Analysis and Prediction of the Earthquake Frequency Sequence in the Anninghe Fault Zone Based on the SARIMA Model

The Anninghe Fault Zone is an active, deep–large fault in southwestern China, with a history of multiple strong earthquakes. To reveal the temporal patterns of seismicity and improve medium- to short-term earthquake frequency prediction, this study constructs a quarterly seismic frequency sequence (M ≥ 3.0) from May 1972 to September 2025 and applies the SARIMA (seasonal autoregressive integrated moving average) model for modeling and prediction. The hypothesis is that the frequency sequence exhibits modelable seasonality, trends, and nested periodic structures. The ADF test and Ljung–Box test confirm that the sequence is stationary and non-white noise, satisfying the prerequisites for SARIMA modeling. The centered moving average method is used to extract short-term (1 year), medium-term (5 years), and long-term (10 years) periodic components, and corresponding SARIMA models are constructed. Results show that the medium-period model ARIMA(2,0,1) × (1,0,0)20 achieves the best prediction accuracy (RMSE = 0.6868, MAE = 0.6143), followed by the short-period model, while the long-period model yields slightly higher errors. All selected models pass residual white noise tests and parameter significance tests, and exhibit good robustness under different training–test splits. The main innovations are: (1) the first systematic application of SARIMA to earthquake frequency prediction in the Anninghe Fault Zone, and (2) a preliminary physical interpretation of multi-scale periodic components (e.g., seasonal loading, strain accumulation fluctuations). This method offers significant application value in regions with sparse seismic networks or limited precursory data, providing a new statistical tool for regional seismic hazard assessment and disaster mitigation planning.