Earth Planets Space, Vol. 56 (No. 8), pp. 761-771, 2004
John B. Rundle1, Paul B. Rundle2, Andrea Donnellan3, and Geoffrey Fox4
1Center for Computational Science and Engineering, University of California, Davis, Davis, CA 95616; and Distinguished Visiting Scientist, Earth & Space Sciences Division, Jet Propulsion Laboratory, Pasadena, CA 91125, U.S.A.
2Department of Physics, Harvey Mudd College, Claremont, CA, U.S.A.
3Earth & Space Sciences Division, Jet Propulsion Laboratory, Pasadena, CA, U.S.A.
4Department of Computer Science, Indiana University, Bloomington, IN, U.S.A.
(Received December 1, 2003; Revised May 6, 2004; Accepted July 1, 2004)
We discuss the problem of earthquake forecasting in the context of new models for the dynamics based on statistical physics. Here we focus on new, topologically realistic system-level approaches to the modeling of earthquake faults. We show that the frictional failure physics of earthquakes in these complex, topologically realistic models leads to self-organization of the statistical dynamics, and produces statistical distributions characterizing the activity, notably the Gutenberg-Richter magnitude frequency distribution, that are similar to those observed in nature. In particular, we show that a parameterization of friction that includes a simple representation of a dynamic stress intensity factor is needed to organize the dynamics. We also show that the slip distributions for synthetic events obtained in the model are also similar to those observed in nature
Key words: Earthquakes, simulations, forecasting, stress, interactions, complex systems, scaling, systems.