Nowcasting Earthquakes: Imaging the Earthquake Cycle in California With Machine Learning

Abstract

We propose a new machine learning-based method for nowcasting earthquakes to image the time-dependent earthquake cycle. The result is a timeseries which may correspond to the process of stress accumulation and release. The timeseries is constructed by using Principal Component Analysis of regional seismicity. The patterns are found as eigenvectors of the cross-correlation matrix of a collection of seismicity timeseries in a coarse grained regional spatial grid (pattern recognition via unsupervised machine learning). The eigenvalues of this matrix represent the relative importance of the various eigenpatterns. Using the eigenvectors and eigenvalues, we compute the weighted correlation timeseries (WCT) of the regional seismicity. This timeseries has the property that the weighted correlation generally decreases prior to major earthquakes in the region, and increases suddenly just after a major earthquake occurs. As in a previous paper (Rundle and Donnellan, 2020), we find that this method produces a nowcasting timeseries that resembles the hypothesized regional stress accumulation and release process characterizing the earthquake cycle. We then address the problem of whether the timeseries contains information regarding future large earthquakes. For this we compute a Receiver Operating Characteristic and determine the decision thresholds for several future time periods of interest (optimization via supervised machine learning). We find that signals can be Accepted ArticleThis article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Estimating the Epicenter of a Future Strong Earthquake in Southern California, Mexico, and Central America by Means of Natural Time Analysis and Earthquake Nowcasting

“…Rundle et al [ 11 ] proposed EQ nowcasting as a method for estimating the seismic risk through the current state of fault systems in the progress of the EQ cycle identified on the basis of natural time (cf. more recently the construction of time series resembling the EQ cycle has been extensively studied in References [ 16 , 18 , 97 ]). To estimate the seismic risk, EN uses an EQ catalog to calculate from the number of ‘small’ EQs, defined as those with magnitude but above a threshold , i.e., , the level of hazard for ‘large’ EQs.…”

Optimizing Earthquake Nowcasting With Machine Learning: The Role of Strain Hardening in the Earthquake Cycle

“…Recent research has developed the idea of earthquake nowcasting, which uses state (“proxy”) variables to infer the current state of the earthquake cycle (Luginbuhl et al., 2019 ; Pasari, 2019a , 2019b , 2020 ; Pasari & Sharma, 2020 ; Rundle et al., 2016 , 2018 , 2019 , 2020 ). An approach such as this is needed since the cycle of stress accumulation and release is not observable (Rundle, Donnellan et al., 2021 ; Rundle, Stein et al., 2021 ; Scholz, 2019 ). These first approaches to nowcasting have been based on the concept of natural time (Sarlis et al., 2018 ; Varotsos et al., 2001 , 2002 , 2011 , 2013 , 2014 ; Varotsos, Sarlis, et al., 2020 ; Varotsos, Skordas, et al., 2020 ).…”

“…A review of the current state of earthquake nowcasting, forecasting, and prediction is given by Rundle, Donnellan et al. ( 2021 ); Rundle, Stein et al. ( 2021 ).…”

Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean

“…It is the scope of the present paper to show that by combining the above two NTA results with the modern method of nowcasting EQs [33], an estimate of the epicenter of the impending EQ with M ≥ 7.1 in the eastern Mediterranean region is achieved. EQ nowcasting employs natural time, which is unique in its characteristics [116], to estimate seismic risk by means of an EQ potential score (EPS) and found many useful applications, both regionally and globally [33,[116][117][118][119][120][121][122][123][124][125][126]. EQ nowcasting [33] has, so far, focused on describing the current state of fault systems.…”