Research on geo-electrical resistivity observation system specially used for earthquake monitoring in China

This paper deals with the design and development of the observational system of geo-electrical resistivity on the basis of the demands for exploring the temporal variations of electrical properties of Earth media in the fixed points of the networks, which would be associated with the earthquake preparation. The observation system is characterized by the high accuracy in measurement, long term stability in operation and high level of rejection to the environmental interference. It consists of three main parts, configuration system measurement system, the calibration and inspection system.

Recent advances in earthquake monitoring I:Ongoing revolution of seismic instrumentation

Seismic networks have significantly improved in the last decade in terms of coverage density,data quality,and instrumental diversity.Moreover,revolutionary advances in ultra-dense seismic instruments,such as nodes and fiber-optic sensing technologies,have recently provided unprecedented high-resolution data for regional and local earthquake monitoring.Nodal arrays have characteristics such as easy installation and flexible apertures,but are limited in power efficiency and data storage and thus most suitable as temporary networks.Fiber-optic sensing techniques,including distributed acoustic sensing,can be operated in real time with an in-house power supply and connected data storage,thereby exhibiting the potential of becoming next-generation permanent networks.Fiber-optic sensing techniques offer a powerful way of filling the observation gap particularly in submarine environments.Despite these technological advancements,various challenges remain.First,the data characteristics of fiber-optic sensing are still unclear.Second,it is challenging to construct software infrastructures to store,transfer,visualize,and process large amount of seismic data.Finally,innovative detection methods are required to exploit the potential of numerous channels.With improved knowledge about data characteristics,enhanced software infrastructures,and suitable data processing techniques,these innovations in seismic instrumentation could profoundly impact observational seismology.

Recent advances in earthquake monitoring II: Emergence of next-generation intelligent systems

Seismic data processing techniques,together with seismic instrumentation,determine our earthquake monitoring capability and the quality of resulting earthquake catalogs.This paper is intended to review the improvement of earthquake monitoring capability from the perspective of data processing.Over the past two decades,seismologists have made considerable advancements in seismic data processing,partly thanks to the significant development of computational power,signal processing,and machine learning techniques.In particular,wide application of template matching and increasing use of deep learning significantly enhance our capability to extract signals of small earthquakes from noisy data.Relative location techniques provide a critical tool to elucidate fault geometries and seismicity migration patterns at unprecedented resolution.These techniques are becoming standard,leading to emerging intelligent software systems for next-generation earthquake monitoring.Prospective improvements in future research must consider the urgent needs in highly generalizable detection algorithms(for both permanent and temporary deployments)and in emergency real-time monitoring of ongoing sequences(e.g.,aftershock and induced seismicity sequences).We believe that the maturing of intelligent and high-resolution processing systems could transform traditional earthquake monitoring workflows and eventually liberate seismologists from laborious catalog construction tasks.

Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow

Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.

Earthquake Emergency Response System of High-speed Railway by Least Square Method

This paper studies the Least Square Method to define high-speed railway(HSR) earthquake risk and solve the problem of its emergency response mechanism. Based on the construction of a monitoring system for HSR earthquake emergency response, the technical operational procedures for HSR seismic emergency response are proposed. The quantity, scale, and location of HSR earthquake emergency response mechanism are defined, and the corresponding emergency response system is built. In particular, the earthquake emergency response system can conduct real-time continuous dynamic monitoring of seismic activity along the railway. When earthquake occurs, the intensity of the ground motion is detected by the system. When the earthquake monitoring value reaches the earthquake alarm threshold, it will send an alarm signal to the dispatch center, and the emergency power supply will be forced to cut off. The earthquake emergency response system will continue to monitor the follow-up ground motion acceleration. The system provides the operation scheduling center with a basis for train operation control to resume operation after stopping. The monitoring result of the system reduces the disaster, and the secondary disaster is caused by the earthquake. This paper improves the HSR response mechanism in detecting earthquake disasters. The result improves the ability of HSR to deal with earthquake disasters, and reduces casualties and economic and property loss caused by earthquake disasters.

Applications of seismic moment tensor inversion in fast response to earthquakes

Using the technique of seismic moment tensor inversion, the source mechanisms of 10 earthquakes with Ms5.2that occurred in China from November 1996 to January 1998 were determined rapidly. The determined resultswere sent as 'Bulletins of Source Mechanism Parameters of Earthquakes' to the Seismic Regime Guards' Office,China Seismological Bureau, and the relevant provincial seismological bureaus. These bulletins have played rolein the fast response to large earthquakes.

A real-time AI-assisted seismic monitoring system based on new nodal stations with 4G telemetry and its application in the Yangbi M_(S) 6.4 aftershock monitoring in southwest China

A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.However,it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time,and it usually takes a great amount of time to process the acquired data manually.To monitor earthquakes in real time flexibly,we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow.The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_(S) 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali,Yunnan in southwest China.The acquired seismic data are transmitted almost in real time through the 4G cellular network,and then processed automat-ically for event detection,positioning,magnitude calculation and source mechanism inversion.From tens of seconds to a couple of minutes at most,the final seismic attributes can be presented remotely to the end users through the integrated system.From May 27 to June 17,the real-time system has detected and located 7905 aftershocks in the Yangbi area before the internal batteries exhausted,far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations.The initial application of this inte-grated real-time monitoring system is promising,and we anticipate the advent of a new era for Real-time Intelligent Array Seismology(RIAS),for better monitoring and understanding the subsurface dynamic pro-cesses caused by Earth's internal forces as well as anthropogenic activities.

Introduction to China’s Earthquake Emergency Response System

Following the M_(S)6.4 earthquake that occurred on May 21,2021 in Yangbi,Yunnan,China,the earthquake emergency response system(EERS)responded immediately.The real-time software delivered many seismic parameters that provided a preliminary assessment of the earthquake.The 24-hour on-duty staff and scientific researchers revised these parameters and produced more detailed reports to understand the cause of the earthquake and the potential damage,which provided valuable information for emergency rescue operations and earthquake situation assessment.Emergency personnel were dispatched immedia-tely to the earthquake site to observe the aftershocks,investigate the damage,and guide and assist in the relief efforts.This paper describes the EERS response to the Yangbi earthquake to demonstrate the characteristics of the system and discuss the potential for further improvement.

Goce derived geoid changes before the Pisagua 2014 earthquake

The analysis of space-time surface deformation during earthquakes reveals the variable state of stress that occurs at deep crustal levels, and this information can be used to better understand the seismic cycle. Understanding the possible mechanisms that produce earthquake precursors is a key issue for earthquake prediction. In the last years, modern geodesy can map the degree of seismic coupling during the interseismic period, as well as the coseismic and postseismic slip for great earthquakes along subduction zones. Earthquakes usually occur due to mass transfer and consequent gravity variations, where these changes have been monitored for intraplate earthquakes by means of terrestrial gravity measurements. When stresses and correspondent rupture areas are large, affecting hundreds of thousands of square kilometres（as occurs in some segments along plate interface zones）, satellite gravimetry data become relevant. This is due to the higher spatial resolution of this type of data when compared to terrestrial data, and also due to their homogeneous precision and availability across the whole Earth.Satellite gravity missions as GOCE can map the Earth gravity field with unprecedented precision and resolution. We mapped geoid changes from two GOCE satellite models obtained by the direct approach,which combines data from other gravity missions as GRACE and LAGEOS regarding their best characteristics. The results show that the geoid height diminished from a year to five months before the main seismic event in the region where maximum slip occurred after the Pisagua Mw = 8.2 great megathrust earthquake. This diminution is interpreted as accelerated inland-directed interseismic mass transfer before the earthquake, coinciding with the intermediate degree of seismic coupling reported in the region. We highlight the advantage of satellite data for modelling surficial deformation related to preseismic displacements. This deformation, combined to geodetical and seismological data, could be useful for delimiting and monitoring areas of higher seismic hazard potential.

Gravity variation before the Akto Ms6.7 earthquake, Xinjiang

The relationship between gravity variation and the Akto Ms6.7 earthquake on November 11, 2016, was studied by use of mobile gravity observation data from the China continental structural environmental monitoring network. The result revealed that before the Akto earthquake, a high positive gravity variation was observed in the Pamir tectonic knots region （within a maximum magnitude of approximately ＋80 microgal）, which was consistent with the existing knowledge of gravity abnormality and the locations of strong earthquakes. In view of the recent strong seismic activities in the Pamir tectonic knots region, as well as the strong upward crust movement and compressive strain, it is believed that gravity change in the Pamir tectonic knots region reflects the recent strong seismic activities and crust movement.

Comprehensive Studies of Seismic Forecast and Seismic Hazard Assessment in Armenia, Current State and Prospects

The study of geophysical processes in different layers of the Earth,seismic hazard assessment,earthquake prediction,etc.are topical fundamental and applied problems.The development of a modern adequate methodology for assessing seismic hazards,operational forecasting of earthquakes.

The Statistical Relationship between the Maximum Amplitude of the Body Strain Record and the Surface-wave Magnitude and Epicenter Distance

Based on the body strain record of Tiantanghe station from 2008 to 2014,we make a statistical analysis of the relationship between the maximum amplitude of the body strain record and the surface-wave magnitude,epicenter distance of the earthquakes,which occurred in the Chinese mainland and its surrounding areas with MS≥6. 0 and the rest of the world with MS≥7. 0. According to statistical results,we propose a statistical formula between the surface-wave magnitude of earthquake and the maximum amplitude of the body strain record,the epicenter distance: M_S~*= 0. 37 ln A_max+ 0. 57 ln D + 0. 07. We can also derive a theoretical estimation formula for the maximum amplitude: A_max=e^(2. 7(M_S^*-0. 07))D^(-1. 54). This demonstrates that the maximum amplitude of the body strain record increases exponentially with the increase of the surface-wave magnitude, and decreases with the increase of the epicenter distance,and shows a negative correlation with their product. We further discuss the necessity of adding instruments with high frequency sampling to earthquake monitoring, and dicuss the prospects for precise earthquake prediction in future.

Aqueous Chemistry of Typical Geothermal Springs with Deep Faults in Xinyi and Fengshun in Guangdong Province,China

This paper investigated aqueous chemistry for two geothermal spring groups responsive and sensitive to flow fluctuations induced by earthquakes. Quake monitorings are favored for their being in residential areas with well-preserved natural flow systems in Xinyi City＇s Xijiang Hot Springs and Fengshun County＇s Shihu Hot Spring. The hot springs are typical in temperatures and flow rates in southern China＇s Guangdong Province. Physical and chemical conditions deep down in the heat sources are important constraints on earthquake, fluid flow, reactive solute transport and heat transfer, but remain challenging to address via field observations and numerical experiments. In this paper, we made daily and annual observations on flow rates, temperature, and/or aqueous chemistry. We employed strontium isotopes as tracers for the water sources, equilibrium phase diagram for K-feldspar and albite stability, and Na-K-Mg diagram for heat reservoir temperatures. The abundant sulfite content in Xi- jiang Hot Springs is discussed. Our main finding are that the deep fault springs are characterized by low reduction-oxidation potential at around -200- -150 mV and relatively large daily flow variations. The resuits provide scientific background features on the field sites regarding earthquake monitoring and predictions and geothermal reservoir.