1D layered structures of the accretionary prism beneath the DONET stations
<p><strong>Description</strong></p> <p>We converted the smooth depth-varying velocity structure model of <a href="https://doi.org/10.1038/s41467-017-02276-8">Tonegawa <em>et al.</em> (2017)</a> to a 5-layer model beneath each DONET station. The physical parameters of each layer are listed in the vmodel.csv.</p> <p>The thicknesses of each layer were determined by fitting the depth-averaged <em>S</em>-wave velocities derived by <a href="https://doi.org/10.1038/s41467-017-02276-8">Tonegawa <em>et al.</em> (2017)</a>. For example, if the depth-averaged <em>VS</em> of <a href="https://doi.org/10.1038/s41467-017-02276-8">Tonegawa <em>et al.</em> (2017)</a> become the <em>VS</em> of layer 1 at a certain depth, this depth is considered as the bottom of layer 1. In DONET_layeredData.csv, the estimated bottom depths of each layer are listed. </p> <p> </p> <p><strong>For seismic wave propagation simulation</strong></p> <p>For simulations of seismic wave propagation along the Nankai Trough, the 3D model used in the simulations was basically constructed from the <a href="https://www.jishin.go.jp/evaluation/seismic_hazard_map/lpshm/12_choshuki_dat/">Japan Integrated Velocity Structure Model</a> (JIVSM) (<a href="https://www.iitk.ac.in/nicee/wcee/article/WCEE2012_1773.pdf">Koketsu et al., 2012</a>). The JIVSM onshore and outer-rise sedimentary structures and structures beneath bedrock were fixed. To construct 3D model of the accretionary prism from layered S wave velocity models in "DONET_layeredData.csv," each station's bottom depths were interpolated and extrapolated via the ‘<em>Surface</em>’ gridding algorithm in Generic Mapping Tools software (GMT; Wessel <em>et al.</em> 2013). Interpolation and extrapolation were only applied within the region of the accretionary prism (Figure S1 of <a href="https://doi.org/10.1093/gji/ggaa404%20">Takemura, Yabe & Emoto 2020</a>). By using interpolated and extrapolated data of layer bottom depths and physical parameters (vmodel.csv), we can obtain 3D model of the accretionary prism along the Nankai Trough. </p> <p>We confirmed very similar simulation results between smooth depth-varying and layered accretionary prism models. </p> <p> </p> <p>Smooth depth varying model case</p> <ul> <li><a href="https://doi.org/10.1007/s00024-018-2013-8">Takemura, Kubo et al., 2019</a> </li> <li><a href="https://doi.org/10.1029/2019GL082448">Takemura, Matsuzawa et al., 2019</a></li> </ul> <p>Layered model case</p> <ul> <li>Figures S3, S4 of <a href="https://doi.org/10.1093/gji/ggaa404%20">Takemura, Yabe & Emoto 2020</a></li> </ul> <p> </p> <p>Related papers</p> <p>For citing general information of this dataset, please include this data DOI and the following references</p> <ul> <li>Tonegawa, T., Araki, E., Kimura, T. <em>et al. </em>(2017). Sporadic low-velocity volumes spatially correlate with shallow very low frequency earthquake clusters. <em>Nat Commun</em> <strong>8, </strong>2048 <a href="https://doi.org/10.1038/s41467-017-02276-8">https://doi.org/10.1038/s41467-017-02276-8</a></li> <li>Takemura, S., Yabe, S., & Emoto (2020), K. Modelling high-frequency seismograms at ocean bottom seismometers: effects of heterogeneous structures on source parameter estimation for small offshore earthquakes and shallow low-frequency tremors, Geophys. J. Int., 223 (3), 1708-1723, <a href="https://doi.org/10.1093/gji/ggaa404">https://doi.org/10.1093/gji/ggaa404</a> </li> </ul>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 0