Search Results (119)

Snow cover, as a critical component of the cryosphere, serves as a vital water resource for arid regions in Northwest China. The Qilian Mountains (QLM), situated on the northeastern margin of the Tibetan Plateau, function as an important ecological barrier and water conservation area in western China. This study presents the first high-resolution historical snow cover product developed specifically for the QLM, utilizing a multi-level snow classification algorithm tailored to the complex topography of the region. By employing Landsat satellite data from 1986–2024, we constructed a comprehensive 39-year snow cover dataset at a resolution of 30 m. A dual adaptive cloud masking strategy and spatial interpolation techniques were employed to effectively address cloud contamination and data gaps prevalent in mountainous regions. The spatiotemporal characteristics and driving mechanisms of snow cover changes in the QLM were systematically analyzed using Sen–Theil trend analysis and Mann–Kendall tests. The results reveal the following: (1) The mean annual snow cover extent in the QLM was 15.73% during 1986–2024, exhibiting a slight declining trend (−0.046% yr⁻¹), though statistically insignificant (p = 0.215); (2) The snowline showed significant upward migration, with mean elevation and minimum elevation rising at rates of 3.98 m yr⁻¹ and 2.81 m yr⁻¹, respectively; (3) Elevation-dependent variations were observed, with significant snow cover decline in high-altitude (>5000 m) and low-altitude (2000–3500 m) regions, while mid-altitude areas remained relatively stable; (4) Comparison with MODIS data demonstrated good correlation (r = 0.828) but revealed systematic differences (RMSE = 12.88%), with MODIS showing underestimation in mountainous environments (Bias: −8.06%). This study elucidates the complex response mechanisms of the QLM snow system under global warming, providing scientific evidence for regional water resource management and climate change adaptation strategies. Full article

The blue-eared pheasant (Crossoptilon auritum), a Near Threatened (NT) species endemic to China, is primarily distributed across the northeastern region of the Qinghai–Tibetan Plateau. To bridge the fine-scale spatiotemporal gap in blue-eared pheasant behavioral ecology, this study combines satellite telemetry, movement modeling, and field-based habitat assessments (vegetation, topography, human disturbance). This multidisciplinary approach reveals detailed patterns of their behavior throughout the breeding season. Using satellite-tracking data from six individuals (five males tracked at 4 h intervals; one female tracked hourly) in Wanglang National Nature Reserve (WLNNR), Sichuan Province during breeding seasons 2018–2019, we quantified their home ranges via Kernel Density Estimation (KDE) and examined the female movement patterns using a Hidden Markov Model (HMM). The results indicated male core (50% KDE: 21.93 ± 16.54 ha) and total (95% KDE: 158.30 ± 109.30 ha) home ranges, with spatial overlap among individuals but no significant temporal variation in home range size. Habitat selection analysis indicated that the blue-eared pheasants favored shrub-dominated areas at higher elevations (steep southeast-facing slopes), regions distant from human disturbance, and with abundant animal trails. We found that their movement patterns differed between sexes: the males exhibited higher daytime activity yet slower movement speeds, while the female remained predominantly near nests, making brief excursions before returning promptly. These results enhance our understanding of the movement ecology of blue-eared pheasants by revealing fine-scale breeding-season behaviors and habitat preferences through satellite-tracking. Such detailed insights provide an essential foundation for developing targeted conservation strategies, particularly regarding effective habitat management and zoning of human activities within the species’ range. Full article

In recent years, high-altitude cities with low emissions in western China have exhibited an upward trend in surface ozone (O₃). Based on observations and reanalysis data, this study analyzed the evolutionary characteristics and pollution mechanisms of ozone in Xining and quantified the impact of stratospheric intrusion. The results indicated that an upward trend in summer O₃ was observed in Xining. A total of 29 ozone exceedance days were found. Potential exceedance days (>150 and >140 μg/m³) showed substantial increases from 2022 to 2023. Using a stratospheric intrusion to surface (SITS) event identification algorithm, 42 events were found in Xining, with an average duration of 8.4 h. Spring exhibited the highest event frequency (13 events) and longest average duration. SITS events contributed an average of 19.7% to surface ozone, significantly exacerbating local exceedance risks. A typical ozone pollution episode from 25 July to 3 August 2021 was analyzed. The peak O₃ reached 170 μg/m³. Elevated temperature, intensified radiation, and unfavorable meteorological conditions synergistically promoted local photochemical ozone production and accumulation. Notably, a SITS event was simultaneously detected, elevating surface ozone by 24%, which confirmed that stratospheric intrusion was the main cause of pollution. Full article

Accurate identification of mattic epipedon degradation is critically important for addressing ecological issues such as the weakening of alpine grassland carbon sink capacity and reduced soil and water conservation. However, efficient and rapid methods for its detection remain limited. This study aimed to clarify the hyperspectral response mechanisms of mattic epipedon degradation and, based on hyperspectral technology, to construct models for identifying degraded mattic epipedon and screen preprocessing methods suitable for different moisture conditions. The results showed the following: (1) The XGBoost model with preprocessing using multiplicative scatter correction combined with second derivative transformation (MSC+SD) performed best, achieving an identification accuracy and Kappa coefficient of 0.85 and 0.82, respectively. The characteristic bands were concentrated in the visible light range (446–450 nm) and short-wave infrared range (2134 nm, 2267–2269 nm), which are closely related to the spectral responses of organic carbon and mineral components. (2) Spectral reflectance was significantly negatively correlated with moisture content, and model accuracy decreased as moisture content increased. (3) After correction using the EPO algorithm, the model accuracy for the high-moisture group improved by 13.2–16.7%, whereas that for the low-moisture group (<15%) decreased by 7.5%, verifying 15% moisture content as the critical threshold for water interference. This study elucidated the impact mechanism of moisture on the hyperspectral characteristics of the mattic epipedon. The established MSC+SD-XGBoost model adapts to varying moisture conditions, providing technical support for the rapid monitoring of mattic epipedon degradation and holding significant practical value for carbon management in alpine ecosystems. Full article

Strong earthquake activity along fault zones can lead to the displacement of geomorphic units such as gullies and terraces while preserving earthquake event data through changes in sedimentary records near faults. The quantitative analysis of these characteristics facilitates the reconstruction of significant earthquake activity history along the fault zone. Recent advancements in acquisition technology for high-precision and high-resolution topographic data have enabled more precise identification of displacements caused by fault activity, allowing for a quantitative assessment of the characteristics of strong earthquakes on faults. The 1920 Haiyuan earthquake, which occurred on the Haiyuan fault in the northeastern Tibetan Plateau, resulted in a surface rupture zone extending nearly 240 km. Although clear traces of surface rupture have been well preserved along the fault, debate regarding the maximum displacement is ongoing. In this study, we focused on two typical offset geomorphic sites along the middle segment of the Haiyuan fault that were previously identified as having experienced the maximum displacement during the Haiyuan earthquake. High-precision geomorphologic images of the two sites were obtained through unmanned aerial vehicle (UAV) surveys, which were combined with light detection and ranging (LiDAR) data along the fault zone. Our findings revealed that the maximum horizontal displacement of the Haiyuan earthquake at the Shikaguan site was approximately 5 m, whereas, at the Tangjiapo site, it was approximately 6 m. A cumulative offset probability distribution (COPD) analysis of high-density fault displacement measurements along the ruptures indicated that the smallest offset clusters on either side of the Ganyanchi Basin were 4.5 and 5.1 m long. This analysis further indicated that the average horizontal displacements of the Haiyuan earthquake were approximately 4–6 m. Further examination of multiple gullies and geomorphic unit displacements at the Shikatougou site, along with a detailed COPD analysis of dense displacement measurements within a specified range on both sides, demonstrated that the cumulative displacement within 30 m of this section of the Haiyuan fault exhibited at least five distinct displacement clusters. These dates may represent the results of five strong earthquake events in this fault segment over the past 10,000–13,000 years. The estimated magnitude, derived from the relationship between displacement and magnitude, ranged from M_w 7.4 to 7.6, with an uneven recurrence interval of approximately 2500–3200 years. Full article

Obtaining precise seasonal yield estimates is challenging, with weather forecast accuracy being a key factor. This study examines the impact of different weather data forecasting methods on yield estimation. Initially, we evaluated the suitability of the WOFOST model for highland barley (HB) and wheat on the northeastern Tibetan Plateau. Yield forecasts were conducted using nine historical weather selection methods under two scenarios, differing in their use of 10-day TIGGE data. The results showed that different weather data fusion methods led to varying forecasted yields. For HB, sequential selection and an improved KNN algorithm were optimal, while for wheat, sequential selection performed best. Early-season forecasts had lower accuracy, while predictions after flowering were more reliable. Incorporating TIGGE short-term forecasts into historical weather data improved HB yield forecasts, with 98.2% of days having an average relative error (ARE) below 20%. For wheat, using only historical weather data provided more stable yield forecasts, with 93.1% of days having an ARE below 20%. The weather data fusion strategy for yield forecasts offered reliable prediction accuracy without the need for full-cycle weather observation. Full article

Soil organic carbon (SOC) plays a crucial role in the terrestrial carbon cycle and climate regulation. Quantifying the sensitivity of SOC to climate change is essential for developing effective strategies to address climate change and optimizing agricultural production. This study compares the performance of four machine learning models in assessing SOC, ultimately selecting the optimal Extreme Gradient Boosting model for spatial predictions of surface SOC (0–30 cm) across the country. The results indicate that areas with higher organic carbon density are primarily concentrated in the Tibetan Plateau and northeastern regions. Notably, regions with high uncertainty in predictions correspond to areas of elevated organic carbon density. Average temperature, average precipitation, and the Normalized Difference Vegetation Index were identified as the most influential factors across all models. Based on the predictions from the optimal model and a bottom-up framework, various potential climate change scenarios were considered, allowing for the quantification of SOC sensitivity to climate change. Under scenarios of increased temperatures and decreased precipitation, SOC loss intensified, hindering SOC accumulation. When the average temperature rose by 1.45 °C and precipitation decreased by 14.67%, a loss of 10% in SOC was projected for most regions of China. These findings provide critical insights for the proactive formulation of climate adaptation strategies, soil health preservation, and the maintenance of ecosystem stability. Full article

The reconstruction of all-weather land surface temperature (LST) has gained increasing attention in recent years, and many reconstructed LST products have been published. However, the spatial resolution of most LST products is still lower than 1 km, which limits the application of all-weather LSTs. This study proposed the geographically constrained machine learning-based kernel-driven method (Geo-MLKM), which is incorporated with the light gradient-boosting machine (LightGBM) model to explore its feasibility in the downscaling of all-weather LST (DALST). Using data from the northeastern Tibetan Plateau (NETP) region and Zhejiang Province, the relationship between all-weather LST and various kernels (i.e., land surface-related kernels, LST-derived kernels, and meteorologically related kernels) was trained to compare the kernel importance; then, advisable kernels were selected for the implementation of DALST. Compared with the 1 km resolution all-weather LST product, the downscaled LST at 250 m obviously adds more spatial details. Evaluated with the in situ measurement, the average root mean square error (RMSE) and r value of the downscaled LST are 2.465 K and 0.981 for clear skies and 4.361 K and 0.925 for cloudy skies, respectively. Compared with the all-weather LST product, the downscaled LST can reduce RMSE by 0.391 K. These results indicate that the Geo-MLKM method is promising for effectively implementing the DALST at a large scale and for generating a large number of high-resolution all-weather LSTs for environmental studies. Full article

The northeastern Tibetan Plateau (NETP) is located at the front of the northeastward expansion of the Tibetan Plateau and is a tectonically active region with complex faults and intense seismicity. In this study, based on the high-order geomagnetic field model EMM2017, the crustal magnetic anomalies and Curie point depths (CPDs) in the NETP and adjacent areas were investigated. The relationship between the magnetic anomalies, CPDs, and seismic activity was assessed. The results show that strong earthquakes occur mainly in areas where the magnetic anomalies are negative or have a strong-to-weak transition. The CPD is located at 18–42 km. In the NETP, a shallow CPD corresponds to high heat flow. In contrast, in surrounding areas, a deep CPD corresponds to low heat flow. The northeast area from Bayan Har to the Qilian orogenic belt, and the region with a deep CPD in the Qaidam Basin, record the northeastward flow of the Tibetan Plateau. High-magnitude earthquakes are associated with depth changes in the CPD and areas with a shallow CPD. The frequent seismic activity in the NETP can be attributed to the northeastward flow of the Tibetan Plateau caused by a deep heat flux. The results can be used as a reference for the prediction of strong regional earthquakes. Full article

Plateau pika (Ochotona curzoniae, hereafter pika) is a key species in the alpine grasslands on the Qinghai-Tibetan Plateau (QTP). They are susceptible to the influence of external disturbance and may present great variation, which is important to evaluate their ecological role in alpine grasslands. However, our knowledge regarding their interannual variation and the influencing mechanism is still limited due to the lack of long-term observation of pika density. This study aimed to investigate the spatiotemporal variations in pika and the associated key influencing factors by aerial photographing at 181 sites in Gannan Tibetan Autonomous Prefecture in 2016, 2019, and 2022. Our findings showed that: (1) pika primarily distributed in the central and northeastern Maqu County and the southwestern part of Luqu County, and their average density was in a range of 9.87 ha⁻¹ to 14.43 ha⁻¹ from 2016 to 2022; (2) high pika density were found in 1.22 to 3.61 °C for annual mean temperature, 12.86 to 15.06 °C for diurnal temperature range, 3400 to 3800 m for DEM and less than 3° for slope; and (3) pika density showed varied response to interannual changes in mean diurnal range, annual precipitation and precipitation of the driest month in different years. Our results concluded that pika density showed significant spatiotemporal variations, and climate and terrain variables dominantly affected pika density. Given the great interannual fluctuation of climate variables and different responses of pika density to these variables, our results suggested that long-term monitoring of pika is crucial to reveal their real distribution, response mechanism to habitat environment, and role in alpine grasslands. Moreover, unmanned aerial vehicles are cost-effective tools for the long-term monitoring of pika. Full article

Double-cropping systems in which two kinds of crops are harvested per year can elevate forage yields significantly. This is the first report on a double-cropping system in the northeastern margin of alpine pastoral areas on the Qinghai–Tibetan Plateau with an elevation of 3500 m. In this experiment, eight triticale genotypes, including five varieties (‘Gannong No. 2’, ‘Gannong No. 3’, ‘Gannong No. 4’, ‘Gannong No. 7’, and ‘Zangsi No. 1’), and three lines (C16, C23, and C25) were used as the fore crops, with the four succeeding crops being 50% of triticale mixed with 50% of forage pea (B1), 50% of triticale mixed with 50% of common vetch, 50% of oat mixed with 50% of forage pea, and 50% of oat mixed with 50% of common vetch. Over 2 years (2020–2021), among the fore crops, ‘Gannong No. 4’ had the highest average hay yield (9.00 t·ha⁻¹), crude protein content (114.97 mg·g⁻¹), and relative feeding value (91.77), as well as the lowest average neutral detergent fiber content (598.17 mg·g⁻¹). Among the succeeding crops, B1 had the highest average hay yield (11.45 t·ha⁻¹) and nutritional quality. Among the interactions between the fore and succeeding crops, the highest hay yield (21.72 t·ha⁻¹), crude protein content (262.22 mg·g⁻¹), and relative feeding value (219.34) were obtained when ‘Gannong No. 4’ was doubled with B1. The results provide a theoretical basis for carrying out a double-cropping system in the alpine pastoral areas on the Qinghai–Tibetan Plateau, and this has very important implications for crop production in this area. Full article

As the forefront of inland extension on the Indian plate, the northeastern Tibetan Plateau, marked by low strain rates and high stress levels, is one of the regions with the highest seismic risk. Analyzing seismicity through statistical methods holds significant scientific value for understanding tectonic conditions and assessing earthquake risk. However, seismic monitoring capacity in this region remains limited, and earthquake frequency is low, complicating efforts to improve earthquake catalogs through enhanced identification and localization techniques. Bi-scale empirical probability integral transformation (BEPIT), a statistical method, can address these data gaps by supplementing missing events shortly after moderate to large earthquakes, resulting in a more reliable statistical data set. In this study, we analyzed six earthquake sequences with magnitudes of M_S ≥ 6.0 that occurred in northeastern Tibet since 2009, following the upgrade of the regional seismic network. Using BEPIT, we supplemented short-term missing aftershocks in these sequences, creating a more complete earthquake catalog. ETAS model parameters and b values for these sequences were then estimated using maximum likelihood methods to analyze parameter variability across sequences. The findings indicate that the b value is low, reflecting relatively high regional stress. The background seismicity rate is very low, with most mainshocks in these sequences being background events rather than foreshock-driven events. The p-parameter of the ETAS model is high, indicating that aftershocks decay relatively quickly, while the α-parameter is also elevated, suggesting that aftershocks are predominantly induced by the mainshock. These conditions suggest that earthquake prediction in this region is challenging through seismicity analysis alone, and alternative approaches integrating non-seismic data, such as electromagnetic and fluid monitoring, may offer more viable solutions. This study provides valuable insights into earthquake forecasting in the northeastern Tibetan Plateau. Full article

This study investigated the source, trajectory, and precipitation of the Southwest (SW) vortex, which was linked with the Plateau (P) vortex. Based on the statistical study of a number of cases, this study showed the following results. The SW vortex tended to originate at the northeastern and western peripheries of the Sichuan Basin, normally coinciding with the presence of the P vortices in the eastern region of the Tibetan Plateau. Most of the aforementioned vortices exhibited a longer life span, and resulted in severe storms averaging approximately 50 mm of rainfall per day, especially in the cases of more than 100 mm of rainfall per day in eastern and southern China. Furthermore, new findings were obtained: (1) The SW vortex and the P vortex were attributed from an ‘Ω’ circulation pattern from blocking high in middle to high latitudes region. The SW vortex was notably influenced by the convergence of two air currents. In the lower troposphere, the southwesterly jet of the South Asian monsoon flowed over and around the Yungui Plateau, and cold–dry air from the north flowed into the Basin. (2) Both the SW vortex and the P vortex displayed a shallow synoptic system characterized below 500 hPa, and wet–cold cores formed around the sources at low altitudes. (3) The analysis on atmospheric instability and dynamics suggested that the vortices’ eddies generated significant convective instability at lower levels. The circulation pattern and instability conditions facilitated the heavy precipitation associated with the SW vortex, and the ample water vapor and subsequent latent heat intensified the precipitation. Full article

The arcuate tectonic belt in the northeast Tibetan Plateau has been a contentious topic regarding its formation and evolution, owing to its distinctive geological structure as the lateral growth boundary of the plateau. In this research, leveraging geological and geophysical data, a three-dimensional finite element numerical model is employed to explore the impact of lateral and vertical inhomogeneities in lithospheric strength on the northeast Tibetan Plateau’s growth and the arcuate tectonic belt’s formation and alteration. Additionally, the kinematic and deformation traits of the arcuate tectonic belt, such as regional motion velocity, stress, and crustal thickness during shortening and strike-slip deformation, are comparatively analyzed. The findings indicate that the arcuate tectonic belt takes shape when the weakly strengthened Tibetan Plateau is impelled into the Yinchuan Basin after being obstructed by the robust Alax and Ordos blocks during lateral expansion. Intense shear deformation occurs at the block boundaries during the arc tectonic belt’s formation. The weak middle-lower crust, serving as a detachment layer, facilitates the plateau’s lateral growth and crustal shortening and thickening without perturbing the overall deformation characteristics. It is verified that the arcuate tectonic belt was formed during the NE-SW compression phase from around 9.5 to 2.5 Ma, accompanied by significant crustal shortening and thickening. Since 2.5 Ma, within the ENE-WSW compression process, the internal faults of the arcuate tectonic belt are predominantly strike-slip, with no pronounced crustal shortening and thickening. Only local topographical modification is conspicuous. This study will enhance our comprehension of the Tibetan Plateau’s uplift and lateral growth process and furnish a foundation for investigating the formation of arcuate tectonic belts. Full article

We observed high-quality waves from a repeatable airgun seismic source recorded by a linear ultra-dense seismic array across the Xiliushui fault zone, one of the inactive faults in the Qilian Mountain, on the northeastern margin of the Tibetan Plateau, China. We used Snell’s law of seismic ray propagation to determine a simplified ambient velocity model. Based on the flexible and precise spectral element method, we computed broadband synthetic seismograms for a shallow low-velocity fault zone (FZ) to model the direct P-wave travel time delay and incident angle of the wavefield near the FZ. The FZ extent range and boundaries were inverted by apparent travel time delays and amplification patterns across the fault. According to prior information on the properties of the direct P-waves, we could constrain the inverse modeling and conduct a grid search for the fault parameters. The velocity reduction between the FZ and host rock, along with the dip angle of the FZ, were also constrained by the P-wave travel time delay systematic analysis and incoming angle of the P-waves. We found that the Xiliushui fault has a 70~80 m-wide low-velocity fault damage zone in which the P-wave velocity is reduced to ~40% with respect to the host rock. The fault damage zone dips ~35°southwest and extends to ~165 m in depth. The repeatability and environment protection characteristics of the airgun seismic survey and the economic benefits of a limited number of instruments setting are prominent. Full article