Development of an offshore ground motion prediction equation for peak ground acceleration considering path effects based on S-net data

Ground motion prediction equations (GMPEs) in offshore regions are important not only for earthquake early warning systems and strong motion prediction but also for evaluating the durability of subsea structures and tsunami risks associated with seafloor slope failures. Since soil conditions and propagation paths differ between onshore and offshore areas, it is desirable to develop a GMPE specific to the seafloor. Previous GMPE models have some problems, such as being influenced by buried observation equipment and path effects. In this study, to predict the distribution of seafloor seismic acceleration, we developed a new GMPE regressed on the peak ground acceleration (PGA) data of S-net using minimum necessary seismic parameters as explanatory variables. Residual analysis using the conventional GMPE emphasized the path effects through the offshore area, which were corrected by the depth up to the plate boundary. The new model successfully predicted PGA with smaller errors compared to conventional onshore and offshore GMPEs. The residuals between the observed and predicted PGAs were used to examine the factors responsible for the effects of the S-net site conditions. The new GMPE can predict PGAs within 300 km of the epicenter from the moment magnitude (Mw 5.4-7.4), focal depth, earthquake type, and source distance. In this model, the distance attenuation coefficient is smaller than in conventional models, and consequently, the PGAs along the trench axis that are amplified due to path effects can be reproduced. This means that PGAs will be unexpectedly larger than those estimated by conventional GMPEs even far from the hypocenter. Our model improves the accuracy of PGA prediction and avoids underestimation in assessing seafloor slope failure and earthquake resistance near the trench.