In this article, ground‐motion prediction equations (GMPEs) based on the horizontal components of the strong‐motion records from shallow crustal and upper‐mantle earthquakes in Japan are presented. We assembled a large dataset from earthquakes with a moment magnitude (Mw) over 4.9 and a reliable earthquake category (the tectonic location of earthquakes) up to the end of 2012. The GMPEs were based on a set of simple geometric attenuation functions. A bilinear magnitude‐scaling function hinged at Mw 7.1 was adopted, with the scaling rates for large events being much smaller than those for the smaller events. Site classes based on site period were used as site terms, and nonlinear site terms were included. We modeled the effect of volcanic zones using an anelastic attenuation coefficient applied to a horizontal portion of the seismic‐wave travel distance within volcanic zones. Most strong‐motion records in our dataset are from stations with a measured shear‐wave velocity profile down to engineering bedrock. A small number of records are from stations with inferred site classes using the response spectral ratio of the horizontal‐to‐vertical components or geologic description of the surface soil layers. We tested the effect of site information quality by comparing the goodness‐of‐fit parameters from the model with and without the sites with inferred site classes. Our results suggest that the site information quality made a significant difference for spectral periods over 0.7 s, that is, the exclusion of sites with inferred site classes improves the model fit significantly. The within‐event residuals were approximately separated into within‐site and between‐site components, and the corresponding standard deviations were calculated. The approximate separation allows for the possibility of adopting different standard deviations for different site classes in a probabilistic seismic‐hazard analysis if desired.
Online Material: References for fault rupture plane models, earthquake records and volcanic zones information, illustration of site information quality effect, standard deviations for between‐event, within‐event, between‐site and within‐site residual, and the distribution of between‐event and within‐event residuals.