Pattern identification of strong earthquakes in North American- Puerto Rico region through Correlation fractal dimension and Coulomb stress

This study attempts to investigate the patterns of correlation fractal dimension (Dc) prior to the occurrence of strong earthquakes by implementing modified Grassberger and Procaccia (1983) algorithm.  The primary input for current research is earthquake epicentre locations. Through this method, dispersed and clustered seismicity can be distinguished by analysing spatiotemporal distribution of earthquake clusters. The low Dc values suggest dense clusters while high Dc values imply a scattered distribution of occurrences. In other words, low Dc represents a highly stressed region. Therefore, by monitoring the variations in Dc, we get valuable insights regarding spatiotemporal clustering of events as well as state of stress. To confirm the high stress brought on by dense clusters prior to the mainshock, we make use of the coulomb failure criterion to measure the Coulomb stress. For testing this hypothesis we have done analysis in southern California (SC), Baja California (BaC), and Puerto Rico Island (PRI).

Major plate movement between the North American plate and the Pacific plate is accommodated by the San Andreas Fault (SAF) and the remaining is by Eastern California Shear Zone (ECSZ). However, the ECSZ has experienced three strong earthquakes in the last thirty years. This indicates an anomalous pattern of seismicity developing in ECSZ. The recent rupture of 2019 Ridgecrest earthquake has caused stress perturbation along Garlock Fault (dormant fault, capable of producing M >7 earthquakes) throws light on the probable future event. We did fractal analysis on 30 years (1990-2020) of data considering 50 earthquakes per each window. Four strong earthquakes have chosen for studying; 2019 Ridgecrest (M_w7.1), 2010 El-Mayor Cucapah (M_w7.2), 1999 Hectormine (M_w7.1), and 1992 Landers (M_w7.3).In general, a relative decrease in Dc before each of the events is observed.

The commencement of 2019 Puerto Rico sequence trailed by the incidence of Mw6.4, 07 January 2020, earthquake highlights the importance of studying seismicity patterns in the PRI. Tectonic setting of the PRI is highly complex; characterized by dynamic seismicity. We have analysed ~32 years of seismicity data (M≥ 2.8). The fractal study of the Puerto Rico earthquake suggests a relative decline in Dc during 2019. It should be noted that the emergence of spatially closed clusters occurred at the same time in the southwestern PRI. When the static stress is calculated, the southwestern clusters indicate a highly stressed crust. This validates the relationship between the stress and low Dc observed prior to the occurrence of Mw6.4 January 2020 event.

Based on our study, it is possible to conclude that a significant drop in the Dc proceeds the mainshock. This pattern is explicit in the five major earthquakes in the study area. So we propose that our approach based on the patterns of correlation fractal dimension is a novel method to identify numerical precursors of strong earthquakes before the rupture.