SCEC Award Number 16089 View PDF
Proposal Category Collaborative Proposal (Integration and Theory)
Proposal Title Global Earthquake Activity Rate Model
Name Organization
Yan Kagan University of California, Los Angeles David Jackson University of California, Los Angeles
Other Participants
SCEC Priorities 2b, 4e, 1d SCEC Groups Seismology, EFP, CSEP
Report Due Date 03/15/2017 Date Report Submitted 06/29/2017
Project Abstract
Recent successes of global geodetic surveys allowed us to construct a high-resolution map of the Earth surface displacement and, after converting this map to earthquake rate, combine these maps with those based on seismicity smoothing. We then constructed a Global Earthquake Activity Rate model as a function of the magnitude at 0.1 by 0.1 degree resolution. Nicknamed “GEAR”, the model relies on a global strain rate model (GSRM) and the instrumental earthquake catalogs. Thus, for our forecast we use datasets that provide uniform global coverage: seismic catalogs, global plate boundary models, and Global Positioning System (GPS) geodetic velocities. We tested this model in a quasi-prospective mode, using data not included in model formulation, and submitted the model to CSEP for formal prospective testing. The model can be used by Global Earthquake Model foundation (GEM) and others in seismic hazard estimation. In our recent work, we’ve updated the estimates of corner magnitudes for the five tectonic categories of earthquakes assumed in the model based on recent large earthquakes; provided statistical methods for assessing the uncertainties in focal mechanism forecasts; devised improved statistical methods for testing forecasts of number of earthquakes in given time and magnitude intervals; and applied the method to short-term forecasts of great earthquakes following moderate to large ones.
Intellectual Merit GEAR forecasts earthquake rates at moment magnitudes 5.8 and larger for periods from years to decades
with no explicit time dependence. The normalized magnitude distribution at each location is a combination
of the tapered Gutenberg-Richter distributions with b-values and the corner magnitudes determined by a
few global parameters that depend on the tectonic style and the focal mechanism proportion. The seismic
and strain-rate components of the model are specified separately and then combined optimally to fit
earthquake occurrence over the last several years. GEAR performs well in quasi-prospective tests using the
GCMT catalog after 2005 and the GEM catalog from 1918 to 1976; GEAR will be rigorously tested by
CSEP prospectively against future earthquakes. Because of its simplicity, GEAR can serve as a well-vetted
reference model and as a null-hypothesis against which more complex models can be tested. With its high
spatial resolution, GEAR can also be compared to detailed regional models. We also discuss potential
methods to improve and extend the forecasts. Such methods include extending the forecast to lower
magnitudes, introducing focal mechanisms into prediction methods, and making the short-term forecast an
integral part of the practical forecast implementation.
Broader Impacts Presentations of project results at UCLA have involved professors, graduate students, and undergrad
students, informing them of the advantages of comprehensive global studies and statistical estimation and
hypothesis testing. Presentation of results at SCEC meetings and AGU and SSA conferences has stimulated
dialog among seismologists, geologists, and computational modelers of earthquake occurrence and
interaction. Our publications and presentation on this topic have interested scientists at USGS, and in the
re-insurance industry, because our methods are fully global, testable, and well documented in our
publications. Our short-term forecasts may greatly enhance decision making for rapid response to
threatening seismic conditions.
Exemplary Figure Figure 2. Short-term earthquake potential for south American area calculated 2015/09/17, the day after the m8.3
Illapel Chile earthquake.

Figure copied from Fig 11 of
Kagan, Yan Y., 2016. Worldwide Earthquake Forecasts,
"Stochastic Environmental Research and Risk Assessment (SERRA)", special
issue Seismomatics, DOI: 10.1007/s00477-016-1268-9 Publication 6260, SCEC.