Assessing Markovian Models for Seismic Hazard and Forecasting

We propose the use of statistical measures to quantify robustness, uncertainty, and significance for Markovian models of large magnitude seismic systems, and we also propose a method for choosing the best of different models by using the normalized measures in a discriminant function. We tested the proposed methods on earthquakes occurring in an area around Japan, divided into four regions; modeling the system as having four states, where each state corresponds to the region where the latest large earthquake, larger than a given threshold moment magnitude, has occurred. Our results show that for the 7.0-7.3 threshold magnitude range the seismicity of this region does occur according to a Markovian process, with optimum results for threshold magnitude 7.1, whereas for magnitudes outside this range seismicity is less Markovian.

Automated summary

The study proposes the use of statistical measures to quantify the robustness, uncertainty, and significance of seismic systems modeled by Markovian models. A method for selecting the best model using normalized measures is also suggested. Testing on earthquake data from Japan showed that seismic events within a specific magnitude range exhibit Markovian behavior.