Empirical Ground‐Motion Model With Spatially Varying Coefficients for Improved Ground‐Motion Prediction Accuracy at Seismic Observation Stations in Japan

It is essential to improve the accuracy of ground‐motion predictions based on long‐term seismic observations because this allows for more accurate ground‐motion models (GMMs). Therefore, this study used a large number of ground‐motion records, focusing on existing seismic observation stations, to propose a GMM with improved accuracy by introducing spatially varying coefficients and a calibration method utilizing large datasets. The study also uniquely employed empirical site terms to eliminate errors due to site characteristic modeling, further enhancing the prediction accuracy at specific stations. Subsequently, a nonergodic GMM for predicting the maximum seismic wave acceleration was constructed using a practical study that incorporated a large dataset of ground‐motion records from a high‐density strong‐motion observation network in Japan. The introduction of spatially varying coefficients allowed the spatial variability of the propagation path and source characteristics to be considered, which effectively reduced ground‐motion prediction errors. The resulting GMM enables more accurate probabilistic analyses of seismic hazards.