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Articles | Volume 15, issue 7
Articles | Volume 15, issue 7
https://doi.org/10.5194/se-15-877-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-15-877-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 7
Research article
 | 
22 Jul 2024
Research article |  | 22 Jul 2024

Extraction of pre-earthquake anomalies from borehole strain data using Graph WaveNet: a case study of the 2013 Lushan earthquake in China

Chenyang Li, Yu Duan, Ying Han, Zining Yu, Chengquan Chi, and Dewang Zhang

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Cited articles

An, Z., Du, X., Tan, D., Fan, Y., Liu, J., and Cui, T.: Study on the Geo-Electric Field Variation of Sichuan Lushan MS7.0 and Wenchuan MS8.0 Earthquake, Chinese J. Geophys., 56, 721–730, https://doi.org/10.1002/cjg2.20065, 2013. 
Bilal, M. A., Ji, Y., Wang, Y., Akhter, M. P., and Yaqub, M.: Early Earthquake Detection Using Batch Normalization Graph Convolutional Neural Network (BNGCNN), Appl. Sci., 12, 7548, https://doi.org/10.3390/app12157548, 2022. 
Campbell, L. R., Menegon, L., Fagereng, Å., and Pennacchioni, G.: Earthquake nucleation in the lower crust by local stress amplification, Nat. Commun., 11, 1322, https://doi.org/10.1038/s41467-020-15150-x, 2020. 
Chen, P., Yao, Y., Chen, J., Yao, W., and Zhu, X.: Study of the 2013 Lushan M7.0 earthquake coseismic ionospheric disturbances, Adv. Space Res., 54, 2194–2199, https://doi.org/10.1016/j.asr.2014.08.014, 2014. 
Chi, C., Zhu, K., Yu, Z., Fan, M., Li, K., and Sun, H.: Detecting Earthquake-Related Borehole Strain Data Anomalies With Variational Mode Decomposition and Principal Component Analysis: A Case Study of the Wenchuan Earthquake, IEEE Access, 7, 157997–158006, https://doi.org/10.1109/access.2019.2950011, 2019. 
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This study advances the field of earthquake prediction by introducing an extraction method for pre-seismic anomalies based on the structure of Graph WaveNet networks. We believe that our study makes a significant contribution to the literature as it not only demonstrates the effectiveness of this innovative approach in integrating borehole strain data from multiple stations but also reveals distinct temporal and spatial correlations preceding earthquake events.
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