AUTHOR=Xu Weijin , Li Xuejing , Gao Mengtan TITLE=Temporal distribution characteristics of earthquakes in Taiwan, China JOURNAL=Frontiers in Earth Science VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.930468 DOI=10.3389/feart.2022.930468 ISSN=2296-6463 ABSTRACT=

The characteristics of seismic temporal distribution represent an important basis for earthquake prediction and seismic hazard analysis. In this paper, based on the seismic catalogs in Taiwan, and using Poisson (exponential distribution), Gamma, Lognormal, Weibull, and Brownian passage time distributions as target models, we adopt the maximum likelihood method for estimating model parameters. The optimal model for describing the temporal distribution of earthquakes in Taiwan is determined according to the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), K-S test, Chi-square test, and coefficient of determination R2 results. The results show that for moderate-strong earthquakes events (MW < 7.0), the Gamma distribution model can well describe the temporal distribution characteristics of earthquakes, while large earthquakes (MW ≥ 7.0) can be described entirely by exponential distribution. In addition, the temporal correlation between earthquakes is also examined through diffusion entropy analysis. The results show that seismic activity features temporal correlation, and earthquakes with relatively small magnitude (MW < 7) are affected by larger events (MW ≥ 7.0), thus suggesting long-term memory in time. In this study, the probability of the occurrence of a major earthquake in Taiwan is also calculated. The results show that the probability of an MW ≥ 7.0 earthquake in Taiwan in the next 10 years reaches 91.3%. The results may be used to inform the selection of seismic time distribution models and the calculation of seismic activity parameters in earthquake prediction and seismic hazard calculation, and hold scientific significance for understanding the mechanism of earthquake genesis.