

NATURAL HAZARDS
Volume 105, Issue 1, Pages 691-715

Publisher

SPRINGER
DOI: 10.1007/s11069-020-04332-x

Keywords

Peak ground acceleration (PGA); Empirical attenuation model; Near field; Strong earthquake; The 2008 Wenchuan earthquake; Earthquake-induced landslides

Funding

  1. Second Tibetan Plateau Scientific Expedition and Research Program (STEP) [2019QZKK0904]
  2. National Science Foundation of China [41825018, 41790442, 41672307, 52199918000C]

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The study introduces an empirical attenuation model that can accurately reconstruct the PGA distribution of earthquakes, especially in the near field. Comparisons with results from a finite-fault model demonstrate that the proposed model offers more details and a more precise outcome.
Empirical methods are commonly employed to predict the PGA distribution of an earthquake and are widely used. However, current empirical methods assume the seismic source to be a point source, a line source, or a plane source, where the energy is concentrated and released uniformly. An empirical attenuation model of the near-field peak ground acceleration (PGA) was proposed that considers a nonuniform spatial distribution of seismic fault energy and its 3D scale. Then, this model was used to reconstruct the PGA distribution of the 2008 Wenchuan, China, Mw7.9 earthquake based on the data of a seismic fault model and ground acceleration records of the mainshock and aftershocks collected by seismic stations. The predicted PGA values show similar attenuation characteristics to the interpolated map of the PGA recorded by seismic stations. A comparison with the results of a finite-fault model developed by the USGS indicates that the proposed model can provide more details and give a more precise result in the near field. The analysis of landslides triggered by the Wenchuan earthquake demonstrates that the PGA distribution estimated by this model can be used to validate the findings of other researchers.

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