Implications of a statistical physics approach for earthquake hazard assessment and forecasting

There is accumulating evidence that distributed seismicity is a problem in statistical physics. Seismicity is taken to be a type example of self-organized criticality. This association has important implications regarding earthquake hazard assessment and forecasting. A characteristic of a thermodynamic system is that it exhibits a background noise that is self-organized. In the case of a dilute gas, this self-organization is the Maxwell-Boltzmann distribution of molecular velocities. In seismicity, it is the Gutenberg-Richter frequency-magnitude scaling; this scaling is fractal. Observations favor the hypothesis that smaller earthquakes in moderate-sized regions occur at rates that are only weakly dependent on time. Thus, the rate of occurrence of smaller earthquakes can be extrapolated to assess the hazard of larger earthquakes in a region. We obtain the rate of occurrence of earthquakes with rn > 4 in 1 degrees x 1 degrees areas from the NEIC catalog. Using only this data we produce global maps of the seismic hazard. Observations also favor the hypothesis that the stress level at which an earthquake occurs is a second-order critical point. As a critical point is approached, correlations extend over increasingly larger distances. In terms of seismicity, the approach to a critical point is associated with an increase in the rate of occurrence of intermediate-sized earthquakes prior to a large earthquake. This precursory activation has been shown to exhibit power-law scaling and to occur over a region about ten times larger than the rupture length of the large earthquake. Analyses of the spinoidal behavior associated with second-order critical points predict the power-law increase in seismic activity prior to a characteristic earthquake. This precursory activation provides the basis for intermediate-range earthquake forecasting.