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Forecasting the evolution of seismicity in southern California:
Animations built on earthquake stress transfer

Journal of Geophysical Research, Vol. 110, B05S16, doi:10.1029/2004JB003415, 2005
[Free access to online article and animations]


Shinji Toda, Active Fault Research Center, AIST, Tsukuba, Japan

Ross Stein, U.S. Geological Survey, Menlo Park, CA

Keith Richards-Dinger, Geothermal Program Office, Naval Air Weapons Station, China Lake, CA

Serkan Bozkurt, U.S. Geological Survey, Menlo Park, CA

Summary. There is growing evidence that large earthquakes can inhibit or promote failure on nearby faults for decades to centuries, and that the transfer of stress plays a governing role in this interaction. Here we attempt to reproduce the distribution of mainshocks, aftershocks and surrounding seismicity observed during 1986-2003 in a 300 x 310 km area centered on the 1992 M=7.3 Landers earthquake. Our approach incorporates the static stress transferred by each M≥6 shock, after which seismicity evolves according to a law developed from laboratory rock mechanics experiments. For this model, Coulomb stress changes amplify the background seismicity, so small stress changes produce large changes in seismicity rate in areas of high background seismicity. Similarly, seismicity rate declines in the stress shadows are evident only in areas with previously high seismicity rates. Thus a key constituent is the background seismicity rate, which we smooth from the 5 years of seismicity preceding the test period. Finally, we offer a M≥5 earthquake forecast for 2005-2015, assigning probabilities to 324 10 x 10-km cells.

There are several ways we assess the model success. The mean correlation coefficient between observed and predicted shocks is 0.52 for 1986-2003, and 0.63 for 1992-2003; a control standard aftershock model yields 0.54 and 0.52 for the same periods. Four M≥6 shocks struck during the test period; three locate at sites where the expected seismicity rate falls above the 92 percentile, and one above the 75 percentile. At heart, we interpret our results to mean that earthquake stress changes do not simply turn on or off seismicity; rather, the background seismicity rate is enhanced by stress increases and suppressed by stress decreases. This, we believe, best explains why seismicity in stress trigger zones is often patchy or discontinuous; why seismicity rate declines in stress shadows are often subtle or absent, and why some aftershock zones expand, migrate or densify. While our model is a far cry from an earthquake prediction, it is, perhaps, on the road to the more useful and accurate earthquake forecasts that we all seek.


Image caption. Observed southern California M≥1.4 seismicity during 1996-1999 is represented by purple dots. This can be compared to the seismicity predicted by the the fading effect of stress changes imparted by large earthquakes, such as the 1992 magnitude=7.4 Landers earthquake (white-inscribed black line in the center of the image). The predicted seismicity is represented by the warm tones; the higher the predicted number of earthquakes, the redder the color. The spatial correlation coefficient between observed and predicted seismicity is 0.85 for this frame of the animation. Los Angeles lies just beyond the left center of the image; the Pacific Ocean is in the lower left and the Salton Sea in the lower right. Image Bozkurt.