Machine-learning based earthquake detection and location around the Tanlu fault zone in eastern China
Abstract
SUMMARY The Tanlu fault zone is an NNE-SSW oriented, large and deep strike-slip fault system running through eastern China. To investigate seismotectonics in and around the Tanlu fault zone, we adopt the LOC-FLOW approach to build a high-precision earthquake catalogue. Our seismic data were recorded at 120 broad-band TanluArray temporary stations with a sampling rate of 40 Hz and 76 broad-band permanent stations with a sampling rate of 10 Hz from July 2019 to March 2023. We first conduct a series of experiments around the Luxi uplift and find that a higher sampling rate and a denser array of stations can significantly enhance the earthquake detection ability. Then we utilize both the temporary and permanent stations to conduct earthquake detection and location for the entire study area. As a result, 9648 earthquakes are detected and located in the REAL catalogue, 6543 earthquakes in the HypoInverse catalogue and 5619 earthquakes in the HypoDD catalogue, representing an increase of 20 per cent, 22 per cent and 22 per cent, respectively, as compared with the cases when only the TanluArray stations are used. Our location results show that earthquakes are mainly distributed in the Tanlu fault zone and active faults in relevant tectonic units. We collect 322 focal mechanism solutions (M > 2.0) of previous results from 2000 to 2020 to invert the stress field of the whole study region. The results show that the maximum principal stress axis of the whole study area is in the NEE-SWW direction, except that the Huoshan region is in the E-W direction. Along the Tanlu fault zone, the highest seismicity occurs in the Suqian-Weifang segment, and the Suqian seismic gap may be due to aseismic slip along the Tanlu fault.
Fields of Study & Subjects
Seismology and Earthquake Studies
earthquake and tectonic studies
Earthquake Detection and Analysis
Publication details
- Journal / source
- Geophysical Journal International
- Publisher
- Oxford University Press (OUP)
- Volume
- 245
- Issue
- 1
- Publication date
- 10 January 2026
- Language
- EN