Earthquake Forecasting Using Hidden Markov Models

TL;DR

This paper introduces a novel earthquake forecasting method using hidden Markov models, predicting mainshock probabilities in specific regions based on historical seismic data, marking the first application of HMMs in this context.

Contribution

The paper presents the first application of hidden Markov models to earthquake forecasting, providing a new probabilistic approach based on seismic event history.

Findings

Effective forecasting of mainshock probabilities within 1, 5, and 10 days

Application to seismic activity in southern California and western Nevada

Demonstrates the potential of HMMs for earthquake prediction

Abstract

This paper develops a novel method, based on hidden Markov models, to forecast earthquakes and applies the method to mainshock seismic activity in southern California and western Nevada. The forecasts are of the probability of a mainshock within one, five, and ten days in the entire study region or in specific subregions and are based on the observations available at the forecast time, namely the inter event times and locations of the previous mainshocks and the elapsed time since the most recent one. Hidden Markov models have been applied to many problems, including earthquake classification; this is the first application to earthquake forecasting.