Based on the focal mechanism solutions of Maduo MS7.4 earthquake given by various institutions after the earthquake, the H-C method is used to quickly judge the seismogenic fault, and quickly identify the seismic rupture direction without reference to aftershocks. The 18 sets of results show the nodal plane I with NWW-trending is the seismogenic fault plane. For validating the results, according to the characteristics of geologic structure in seismic source area, space distribution of aftershock sequence, regional tectonic stress field, isoseismal of seismic intensity, initial findings from field geological survey, we conclude that the Maduo earthquake shows strike-slip mechanism and the nodal plane I with NWW-trending is inferred from the seismogenic fault plane, and the Kunlun-Jiangcuo fault is the seismogenic structure.
We use InSAR deformation data after the 2014 Kangding MS6.3 earthquake as constraints, and use the three-layer viscoelastic seismic period model and genetic algorithm to invert the viscoelastic layer thickness and viscosity coefficient of deep medium in the focal region of Kangding earthquake in the southeast section of Xianshuihe fault. The results show that: 1) The thickness of the viscoelastic layer in the lower crust of Kangding area is 5 km, and the viscosity coefficient is 9.9 × 1017 Pa·s. The rheological properties of lower crust and lower mantle media on both sides of the fault have significant lateral heterogeneity. 2) By inversion on both sides of the fault, the viscous coefficient of the lower crust of the southwest fault (8.7 × 1017 Pa·s) is slightly smaller than that of the northeast fault (1.2 × 1018 Pa·s).
We analyze the characteristics of fault structure and tectonic deformation in the middle-east section of Qilian mountain based on the relocation results of small and medium earthquakes and geophysical data of stress field. The results show that: 1) The focal depth of the middle-east section of Qilian mountain is 2-20 km. The focal depth distribution of the Longshoushan fault is an inverted triangle with a wide upper and narrow lower. The aftershock depth of the Menyuan MS6.4 earthquake is 5-15 km, with a tendency of SW. The eastern section of Jinqianghe fault has strong seismicity, with a tendency of NE and high dip angle. The eastern section of Laohushan fault is highly seismically active, with a tendency of NE and a near vertical occurrence in its depth. The focal depth of the middle-east section of Qilian mountain increases gradually from west to east. It is speculated that deeper tectonic activity may have occurred in the eastern Qilian mountains. 2) The direction of principal compressive stress in the study area is NE-NEE. 3) The combined fracture of a series of strike-slip faults and front thrust faults along the middle-east section of Qilian mountain is an important structural deformation regulation mode for the NE extrusion of the Qinghai-Tibet plateau.
With the help of visible light, microwave, GPS and gravity data in recent years, we study the surface outcrop morphology, deformation field around the fault zone and block gravity of the Jiangsu section of the Tan-Lu fault zone from the perspective of multi-source remote sensing, supplemented by field investigation and trench excavation. The analysis shows that: 1) The interpretation of the controversial southern position of F5 fault should be located in Houchen village, Sihong county, which is verified by field trench exploration. The exposed length of the surface is about 9 km and the strike is about NNE12°. 2) The surface deformation field retrieved from Sentinel-1A data is consistent with the dextral characteristics of Tan-Lu fault zone since Quaternary, and Suqian, Xinyi and Sixian show subsidence, Pizhou, Suining and Sihong show uplift; the horizontal and vertical deformation rate differences on both sides of the fault are about 4 mm/a and 3 mm/a respectively. 3) GPS deformation field analysis shows that the relative slip on both sides of the fault is about 1.4 mm/a, which is different from the microwave results, reflecting the acceleration of strike slip movement of the fault in recent years. 4) The analysis of Bouguer gravity anomaly shows that the gravity differentiation on both sides of the fault is obvious, showing a characteristic differentiation state of low west and high east. This paper can be used as a reference for the deformation of crustal blocks, potential seismogenesis, earthquake grade and earthquake disaster prevention around the Jiangsu section of the Tan-Lu fault zone.
Based on the geological survey, through drilling, fault gas radon detection, shallow seismic detection and intelligent micro-motion detection, we reveal the geometric characteristics of buried faults F1 and F2 in the Houhai reclamation area of Shenzhen, and analyze the weathering genesis of the NW trending faults. The results show that: 1) The buried faults F1 and F2 are developed in Yanshanian granite, and the occurrences are N38°-40°W, NE, 59°-63° and N50°W, NW, 70°, respectively. The width of the faults are 30-35 m and 40 m, respectively. Cataclasite rocks can be widely found around the faults and the chlorite phenomenon is obvious as well. A thin layer of powdery rock is developed in the fault surface zone, but the overlying Quaternary strata is not disturbed. The faults belong to brittle fracture system and present both tensile and reverse torsional features. 2) The relative activity of the buried faults are measured by fault gas Rn concentration intensity, which shows that the relative activity of F1 buried fault is strong. 3) F1 and F2 faults control the southwest and northeast boundaries of the weathered trough respectively. The main causes of the weathered trough are that the hanging wall of the extensional fault is more cataclastic compared to the lower wall, the cracks, pores and secondary faults are denser, and the rapid weathering of feldspar in broken granite under the action of water and temperature.
This paper selects the continuous seismic background noise of seismic survey line from Meixian to Fufeng in the Weihe basin. Based on the HVSR method, the HVSR curves of each station are obtained. The structural characteristics of the Quaternary sedimentary layer near the surface below the survey profile are obtained through the conversion between frequency and depth. The results show that the thickness of the Quaternary sedimentary layer in the basin is in a U-shaped distribution, gradually becoming thicker from both sides of the basin to the middle of the basin. The depth on both sides is 100 to 400 meters, and middle of the basin is about 400-600 meters. The depth profile of the sedimentary layer shows intermittent and jumping characteristics at 25 km and 33 km from the starting point of the survey line, which is in good agreement with the Qishan-Mazhao fault and Fufeng-Qianxian fault in spatial location.
To accurately grasp the landslide deformation potential in the reservoir area, based on the statistics of deformation monitoring results, we use the limit displacement criterion to analyze the landslide deformation potential. Based on the theory of relevance vector machine, we apply optimization processing to ensure the optimum parameters. We build a prediction model of landslide deformation and evaluate the development trend of landslide deformation potential based on the prediction results. Combined with results of the two analyses, we realize the comprehensive landslide deformation potential analysis. The results show that there are some differences in the deformation potential of different monitoring points. According to the disadvantage principle, the deformation potential level is grade IV, and the potential degree is serious. The deformation potential will continue to increase and tend to develop unfavorably. Based on the two analysis results, the landslide deformation potential is in a disadvantageous state, and the possibility of instability in the later period is relatively large. Therefore, disaster prevention and control should be strengthened to avoid disaster losses.
We select the Heifangtai Dangchuan #6 landslide body in Gansu province as the study region, which is a typical loess landslide area in Chinese mainland. Three recurrent neural network prediction models of landslide are established using the deep learning framework Tensorflow based on the monitoring data of Beidou and displacement meter, namely, the simple recurrent neural network(SimpleRNN), long short-term memory(LSTM), and gated recurrent unit(GRU). Further, in view of the prominent problems of large subjective impact and low computational efficiency caused by the fact that the parameters of the recurrent neural network are mostly adjusted manually by experience or the grid search method, we introduce a genetic algorithm(GA) to optimize the automatic optimization selection of the parameters of the recurrent neural network. Thereby, three recurrent neural network prediction models of landslide optimized by GA are established, namely, GA-SimpleRNN, GA-LSTM, and GA-GRU. The results show that the improved three recurrent neural network prediction models with automatic optimization of parameters have better prediction performance. The GA-GRU model has the highest prediction accuracy, which is more suitable for the high-precision prediction of the long-time displacement of landslides.
We obtain by SBAS-InSAR technique the surface subsidence information of WLL reservoir and its surrounding area. The results show that: 1) The settlement of WLL reservoir dam is overall, the settlement rate decreases year by year, and the settlement tends to be stable. 2) Due to the influence of reservoir water level, dam weight and underground water level, the settlement rate and cumulative settlement of the dam gradually increase from southeast to northwest. 3) The subsidence around the reservoir has no substantial influence on the dam.
To solve the problems of unreasonable distribution of global grid points, biased statistical results and low calculation and storage efficiency of the equal-arch-length grid (GRID_ELL), which is often used in position dilution of precision (PDOP) monitoring and evaluation, we introduce the equal-arch-length grid (GRID_EAL) and the icosahedron-based grid (GRID_IB) to further develop the global PDOP long-period real-time monitoring service. We analyze the differences between them and the GRID_ELL model. The results show that the two equal-area grid models can significantly improve the uneven distribution of global grid points in the GRID_ELL model and the bias in the current global PDOP monitoring assessment statistics. Focusing on the applicability of the GRID_EAL model with different grid spacing, the results show that the GRID_EAL model with 5° spacing can bring 36.3% and 34.1% improvement and optimization in its computational efficiency and storage while maintaining the accuracy of the global PDOP monitoring assessment.
This paper focuses on the selection of the optimal combination of observations in the BDS-3 multi-frequency ambiguity resolution, and uses fuzzy clustering analysis to realize the selection of the optimal combination of three-frequency, four-frequency and five-frequency observations under different baseline lengths. The results show that as the number of frequencies increases, the number of high-quality linear combinations increases sharply; at the same time, it is more conducive to the formation of combined observations with a smaller total noise level, and it is more to the rapid fixation of the single epoch of the long baseline ambiguity, which is conducive to realization real-time precise positioning.
Applying the principles of PPP and Beidou-3 PPP-B2b telegram correction model, we analyze the matching problems between two correction parameters that must be attended to in using telegram correction information for PPP. We further analyze positioning service performance in two modes, B1C+B2a and B1I+B3I, after the correction of the message information under static and imitation dynamic conditions. The results show that under static conditions, the positioning accuracy in the horizontal and elevation directions of the two positioning modes are better than 11 cm. Under dynamic conditions, the positioning accuracy in the horizontal and elevation directions are both better than 22 cm; the horizontal and elevation directions can be reached within 15 min, and do not exceed the accuracy requirements of 0.3 m and 0.6 m. The B1C+B2a combination is slightly better than the B1I+B3I combination in terms of positioning accuracy and convergence speed.
Aiming at the problem of low interpolation accuracy caused by the spatiotemporal characteristics of regional zenith tropospheric delay (ZTD) in real-time precision positioning, we propose a Kriging interpolation model based on elevation reduction. We use regional CORS network observation data to solve the ZTD value for modeling analysis. Compared with other existing methods, the model can improve interpolation accuracy. When fewer stations participate in modeling, the RMSE can still be kept below 10 mm, which provides a basis for regional real-time high-precision positioning.
Aiming at the high noise, nonlinear and non-stationary dynamic characteristics of ionospheric total electron content(TEC) time series, we construct an improved short-term ionospheric combined prediction model based on singular spectrum analysis(SSA) and long short term memory(LSTM) neural network model, to realize the model’s ionospheric TEC prediction during magnetic storms and magnetic quiet periods and analyze its accuracy. The results show that the relative accuracy of model is 91.17% and 95.46% respectively, which is 4.92 percent and 3.17 percent higher than that of single LSTM model, during the period of magnetic explosion and magnetic calm.
We calculate the traditional atmospheric load correction according to the global atmospheric pressure model, but the medium-wave and long-wave signal is dominant in the global atmospheric pressure model, and the short-wave signal, which highlights the regional characteristic information, is lacking. The short-wave signal in the spatial information cannot be ignored when studying the influence of high precision regional atmospheric load. Based on the theory of the earth gravity field, we introduce the removal-recovery method, and combine the global atmospheric pressure data provided by ECMWF and the regional high precision atmospheric pressure data CLDAS-V2.0. Based on the load spherical harmonic coefficient and the regional load Green’s function method, we obtain the load effect of atmospheric pressure change in western Yunnan. The results show improvement in both the spatial and temporal resolution of the atmospheric load deformation field. The influence of regional atmospheric pressure load calculated by removal-recovery method can provide reference for solid earth deformation and CORS station time series analysis.
We present a new method to obtain the nonlinear zero drift of DZW gravimeter by using gravity observation data. The main algorithm of this method is a Bayesian formula. The principle is to take the continuity of zero drift as an a priori constraint, consider the deviation caused by the floating of gravity observation data, and solve the mean and variance of drift at each sampling point as hyper-parameters. The algorithm in this paper can be used repeatedly. With the increase of evaluation time, the hyper-parameters will tend to the convergence limit, so as to obtain the optimal solution of the algorithm. Through data verification, the accurate nonlinear zero drift curve can be obtained. During zero drift correction, the variance of gravity observation value can be obtained which is 1.595 53×10-10 [μGal]2 . The algorithm in the paper ensures the measurement accuracy of DZW gravimeter.
Based on the continuous observation data of 8 sets of VP broadband vertical pendulum tiltmeters in Hebei province, the paper analyzes reflecting-earthquake characteristics, reflecting-earthquake ability and time-frequency characteristics, and discusses the reflecting-earthquake efficiency of broadband vertical pendulum tiltmeters in Hebei province. The results show that: 1) The reflecting-earthquake capacity of broadband vertical pendulum tiltmeter in Hebei area is directly proportional to the magnitude, inversely proportional to the focal depth (except Chongli station), and has little correlation with the epicentral distance. 2) All instruments can record relatively complete teleseismic seismic waves, and the starting time of P wave and S wave can be seen clearly from the waveform diagram. 3) The time-frequency analysis shows that the instrument can record relatively complete surface wave signals, but due to the limitation of sampling rate, the body wave (P and S wave) signals are not fully recorded, and the signals above 0.5 Hz cannot be recorded. 4) Due to the modification of instrument parameters by the manufacturer, Chongli station has obvious difference in signal response ability in high-frequency part from other station instruments, and can record more high-frequency signals. However, the reflecting-earthquake efficiency of shallow source earthquakes is contrary to that of other instruments. Therefore, the modification results of instrument parameters need to be further verified.
In view of the incompleteness of the existing component-type borehole strainmeters and the future development of borehole strainmeters, we theoretically derive generalized formulas for surface strain, north-directional differential strain, and north-directional shear strain for the n≥3-component horizontally equally spaced borehole strain observation scheme. We qualitatively evaluate their accuracy self-verification capabilities. If only the accuracy self-verification of areal strain observation is considered, the existing four-component borehole strainmeter in China is the best solution; if the comprehensive self-verification of observation accuracy is considered, i.e., the accuracy self-verification of both areal strain and shear strain, then the six-component is the best solution. For the six-component scheme, we give formulas for accuracy self-verification of areal strain and shear strain.
Natural seismic event property recognition used to rely on manual detection of seismic waveforms, leading to insufficient automation and large errors. To solve this problem, using least squares support vector machine(LSSVM) in machine learning and feature parameters such as permutation entropy, approximate entropy and Shannon entropy in information theory, we develop the Entropy-LSSVM seismic waveform feature extraction and event property recognition model. Based on a total of 500 waveform data from the 2021 Qinghai Maduo MS7.4 earthquake, Yunnan Yangbi seismic event and an artificial blast disturbance event, we design several random extraction sub-experiments with different training and testing ratios to verify the effectiveness of the model using accuracy, recall, effectiveness, precision and F-measure. The experimental results show that the entropy feature is effective in distinguishing natural and non-natural seismic event waveforms, and the overall performance of the model is better than that of QDA, LDA, plain Bayes, decision tree, LogitBoost, and RobustBoost, etc. The recognition accuracy and recall of the training set/test set ratio of 3∶2 can reach 99.00% and 96.97%. The recognition accuracy can reach more than 98%, even with only 50 entries in the training set, which provides some reference value for the effective screening of natural seismic events.