Power-law magnitude distributions and spatio-temporal clustering and separation in a cellular automata model of earthquakes

Abstract

We propose a cellular automata model for earthquake occurrences patterned after the sand pile model of self-organized criticality. By incorporating a single parameter describing the probability to target the most susceptible site, the model successfully reproduces the statistical signatures of seismicity in space, time, and magnitude dimensions, simultaneously. Model statistics show remarkable comparison with long-period empirical data from Philippine earthquakes, suggesting that the critical-targeting probability is related to the rate of aftershock occurrences.