Cluster-based foreshock discrimination model with flexible time horizon and mainshock magnitudes

Abstract

Abstract Foreshock detection before mainshock occurrence is an important challenge limiting the short-term forecasts of large earthquakes. Various models for predicting mainshocks based on discrimination of foreshocks activity have been proposed, but many of them work in restricted scenarios and neglect foreshocks and mainshocks out of their scope. In disaster prevention, it is often necessary to change the forecast period and the magnitude of target mainshocks. This paper presents a cluster-based statistical discrimination of foreshocks which is applicable all over Japan and adjustable with respect to forecasting time span and mainshock magnitudes. Using the single-link clustering method, the model updates the expanding seismic clusters and determines in real time the probabilities that larger subsequent events will occur. The foreshock clusters and the others show different trends of certain feature statistics with respect to their magnitudes and spatiotemporal distances. Based on those features and the epicentral location, a nonlinear logistic regression model is used to evaluate the probabilities that growing seismic clusters are foreshocks that will trigger mainshocks within 30 days. The log of odds is estimated between the foreshock clusters and other clusters for respective feature values as nonlinear spline functions from a Japanese hypocenter catalog for the period 1926–1999. Based on the estimated odds functions, foreshock clusters tend to have smaller differences in their two largest magnitudes, shorter time durations, and slightly longer epicentral distances within the individual clusters. Given a potential foreshock cluster, its mainshock magnitude can be predicted by the Gutenberg–Richter law over the largest foreshock magnitude. The timing of mainshock occurrences from foreshocks is also predicted by multiplying the portion of mainshocks within a shorter span from those within 30 days by the evaluated foreshock probabilities. The predictive performance of our model is validated by the holdout method using a Japanese hypocenter catalog before and after 2000. The evaluated foreshock probabilities are roughly consistent with the actual portion of foreshocks in the validation catalog and could serve as an alert for large mainshocks.

Keywords

• Earthquake prediction
• JMA catalog
• Foreshock discrimination
• Mainshock magnitude
• Seismic clustering
• Logistic regression