Spatio-temporal clustering of earthquakes: Comparative analysis of marginal vs. coupled components in different regions

Natalie Bladis, & Ilya Zaliapin

Published September 11, 2022, SCEC Contribution #12474, 2022 SCEC Annual Meeting Poster #212 (PDF)

Poster Image: 
Earthquake clustering is a fundamental component of seismicity that reflects various forms of earthquake triggering mechanisms. Zaliapin and Ben-Zion (SRL, 2021) introduced a simple and robust measure of space-time clustering, using the receiver operating characteristic (ROC) diagram, that allows disentangling effects related to concentration of events around a heterogeneous regional fault network (marginal space distribution of events) from coupled space-time fluctuations (joint space-time distribution). Their analysis has shown that the overall observed earthquake clustering is high, and the marginal space clustering plays a dominant role in the catalog clustering for a variety of regional catalogs and the global seismicity. At the same time, when one removes the marginal clustering and focuses on the coupled space-time clustering, different catalogs show different degrees of clustering, reflecting a variety of specific triggering conditions and mechanisms. This work applies the clustering measure of Zaliapin and Ben-Zion (SRL, 2021) to examine additional regions and catalogs. We discuss robustness of the results with respect to the lower magnitude cutoff and spatio-temporal resolutions of analysis, and relative importance of the marginal space clustering vs. coupled space-time clustering in different environments.

Zaliapin, I. and Y. Ben-Zion (2021) Perspectives on clustering and declustering of earthquakes. Seismological Research Letters, 93 (1): 386–401 doi:10.1785/0220210127

Citation
Bladis, N., & Zaliapin, I. (2022, 09). Spatio-temporal clustering of earthquakes: Comparative analysis of marginal vs. coupled components in different regions . Poster Presentation at 2022 SCEC Annual Meeting.


Related Projects & Working Groups
Earthquake Forecasting and Predictability (EFP)