Colliding Cascades Model for Earthquake Prediction

A wide set of premonitory seismicity patterns is reproduced on a numerical model of seismicity, and their performance in prediction of major earthquakes is evaluated. Seismicity is generated by the Colliding Cascades Model, recently developed by the same authors. The model has a hierarchical structure. It describes the interaction of two cascades: a direct cascade of loading, which is applied to the top (largest) element and transfers down the hierarchy, and inverse cascade of failures, which goes up the hierarchy, from smaller to larger elements. These cascades collide and interact: loading leads to failures, while failures release and redistribute the loading. Three basic types of earthquake precursors are considered. They reflect the following integral characteristics of seismicity: (i) the clustering of earthquakes in space and time, (ii) the intensity of earthquake sequences, and (iii) the correlation distance between earthquakes. Patterns of the first two types were established mainly by the analysis of observations and are used in the intermediate term earthquake prediction algorithms with a characteristic duration of the alarm of a few years. These patterns are validated by advance earthquake prediction. Patterns of the third type have been found very recently in the Colliding Cascades Model, though they were hypothesized previously. They have yet to be validated by observations of real seismicity. For each precursor, we explore what is called an “error diagram” showing the total duration of alarms, the rate of failures to predict, and the rate of false alarms.