Published February 2026 | Version Supplemental material
Journal Article Open

Distinguishing Tapered and Non-Tapered Gutenberg–Richter Distributions

  • 1. ROR icon California Institute of Technology

Abstract

The magnitude–frequency distribution (MFD), which quantifies the relative frequency of large versus small earthquakes, is commonly used in seismic hazard assessment studies and is thought to characterize earthquake dynamics. The classic Gutenberg–Richter (GR) model posits that earthquake frequency decays exponentially with magnitude. The tapered Gutenberg–Richter (TGR) model is a variant that assumes a further reduced frequency of larger earthquakes. Distinguishing which of these two distributions better fits observations is important not only for a better understanding of earthquake physics but also for robust forecasting of earthquake magnitudes. Therefore, we evaluate methods used to differentiate these two distributions and their statistical significance given a set of observations. We find the likelihood-ratio test to be the most effective approach. It rarely misclassifies a GR distribution as a TGR distribution, whereas a TGR distribution can be misclassified as GR when the tail of the MFD is insufficiently sampled. We demonstrate that the probability of correctly identifying a TGR model exceeds 90% when the corner magnitude is one unit smaller than the maximum magnitude predicted by the GR distribution. Furthermore, we introduce an objective framework aimed at detecting potential temporal shifts between the two distributions. We apply this framework to global seismicity and two observational cases of induced seismicity. The MFD of global seismicity shows transitions between GR and TGR distributions over time, which might be explained by either inherent temporal variation in behavior or by the random sampling of a bilinear GR model with a larger b value for M >7.6. Regarding the induced seismicity cases, we demonstrate significant and persistent TGR distributions in seismicity induced by geothermal well stimulations at Otaniemi, Finland. Furthermore, we find that earthquakes in the Coso geothermal field (California) exhibit TGR behavior during a specific period, likely influenced by the type of magnitude scale used.

Copyright and License

© 2025 Seismological Society of America.

Acknowledgement

This study was supported by the National Science Foundation (NSF; Award Number 1822214) via the Industry‐University Cooperative Research (ICUR) Center for Geomechanics and Mitigation of Geohazards. The authors thank Editor‐in‐Chief P. Martin Mai, Associate Editor Matthew C. Gerstenberger, and the two reviewers (Matteo Taroni and an anonymous) for their comments. Linxuan Li contributes conceptualization, methodology, validation, formal analysis, writing—original draft, writing—review and editing, and visualization. Jean‐Philippe Avouac contributes conceptualization, methodology, validation, formal analysis, writing—review and editing, supervision, and funding acquisition.

Data Availability

The global earthquake catalog is sourced from the International Seismological Centre (ISC) and can be accessed at https://www.isc.ac.uk/iscgem. The catalog for the Otaniemi Geothermal Site is from Leonhardt et al. (2020) and is available at https://gfzpublic.gfz-potsdam.de/pubman/item/item_5005600. The catalog for the Coso geothermal field is sourced from the Southern California Earthquake Data Center (SCEDC) and is available at https://scedc.caltech.edu (last accessed July 2024). The production history at Coso is obtained from California Department of Conservation and can be accessed at https://www.conservation.ca.gov (last accessed July 2024). Some figures are plotted by Scientific Color Maps (Crameri et al., 2020). The code used to reproduce the results of this study is available at https://github.com/lxli0/Scripts_for_papers/tree/main/LiandAvouac_GRvsTGR_script (last accessed September 2025). The supplemental material for this article includes one text explaining the generation of random synthetic catalogs and eight figures supporting the analysis in the main article.

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Additional details

Funding

National Science Foundation
1822214

Dates

Available
2025-10-17
First online