The Haiyuan-Liupanshan tectonic belt is one of the most significant tectonic deformation areas in the northeastern Qinghai-Tibetan plateau with frequent strong earthquakes. It is an important opportunity to study the northeast extension of the Qinghai-Tibetan plateau and an ideal place to study the earthquake breeding process.

The published GPS observations show that the southwest side of the Haiyuan fault may still be undergoing deformation caused by the crustal viscoelastic relaxation effect of the 1920 Haiyuan M8.5 earthquake. And the publicly published leveling data results show local vertical deformation of the crust in the area west of the Liupanshan fault is significant. According to the seismic geological data, there exist historical earthquake rupture gaps in the middle and south sections of the Liupanshan fault and the southeast section of the Xiangshan-Tianjingshan fault in the Haiyuan-Liupanshan structural area, which have the background of strong earthquakes above M7.0. In view of the low spatial resolution of GPS and leveling observations, we need to use high-resolution crustal deformation fields to further study the crustal deformation characteristics of the above regions. Therefore, we further discuss the above issues in combination with InSAR observations.

The Sentinel-1A/B SAR data of two orbits covering the Haiyuan-Liupanshan fault from 2014 to 2020 were processed to obtain the current crustal deformation field in the line-of-sight direction. Furthermore, the high-density regional crustal deformation field was obtained by integrating InSAR and published GPS observations of the horizontal crustal movement velocity field on a time scale of 20 years. By comparing the observations of GPS, leveling and InSAR and high-resolution three-dimensional deformation integrated GPS-InSAR field, the characteristics of crustal deformation and strain field in the region are analyzed and discussed. The main conclusions are as follows:

(1)GPS and InSAR observations show that the post-seismic viscoelastic relaxation effect of the 1920 Haiyuan M8.5 earthquake may still be pronounced on the south side of the Haiyuan fault, but this conclusion is still speculative and needs to be confirmed by further observations;

(2)The high-resolution horizontal deformation field from GPS-InSAR shows that the decrease of the sinistral slip rate of the Haiyuan fault along the fault strike mainly occurs in the Middle East section. In contrast, the decrease of the middle and west sections is not significant, which may be related to the transformation of the left-lateral strike-slip to thrust nappe structure between the Haiyuan fault and the Liupanshan fault.

(3)GPS vertical and leveling observations both show that the vertical crustal deformation characteristics in the middle and south sections of the Liupanshan fault are similar to the vertical deformation of the Longmenshan fault before the Wenchuan earthquake. Considering the similar structural characteristics of the Liupanshan fault and the Longmenshan fault, and combining with the seismic and geological data, we believe that the Liupanshan fault may be in the relatively late stage of the earthquake breeding process. It can also be recognized by the high-resolution horizontal deformation and strain field derived from GPS-InSAR data. According to the fault motion parameters obtained in our study and the existing seismic and geological data, it is estimated that the maximum moment magnitude of an earthquake in the middle-south section of Liupanshan Mountain is approximately 7.5.

(4)The areas with rapid maximum strain accumulation in the study region are mainly concentrated in the vicinity of the Haiyuan fault and the left lateral shear zone between the Haiyuan fault and the Xiangshan-Tianjingshan fault. The dilatation strain rate west of the Liupanshan fault shows prominent compressive deformation characteristics corresponding to the nappe deformation in the Liupanshan tectonic area. The strain rate field in the southeast section of the Xiangshan-Tianjingshan fault is smaller than that of the surrounding area. There is a strain mismatch phenomenon, which may be related to the preparation for strong earthquakes. From the perspective of rotational deformation, the study area presents multiple deformation units, among which counterclockwise rotation corresponds to left-lateral strike-slip deformation(the left-lateral shear belt from the Haiyuan fault to the Xiangshan-Tianjingshan fault). In contrast, clockwise rotation corresponds to right-lateral strike-slip deformation(the right-lateral shear belt in the western margin of Ordos and Longxi block).

The first control source extremely low frequency(CSELF)electromagnetic observation network through the world, consisting of 30 fixed stations located in the Beijing captical circle region(15 staions)and the sourthern secton of the north-south earthquake belt(15 stations), China, has been established under the support of the wireless electromagnetic method(WEM)project, one of the national science and technology infrastructure construction projects during the 11th Five-year Plan period. As a subsystem of the WEM project, the CSELF network is mainly to study the relationship between elctromagnetic anomalies and mechanisms of earthquake, and further improve our ability to monitor and predict earthquakes by monitoring real-time dynamic changes in both electromagnetic fields and subsurface electric structure. Carrying out the detection of the underground background electric structure in the CSELF network area/station is an important part of this project and of great significance to play its role in the study of earthquake prediction and forecast. In this paper, we elaborate how to acquire the subsurface electric structure of the CSELF network in the Beijing captical circle region and make a simple explanation for the structure. Firstly, a short magnetotelluric(MT)profile, almostly perpendicular to the regional geological strike, was deployed at each station of the CSELF network in the capital circle region during the 2016 and a total of 60 broadband MT sites was collected using ADU -07e systems. Then, all the time series data were processed carefully using the robust method with remote reference technique to MT transfer functions. MT data quality was assessed using the D+algorithm. In general, data at most sites are of high quality as shown by the good consistency in the apparent resistivity and phase curves. Different impedance tensor decomposition methods including the phase tensor analysis, Groom and Bailey(GB)tensor decompositon, and statistical image method based on multi-site, multi-frequency tensor decompositon were used to analyze data dimensionality and directionality. For data inversion, on the one hand, one-dimensional(1-D)subsurface electrical resistivity structures at each station and MT site were derived from 1-D adaptive regularized MT inversion algorithm. On the other hand, we also imaged the 2-D electric structures along the short MT profile by the nonlinear conjugate gradients inversion algorithm at each station. Robustness of all 2-D structures along each short profile were verified by sensitivity tests. Although fixed stations and MT sites are limited and distributed unevenly, the 3-D inversion of 15 stations was also performed to produce a 3-D crustal electrical resistivity model for the entire network using the modular system for 3-D MT inverson: ModEM based on the nonlinear conjugate gradients algorithem. Intergrating 1-D, 2-D and 3-D inversion results, the resistivity structure beneath the CSELF network in captical circle region revealed some significant features: The crustal electrical structures are mainly characterized by high resistivity beneath the Yinshan-Yanshan orogenic belt in the northern margin of North China, the Taihangshan area in the middle, the Jiao-Liao block in the east, while the North China Plain and Shanxi depression areas have relatively lower resistivity in the crust; There are obvious electrical resistivity difference on both sides of the gravity gradient of Taihang Mountains and the Tanlu fault zone, which indicates they could be manifested as an electric structure boundary zone, respectively. Overall, the electric structure characteristics of the entire network area shows high correspondence with the regional geological structure and earthquake activity to some extent. In summary, implementing the detection of underground electrical resistivity structure in the CSELF network of the capital circle region will provide important foundations for the researches on the regional seismogenic environment, the generation mechanism of seismic electromagnetic anomaly signals, and earthquake prediction and forecast.

A M_S6.4 earthquake occurred on January 19^th, 2020 at Jiashi, Xinjiang, this earthquake is another strong earthquake since the Jiashi M_S6~7 earthquake swarm events from 1997 to 2003, and the epicenter was located near the Kalpin nappe in the western part of southern Tianshan. The Kaplin nappe is located in front of southern Tianshan Mountains, which is a thin skinned thrust belt composed of a series of nearly NE-SW thrust nappes under the strong and sustained regenerative orogeny in the Tianshan area. There are some differences in focal positions and fault parameters given by different institutions, therefore in this paper, high resolution InSAR coseismic deformation fields were obtained based on the ascending and descending tracks of Sentinel-1 SAR images to obtain the focal mechanism. The 30m resolution SRTM DEM data is chosen as the external DEM to eliminate the phases caused by topography, the robust Goldstein filtering is applied for phase smoothing, and the Delaunay minimum cost flow method is used for phase unwrapping. The variation range of interference fringes shows that the east-west span of the earthquake deformation field is about 40km, and that of the north-south direction is about 20km, the displacement results show that the maximum uplift displacement is 5.9cm and the maximum subsidence is 3.7cm along the LOS direction of the ascending data, the maximum uplift displacement is 6.4cm and the maximum subsidence is 2cm along the LOS direction of the descending data. And then the InSAR-derived deformation fields are used to obtain the seismogenic mechanism of this earthquake, and to improve the computational efficiency, the quadtree segmentation method is used to desample the original high-resolution InSAR observations before inversion. The coseismic slip distribution of the causative fault was inversed using a uniform sliding inversion method based on a Bayesian approach, and then the fine slip distribution of the fault plane of Jiashi earthquake was inversed using the distributed slip inversion method based on the constrained least squares. It should be noted that the fault plane is set as the shovel shape according to the geometric relationship between the seismogenic fault parameters inverted by uniform sliding and the exposed position of the Kapling Fault on the surface during the distributed slip inversion. According to the difference between the observed and simulated values, it can be seen that the residual error of the inversion model is small, indicating the reliability of the inversion result. The final result shows that the epicenter is located at 39.9°N, 77.28°E and the strike and dip angle of the seismogenic fault is 276° and 10.7°, respectively, the maximum dip slip and strike slip of fault plane is about 0.29m and 0.03m, respectively, which are located at the depth of about 5km underground. The cumulative coseismic moment is 1.73×10¹⁸N·m from InSAR inversion, which is equal to the moment magnitude of M_W6.1 and the Kalpin Fault is supposed to be the causative fault. Then, regional GPS-derived surface strain rate, tectonic dynamic background, and regional deep and shallow structures were comprehensively analyzed. The results show that the Jiashi M_S6.4 earthquake is a typical thrust event that occurred in the thrust nappe of the southern Tianshan. The 2020 Jiashi event and the 1997—2003 Jiashi M6~7 earthquakes swarm are the results of rupture of many faults with different scales and properties. And these events are all controlled by the thrust nappe of southern Tianshan.

Many synthetic model studies suggested that the best way to obtain good 3D interpretation results is to distribute the MT sites at a 2D grid array with regular site spacing over the target area. However, MT 3D inversion was very difficult about 10 years ago. A lot of MT data were collected along one profile and then interpreted with 2D inversion. How to apply the state-of-the-art 3D inversion technique to interpret the accumulated mass MT profiles data is an important topic. Some studies on 3D inversion of measured MT profile data suggested that 2D inversions usually had higher resolution for the subsurface than 3D inversions. Meanwhile, they often made their interpretation based on 2D inversion results, and 3D inversion results were only used to evaluate whether the overall resistivity structures were correct. Some researchers thought that 3D inversions could not resolute the local structure well, while 2D inversion results could agree with the surface geologic features much well and interpret the geologic structures easily. But in the present paper, we find that the result of 3D inversion is better than that of 2D inversion in identifying the location of the two local faults, the Shade Fault(SDF)and the Yunongxi Fault(YNXF), and the deep structures.
In this paper, we first studied the electrical structure of SDF and YNXF based on a measured magnetotelluric(MT) profile data. Besides, from the point of identifying active faults, we compared the capacity of identifying deep existing faults between 2D inversion models and 3D models with different inversion parameters. The results show that both 2D and 3D inversion of the single-profile data could obtain reasonable and reliable electrical structures on a regional scale. Combining 2D and 3D models, and according to our present data, we find that both SDF and YNXF probably have cut completely the high resistivity layer in the upper crust and extended to the high conductivity layer in the middle crust. In terms of the deep geometry of the faults, at the profile's location, the SDF dips nearly vertically or dips southeast with high dip angle, and the YNXF dips southeast at depth. In addition, according to the results from our measured MT profile, we find that the 3D inversion of single-profile MT data has the capacity of identifying the location and deep geometry of local faults under present computing ability. Finally, this research suggests that appropriate cell size and reasonable smoothing parameters are important factors for the 3D inversion of single-profile MT data, more specifically, too coarse meshes or too large smoothing parameters on horizontal direction of 3D inversion may result in low resolution of 3D inversions that cannot identify the structure of faults. While, for vertical mesh size and data error thresholds, they have limited effect on identifying shallow tectonics as long as their changes are within a reasonable range. 3D inversion results also indicate that, to some extent, adding tippers to the 3D inversion of a MT profile can improve the model's constraint on the deep geometry of the outcropped faults.

In this paper,we propose a method of seismic prediction using the geo-electric resistivity shifting self-correlation (SSC),and a numerical test is carried out using random time series analysis to verify the validity of the method.The SSC method is applied to the actual observation data of three geo-electric resistivity stations,and results are obtained as follows:(1) SSC coefficient changes in Ganzi and Shandan stations have good correspondence to earthquake,which is represented mainly by the phased increase of correlation coefficient appearing six months to a year before the earthquake.At the same time,the correlation coefficient anomalies of the two stations also exhibit strong anisotropy.(2) Although Chengdu geo-electric resistivity station had suffered serious disturbance,the correlation coefficient anomaly also has a good correspondence with earthquake.In addition to the validity of the SSC method,it may also be attributed to the magnitude of the earthquake event,the smaller distance of epicenter,and the time of the earthquake.Anisotropy also exists in the anomaly at Chengdu station.(3) By comparing the characteristics of different magnitudes of earthquakes,the results are obtained that,when the magnitude of the selected characteristic earthquake is relatively small,the amplitude of the anomaly before earthquake is different,but when the magnitude is larger,for example M_S ≥ 5.0,the impact on the results of this study is very limited.In addition,we briefly discussed the anisotropy of seismic geoelectrical resistivity anomalies and the selection of the characteristic earthquake.

On July 22, 2013, an M_S6.6 earthquake occurred at the junction of Minxian and Zhangxian. After the earthquake, magnetotelluric(MT)measurement was carried out at 45 sites along the NE-oriented profile across the West Qinling orogen(the west segment)and the earthquake area. Remote reference, "robust", and phase tensor decomposition techniques were used to process the MT data, and the NLCG two-dimensional inversion method was adopted to get the deep electrical structures. The deep electrical structure images indicate that there exists an inverted trapezoidal high-resistivity layer in the West Qinling orogenic belt(west segment)at the depth from the surface to about 20km deep, which is shallow in the northeast and southwest and deep in the middle. Under the high-resistivity layer is a low-resistivity layer, and they conjoin each other. There is a low-resistivity layer in the Songpan-Ganzi block(north part)at the southwest side of West Qinling orogenic belt(west segment)under the depth of 20km in the lower crust, which is shallow in the northeast and deep in the southwest, and the Longxi Basin at its northeast has a stable layered structure, suggesting that West Qinling orogenic belt(west segment)is being subject to the northward extrusion of the Songpan-Ganzi block and southward resistance of the Longxi Basin. The East Kunlun Fault(Tazang segment)faulted the low-resistivity layer in the lower crust of Songpan-Ganzi block. The Diebu-Bailongjiang Fault and Guangaishan-Dieshan Fault zone extend to a shallow depth and merge into the East Kunlun Fault(Tazang segment)in the deep part. The characteristic of low-resistivity of the media in the deep-seated structures in the East Kunlun Fault(Tazang segment)is the underlying cause for the gradual decrease of horizontal slip rate and gradual increase of vertical movement of the Tazang segment. The West Qinling Fault is a main geoelectric boundary zone, which extends through the Moho; Lintan-Tanchang Fault zone behaves as a low-resistivity layer with a certain width, which extends into the low-resistivity layer in the mid to lower crust. The source region of Minxian-Zhangxian M_S6.6 earthquake locates in the core of inverted "trapezoid" of the low-resistivity layer in the West Qinling orogenic belt(west segment), that is, in the contact area between the high to low resistivity layers, and also in the low-resistivity fractured zone near the Lintan-Tanchang Fault. The interaction of southwest-northeast pushing from Songpan-Ganzi block and resistance of Longxi Basin block at its northeast is external dynamics of the Minxian-Zhangxian M_S6.6 earthquake, and the high- and low-resistivity medium property and their contact relation in the seismic source region of the earthquake are the internal factor to generate this earthquake.

To better understand the mechanism responsible for groundwater radon anomalies and other seismo-geochemical precursors,the following modeling experiments have been carried out: 1) measurements of Rn emitted from rocks with various uranium concentration during stress loading and rupture of rocks;2) determination of the coefficient of distribution of emitted radon in CO₂ saturated water and gas under pressure;3) leaching experiment with rock samples in pure and CO₂-saturated distilled water under atmosphere and stress loading,respectively.It can be seen from the preliminary results that the maximal Rn concentration was recorded when the rupture of the rocks occurred;Rn emitted from the rock was proportional to the uranium content in the rock;Rn emitted from the rock was distributed somewhat more in water than in gas;and the leaching of rocks may prefer CO₂-saturated water under stress loading to distilled water under atmosphere.Therefore,it is reasonable to see some anomalous changes in Rn concentration and other ionic and gaseous components prior to a few strong earthquakes.Meanwhile,the preliminary results of the experiments indicate that the seismo-geochemical anomalies appear to be related to both the stress variation and the physico-chemical processes involved in the water-gas-rock equilibrium system within the earth preceding an impending earthquake.