Frontiers in Earth Science (Feb 2021)
Strong Earthquakes Recurrence Times of the Southern Thessaly, Greece, Fault System: Insights from a Physics-Based Simulator Application
Abstract
The recurrence time, Tr, of strong earthquakes above a predefined magnitude threshold on specific faults or fault segments is an important parameter, that could be used as an input in the development of long-term fault-based Earthquake Rupture Forecasts (ERF). The amount of observational recurrence time data per segment is often limited, due to the long duration of the stress rebuilt and the shortage of earthquake catalogs. As a consequence, the application of robust statistical models is difficult to implement with a precise conclusion, concerning Tr and its variability. Physics-based earthquake simulators are a powerful tool to overcome these limitations, and could provide much longer earthquake records than the historical and instrumental earthquake catalogs. A physics-based simulator, which embodies known physical processes, is applied in the Southern Thessaly Fault Zone (Greece), aiming to provide insights about the recurrence behavior of earthquakes with Mw ≥ 6.0 in the six major fault segments in the study area. The build of the input fault model is made by compiling the geometrical and kinematic parameters of the fault network from the available seismotectonic studies. The simulation is implemented through the application of the algorithm multiple times, with a series of different input free parameters, in order to conclude in the simulated catalog which showed the best performance in respect to the observational data. The detailed examination of the 254 Mw ≥ 6.0 earthquakes reported in the simulated catalog reveals that both single and multiple segmented ruptures can be realized in the study area. Results of statistical analysis of the interevent times of the Mw ≥ 6.0 earthquakes per segment evidence quasi-periodic recurrence behavior and better performance of the Brownian Passage Time (BPT) renewal model in comparison to the Poissonian behavior.
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