A high-precision seismic dataset was constructed using deep learning methods, and a regional three-dimensional velocity model was obtained through double-difference tomography. The study reveals a correlation between surface velocity structures and geological features: mountainous areas generally exhibit high-velocity P-wave anomalies, whereas depression zones are characterized by low-velocity P-wave anomalies. This pattern may be attributed to the widespread presence of bedrock with relatively high wave velocity in folded regions, in contrast to the Quaternary sedimentary layers with lower velocity in depression areas. Seismic epicenters are densely distributed along the transition zones between high- and low-velocity anomalies. These transitional regions experience significant stress gradients, which facilitate rock fracturing and lead to heightened seismic activity.The Luxi uplift is characterized by several near-vertical high- and low-velocity blocks, with some earthquake epicenters also displaying steeply dipping distributions, suggesting the presence of high-angle faults. This structural configuration may result from multiple phases of compression and extension under the influence of Pacific Plate subduction and the tectonic activity of the Tan-Lu fault zone. These processes have led to cyclic uplift and subsidence in the region, during which progressive compression and extension of rock folds gradually increased their dip angles, forming near-vertical velocity blocks and high-angle faults.Integrated analysis of P- and S-wave velocities suggests the presence of mantle-derived basaltic magmatic intrusions beneath both the Nishan area and the northeastern region of the Lushan. In the Nishan area, the intrusions are predominantly plutonic, whereas in northeastern Lushan, mantle-derived basaltic magma likely reached the surface, forming ancient volcanoes and extrusive rocks.

Under an elastic Earth model, clear analytical solutions exist for surface gravity changes induced by a single strike-slip fault. However, the quantitative relationship between multiple fault zones and their geometric parameters with the resulting surface gravity change patterns remains unclear. Based on dislocation theory in an elastic half-space, this paper systematically investigates the quantitative connection between the geometric parameters of parallel strike-slip dislocation sources and the characteristics of the surface gravity change patterns through numerical simulations. Using the control variable method, we separately analyze the influence of fault length (L), width (W), slip amount (K), number of faults (N), dip angle (δ), and top depth (dep) on the four-quadrant distribution pattern and amplitude of the gravity anomaly. The results show that: 1) Fault length L is linearly positively correlated with the distance between gravity extremal points along the fault strike (X-direction). 2) Increasing fault width W elevates the gravity anomaly amplitude, but the growth trend diminishes, without altering the four-quadrant structure. 3) The strike-slip width K is linearly positively correlated with the distance between gravity extremal points along the Y-direction, but negatively correlated with the gravity anomaly amplitude. 4) An increase in the number of strike-slip faults N leads to a linear increase in the gravity change amplitude. 5) Variations in the dip angle δ affect the symmetry of the gravity change pattern. 6) An increase in the top depth dep causes a significant increase in the distance between extremal points in the Y-direction. 7) The fault center position (s_x, s_y) coincides with the four-quadrant symmetric center of the gravity change pattern, and the line connecting a pair of extremal points in the X-direction aligns with the fault strike angle α. In summary, the main geometric parameters of multiple dislocation sources can be determined based on observed gravity change patterns.

Based on the observation data of VP-type broadband vertical pendulum inclinometers from 5 stations in Inner Mongolia, this study adopted a method combining the wave propagation theoretical model and the deep learning prediction framework to preliminarily reveal the multi-frequency quantitative influence mechanism of the overburden thickness of observation caves on the observation signals. The results show that the overburden thickness is significantly negatively correlated with background noise (especially in the north-south direction), but has a weak impact on low-frequency signals. It exerts a directional regulatory effect on the amplitude of M₂ tidal waves: the amplitude of the north-south component increases linearly with the increase of thickness, while the east-west component shows a unique resonance amplification effect at the thickness of 20 m (the peak value is about 3.6 times higher than that at 10 m). When the thickness is greater than or equal to 20 m, it can effectively suppress the seasonal fluctuation of data, significantly reduce the variation amplitude, delay the peak value by 1-2 seasons, and simultaneously decrease the barometric admittance coefficient remarkably. Verified by the random forest model, it is found that the optimal thickness range of the cave overburden is 18-22 m (with 20 m as the optimal value). Lithology is a secondary influencing factor, while the overburden thickness and its interaction with the density of mountain lithologic media constitute the dominant control parameters. In this study, 20 m of overburden thickness was selected as the engineering threshold, which provides an important design basis for effectively suppressing background noise, ensuring the fidelity of tidal signals and resisting seasonal interference, and gradually promotes the construction of cave-based observation at stations from an empirical mode to a quantitative and engineering-oriented direction.

Aiming at the problem that it is difficult for the temporal decomposition model to accurately distinguish the effects of induced factors on different displacement components, and the prediction accuracy is insufficient under the uncertainty of meteorological data, a landslide displacement prediction network model based on optimized time series decomposition and feature selection is proposed. Firstly, the variational modal decomposition (GA-VMD) method optimized by singular spectral analysis (SSA) and genetic algorithm is combined with induced factors to decompose the landslide displacement. Subsequently, an improved Nishihara model with fusion inducible factors is constructed to predict the trend term displacement, and the combined network of convolutional neural network and gated recurrent unit (CNN-SE-GRU) combined with compression and excitation network was used to model the period term displacement, and the random term displacement is reconstructed through frequency domain analysis. Finally, the probability interval of the displacement prediction results is constructed by combining kernel density estimation (KDE) and Monte Carlo simulation. Taking the Heifangtai landslide in Gansu province as an example, the RMSE and MAPE of the prediction model are 1.52 mm and 0.38%, respectively, and the prediction accuracy of the model is significantly improved compared with the traditional prediction model, providing more reliable technical support for landslide early warning.

To address the issues of reduced accuracy and misidentification of single water bodies caused by interpolation in large-scale flood inundation mapping using spaceborne GNSS-R technology, this paper proposes a dynamic monitoring method based on the reflectivity change rate using period-matched observation-based interpolation (POBI). Utilizing CYGNSS reflectivity data during the rainy seasons from 2019 to 2023 and China's 1 km resolution monthly precipitation products, we constructed a POBI spatial interpolation model. By combining this with the bistatic radar equation to retrieve surface reflectivity, we systematically analyzed the flood evolution process during the extreme rainfall event in Guilin in June 2024. The results show that, for reflectivity interpolation in unsampled areas, the root mean square error (RMSE) decreased by an average of 20.98% compared to the natural neighbor method. The inundation identification mechanism based on the change rate effectively avoids the subjectivity of traditional threshold methods. The monitoring results indicate that the inundated area in the central urban district expanded by 48.68% from June 19 to June 12, with spatial evolution highly consistent with changes in SMAP soil moisture. This study provides reliable methodological support for refined flood monitoring in highly dynamic, low-coverage areas using spaceborne GNSS-R.

This study proposed a novel monitoring scheme that integrates GNSS interferometric reflectometry (GNSS-IR) with GNSS positioning for monitoring coastal absolute sea level changes. Using over 10 years of observational data from seven coastal stations in Hong Kong as an example, research on absolute sea level change monitoring in nearshore areas was conducted. The results indicated that after excluding the stations HKSL and KYC1, which had lower data quality, the GNSS-IR-derived relative sea level changes from the remaining stations showed good agreement with tide gauge data in their monthly averages. For most stations, the RMSE was less than 6 cm, the correlation coefficient was greater than 0.86, and the difference in estimated sea level rise trends was less than 1 mm/a compared to tide gauges (with a regional average difference of only 0.036 mm/a). In absolute sea level monitoring, after applying the dynamic atmospheric correction (DAC), the difference in regional average rates between coastal GNSS and satellite altimetry at corresponding points was reduced from -3.40 mm/a to -0.76 mm/a, indicating highly consistent trends. Compared with 50-year long-term absolute sea level data from Hong Kong tide gauges, the deviations were mostly less than 1 mm/a, and all stations fell within reasonable error margins for regional absolute sea level monitoring. The research demonstrates that the fusion of GNSS-IR and GNSS positioning can effectively address traditional monitoring gaps, providing a scalable new technical approach for monitoring coastal sea level changes and conducting risk assessments.

Landslide disasters pose a continuous threat to the safety of life and property of mountain residents. Especially under heavy rainfall, landslide areas are often accompanied by severe surface deformation, resulting in serious incoherence of synthetic aperture radar interference data, which restricts the deformation monitoring capability of traditional timing InSAR technology in this type of area. To address this problem, this paper takes the large landslide that occurred in Nanyu township, Zhouqu county, Gansu province in July 2018 as the research object, and prensents the distributed scatterer InSAR (DS-InSAR) deformation monitoring method based on statistical homogeneity detection and time phase link optimization. This method introduces a statistical homogeneity determination model under the traditional DS-InSAR framework, and identifies clusters of pixels with stable scattering characteristics through non-parametric testing, thereby expanding the monitoring coverage of low-coherence areas. At the same time, the shortest path constraint strategy is used to optimize the interferogram network structure to improve connection density and temporal coherence. It is also combined with a time-Phase Linking joint estimation algorithm to optimize the interference phase as a whole, enhancing the temporal continuity and stability of deformation information. The research results show that this method significantly improves the distribution density and temporal coherence of monitoring points in the collapse area of Nanyu landslide. The number of effective coherent points in creased from 23 232 to 43 463, an increase of about 87%, and the average posterior coherence coefficient was improved by 0.3, which effectively revealing the dynamic evolution characteristics of the landslide main body. The optimized annual average deformation rate chart shows that the maximum sliding rate of the main deformation area of the landslide exceeds 70 mm/a, and the timing curve of the characteristic point is highly consistent with the rainfall process. This study verifies the applicability and effectiveness of the timing phase optimization method in high-voltage landslide areas, and provides strong technical support for InSAR monitoring of landslides in complex mountainous areas.

Based on over 20 years of MODIS satellite remote sensing infrared data, we extract brightness temperature low-frequency information using anomaly method and spatial anomaly superposition method, and investigate the temporal and spatial evolution and characteristics of infrared radiation anomalies before the Wenchuan M_S8.0 earthquake on May 12, 2008. The results show that there was a significant radiation enhancement anomaly before the earthquake. In terms of time, from 2006 to 2007, there was a trend of radiation enhancement in the core area located west of the epicenter. Conversely, from 2008 until the earthquake occurrence, this radiation enhancement exhibited a weakening trend. Spatially, the core area of radiation enhancement is located in the eastern section of Bayan Har and Qiangtang blocks, encompassing approximately 5.8×10⁵ km². The spatial distribution characteristics are consistent with the dynamic background of Wenchuan earthquake.

Based on the MSATSI method with 1°×1° grid resolution, we inverted the present-day tectonic stress field of the Qinghai-Xizang plateau. The results show that: 1) The focal mechanisms are predominantly strike-slip and thrust types, with 72.70% of P-axes and 58.97% of T-axes plunging less than 30°, indicating that the Qinghai-Xizang plateau is dominated by horizontal compression and shear stress. 2) The stress shape ratio R is significantly higher at the plateau margins than in the interior, with 76.21% of maximum principal compressive stress axes (σ₁) plunging less than 15° and trending overall NNE-SSW. 3) The maximum horizontal stress (S_Hmax) of Qinghai-Xizang plateau rotates clockwise around the eastern syntaxis. In the shallow crust (0 to 10 km), S_Hmax direction aligns with GPS velocity fields and is controlled by active tectonics. S_Hmax of the northeast margin of Qinghai-Xizang plateau, northeast of the Longmenshan, rotates counterclockwise by 20° to 30° at 10 to 20 km depth, indicating decoupling between shallow and deep stress fields, likely associated with differential deformation mechanisms of upper strike-slip and deep thrust thickening.

We analyze the geochemical characteristics of five hot spring fluids in Eryuan and its surrounding areas, and explore the relationship among geothermal distribution, mantle-derived fluid degassing, hydrochemical anomalies, and seismic activity. The results show that hydrochemical type of hot springs in the study area include HCO₃·SO₄-Na·Ca, HCO₃·SO₄-Na, HCO₃·Cl-Na, SO₄-Ca·Na, and SO₄·Cl-Na·Ca. The main sources of hot spring gases are atmospheric saturated water and air, with contributions from volatile components in the crust and mantle. The heat storage temperatures of hot springs in the study area ranges from 164 to 275 ℃, and circulation depths is from 6 369.78 to 11 143.98 meters. The content of He is from 12.90 to 821.62 ppm. Large-scale deep faults in Eryuan area provide favorable channels for the upward migration of deep-sourced fluids, and the deep-sourced fluids are the direct sources of geothermal energy and He. There is a correlation between the geochemical characteristics of hot spring fluids and seismic activities, which is characterized by the deeper the circulation depth, the higher the geothermal reservoir temperature, and the stronger the seismic activity. Moreover, most of the M≥4 earthquakes are located in the transition zone between high and low geothermal reservoir temperatures. The Cl^- and SO₄^2- concentrations of Wenmiao hot spring show abnormal increases before and after earthquakes, mainly due to the contribution of the mixing of deep-sourced fluids and different aquifers. The temperature at spring outlet shows an abnormal decrease, which may be related to the fact that multiple fractures provide heat dissipation channels after the earthquake. The hydrochemical values of hot springs were restored after the earthquake, indicating that the deep-sourced fluid activity in Eryuan area weakened.