Statistical Modeling of the Migrating Pattern of the Occurrence of Successive Earthquakes in the Zagros Region

1. Introduction
Most of the seismic energy (or tectonic loading) accumulated in lithosphere of active regions is released through the occurrence of large earthquakes that usually show complex spatio-temporal patterns. Hence, the study of the spatial and temporal pattern of these occurrences is very important for revealing the seismotectonic nature of these regions. Over the past decades, the statistics of the waiting times between consecutive earthquakes (so-called inter-event times) have become the focus of research. Statistical analysis of inter-event times of earthquakes allows the derivation of useful information that can allow the development of earthquake forecasting strategies, and inter-event time statistics for moderate to small events may be used to extrapolate inter-event time behaviour at larger scales. Assuming that the release of seismic energy (by occurring earthquakes) is stationary in the whole region of Zagros, in this research, the spatio-temporal relationships of the occurrences of large earthquakes that occurred in this region have been studied.

Methodology

In this study, the migration pattern of successive earthquakes in the Zagros region during the period 1976-2019 has been studied for earthquakes with magnitude 4.5 and greater. In order to carry out this work, the earthquake data of the examined region with M ≥ 4.5 (1976-2019) have been obtained from the USGS catalog. Then, the inter-event time, migration distance, and migration trend of successive earthquakes with different lower magnitude thresholds of 4.5, 0.5 and 5.5 were calculated and the statistical distribution of these data was analyzed and modeled.

Results and Discussion

Statistical analysis of the inter-event times between consecutive earthquakes in the Zagros region shows that among the different models used in statistical modeling of data, Weibull and Gamma models show the best agreement with the statistical distribution of inter-event time data. In addition, it is observed that larger earthquakes are less compatible with these models. Furthermore, migration distance data from successive earthquakes also shows a decreasing pattern, similar to the inter-event time distribution data. In addition, the study of the relationship between the two variables of migration distance and time interval between events shows that it is not possible to find a significant relationship between these two variables especially for earthquakes of smaller magnitude, but for larger earthquakes, it seems that a positive correlation between these two variables exists. This finding indicates that earthquakes with more inter-event times are expected to occur farther apart from each other, which could be a reason for seismicity migration behavior of earthquakes in this region. Also, the directional pattern of earthquakes migration data shows a pattern consistent with the general trend of active faults in the Zagros region, which confirms the idea that the activation of discrete segments of fault systems in this region plays a key role in the temporal and temporal pattern of seismicity. Based on the results of this study, it is expected that earthquakes with magnitude 5.5 and greater, tend to occur with an average migration distance of about 418 km and an average waiting time of 198 days, and in the dominant directional azimuth of N62W or S62E, compared to their previous events.

Conclusions

The results of this study can be considered as an effective step to better understanding the temporal-spatial pattern of seismicity in the Zagros region and also as an attempt to achieve earthquake prediction in a regional scale.
It is expected that in the future, with the possibility of access to more accurate data and the use of other new methods such as neural network modeling and artificial intelligence, it will be possible to better understand the temporal and spatial pattern of earthquakes, which undoubtedly is an important and effective step to achieve earthquake prediction on a regional scale.