The Collaboratory for the Study of Earthquake Predictability in China:Experiment Design and Preliminary Results of CSEP2.0

Since the inaugural international collaboration under the framework of the Collaboratory for the Study of Earthquake Predictability(CSEP)in 2007,numerous forecast models have been developed and operated for earthquake forecasting experiments across CSEP testing centers(Schorlemmer et al.,2018).Over more than a decade,efforts to compare forecasts with observed earthquakes using numerous statistical test methods and insights into earthquake predictability,which have become a highlight of the CSEP platform.

Moment magnitudes of two large Turkish earthquakes on February 6,2023 from long-period coda

Two large earthquakes(an earthquake doublet)occurred in south-central Turkey on February 6,2023,causing massive damages and casualties.The magnitudes and the relative sizes of the two mainshocks are essential information for scientific research and public awareness.There are obvious discrepancies among the results that have been reported so far,which may be revised and updated later.Here we applied a novel and reliable long-period coda moment magnitude method to the two large earthquakes.The moment magnitudes(with one standard error)are 7.95±0.013 and 7.86±0.012,respectively,which are larger than all the previous reports.The first mainshock,which matches the largest recorded earthquakes in the Turkish history,is slightly larger than the second one by 0.11±0.035 in magnitude or by 0.04 to 0.18 at 95%confidence level.

Real-time prediction of earthquake potential damage:A case study for the January 8,2022 M_(S) 6.9 Menyuan earthquake in Qinghai,China

It is critical to determine whether a site has potential damage in real-time after an earthquake occurs,which is a challenge in earthquake disaster reduction.Here,we propose a real-time Earthquake Potential Damage predictor(EPDor)based on predicting peak ground velocities(PGVs)of sites.The EPDor is composed of three parts:(1)predicting the magnitude of an earthquake and PGVs of triggered stations based on the machine learning prediction models;(2)predicting the PGVs at distant sites based on the empirical ground motion prediction equation;(3)generating the PGV map through predicting the PGV of each grid point based on an interpolation process of weighted average based on the predicted values in(1)and(2).We apply the EPDor to the 2022 M_(S) 6.9 Menyuan earthquake in Qinghai Province,China to predict its potential damage.Within the initial few seconds after the first station is triggered,the EPDor can determine directly whether there is potential damage for some sites to a certain degree.Hence,we infer that the EPDor has potential application for future earthquakes.Meanwhile,it also has potential in Chinese earthquake early warning system.

Rapid communications of preliminary results for the recent magnitude 6.6 Menyuan,Qinghai,China earthquake helps scientists better study intraplate earthquakes

Within one month of the magnitude 6.6 Qinghai,China Earthquake on 01/07/2022,several articles were published online in peer-reviewed journals and websites focusing on different aspects of this significant event.

Earthquake probabilities and magnitude distribution (M ≥ 6.7) along the Haiyuan fault, northwestern China

In recent years, some researchers have studied the paleoearthquake along the Haiyuan fault and revealed a lot of paleoearthquake events. All available information allows more reliable analysis of earthquake recurrence interval and earthquake rupture patterns along the Haiyuan fault. Based on this paleoseismological information, the recur- rence probability and magnitude distribution for M≥6.7 earthquakes in future 100 years along the Haiyuan fault can be obtained through weighted computation by using Poisson and Brownian passage time models and consid- ering different rupture patterns. The result shows that the recurrence probability of MS≥6.7 earthquakes is about 0.035 in future 100 years along the Haiyuan fault.

Results of Geomagnetic Studies on the Problem of Forecasting Strong Earthquakes in Uzbekistan

The article is devoted to the problem of forecasting strong earthquakes by the geomagnetic method. The geomagnetic method is widely used on this problem in seismically active regions of the world as one of the promising, informative and operational geophysical methods. The results of long-term geomagnetic studies on the problem of forecasting strong earthquakes in Uzbekistan are presented. Geomagnetic studies were carried out on the territories of the Tashkent, Ferghana, and Kyzylkum geodynamic polygons in the epicentral zones of strong earthquakes that occurred. Long-term, medium- and short-term precursors of earthquakes have been identified. Anomalous changes in the geomagnetic field associated with the decline in aftershock activity were also revealed. The dependence between the duration of the manifestation of long-term magnetic precursors and the magnitude of earthquakes is determined. Absolute proton magnetometers MMP-1, MV-01 (Russia), and G-856 (USA) were used to measure the geomagnetic field.

Earthquake probabilities and magnitude distribution (M≥6.7) along the Haiyuan fault, northwestern China

In recent years, some researchers have studied the paleoearthquake along the Haiyuan fault and revealed a lot of paleoearthquake events. All available information allows more reliable analysis of earthquake recurrence interval and earthquake rupture patterns along the Haiyuan fault. Based on this paleoseismological information, the recur- rence probability and magnitude distribution for M≥6.7 earthquakes in future 100 years along the Haiyuan fault can be obtained through weighted computation by using Poisson and Brownian passage time models and consid- ering different rupture patterns. The result shows that the recurrence probability of MS≥6.7 earthquakes is about 0.035 in future 100 years along the Haiyuan fault.

Rapid report of the 8 January 2022 M_(S)6.9 Menyuan earthquake,Qinghai,China

The M_(S)6.9 Menyuan earthquake in Qinghai Province,west China is the largest earthquake by far in 2022.The earthquake occurs in a tectonically active region,with a background b-value of 0.87 within 100 km of the epicenter that we derived from the unified catalog produced by China Earthquake Networks Center since late 2008.Field surveys have revealed surface ruptures extending 22 km along strike,with a maximum ground displacement of 2.1 m.We construct a finite fault model with constraints from In SAR observations,which showed multiple fault segments during the Menyuan earthquake.The major slip asperity is confined within 10 km at depth,with the maximum slip of 3.5 m.Near real-time back-projection results of coseismic radiation indicate a northwest propagating rupture that lasted for~10 s.Intensity estimates from the back-projection results show up to a Mercalli scale of IX near the ruptured area,consistent with instrumental measurements and the observations from the field surveys.Aftershock locations(up to January 21,2022)exhibit two segments,extending to~20 km in depth.The largest one reaches M_(S)5.3,locating near the eastern end of the aftershock zone.Although the location and the approximate magnitude of the mainshock had been indicated by previous studies based on paleoearthquake records and seismic gap,as well as estimated stressing rate on faults,significant surfacebreaching rupture leads to severe damage of the high-speed railway system,which poses a challenge in accurately assessing earthquake hazards and risks,and thus demands further investigations of the rupture behaviors for crustal earthquakes.

Study on Variation of Fitting Goodness of Relation Between Earthquake Frequency and Magnitude before Moderately Strong Earthquakes (Ms≥5.0)

In this paper,characteristics of spatial and temporal variation of linear fitting goodness before some moderately strong earthquakes(Ms≥5.0)in the eastern part of China(east of longitude 180)are studied according to the famous Gutenberg-Richter’s relation expressed as lgN=a-bM,by using the moderate and small events that occurred in and around the source area.The results show that the linear goodness of fitting varies abnormally prior to these moderately strong earthquakes.In the early stage of the earthquake preparatory process,distribution of the energy released through small events in and around the source area is isostatic and the fitting goodness approximates 1,while the distribution of the energy turns to be isostatic before moderately strong earthquakes,leading to the obvious decrease of the linear goodness of fitting.This phenomenon could be a medium term anomaly and a medium term criterion for moderately strong earthquake prediction.

Analysis of Abnormal Characteristics of Regional Crustal Deformation before the Menyuan MS6.4 Earthquake by GPS Continuous Data

In order to study the characteristics of crustal deformation around the epicenter before the 2016 M_S6. 4 Menyuan earthquake,the GPS continuous stations of the period from 2010 to 2016 were selected according to the observation data of the tectonic environment monitoring network in Chinese Mainland. The deformation characteristics of the crust before the earthquake were discussed through inter-station baseline time series analysis and the strain time series analysis in the epicentral region. The results show that a trend turn of the baseline movement state around the epicenter region occurred after 2014,and the movement after 2014 reflects an obvious decreasing trend of compressional deformation.During this period,the stress field energy was in a certain accumulation state. Since the beginning of 2014,the EW-component linear strain and surface strain rate weakened gradually before the earthquake. It shows that there was an obvious deformation deficit at the epicentral area in the past two years,which indicates that the region accumulated a high degree of strain energy before the earthquake. Therefore,there was a significant background change in the area before the earthquake. The results of the study can provide basic research data for understanding the seismogenic process and mechanism of this earthquake.

A theoretical study of correlation between scaled energy and earthquake magnitude based on two source displacement models

The correlation of the scaled energy,e = Es/ Mo, versus earthquake magnitude, Ms, is studied based on two models： （1） Model 1 based on the use of the time function of the average displacements, with a ω^-2 source spectrum, across a fault plane; and （2） Model 2 based on the use of the time function of the average displacements, with a ω^-3 source spectrum, across a fault plane. For the second model, there are two cases： （a） As ζ= T, where r is the rise time and T the rupture time, lg（e） - -Ms; and （b） As ζ 〈〈 T, lg（e）- -（1/2）Ms. The second model leads to a negative value of e. This means that Model 2 cannot work for studying the present problem. The results obtained from Model 1 suggest that the source model is a factor, yet not a unique one, in controlling the correlation of e versus Ms.

Application of a time-magnitude prediction model for earthquakes

In this paper we discuss the physical meaning of the magnitude-time model parameters for earthquake prediction. The gestation process for strong earthquake in all eleven seismic zones in China can be described by the magnitude-time prediction model using the computations of the parameters of the model. The average model parameter values for China are： b = 0.383, c=0.154, d = 0.035, B = 0.844, C = -0.209, and D = 0.188. The robustness of the model parameters is estimated from the variation in the minimum magnitude of the transformed data, the spatial extent, and the temporal period. Analysis of the spatial and temporal suitability of the model indicates that the computation unit size should be at least 4°× 4°for seismic zones in North China, at least 3° × 3° in Southwest and Northwest China, and the time period should be as long as possible.

Probability forecast of earthquake magnitude in Chinese mainland before A．D． 2005

A probability forecast method of earthquake magnitude, based on the earthquake frequency magnitude relation and the model of Bernoulli′s random independent trial, is applied to the earthquake risk assessment of seismic zones in China's Mainland before A.D.2005 in the paper. The forecasting results indicate that the probabilities of earthquake occurrence with magnitude 5 in seismic zones before 2005 are estimated to be over 0.7 in common and 0.8 in most zones; and from 0.5 to 0.7 with M =6; the maximum probability of earthquake occurrence with magnitude 7 is estimated at 0.858, which is also expected in Shanxi seismic zone. In west China's Mainland, earthquakes with magnitude 6 are expected to occur in most seismic zones with high probability (over 0.9 in general) ; the relatively high probabilities of earthquake occurrence (more than 0.7) with magnitude 7 are expected in the seismic zones surrounding the Qinghai Tibet plateau and south Tianshan seismic zone. A discussion about the result confidence and the relationship between the estimated probability and the possible annual rate of earthquake occurrence is made in the last part of the paper.

Control Parameters of Magnitude—Seismic Moment Correlation for the Crustal Earthquakes

In connection with conversion from energy class KR (KR = log10E R, where ER — seismic energy, J) to the universal magnitude estimation of the Tien Shan crustal earthquakes the development of the self-coordinated correlation of the magnitudes (mb , ML, Ms ) and KR with the seismic moment M0 as the base scale became necessary. To this purpose, the first attempt to develop functional correlations in the magnitude—seismic moment system subject to the previous studies has been done. It is assumed that in the expression M (mb , ML , Ms) = Ki + zi log10M0 , the coefficients ki? and zi? are controlled by the parameters of ratio?(where;f0 —corner frequency, Brune, 1970, 1971;M0, N×m). According to the new theoretical predictions common functional correlation of the advanced magnitudes Mm (mbm = mb , MLm = ML , MSm = MS ) from log10M0,? log10t0? and the elastic properties (Ci) can be presented as , where , and , for the averaged elastic properties of the Earth’s crust for thembmthe coefficients Ci= –11.30 and di = 1.0, for MLm: Ci = –14.12, di = 7/6;for MSm : Ci = –16.95 and di = 4/3. For theTien Shan earthquakes (1960-2012 years) it was obtained that , and on the basis of the above expressions we received that MSm = 1.59mbm – 3.06. According to the instrumental data the correlation Ms = 1.57mb – 3.05 was determined. Some other examples of comparison of the calculated and observed magnitude - seismic moment ratios for earthquakes of California, the Kuril Islands, Japan, Sumatra and South America are presented.

Study of Minimum Magnitude of Completeness in the North-South Trending Seismic Belt for the Collaboratory for the Study of Earthquake Predictability Project

To determine the studying region of China Testing Center of the Collaboratory for the Study of Earthquake Predictability （CSEP）, we adopted the Entire-Magnitude-Range （EMR） method to study the spatial distribution of minimum magnitude of completeness （Mc） in the North-South Trending Seismic Belt （NSTSB） during the period from October 1, 2008 to May 31, 2011. Also bootstrap testing was performed to estimate the uncertainty of Mc, i. e. 8Mc. The results show that Mc （EMR） = 1.6 ± 0. 03 for the whole region. From the spatial distributions of Mc we find that Mc is in the range of Mu 1.3 ±2.0 for most regions. Specifically, the spatial distribution of Mc is consistent with the distribution of stations indicating high monitoring level in the southern part and low monitoring level in the northern part. Events located with less than three stations have great influence on Me. Moreover, the uncertainty of minimum magnitude of completeness 6Mc ranges from 0. 07 to 0.22. The spatial distribution of 6Mc agrees with the seismic rate. The shorter time span may cause larger 6Mc

Estimating the Frequency, Magnitude and Recurrence of Extreme Earthquakes in Gulf of Aqaba, Northern Red Sea

Humans coexist with extreme events all the time, only when the intensity of the event becomes greater than a certain level there is a resulting disaster. Small earthquakes occur all of the time with no adverse effects. Only large earthquakes cause disasters. Statistical analysis reveals that larger events occur less frequently than small events. In a year, we would have many values for the events;the annual maximum was the greatest of those values. Within an annual series, only the largest value per year is allowed, even if an additional significant peak occurs. As the magnitude of a hazardous increases, the frequency of occurrence (how often a given magnitude is equaled or exceeded) decreases. Thus, major disasters result from a small number of large events that rarely occur. A plot of recurrence intervals versus associated magnitudes produces a group of points that also approximates a straight line on semi-logarithmic paper. Therefore, past records of earthquakes at the Gulf of Aqaba, Northern Red Sea for months from May, 1999 to Feb, 2016 are used to predict future conditions concerning the annual frequency, the return period, the percentage probability for each event, and the probability of a certain-magnitude earthquake occurring in the region during any period.

The December 26, 2004, off the west coast of northern Sumatra, Indonesia, M_W=9.0, earthquake and the critical-point-like model of earthquake preparation

Long-term seismic activity prior to the December 26, 2004, off the west coast of northern Sumatra, Indonesia, MW=9.0 earthquake was investigated using the Harvard CMT catalogue. It is observed that before this great earth-quake, there exists an accelerating moment release (AMR) process with the temporal scale of a quarter century and the spatial scale of 1 500 km. Within this spatial range, the MW=9.0 event falls into the piece-wise power-law-like frequency-magnitude distribution. Therefore, in the perspective of the critical-point-like model of earthquake preparation, the failure to forecast/predict the approaching and/or the size of this earthquake is not due to the physically intrinsic unpredictability of earthquakes.

Abnormal Earthquake Intensity Areas and Formation Mechanism of the Minxian-Zhangxian M_S6.6 Earthquake on July 22,2013,Gansu

On July 22, 2013, the Minxian-Zhangxian Ms6. 6 earthquake occurred on the east segment of Lintan-Dangchang fault. The analysis of digital elevation and remote sensing imaging shows that the east segment of Lintan-Dangchang fault is still active and the main thrust feature of the fault switches to left lateral slip. With the field research of intensity and damage, several abnormal areas of degree VIII spread in the isoseismal line of degree VII and some abnormal areas of degree VII spread in the isoseismal line of degree VI. These abnormal areas are distributed along the hanging wall of the fault in a width of 2km. The analysis based on the remote sensing and digital elevation model shows that the segment of the Lintan-Dangchang fault south of Minxian mainly slips in left literal. The fault movement made the soil soft in the fault zone. The earthquake motion propagated along the fault zone. Therefore the strong earthquake motion caused foundation failure in the soft soil along the fault zone and the abnormal intense areas of disaster formed.

Continuous prediction method of earthquake early warning magnitude for high-speed railway based on support vector machine

Purpose–Using the strong motion data ofK-net in Japan,the continuous magnitude prediction method based on support vector machine(SVM)was studied.Design/methodology/approach–In the range of 0.5–10.0 s after the P-wave arrival,the prediction time window was established at an interval of 0.5 s.12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning(EEW)magnitude prediction model(SVM-HRM)for high-speed railway based on SVM.Findings–The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm.Results show that at the 3.0 s time window,themagnitude prediction error of the SVM-HRMmodel is obviously smaller than that of the traditionalτc method and Pd method.The overestimation of small earthquakes is obviously improved,and the construction of the model is not affected by epicenter distance,so it has generalization performance.For earthquake events with themagnitude range of 3–5,the single station realization rate of the SVM-HRMmodel reaches 95%at 0.5 s after the arrival of P-wave,which is better than the first alarm realization rate norm required by“The TestMethod of EEW andMonitoring Systemfor High-Speed Railway.”For earthquake eventswithmagnitudes ranging from3 to 5,5 to 7 and 7 to 8,the single station realization rate of the SVM-HRM model is at 0.5 s,1.5 s and 0.5 s after the P-wave arrival,respectively,which is better than the realization rate norm of multiple stations.Originality/value–At the latest,1.5 s after the P-wave arrival,the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate,which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction.

Seismic Sequence Characteristics and Precursory Anomalies of the M_S6.3 and M_S6.4 Da Qaidam Earthquakes in 2008～2009

In this paper,the seismogenic structures of the Da Qaidam strong earthquakes are preliminarily discussed by using the regional seismotectonic data and focal mechanism solutions. Analysis is done on the temporal and spatial distribution characteristics of the two strong earthquake sequences in Da Qaidam in combination with the sequence distribution characteristics of the M6. 6 earthquake of 2003 and the five strong earthquakes of about M5. 0 in 2004 in Delingha. At the same time,the regional characteristics of the historical seismic activity are also investigated. Preliminary analysis is done on the influence of the two M8. 0 earthquakes in the past 10 years on this region. Precursory anomalies and their characteristics are discussed in combination with the analysis of the precursor observation data of Qinghai Province.