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Abstract:
The 2016 Kumamoto (Japan) earthquake is a significant seismic event that sparked the interest of the scientific community, particularly with regard to its source rupture processes. In an effort to gain a deeper understanding of the earthquake process, this study focuses on exploring the high-frequency source details of the rupture with the source-scanning algorithm, using as input local strong-motion data from the K-net and Kik-net networks. This algorithm is a powerful tool that can provide insights into the spatial and temporal distribution of seismic energy release during an earthquake. One of the primary objectives of the study was to determine if the consideration of site effects could improve the accuracy and robustness of the backprojection method. The advantage of having borehole sensors, which are typically less affected by local geology (but also more difficult and expensive to implement) allowed us to develop procedures for making better use of surface data. Our premise is that using amplification-free data can yield a more accurate representation of the earthquake source, leading to improved understanding of the high-frequency mechanics of earthquakes. This is important, as high-frequency information is critical for understanding the rupture process and the physical properties of the fault, which in turn can provide valuable information for seismic hazard assessment and seismic source modeling. Our findings indicate that the rupture process was complex, featuring multiple sub-events occurring at different times and locations, and that considering site effects when only surface stations are available can significantly enhance accuracy and yield more straightforward results.
