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- Title
Strong motion uncertainty determined from observed records by dense network in Japan.
- Authors
Nobuyuki Morikawa; Tatsuo Kanno; Akira Narita; Hiroyuki Fujiwara; Toshihiko Okumura; Yoshimitsu Fukushima; Aybars Guerpinar
- Abstract
Abstract 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.
- Subjects
DISTRIBUTION (Probability theory); PROBABILITY theory; CHARACTERISTIC functions; ROBUST statistics
- Publication
Journal of Seismology, 2008, Vol 12, Issue 4, p529
- ISSN
1383-4649
- Publication type
Article
- DOI
10.1007/s10950-008-9106-2