Water resources are important for agricultural, industrial, and urban development. In this paper, we analyzed the influence of rainfall and snowfall on variations in terrestrial water storage (TWS) in Northeast China from Gravity Recovery and Climate Experiment (GRACE) gravity satellite data, GlobSnow snow water equivalent product, and ERA5-land monthly total precipitation, snowfall, and snow depth data. This study revealed the main composition and variation characteristics of TWS in Northeast China. We found that GRACE provided an effective method for monitoring large areas of stable seasonal snow cover and variations in TWS in Northeast China at both seasonal and interannual scales. On the seasonal scale, although summer rainfall was 10 times greater than winter snowfall, the terrestrial water storage in Northeast China peaked in winter, and summer rainfall brought about only a sub-peak, 1 month later than the maximum rainfall. On the interannual scale, TWS in Northeast China was controlled by rainfall. The correlation analysis results revealed that the annual fluctuations of TWS and rainfall in Northeast China appear to be influenced by ENSO (EI Niño–Southern Oscillation) events with a lag of 2–3 years. In addition, this study proposed a reconstruction model for the interannual variation in TWS in Northeast China from 2003 to 2016 on the basis of the contemporary terrestrial water storage and rainfall data.

The Gravity Recovery and Climate Experiment (GRACE) gravity mission has become a leading platform for monitoring temporal changes in the Earth’s global gravity field. However, the usability of GRACE data is severely limited by 11 months of missing data between the GRACE and GRACE Follow-on (GRACE-FO) missions. To date, several approaches have been proposed to fill this data gap in the form of spherical harmonic coefficients (an expression of the Earth’s gravity field, SHCs). However, systematic analysis to reveal the characteristics and consistency of the datasets produced by these latest gap-filling techniques is yet to be carried out. Here, three SHC gap-filling products are systematically analyzed and compared: (1) Combining high–low satellite-to-satellite tracking with satellite laser ranging (SLR) observations (QuantumFrontiers, QF), (2) SLR-based recovery incorporating the GRACE empirical orthogonal function decomposition model proposed by the Institute of Geodesy and Geoinformation at the University of Bonn (hereafter, denoted as IGG), and (3) applying the singular spectrum analysis approach (SSA). The results show that (1) the SHCs of the QF, IGG, and SSA data are consistent up to degree 12; (2) the IGG and SSA data give similar results over the 11 gap months, but the IGG shows a faster increase in the mean ocean water mass and the SSA appears to better capture the interannual variation in the terrestrial water storage; and (3) the noise level increases significantly in the high-degree terms (l > 16) of the QF data, so these data are only applicable for large-scale mass migration research. These results provide a reference for users to select a gap-filling product. Finally, we propose a new scheme based on the triple collocation method to derive a weight matrix to fuse these three datasets into a more robust solution.

Accurate landslide segmentation using remote sensing imagery is a critical component of geohazards response systems, particularly in time-sensitive tasks such as post-earthquake landslide damage assessment and emergency resource allocation. However, current methodologies struggle with two persistent challenges in sub-meter true-color imagery: fine-grained inter-class confusion between landslides and spectrally analogous terrain features, and within-landslide heterogeneity where localized damage signatures coexist with macro-scale deformation patterns within individual landslide bodies. To overcome these, we propose the Cross-Attention Landslide Detector (CALandDet), which improves the model’s ability to distinguish between landslide and background features by sharply capturing global landslide feature information and integrating global landslide feature information with local information via a cross-attention feature enhancement mechanism. Ablation experiments show that CALandDet outperforms baselines, as evidenced by a 4.89% enhanced F1 score and an 8.73% greater Intersection over Union (IoU). In comparative experiments, it outperforms the other models by 8.05–10.78% in IoU and 1.05–8.9% in F1 score, achieving an IoU of 82.65% and an F1 score of 81.64%. Furthermore, the Gradient-weighted Class Activation Mapping (Grad-CAM) visualizations confirm that the decision regions generated by the CALandDet model exhibit a higher spatial consistency with the actual landslide areas, effectively capturing indicative features including surface textures, sliding debris, accumulation bodies, and vegetation destruction. The proposed method may serve as a reference for future advancements in landslide segmentation and other remote sensing segmentation tasks.

Lakes on the Tibetan Plateau are sensitive indicators of climate change. Their water storage variations play an important role in regional hydrological processes and ecological security. This study is based on multi-source remote sensing and meteorological data from 1988 to 2025. Lake area was extracted using the MNDWI and the Otsu threshold method. HYDROWEB water level data were used to establish an area-water level relationship. This relationship was then applied to reconstruct a long-term water level time-series and estimate changes in lake water storage. GRACE/GRACE-FO data and meteorological observations were further analyzed to identify the driving factors. The results show that Siling Co experienced a persistent expansion over the study period, with the lake area increasing by 805.83 km², water level rising by 14.33 m, and water storage increasing by 30.42 km³. Correlation analysis indicates that air temperature, precipitation, and evaporation jointly influenced lake water storage variations. Among these factors, precipitation plays a relatively more important role. During 2002–2019, lake water storage changes (LWSC) were highly consistent with terrestrial water storage (TWS) variations. However, TWS anomalies lagged approximately one year behind LWSC. These findings improve the understanding of the long-term hydrological responses of Siling Co to climate change. They also provide a scientific basis for water resource management and infrastructure planning in the region.

On 18 December 2023, an Ms 6.2 earthquake occurred in Jishishan County, Linxia Prefecture, Gansu Province, China. As the strongest seismic event in the region since records began, it caused significant casualties and property damage while providing a valuable opportunity to investigate local seismogenic structures. In this study, the seismogenic structure and seismogenesis mechanism of earthquakes were explored through high-precision coseismic deformation analysis and fault modeling combined with regional tectonic background and aftershock distribution data. The results indicate that the earthquake was a typical shallow thrust event with a maximum slip of 0.7 m and a minor dextral strike-slip component. A small-scale dextral adjustment fault that developed at the intersection of Lajishan, the Yellow River, and Jishishan is presumably the primary controlling factor for the dextral component. This study revealed that the northeastern margin of the Qinghai‒Tibet Plateau achieves strain release through local block rotation, resulting in a unique plateau expansion mode. These findings are crucial for understanding the tectonic evolution at the frontal edge of the Himalayan collision zone and improving regional strong earthquake risk assessment.

On 29 July 2025, an Mw 8.8 megathrust earthquake occurred offshore of the southeastern Kamchatka Peninsula, ranking among the ten largest earthquakes worldwide since 1900. Due to observational limitations, the rupture characteristics of large earthquakes along the Kamchatka subduction zone and the north–south contrast in earthquake magnitudes remain poorly understood. In this study, we combine InSAR data, GNSS displacements, and teleseismic waveforms to investigate the spatiotemporal evolution of the 2025 mainshock by constructing a curved fault geometry with along-strike and downdip variations and applying finite-fault inversion together with back-projection analysis. The inversion results show that the mainshock was characterized by unilateral rupture propagating from northeast to southwest, with a rupture length of about 560 km, a duration of about 200 s, and dominant slip concentrated at depths of 15–30 km, with a peak slip of about 10 m. Slip was weak during the initial nucleation stage near the hypocenter, whereas the main slip patch was located within a strongly locked region in the southern segment, and the rupture accelerated rapidly after entering that region. The back-projection results indicate that high-frequency radiation mainly migrated southwestward and was concentrated along the boundaries of the large-slip region and possible structural segmentation zones. These results indicate that the rupture behavior of the 2025 mainshock was jointly controlled by curved megathrust geometry and along-strike locking heterogeneity. The north–south contrast in earthquake size along the Kamchatka subduction zone may result from the combined effects of stronger locking and smoother megathrust geometry in the south, versus more complex fault geometry and submarine tectonic features in the north. This study provides new constraints on rupture processes, seismic cycle behavior, and regional seismic hazard along the Kamchatka subduction zone, and offers important implications for understanding the mechanisms and magnitude potential of future great earthquakes in the Kamchatka region.