Strong motion uncertainty determined from observed records by dense network in Japan

Nobuyuki Morikawa, Tatsuo Kanno, Akira Narita, Hiroyuki Fujiwara, Toshihiko Okumura, Yoshimitsu Fukushima, Aybars Guerpinar

Research output: Contribution to journalArticlepeer-review

66 Citations (Scopus)


The variation of ground motions at specific stations from events in six narrow areas was inspected by using K-NET and KiK-net records. A source-area factor for individual observation stations was calculated by averaging ratios between observed values for horizontal peak acceleration and velocity, as well as acceleration response spectra for 5% damping, and predicted values using a ground-motion model (usually known as an attenuation relation) by Kanno et al. (Bull Seismol Soc Am, 96:879-897, 2006). Standard deviations between observed and predicted amplitudes after the correction factor are less than 0.2 on the logarithmic scale and decrease down to around 0.15 in the short-period range. Intra-event standard deviation clearly increases with decreasing distance due to differing paths around near source area. Standard deviations may increase with amplitude or decrease with magnitude; however, both amplitude and magnitude of the data are strongly correlated with distance. The standard deviation calculated in this study is obviously much smaller than that of the original ground-motion model, as epistemic uncertainties are minimized by grouping ground motions at specific stations. This result indicates that the accuracy of strong ground motion prediction could be improved if ground-motion models for specified region are determined individually. For this to be possible, it is necessary to have dense strong-motion networks in high-seismicity regions, such as K-NET and KiK-net.

Original languageEnglish
Pages (from-to)529-546
Number of pages18
JournalJournal of Seismology
Issue number4
Publication statusPublished - 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Geochemistry and Petrology


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