Group A, Poster #213, Earthquake Forecasting and Predictability (EFP)
Critical Invariant Galton-Watson Branching Process for Earthquake Occurrence
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Poster Presentation
2022 SCEC Annual Meeting, Poster #213, SCEC Contribution #12499 VIEW PDF
s explicit distributions for multiple clustering statistics, including magnitude-dependent and magnitude-independent offspring number, cluster size, and cluster combinatorial depth. The framework provides a one-parametric model that can fit observed clusters of all sizes (not only the largest ones), and it suggests new observed statistics based on the Horton-Strahler analysis of earthquake clusters. We show that the IGW model closely approximates the ETAS model, while allowing for a comprehensive theoretical analysis and more robust estimates of parameters. Analysis of seismicity in southern California demonstrates that the IGW model provides a very close fit to observed earthquake clusters, and that the estimated IWG parameters and derived statistics are robust with respect to the lower magnitude threshold used in the analysis. The proposed model facilitates analyses of additional quantities of seismicity based on self-similar tree attributes, and may be used to assess the proximity of seismicity to criticality.
Reference:
Kovchegov, Y., I. Zaliapin, and Y. Ben-Zion (2022) Invariant Galton-Watson Branching Process for Earthquake Occurrence. Geophysical Journal International, ggac204, doi:10.1093/gji/ggac204
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Reference:
Kovchegov, Y., I. Zaliapin, and Y. Ben-Zion (2022) Invariant Galton-Watson Branching Process for Earthquake Occurrence. Geophysical Journal International, ggac204, doi:10.1093/gji/ggac204
SHOW MORE