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 the prediction of major model earthquakes is evaluated. Seismicity is generated by the colliding cascade s model, recently developed by the authors. The model has a hierarchical st ructure. It describes the interaction of two cascades: a direct cascade of loading, which is applied to the top (largest) element and transfers down t he hierarchy, and an inverse cascade of failures, which goes up the hierarc hy, from the smaller to the larger elements. These cascades collide and int eract: loading leads to failures, while failures release and redistribute t he loading. Three basic types of earthquake precursors are considered: (i) the clustering of earthquakes in space and time, (ii) the intensity of eart hquake sequences, and (iii) the correlation distance between earthquakes. P atterns of the first two types are used in intermediate-term earthquake pre diction algorithms. Patterns of the third type are found in the colliding c ascades model, although they were hypothesized previously. They have not be en validated by observations. For each precursor, we explore what is called an 'error diagram' showing the total duration of alarms, the rate of failu res to predict, and the rate of false alarms.