Connectivity of geoelectric network before strong earthquakes

Earthquakes are reported to relate to rupture phenomena in complex self-organizing systems. Hence, the earthquake rupture is regarded as a critical point. The preparation process of an earthquake could be considered as the crustal system approaching this critical point. Complex dynamical systems can have critical tipping points at which a sudden shift to a contrasting dynamical regime may occur; in the meantime, the time series of the systems can behave much differently. Although it is extremely challenging to predict such critical points before they are reached, work in different scientific fields is now suggesting the existence of generic early-warning signals that may indicate a wide class of systems if a critical threshold is approaching. Those precursory signals include increasing correlations and variance, varying skewness, and so on. The critical transition of a system includes spatial criticality and temporal criticality. In this study, we attempt to research the spatial and temporal criticality of the crustal system by using the self-potential (SP) signals of the Taiwan Geoelectric Monitoring System (GEMS). The GEMS network consists of 20 SP stations with an interstation distance of 50 km. We calculate the correlations of the daily signals between any two stations, which formed an adjacency matrix. Then, we estimate the connectivity density based on the adjacency matrix and compare the daily connectivity density time series with M_L ≥ 5 earthquakes. We would expect to find out high connectivity densities before a strong earthquake. This would mean that earthquake-related telluric currents flow out through the GEMS stations during the earthquake preparation process; hence, the SP signals of most stations would almost be connected. As a result, we might establish an earthquake forecasting technique using the SP data based on the concept of the critical-point theory.