Co-seismic landslide directions may help identifying earthquake fault ruptures

crossref(2024)

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摘要
Several studies have suggested that directions of earthquake-triggered landslides might be preferentially oriented according to the seismic waves’ characteristics.  Here we further address this issue by analyzing three landslide populations attributed to 1998 Ruei-Li Mw 6.5, 1999 Chi-Chi Mw 7.3 and 2022 Taitung Mw 6.9 earthquakes in Taiwan. In particular, we seek possible linkages between the patterns of co-seismic landsliding (predominant orientations) and the epicenter and fault rupture locations, by exploiting the assumption that surface waves with horizontal particle motions (Love waves) and horizontal shear waves, both characterized by transverse vibrations perpendicular to the direction of wave radiation from the source, are the major agents responsible for earthquake induced slope failures. First, we take the aspect of each landslide source zone as representing the landslide directions. These directions are then statistically evaluated with respect to the epicentre and fault rupture positions for the characteristic segments of the landslide population. In the next step, we consider numerous possible pairs of the landslides to obtain intersections of the lines normal to their aspect directions using custom-designed Python code. At each particular landslide population segment, the landslide displacement directions revealed slight preferential orientation with the maxima sub-perpendicular to the fault rupture. Symmetrically distributed and round landslide population of the Ruei-Li earthquake showed even better results than elongated landslide population of the Chi-Chi earthquake. In all three earthquake cases, the intersections maxima coincided with the maximum slip velocities and/or displacements along the fault ruptures, as revealed by GNSS. These promising results indicate that such an approach might be useful for identifying fault ruptures of old or even prehistoric earthquakes.    The research was funded by the Grant Agency of the Czech Republic (GC22-24206J) and Taiwanese National Technological and Science Council (MOST/NTSC 111-2923-M-008-006-MY3).
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