# Precursory Analysis of GPS Time Series for Seismic Hazard Assessment

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## Abstract

We discuss the use of fractal analysis of geophysical big data as a precursory method for the estimation of current seismic hazard. We begin by analyzing GPS time series of land surface displacements recorded in various regions of the planet exhibiting different degrees of seismic activity. We show how the quantitative measure of chaoticity based on a modified detrended fluctuation analysis (DFA) method can be used to distinguish critical and noncritical regimes of evolution of the Earth’s crust. Having established the reference values for the measure of chaoticity, we then choose California as the case study region and apply modified DFA to over 1200 time series for determining local areas currently exposed to higher seismic hazard. We comprehensively analyze the results obtained and compare them with those produced by conventional risk assessment methods. We demonstrate consistency of our results and yet discover that the suggested approach allows us to quantify two qualitatively different mechanisms involved in the growth of seismic hazards. We propose a hypothesis which relates these mechanisms to the known mechanisms of earthquake generation that evince a growth of collective behavior in the Earth’s crust on the eve of an earthquake. In order to verify the hypothesis, we analyze the same GPS data by an independent statistical method, canonical coherence analysis (CCA), which permits us to quantify the degree of synchronized behavior of constituents of the Earth’s crust. The CCA method confirms our previously obtained estimates, thus supporting fractal analysis of GPS time series as a suitable precursory method for current seismic hazard assessment.

## Keywords

Short- and intermediate-term seismic hazard assessment GPS time series collective behavior detrended fluctuation analysis coherence analysis transition to criticality## Notes

### Acknowledgements

We are grateful to scientists of the Nevada Geodetic Laboratory (University of Nevada, the USA) for preprocessing the raw GPS data and making them publicly available. The software implementing the modified DFA method used for processing the time series is freely available at the website of Sceptica Scientific Ltd (www.sceptica.co.uk/?catastrophes) under a copyleft license. We acknowledge valuable comments of the anonymous referees that have contributed to the improvement of the final version of the paper. The research was partially supported by the Russian Foundation for Basic Research, Grant No. 18-05-00133, project ”Estimation of fluctuations of seismic hazard on the basis of complex analysis of the Earth’s ambient noise.”

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