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.

Manifestation of earthquake preparation zone in the ionosphere before 2021 Sonitpur,Assam earthquake revealed by GPS-TEC data

Global Positioning System(GPS)Continuously Operating Reference Station(CORS)data analysis shows that the ionosphere’s electron density variability is linked to the deformation and stress accumulation in the Earth’s crust.Anomalies in ionosphere total electron content(TEC)variability before 2021 M6.4 Sonitpur,Assam earthquake were detected using L1 and L2 GPS frequencies that showed three distinct abnormalities on April 3,9,10,2021.Pearson’s correlation coefficient(r)of TEC decreases in the CORS that lies away from the earthquake epicenter,indicating the possibilities of a positive relationship between TEC variability and earthquake epicenter.TEC concentration also decreases towards the epicenter within the earthquake preparation zone(EPZ).It is also observed that the Pearson’s correlation coefficient(r)of TEC decreases linearly near the EPZ.The study demonstrates the possibilities of determining the TEC anomalous zone in the ionosphere that coincides with the EPZ in the crustal rocks.The research indicated the possibilities of magnitude estimation of an impending earthquake based on the TEC anomalous zone in the ionosphere using closely spaced dense CORS network data.

Evaluation of earthquake signal characteristics for early warning

This paper evaluates different characteristics for earthquake early warning. The scaling relationships between magnitude, epicenter distance and calculated parameters are derived from earthquake event data fi＇om USGS. The standard STA/LTA method is modified by adding two new parameters to eliminate the effects of the spike-type noise and small pulsetype noise ahead of the onset of the P-wave. After the detection of the P-wave, the algorithm extracts 12 kinds of parameters from the first 3 seconds of the P-wave. Then stepwise regression analysis of these parameters is performed to estimate the epicentral distance and magnitude. Six different parameters are selected to estimate the epicentral distance, and the median error for all 419 estimates is 16.5 krn. Four parameters are optimally combined to estimate the magnitude, and the mean error for all events is 0.0 magnitude units, with a standard deviation of 0.5. Finally, based on the estimation results, additional work is proposed to improve the accuracy of the results.

Determining the time and space domains forestimating b value in seismic zoning

To take the seismic zone that includes the great shock with M S8.5 as the statistical unit of estimating b value can often lead to more large variance, because the seismogenic zone of the great shock with M S8.5 are larger than that delineated in general seismic zone. Two-level statistical units are considered in this paper. The seismic province is the first level unit that is suitable for group of earthquakes including the great shock of M S8.5. A seismic province can be divided into several seismic zones. They can be taken as the second level unit for group of quakes in which the super magnitude of the greatest shock do not exceed 8. Because of the nonstationarity in time of seismic activity, the unbalancedness of data and differential of seismic temporal series feature in different areas need to be considered when we select the time period for estimating b value. According to local conditions, the time period is selected at one′s discretion in order to reflect seismicity level of this statistical unit in future 100 years.