Samenvatting
Volcano monitoring requires simple techniques to rapidly identify the cause of volcanic unrest. The so-called RSAM (real-time seismic amplitude measurements) technique, used in many observatories, is a good example of extracting information from seismograms with minimal processing. Built on a similar principle, the more recent seismic amplitude ratio analysis (SARA) technique allows locating migrating seismicity at high frequency (> 2 Hz, e.g., due to dike intrusions) under certain assumptions. However, such analysis generally requires a dense distribution of stations close to the seismic sources (depending on the magnitude) and/or station sites undisturbed by human activity. In a more straightforward and qualitative approach, computing amplitude ratios between station pairs can also allow for the detection of temporal and (2D) spatial changes of volcanic activity. In this work, we adopt such a simplified approach of SARA in order to characterize seismic tremors originating from two open-vent neighboring volcanoes, Nyiragongo and Nyamulagira, in the Virunga Volcanic Province (VVP) in the Democratic Republic of the Congo (DRC). In contrast with previous studies, we focus here on the low-frequency band (0.3–1 Hz), free from anthropogenic noise and sensitive to shallow volcanic tremors linked to intermittent or permanent intra-crater eruptive activity recorded through the large-aperture local network. We apply for the first time the SARA methodology for volcanic sources predominantly generating surface waves and propagating over long distances. The analysis is performed on more than two years of continuous seismic data. Seismic amplitude analysis in this frequency band is strongly influenced by the short-period microseisms originating from nearby Lake Kivu. Despite this diurnal to seasonal amplitude variability, SARA successfully detects continuous volcanic tremor activity and its arrest at both volcanoes. In light of these findings, we discuss the applicability of the method to the continuous, real-time detection, and characterization of long-period shallow volcanic tremor sources in this region.
| Originele taal-2 | English |
|---|---|
| Artikelnummer | 27 |
| Aantal pagina's | 17 |
| Tijdschrift | Bulletin of Volcanology |
| Volume | 85 |
| Nummer van het tijdschrift | 5 |
| DOI's | |
| Status | Published - 3 apr 2023 |
Bibliografische nota
Funding Information:This work is achieved in the framework of the HARISSA project funded by the development cooperation program of the Royal Museum for Central Africa with support of the Directorate-General for Development Cooperation and Humanitarian Aid of Belgium (RMCA-DGD).
Funding Information:
The authors would like to thank the people at GVO involved in the operation of KivuSNet, the sentinels of the monitoring stations and the MONUSCO (UN stabilization mission in Congo) for their continuous support, including hosting seismic stations in their compounds. Special thanks to C. Samba (GVO) for providing the weather data and to T. Lecocq (ORB) for helpful discussion about the MSNoise software. The authors would also like to thank the anonymous reviewers and the associate editor A. Cannata for their comments that helped to improve the former manuscript. Data archiving and accessibility from KivuSnet is ensured through the GEOFON program of the GFZ German Research Centre for Geosciences (https:// doi.org /10.14470/XI058335) under the KV FDSN code (http://www.fdsn.org/networks/detail/KV/). The MSNoise software is available at https://github.com/ROBelgium/MSNoise.git.
Publisher Copyright:
© 2023, International Association of Volcanology & Chemistry of the Earth's Interior.
Copyright:
Copyright 2023 Elsevier B.V., All rights reserved.