Shear-Wave Velocity Model for the Dead Sea Transform from Multimode Inversion of Surface Waves Excited by the February 2023 Southeast Türkiye Earthquake Sequence

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-02-02 DOI:10.1785/0220230303
A. Lellouch, A. Inbal, A. Ziv
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Abstract

The dispersive nature of surface waves can be used for shear-wave velocity inversion at different scales. We show that four large earthquakes from the 2023 Türkiye earthquake sequence generate visible surface waves recorded by a dense strong-motion network deployed along the Dead Sea Transform (DST) in Israel. Thanks to favorable geometrical conditions and source radiation patterns, we observe both Rayleigh and Love waves that travel predominantly parallel to the network. We can reliably compute the dispersion of three Love-wave modes and two Rayleigh-wave modes. Using these dispersion curves, we invert for a 1D S-wave velocity model of the entire DST, outperforming an existing model. Statistical and kernel sensitivity analysis show high certainty down to a depth of 30 km thanks to the multimode joint inversion in the frequency band of 0.03–0.3 Hz. Using a multiwindow approach, we invert for an along-strike laterally varying velocity model of the DST. Although it is limited to the fundamental Love-wave mode, using the 1D model as a constraint allows us to recover a shallow (10 km) velocity structure in agreement with previous studies of the area. Despite the simplicity of our used approach, it can be used as a basis for more advanced studies.
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根据 2023 年 2 月土尔其东南地震序列激发的地表波的多模反演建立的死海转换剪切波速度模型
面波的色散特性可用于不同尺度的剪切波速度反演。我们展示了 2023 年图尔基耶地震序列中的四次大地震产生的可见面波,该面波由沿以色列死海转换(DST)部署的密集强震网络记录。得益于有利的几何条件和震源辐射模式,我们观测到了主要平行于网络传播的瑞利波和爱波。我们可以可靠地计算出三种爱波模式和两种瑞利波模式的频散曲线。利用这些频散曲线,我们反演了整个 DST 的一维 S 波速度模型,结果优于现有模型。统计和核敏感性分析表明,由于在 0.03-0.3 Hz 频率带进行了多模联合反演,深度达 30 km 的确定性很高。利用多窗口方法,我们反演了 DST 的沿线横向变化速度模型。虽然仅限于基本的爱波模式,但以一维模型为约束,我们可以恢复出一个浅层(10 公里)的速度结构,这与该地区以前的研究结果是一致的。尽管我们使用的方法很简单,但它可以作为更高级研究的基础。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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