Articles | Volume 25, issue 1
https://doi.org/10.5194/nhess-25-231-2025
https://doi.org/10.5194/nhess-25-231-2025
Research article
 | 
14 Jan 2025
Research article |  | 14 Jan 2025

Analysis of borehole strain anomalies before the 2017 Jiuzhaigou Ms 7.0 earthquake based on a graph neural network

Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi

Related authors

Research on the Extraction of Pre-Seismic Anomalies in Borehole Strain Data of the Mado Earthquake Based on the SVMD-Informer Model
Shanzhi Dong, Jie Zhang, Changfeng Qin, Yu Duan, Chenyang Li, Chengquan Chi, and Zhichao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1130,https://doi.org/10.5194/egusphere-2025-1130, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
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
Solid Earth, 15, 877–893, https://doi.org/10.5194/se-15-877-2024,https://doi.org/10.5194/se-15-877-2024, 2024
Short summary

Related subject area

Earthquake Hazards
Towards a harmonized operational earthquake forecasting model for Europe
Marta Han, Leila Mizrahi, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 25, 991–1012, https://doi.org/10.5194/nhess-25-991-2025,https://doi.org/10.5194/nhess-25-991-2025, 2025
Short summary
Modeling seismic hazard and landslide occurrence probabilities in northwestern Yunnan, China: exploring complex fault systems with multi-segment rupturing in a block rotational tectonic zone
Jia Cheng, Chong Xu, Xiwei Xu, Shimin Zhang, and Pengyu Zhu
Nat. Hazards Earth Syst. Sci., 25, 857–877, https://doi.org/10.5194/nhess-25-857-2025,https://doi.org/10.5194/nhess-25-857-2025, 2025
Short summary
Development of a regional probabilistic seismic hazard model for Central Asia
Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, Marco Santulin, and Paolo Bazzurro
Nat. Hazards Earth Syst. Sci., 25, 817–842, https://doi.org/10.5194/nhess-25-817-2025,https://doi.org/10.5194/nhess-25-817-2025, 2025
Short summary
Computing the time-dependent activity rate using non-declustered and declustered catalogues – a first step towards time-dependent seismic hazard calculations for operational earthquake forecasting
David Montiel-López, Sergio Molina, Juan José Galiana-Merino, Igor Gómez, Alireza Kharazian, Juan Luis Soler-Llorens, José Antonio Huesca-Tortosa, Arianna Guardiola-Villora, and Gonzalo Ortuño-Sáez
Nat. Hazards Earth Syst. Sci., 25, 515–539, https://doi.org/10.5194/nhess-25-515-2025,https://doi.org/10.5194/nhess-25-515-2025, 2025
Short summary
Testing the 2020 European Seismic Hazard Model (ESHM20) against observations from Romania
Elena F. Manea, Laurentiu Danciu, Carmen O. Cioflan, Dragos Toma-Danila, and Matthew C. Gerstenberger
Nat. Hazards Earth Syst. Sci., 25, 1–12, https://doi.org/10.5194/nhess-25-1-2025,https://doi.org/10.5194/nhess-25-1-2025, 2025
Short summary

Cited articles

Abu Bakar, M. A., Mohd Ariff, N., Abu Bakar, S., Goh, P. C., and Rajendran, R.: Peramalan Kualiti Udara menggunakan Kaedah Pembelajaran Mendalam Rangkaian Perlingkaran Temporal (TCN), Sains Malays., 51, 3785–3793, https://doi.org/10.17576/jsm-2022-5111-22, 2021. 
Akhoondzadeh, M., De Santis, A., Marchetti, D., and Shen, X.: Swarm-TEC Satellite Measurements as a Potential Earthquake Precursor Together With Other Swarm and CSES Data: The Case of Mw 7.6 2019 Papua New Guinea Seismic Event, Front. Earth Sci., 10, 820189, https://doi.org/10.3389/feart.2022.820189, 2022. 
Bai, S., Kolter, J. Z., and Koltun, V.: An empirical evaluation of generic convolutional and recurrent networks for sequence modeling, arXiv [preprint], https://doi.org/10.48550/arXiv.1803.01271, 2018. 
Barino, F. O., Silva, V. N. H., Lopez-Barbero, A. P., De Mello Honorio, L., and Santos, A. B. D.: Correlated Time-Series in Multi-Day-Ahead Streamflow Forecasting Using Convolutional Networks, IEEE Access, 8, 215748–215757, https://doi.org/10.1109/access.2020.3040942, 2020. 
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.-Basel, 12, 7548, https://doi.org/10.3390/app12157548, 2022. 
Download
Short summary
In this study, we advance the field of earthquake prediction by introducing a pre-seismic anomaly extraction method based on the structure of a graph WaveNet model, which reveals the temporal correlation and spatial correlation of the strain observation data from different boreholes prior to the occurrence of an earthquake event.
Share
Altmetrics
Final-revised paper
Preprint