Probabilistic characterization of spatially-correlated response spectra for earthquakes in Japan

Seismic hazard and risk assessments of spatially distributed infrastructural systems require seismic demand models that capture random but correlated simultaneous seismic effects at multiple sites. This study characterizes spatially correlated ground-motion parameters probabilistically using comprehensive databases of the K-NET and KiK-net strong-motion networks in Japan by developing a ground-motion prediction equation and then investigating the correlation structure of regression residuals from the prediction equation. Analysis results indicate that (1) interevent residuals of ground-motion parameters at different vibration periods are more strongly correlated than intraevent and total residuals with zero separation distance; and (2) intraevent spatial correlation coefficients can be described as a simple exponential decay function that is independent of the way the event-based intraevent standard deviation is calculated, of the earthquake type, and of the vibration period. The developed overall correlation model of spatially correlated ground-motion parameters may be used for seismic hazard and risk assessments in a subduction environment.