scholarly journals Long-term earthquake forecasts based on the epidemic-type aftershock sequence (ETAS) model for short-term clustering

2012 ◽  
Vol 2 (1) ◽  
pp. 8 ◽  
Author(s):  
Jiancang Zhuang
Keyword(s):  
Time Window ◽  
Space Time ◽  
Aftershock Sequence ◽  
Maximum Magnitude ◽  
Short Term ◽  
Magnitude Distribution ◽  
Seismicity Rate ◽  
Distribution Of The Maximum ◽  
Epidemic Type Aftershock Sequence ◽  
Term Clustering

Based on the ETAS (epidemic-type aftershock sequence) model, which is used for describing the features of short-term clustering of earthquake occurrence, this paper presents some theories and techniques related to evaluating the probability distribution of the maximum magnitude in a given space-time window, where the Gutenberg-Richter law for earthquake magnitude distribution cannot be directly applied. It is seen that the distribution of the maximum magnitude in a given space-time volume is determined in the longterm by the background seismicity rate and the magnitude distribution of the largest events in each earthquake cluster. The techniques introduced were applied to the seismicity in the Japan region in the period from 1926 to 2009. It was found that the regions most likely to have big earthquakes are along the Tohoku (northeastern Japan) Arc and the Kuril Arc, both with much higher probabilities than the offshore Nankai and Tokai regions.

ETAS-Approach Accounting for Short-Term Incompleteness of Earthquake Catalogs

2021 ◽  
Author(s):  
Sebastian Hainzl
Keyword(s):  
Aftershock Sequence ◽  
Additional Parameter ◽  
Spatiotemporal Evolution ◽  
Short Term ◽  
Seismicity Rate ◽  
Detection Algorithms ◽  
Estimated Parameters ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences ◽  
Completeness Magnitude

ABSTRACT The epidemic-type aftershock sequence (ETAS) model is a powerful statistical model to explain and forecast the spatiotemporal evolution of seismicity. However, its parameter estimation can be strongly biased by catalog deficiencies, particularly short-term incompleteness related to missing events in phases of high-seismic activity. Recent studies have shown that these short-term fluctuations of the completeness magnitude can be explained by the blindness of detection algorithms after earthquakes, preventing the detection of events with a smaller magnitude. Based on this assumption, I derive a direct relation between the true and detectable seismicity rate and magnitude distributions, respectively. These relations only include one additional parameter, the so-called blind time Tb, and lead to a closed-form maximum-likelihood formulation to estimate the ETAS parameters directly accounting for varying completeness. Tests using synthetic simulations show that the true parameters can be resolved from incomplete catalogs. Finally, I apply the new model to California’s most prominent mainshock–aftershock sequences in the last decades. The results show that the model leads to superior fits with Tb decreasing with time, indicating improved detection algorithms. The estimated parameters significantly differ from the estimation with the standard approach, indicating higher b-values and larger trigger potentials than previously thought.

scholarly journals Short-term earthquake forecasting experiment before and during the L’Aquila (central Italy) seismic sequence of April 2009

2015 ◽  
Vol 57 (6) ◽  
Author(s):  
Maura Murru ◽  
Jiancang Zhuang ◽  
Rodolfo Console ◽  
Giuseppe Falcone
Keyword(s):  
Central Italy ◽  
Aftershock Sequence ◽  
Earthquake Forecasting ◽  
Model Parameters ◽  
Short Term ◽  
Productivity Function ◽  
Epidemic Type Aftershock Sequence ◽  
Forecasting Performance ◽  
The One ◽  
Lower Magnitude

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>In this paper, we compare the forecasting performance of several statistical models, which are used to describe the occurrence process of earthquakes in forecasting the short-term earthquake probabilities during the L’Aquila earthquake sequence in central Italy in 2009. These models include the Proximity to Past Earthquakes (PPE) model and two versions of the Epidemic Type Aftershock Sequence (ETAS) model. We used the information gains corresponding to the Poisson and binomial scores to evaluate the performance of these models. It is shown that both ETAS models work better than the PPE model. However, in comparing the two types of ETAS models, the one with the same fixed exponent coefficient (<span>alpha)</span> = 2.3 for both the productivity function and the scaling factor in the spatial response function (ETAS I), performs better in forecasting the active aftershock sequence than the model with different exponent coefficients (ETAS II), when the Poisson score is adopted. ETAS II performs better when a lower magnitude threshold of 2.0 and the binomial score are used. The reason is found to be that the catalog does not have an event of similar magnitude to the L’Aquila mainshock (M<sub>w</sub> 6.3) in the training period (April 16, 2005 to March 15, 2009), and the (<span>alpha)</span>-value is underestimated, thus the forecast seismicity is underestimated when the productivity function is extrapolated to high magnitudes. We also investigate the effect of the inclusion of small events in forecasting larger events. These results suggest that the training catalog used for estimating the model parameters should include earthquakes of magnitudes similar to the mainshock when forecasting seismicity during an aftershock sequence.</p></div></div></div>

Maximum Earthquake Size and Seismicity Rate from an ETAS Model with Slip Budget

2020 ◽  
Vol 110 (2) ◽  
pp. 874-885
Author(s):  
David Marsan ◽  
Yen Joe Tan
Keyword(s):  
Seismic Moment ◽  
Aftershock Sequence ◽  
Physical Parameters ◽  
Model Parameters ◽  
Seismicity Rate ◽  
Omori Law ◽  
Epidemic Type Aftershock Sequence ◽  
Earthquake Size ◽  
Maximum Earthquake ◽  
Seismicity Model

ABSTRACT We define a seismicity model based on (1) the epidemic-type aftershock sequence model that accounts for earthquake clustering, and (2) a closed slip budget at long timescale. This is achieved by not permitting an earthquake to have a seismic moment greater than the current seismic moment deficit. This causes the Gutenberg–Richter law to be modulated by a smooth upper cutoff, the location of which can be predicted from the model parameters. We investigate the various regimes of this model that more particularly include a regime in which the activity does not die off even with a vanishingly small spontaneous (i.e., background) earthquake rate and one that bears strong statistical similarities with repeating earthquake time series. Finally, this model relates the earthquake rate and the geodetic moment rate and, therefore, allows to make sense of this relationship in terms of fundamental empirical law (the Gutenberg–Richter law, the productivity law, and the Omori law) and physical parameters (seismic coupling, tectonic loading rate).

Testing of the foreshock hypothesis within an epidemic like description of seismicity

2020 ◽  
Author(s):  
G Petrillo ◽  
E Lippiello
Keyword(s):  
Seismic Activity ◽  
Good Description ◽  
Aftershock Sequence ◽  
Short Term ◽  
Etas Model ◽  
Temporal Clustering ◽  
Epidemic Type Aftershock Sequence ◽  
Preparatory Phase ◽  
Spatio Temporal ◽  
The One

Summary The Epidemic Type Aftershock Sequence (ETAS) model provides a good description of the post-seismic spatio-temporal clustering of seismicity and is also able to capture some features of the increase of seismic activity caused by foreshocks. Recent results, however, have shown that the number of foreshocks observed in instrumental catalogs is significantly much larger than the one predicted by the ETAS model. Here we show that it is possible to keep an epidemic description of post-seismic activity and, at the same time, to incorporate pre-seismic temporal clustering, related to foreshocks. Taking also into-account the short-term incompleteness of instrumental catalogs, we present a model which achieves very good description of the southern California seismicity both on the aftershock and on the foreshock side. Our results indicate that the existence of a preparatory phase anticipating mainshocks represents the most plausible explanation for the occurrence of foreshocks.

The overlap of aftershock coda waves and forecasting the first hour aftershocks

2020 ◽  
Author(s):  
Eugenio Lippiello ◽  
Giuseppe Petrillo ◽  
Cataldo Godano ◽  
Lucilla de Arcangelis ◽  
Anna Tramelli ◽  
...  
Keyword(s):  
Aftershock Sequence ◽  
Coda Waves ◽  
Statistical Features ◽  
Short Term ◽  
Geophysical Research ◽  
Ground Shaking ◽  
Epidemic Type Aftershock Sequence ◽  
Novel Approach ◽  
Single Station ◽  
Strong Ground

&lt;p&gt;We show that short term post-seismic incompleteness can be interpreted in terms of the overlap of aftershock coda waves. We use this information to develop a novel procedure which gives accurate occurrence probabilities of post-seismic strong ground shaking within 30 minutes after the mainshock. This novel approach uses, as only information, the ground velocity recorded at a single station without requiring that signals are transferred and elaborated by operational units. We will also discuss how this information can be implemented in the Epidemic-Type Aftershock Sequence model in order to reproduce statistical features in time and magnitude of recorded aftershocks.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Main references &lt;/strong&gt;&lt;/p&gt;&lt;p&gt;de Arcangelis L., Godano C. &amp; Lippiello E. (2018) &lt;em&gt;The Overlap of Aftershock Coda Waves and Short-Term Postseismic Forecasting. &lt;/em&gt;&lt;strong&gt;Journal of Geophysical Research: Solid Earth, &lt;/strong&gt;123: 5661-5674,doi:10.1029/2018JB015518&lt;/p&gt;&lt;p&gt;Lippiello E., Petrillo G. , Godano G. , Tramelli A., Papadimitriou E. &amp;, Karakostas V. (2019)&lt;em&gt; Forecasting of the first hour aftershocks by means of the perceived magnitude. &lt;/em&gt;&lt;strong&gt;Nature Communications&lt;/strong&gt; , 10, 2953, doi:10.1038/s41467-019-10763-3&lt;/p&gt;

How Do Statistical Parameters of Induced Seismicity Correlate with Fluid Injection? Case of Oklahoma

2021 ◽  
Author(s):  
Hideo Aochi ◽  
Julie Maury ◽  
Thomas Le Guenan
Keyword(s):  
Induced Seismicity ◽  
Aftershock Sequence ◽  
Statistical Parameters ◽  
Exponential Equation ◽  
Seismicity Rate ◽  
Epidemic Type Aftershock Sequence ◽  
Background Seismicity ◽  
Mechanical Interpretation ◽  
Independent Variable ◽  
Grid Points

Abstract The seismicity evolution in Oklahoma between 2010 and 2018 is analyzed systematically using an epidemic-type aftershock sequence model. To retrieve the nonstationary seismicity component, we systematically use a moving window of 200 events, each within a radius of 20 km at grid points spaced every 0.2°. Fifty-three areas in total are selected for our analysis. The evolution of the background seismicity rate μ is successfully retrieved toward its peak at the end of 2014 and during 2015, whereas the triggering parameter K is stable, slightly decreasing when the seismicity is activated. Consequently, the ratio of μ to the observed seismicity rate is not stationary. The acceleration of μ can be fit with an exponential equation relating μ to the normalized injected volume. After the peak, the attenuation phase can be fit with an exponential equation with time since peak as the independent variable. As a result, the evolution of induced seismicity can be followed statistically after it begins. The turning points, such as activation of the seismicity and timing of the peak, are difficult to identify solely from this statistical analysis and require a subsequent mechanical interpretation.

scholarly journals SEISMICITY CHANGES DETECTION DURING THE SEISMIC SEQUENCES EVOLUTION AS EVIDENCE OF STRESS CHANGES

2017 ◽  
Vol 43 (4) ◽  
pp. 1994
Author(s):  
A.C. Astiopoulos ◽  
E. Papadimitriou ◽  
V. Karakostas ◽  
D. Gospodinov ◽  
G. Drakatos
Keyword(s):  
Temporal Distribution ◽  
Aftershock Sequence ◽  
Occurrence Rate ◽  
Generation Process ◽  
Seismicity Rate ◽  
Seismic Sequences ◽  
Epidemic Type Aftershock Sequence ◽  
Stress Changes ◽  
Lefkada Island ◽  
Seismicity Rate Changes

The statistical properties of the aftershock occurrence are among the main issues in investigating the earthquake generation process. Seismicity rate changes during a seismic sequence, which are detected by the application of statistical models, are proved to be precursors of strong events occurring during the seismic excitation. Application of these models provides a tool in assessing the imminent seismic hazard, oftentimes by the estimation of the expected occurrence rate and comparison of the predicted rate with the observed one. The aim of this study is to examine the temporal distribution and especially the occurrence rate variations of aftershocks for two seismic sequences that took place, the first one near Skyros island in 2001 and the second one near Lefkada island in 2003, in order to detect and determine rate changes in connection with the evolution of the seismic activity. Analysis is performed through space–time stochastic models which are developed, based upon both aftershocks clustering studies and specific assumptions. The models applied are the Modified Omori Formula (MOF), the Epidemic Type Aftershock Sequence (ETAS) and the Restricted Epidemic Type Aftershock Sequence (RETAS). The modelling of seismicity rate changes, during the evolution of the particular seismic sequences, is then attempted in association with and as evidence of static stress changes

scholarly journals The Effect of Declustering on the Size Distribution of Mainshocks

2021 ◽  
Author(s):  
Leila Mizrahi ◽  
Shyam Nandan ◽  
Stefan Wiemer
Keyword(s):  
Seismic Hazard Assessment ◽  
B Value ◽  
Aftershock Sequence ◽  
Earthquake Catalogs ◽  
Magnitude Distribution ◽  
Independent Events ◽  
Potential Source ◽  
Epidemic Type Aftershock Sequence ◽  
Frequency Magnitude Distribution ◽  
Frequency Magnitude

Abstract Declustering aims to divide earthquake catalogs into independent events (mainshocks), and dependent (clustered) events, and is an integral component of many seismicity studies, including seismic hazard assessment. We assess the effect of declustering on the frequency–magnitude distribution of mainshocks. In particular, we examine the dependence of the b-value of declustered catalogs on the choice of declustering approach and algorithm-specific parameters. Using the catalog of earthquakes in California since 1980, we show that the b-value decreases by up to 30% due to declustering with respect to the undeclustered catalog. The extent of the reduction is highly dependent on the declustering method and parameters applied. We then reproduce a similar effect by declustering synthetic earthquake catalogs with known b-value, which have been generated using an epidemic-type aftershock sequence model. Our analysis suggests that the observed decrease in b-value must, at least partially, arise from the application of the declustering algorithm on the catalog, rather than from differences in the nature of mainshocks versus fore- or aftershocks. We conclude that declustering should be considered as a potential source of bias in seismicity and hazard studies.

scholarly journals EVIDENCE OF PRECURSORY PATTERNS IN AGGREGATED TIME SERIES

2017 ◽  
Vol 50 (3) ◽  
pp. 1283
Author(s):  
K.A. Adamaki ◽  
R.G. Roberts
Keyword(s):  
Aftershock Sequence ◽  
Magnitude Of Completeness ◽  
The West ◽  
Seismic Precursors ◽  
Corinth Gulf ◽  
North West ◽  
Seismicity Rate ◽  
Epidemic Type Aftershock Sequence ◽  
Earthquake Sequences ◽  
Foreshock Activity

We investigate temporal changes in seismic activity observed in the West Corinth Gulf and North-West Peloponnese during 2008 to 2010. Two major earthquake sequences took place in the area at that time (in 2008 and 2010). Our aim is to analyse Greek seismicity to attempt to confirm the existence or non-existence of seismic precursors prior to the strongest earthquakes. Perhaps because the area is geologically and tectonically complex, we found that it was not possible to fit the data well using a consistent Epidemic Type Aftershock Sequence (ETAS) model. Nor could we unambiguously identify foreshocks to individual mainshocks. Therefore we sought patterns in aggregated foreshock catalogues. We set a magnitude threshold (M3.5) above which all the earthquakes detected in the study area are considered as “mainshocks”, and we combined all data preceding these into a single foreshock catalogue. This reveals an increase in seismicity rate not robustly observable for individual cases. The observed effect is significantly greater than that consistent with stochastic models, including ETAS, thus indicating genuine foreshock activity with potential useful precursory power, if sufficient data is available, i.e. if the magnitude of completeness is sufficiently low.

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