SCEC Award Number 12085 View PDF
Proposal Category Collaborative Proposal (Integration and Theory)
Proposal Title Towards a unifying statistical framework for identification and analysis of earthquake clusters
Name Organization
Ilya Zaliapin University of Nevada, Reno Yehuda Ben-Zion University of Southern California
Other Participants Maggie Michalowski (UNR, undergraduate)
Zachary Ross (USC, graduate)
SCEC Priorities 2b, 2f, 4e SCEC Groups FARM, EFP, CSEP
Report Due Date 03/15/2013 Date Report Submitted N/A
Project Abstract
The project has developed and tested a robust method for comprehensive detection and analysis of earthquake clusters. Analysis of the ETAS model demonstrates that the cluster detection results are accurate and stable with respect to (i) three numerical parameters of the method, (ii) variations of the minimal reported magnitude, (iii) catalog incompleteness, and (iv) location errors. The method was applied to a 1981-2011 relocated seismicity catalog of southern California having 111,981 events with magnitudes m ≥ 2, and corresponding synthetic catalogs produced by the ETAS model. Application of the method to the observed catalog separates the 111,981 examined earthquakes into 41,393 statistically significant clusters comprised of foreshocks, mainshocks and aftershocks. Systematic analysis allows us to detect several new features of seismicity. Notably, the project results establish the existence of two dominant types of small-to-medium magnitude earthquake families – burst-like and swarm-like sequences – and a variety of intermediate cluster forms obtained as a mixture of the two dominant types, and demonstrate systematic spatial variability of the cluster characteristics on a scale of tens of kilometers in relation to heat flow and other properties governing the effective viscosity of a region. The burst-like clusters likely reflect highly-brittle failures in relatively cold regions, while the swarm-like clusters are likely associated with mixed brittle-ductile failures in regions with relatively high temperature and/or fluid content. The results of this project may be used to develop improved region-specific hazard estimates and earthquake forecasts.
Intellectual Merit The project introduced, tested, and applied a novel statistical approach for studying seismic clustering, which is conceptually different from the existing cluster techniques. The results directly address the problems of triggered seismicity (including triggering in geothermal zones), fault-specific description of seismicity, and physical interpretation of seismic patterns.
Broader Impacts The project results might be of interest to a broader community in statistical seismology. The results of this project may be used to develop improved region-specific hazard estimates and earthquake forecasts.
Exemplary Figure Figure 3
Spatial distribution of clusters of different types in southern California (magnitude m > 4, size N > 10). The cluster type is quantified using a scalar measure average topologic leaf depth . Large depth corresponds to swarm-like clusters, small depth – to burst-like clusters. The figure shows five special study regions of Zaliapin and Ben-Zion [2013b]. Regions with decreased level of effective viscosity (Coso and Salton trough) are characterized by predominantly swarm-like clusters. Regions with increased level of effective viscosity (Ventura, San Bernardino, San Gabriel, Mojave) – have predominantly burst-like clusters.