High-rate GNSS data in seismic moment tensor inversion: application to anthropogenic earthquakes

Abstract

Earthquakes are traditionally monitored by seismic networks. However, the progress in high-rate Global Navigation Satellite Systems (GNSS) observations caused them to be included as a standard supplementary tool for strong natural earthquake monitoring. Here, we demonstrate that the displacement time series obtained with high-rate GNSS data can be included as a supplementary tool for the characterization of low-magnitude anthropogenic earthquakes to monitor the dangerous impact that such tremors may have on infrastructure. We analyzed two mining tremors with magnitudes of 3.7 and 4.0, respectively, and utilized the spectral amplitudes of seismic and high-rate GNSS observations in the seismic moment tensor calculation. Our study reveals that the high-rate GNSS time series can be successfully included in moment tensor calculations and might also be crucial if there is a lack of seismic data.

Keywords:

• High-rate GNSS
• moment tensor inversion
• mining tremors
• anthropogenic earthquakes
• seismogeodesy

Data availability statement

The seismological data are available from the repository of the European Plate Observing System (EPOS) Thematic Core Service Anthropogenic Hazards (EPISODES platform) at https://episodesplatform.eu/?lang=en#episode:LGCD (last accessed in April 2023). The non-filtered HR-GNSS coordinate time series used in this study are available at https://doi.org/10.5281/zenodo.7503137. The HR-GNSS raw data will be shared on reasonable request with the corresponding author. The GNSS processing was performed using RTKlib (http://www.rtklib.com/). The figures in this paper were generated using QGIS and MATLAB.

Additional information

Funding

This research was conducted within the European Plate Observing System (EPOS), which is co-financed by the European Union from the funds of the European Regional Development Fund (POIR.04.02.00-14-A0003/16 and POIR.04.02.00-00-C005/19-00). This research was partially financed by Polish National Science Centre grant No 2021/41/B/ST10/02618 and National Statutory Activity of the Ministry of Education and Science of Poland grant No 3841/E-41/S/2023. Seismological data for this study were provided by the Institute of Geophysics, Polish Academy of Sciences, and are available at https://episodesplatform.eu/?lang=en#episode:LGCD. The GNSS data from the TRZB and TARN stations were provided courtesy of KGHM Cuprum Sp. Z. o. o. and the University of Warmia and Mazury in Olsztyn, which are co-financed by the National Centre for Research and Development (POIR.04.01.04-00-0056/17). This work was supported by the Wroclaw Centre of Networking and Supercomputing (http://www.wcss.wroc.pl) computational grant using MATLAB software license No 101979.