Detection of Gutenberg-Richter b-Value Changes in Earthquake Time Series
- The Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability toThe Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability to detect change-points as function of the size of the sample and the b-value contrast. Finally, we apply this approach to examples of observational data sets for which b-value changes have previously been stated. Our analysis of foreshock and after-shock sequences related to mainshocks, as well as earthquake swarms, shows that only a portion of the b-value changes is statistically significant.…
Author details: | Bernhard FiedlerORCiDGND, Sebastian HainzlORCiDGND, Gert ZöllerORCiDGND, Matthias HolschneiderORCiDGND |
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DOI: | https://doi.org/10.1785/0120180091 |
ISSN: | 0037-1106 |
ISSN: | 1943-3573 |
Title of parent work (English): | Bulletin of the Seismological Society of America |
Publisher: | Seismological Society of America |
Place of publishing: | Albany |
Publication type: | Article |
Language: | English |
Year of first publication: | 2018 |
Publication year: | 2018 |
Release date: | 2021/09/22 |
Volume: | 108 |
Issue: | 5A |
Number of pages: | 10 |
First page: | 2778 |
Last Page: | 2787 |
Funding institution: | Deutsche Forschungsgemeinschaft (DFG) Research Training Group "Natural hazards and risks in a changing world"(NatRiskChange); DFGGerman Research Foundation (DFG) [1294] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Green Open-Access |