Search Results (81)

The Qinghai Lake Basin, a typical ecologically vulnerable, high-altitude, cold region, requires coordinated ecosystem conservation and socio-economic development to achieve territorial sustainability. Based on the Production–Living–Ecological Space (PLES) framework, this study used land use data from five periods between 2000 and 2020 and integrated the PLUS and InVEST models to examine and simulate the evolution of PLES patterns and carbon stock under four scenarios—natural development, ecological protection, economic development, and sustainable development—in 2035. The results show that the PLES pattern in the Qinghai Lake Basin remained generally stable from 2000 to 2020, with ecological space dominating the landscape, while production and living spaces expanded slowly. Carbon stock increased from 214.73 × 10⁶ Mg to 264.70 × 10⁶ Mg, representing a growth rate of 23.27%. Its spatial distribution is highly consistent with the PLES pattern, with ecological space being the main contributor. By 2035, carbon stock is projected to slightly increase under the natural development scenario; under the ecological protection scenario, the expansion of ecological space leads to an increase in carbon stock; it decreases under the economic development scenario due to the encroachment of ecological space by construction land expansion; and under the sustainable development scenario, which balances economic development and ecological protection, carbon stock increases by 4.87 × 10⁶ Mg, achieving the best overall performance. Therefore, it is essential to properly coordinate the relationships among PLES components to achieve synergistic enhancement of ecosystem services and regional sustainable development. The findings provide methodological references and decision support for sustainable development in the Qinghai–Tibet Plateau and other ecologically vulnerable regions. Full article

Qinghai Lake, the largest endorheic saline lake in China, has undergone a pronounced hydrological regime shift from a multi-decadal decline to a rapid post-2004 recovery, reflecting strong hydroclimatic non-stationarity in the northeastern Tibetan Plateau (TP). This paper supplements the current water level and lake area status of Qinghai Lake to provide basic background for future prediction. Reliable forecasting of such climate sensitive lake systems remains difficult because conventional statistical models often fail to capture non-linear fluctuations, whereas standalone deep learning models may overlook long-term deterministic evolution. To address this challenge, we developed a serial decomposition GeoAI framework that integrates autoregressive integrated moving average (ARIMA), one-dimensional convolutional neural networks (1D-CNNs), and long short-term memory (LSTM) networks for non-stationary water level forecasting. Using annual water level observations from 1960 to 2025, the ARIMA component was first used to extract the low-frequency deterministic trend, after which the CNN-LSTM module reconstructed the nonlinear residual variability. The model was trained on the 1960–2012 period and validated over 2013–2025, which represents the most dynamic expansion stage of Qinghai Lake. The hybrid framework outperformed the benchmark models, achieving a Root Mean Square Error (RMSE) of 0.2033 m, Mean Absolute Error (MAE) of 0.1727 m, and Mean Squared Error (MSE) of 0.0413 m² during validation. The decomposition strategy effectively reduced phase lag and amplitude attenuation, improving both predictive accuracy and process interpretability. Multi-step forecasting for 2026–2056 suggests that Qinghai Lake will continue to rise, reaching approximately 3204.08 m by 2056, although the growth rate is projected to slow as negative hydrological feedback strengthen. By explicitly separating deterministic climate scale signals from nonlinear short-term variability, the proposed framework provides a robust and transferable geoinformation based tool for forecasting water level dynamics and supporting adaptive management in climate sensitive, data scarce lake basins. Full article

The Qinghai Lake Basin represents a critical ecological security barrier in the northeastern Qinghai–Tibet Plateau. Water yield and carbon storage within this basin are closely linked to regional ecological security and sustainable development. To investigate their spatiotemporal patterns, influencing factors, and spatial interrelationships from 1995 to 2020, this study integrated the InVEST model, the Optimal Parameter Geodetector model, and spatial autocorrelation analysis. The results indicate that water yield exhibited a fluctuating yet generally increasing trend over the study period, rising from 1.42 × 10⁹ m³ to 1.97 × 10⁹ m³. High water yield values were predominantly concentrated in high-altitude headwater areas, whereas low values mainly occurred in the lake area and its surroundings. Elevation, annual mean temperature, and precipitation were identified as the primary drivers of water yield. Carbon storage increased from 1.76 × 10⁸ t in 1995 to 2.14 × 10⁸ t in 2020. High carbon storage values were mainly concentrated in grassland and forested areas, while low values were largely distributed in built-up land, unused land, and the lake area. Elevation, NDVI, and water yield emerged as the main influencing factors of carbon storage. A significant positive spatial correlation was observed between water yield and carbon storage. Persistent patterns of high-carbon-storage–high-water-yield clusters and low-carbon-storage–low-water-yield clusters demonstrate a clear spatial synergy. These findings provide scientific support for ecological conservation, water resource management, and carbon sink enhancement in the Qinghai Lake Basin and are of practical significance for sustaining regional ecosystem services and safeguarding sustainability. Full article

This study investigated the interactive effects of warming and inundation on methane (CH₄) fluxes and soil physicochemical mechanisms in the littoral wetland of Qinghai Lake. Soil samples were collected from the Bird Island littoral wetland. Eight treatments were established: natural control (CK), different inundation depths (S0, S10, S20), warming alone (ZWCK), and warming combined with inundation (ZW0, ZW10, ZW20). CH₄ fluxes were measured over one year using an ABB LGR analyzer. Principal component analysis (PCA) and Mantel tests were used to identify environmental drivers. The main findings are as follows: (1) Under different water level treatments, CH₄ fluxes showed a unimodal seasonal pattern, peaking in autumn. Warming and the interactive treatments shifted the emission pattern to bimodal or multimodal and significantly increased emission intensity. The warming-alone group had the highest annual emission, with anomalously high winter emission (47.683 μg·m⁻²·h⁻¹). Under the ZW20 treatment, emissions were synergistically enhanced in summer and autumn but turned to suppression in winter. (2) PCA showed that the carbon nitrogen pool (70.5%) and the salinity pH gradient (14.9%) were the main drivers of soil variation. The interactive effects on carbon-nitrogen dynamics shifted with season: warming promoted accumulation in spring; warming with shallow inundation retained carbon-nitrogen in summer, but deep inundation caused loss; warming with deep inundation formed a nutrient center in autumn; inundation dominated accumulation in winter, while warming increased loss. (3) Mantel tests showed that carbon-nitrogen components were highly correlated across seasons, but were strongly and positively correlated with CH₄ flux only in autumn (Mantel’s r ≥ 0.4, p < 0.05), indicating autumn as the key window. These findings provide important insights into carbon cycling processes and regulatory mechanisms of alpine wetlands under future climate change scenarios. Full article

Under the influence of climate change and human activities, alpine grasslands in the Qinghai Lake basin have undergone a degradation trend over recent decades. In this context, investigating the distribution and stability of soil aggregates across varying degradation degrees of alpine grasslands, along with their driving factors, is critical for formulating sustainable management strategies to maintain grassland health and soil structural resilience in this ecologically sensitive region. In this study, plant and soil samples (0–20 cm) were collected at nine sites in the Qinghai Lake basin, each encompassing a non-degraded (ND), a lightly degraded (LD), and a heavily degraded (HD) grassland plot. The distribution and stability of mechanically stable aggregates and water-stable aggregates were evaluated using the dry-sieving and wet-sieving methods, respectively. The results showed that grassland degradation led to declines in plant above-ground and below-ground biomass, soil carbon, nitrogen, phosphorus, and microbial biomass carbon contents, and β-1,4-nacetylglucosaminidase activity, alongside an increase in soil pH. However, soil β-1,4-glucosidase and alkaline phosphatase activities exhibited no significant changes. The 2–0.25 mm fraction is the primary component of mechanically stable aggregates in alpine grasslands across three degradation levels. After degradation, neither the distribution nor the stability of mechanically stable aggregates exhibited significant changes. In terms of water-stable aggregates, the 2–0.25 mm fraction constituted the primary component in ND and LD, whereas the <0.053 mm fraction predominated in HD. Additionally, the mass proportions of the >2 mm and 2–0.25 mm size fractions were significantly lower in HD compared to ND, while the mass fraction of the <0.053 mm fraction was notably higher. The altered distribution of water-stable aggregates resulted in a significant decrease in mean weight diameter and a notable increase in the percentage of aggregate destruction, suggesting a reduced resistance of the soil to water erosion. Plant below-ground biomass, soil total organic carbon, and total nitrogen were identified as crucial factors modulating the dynamics of aggregate stability during grassland degradation. The findings of this study suggest that alpine grassland degradation in the Qinghai Lake basin reduces the water stability rather than the mechanical stability of soil aggregates. Full article

Against the background of a warming and humidifying climate on the Qinghai–Tibet Plateau, increasing attention has been paid to the sustainability of water resources and ecosystems in the Qinghai Lake Basin. Investigating the characteristics of precipitation stable isotopes and moisture sources provides critical insights into the driving mechanisms of the regional hydrological cycle. In this study, precipitation samples collected at the Qinghai Lake Wetland Ecosystem National Observation and Research Station from June 2023 to October 2024 were analyzed for hydrogen (δ²H) and oxygen (δ¹⁸O) stable isotopes. The temporal variations of δ²H, δ¹⁸O, and deuterium excess (d-excess) were characterized, and their relationships with air temperature and precipitation amount were examined. In addition, a backward trajectory model was employed to identify the moisture sources of precipitation during the observation period. The results indicate that: (1) precipitation stable isotopes and d-excess exhibit pronounced seasonal variability, characterized by enrichment in summer and depletion in spring and autumn; (2) the Local Meteoric Water Line (LMWL) for the basin is defined as δ²H = 8.15δ¹⁸O + 38.71 (R² = 0.93), with both slope and intercept exceeding those of the Global Meteoric Water Line (GMWL); (3) precipitation isotopes show a discernible temperature effect but are jointly controlled by multiple moisture sources and meteorological factors; and (4) backward trajectory analysis combined with d-excess values reveals that precipitation moisture is primarily derived from westerly transport, while locally recycled moisture and continental air masses also exert significant influences. Overall, these findings reveal the multi-source driving mechanisms of the regional hydrological cycle and provide critical scientific support for understanding hydrological processes in alpine inland basins and their responses to future climate change, thereby contributing to the sustainable management of regional water resources. Full article

Alpine wetlands in the Qinghai Lake Basin, located on the northeastern Qinghai–Tibetan Plateau, are ecologically important but highly vulnerable to climate change and anthropogenic disturbance. Traditional field-based surveys are labor-intensive and spatially constrained, underscoring the need for automated remote sensing approaches for large-scale wetland mapping. In this study, an object-based image analysis (OBIA) framework was developed by integrating Sentinel-2 optical imagery with Sentinel-1 synthetic aperture radar (SAR) data to classify two representative plateau wetland types: marsh meadows and inland tidal flats. Seven categories of features were evaluated, including spectral features, vegetation indices, water indices, red-edge features, topographic variables, radar backscatter, and geometric-textural metrics. The Separability and Thresholds (SEaTH) algorithm was employed for feature selection and optimization prior to classification using a Random Forest model. The results indicate that the incorporating geometric and textural features significantly improved classification performance, achieving an overall accuracy (OA) of 82.53% and a Kappa coefficient of 0.74. Moreover, the SEaTH-based feature optimization scheme yielded the best performance, with an OA of 86.24% and a Kappa coefficient of 0.79. Compared with the full feature set, this approach improved producer’s accuracy by 3.96–6.11% and increased overall accuracy by 1.48%. The proposed framework provides an effective and computationally efficient approach for mapping ecologically fragile alpine wetlands and offers valuable support for wetland conservation in the Qinghai Lake Basin. Full article

Understanding the forage resources that sustain endangered herbivores under strong seasonal constraints is essential for effective habitat restoration. Przewalski’s gazelle (Procapra przewalskii), an endemic ungulate restricted to the Qinghai Lake Basin on the Qinghai–Tibet Plateau, persists in fragmented subpopulations facing pronounced seasonal bottlenecks in forage availability. Here, we investigated seasonal dietary strategies and forage selectivity across nine geographically isolated subpopulations by integrating fecal microhistological diet analysis with vegetation surveys and availability-corrected Jacobs’ electivity indices. Gazelle diets were compressed in early spring, dominated by graminoids (Poaceae and Cyperaceae), but expanded substantially during summer, with increased contributions from Fabaceae and Rosaceae and significantly higher richness and niche breadth. Electivity analyses revealed a hierarchical spectrum of preferences structured around core foundation taxa consistently selected across seasons, complemented by season-specific priority resources during spring bottlenecks and summer abundance. Basin-wide pairwise ranking further identified seasonal priority forage taxa with varying spatial consistency across subpopulations. These findings provide a seasonally explicit framework for identifying key forage targets and guiding evidence-based restoration and zoned management within Qinghai Lake National Park, offering transferable insights for conserving endangered plateau herbivores under fragmentation and strong seasonal resource limitation. Full article

Alluvial–proluvial parent-material soils are widely distributed in the Qinghai Lake Basin; however, their timing of development and associated climatic background remain poorly constrained. In this study, two representative alluvial–proluvial fan-covered soil profiles (QRZQ and YXC) from the Qinghai Lake Basin were investigated. Quartz optically stimulated luminescence (OSL) dating was combined with analyses of grain-size composition and soil organic carbon (SOC) to constrain the timing of soil development and its climatic background. The results show that the studied soil profiles are mainly characterized by Ah–As–C and Ah–A–C horizon configurations, with soil development spanning from 15.7 to 1.0 ka. The underlying alluvial–proluvial parent material of the QRZQ profile formed during the Last deglaciation, whereas the oldest OSL ages in the YXC profile occur within a weakly developed A horizon, indicating that this profile had already transitioned from a depositional environment to a pedogenic environment during the Last deglaciation. This contrast reflects staged differences between depositional and pedogenic processes within alluvial–proluvial settings. The soils were formed through upbuilding pedogenesis, in which sediment accumulation and top-down pedogenic modification proceeded concurrently. Grain-size composition and SOC characteristics further indicate that the depositional environment of the YXC profile was relatively stable. Integrating the obtained chronological results with regional climatic changes suggests that climate variability in the Qinghai Lake Basin exerted a primary control on the transformation between sedimentary processes and soil development. In particular, the Late Holocene (0–4 ka), characterized by a generally cold–dry climate accompanied by pronounced humidity fluctuations, represents an important pedogenic stage for alluvial–proluvial parent-material soils in the Qinghai Lake Basin. This study provides a robust chronological framework for further investigating the mechanisms of soil development in alluvial–proluvial environments from a climatic perspective. Full article

The mechanisms driving the uplift and outward expansion of the Tibetan Plateau remain debated. The Qinghai Lake region at the plateau front, characterized by pronounced basin–range differential uplift, provides a key natural laboratory. Here, we first predict vertical deformation induced by the horizontal GPS velocity field and then construct a three-dimensional (3D) viscoelastic finite-element model to evaluate how lithospheric rheology shapes present-day 3D deformation. Horizontal GPS velocities predict higher uplift in the Songpan–Ganzi Terrane and the Qilian Orogen and lower values in the intervening basins, capturing the first-order basin–range pattern; the predicted uplift in the Qilian Orogen is ~1.0 mm/yr and agrees with observations, indicating that its dominant mechanism is crustal shortening and thickening. However, horizontal constraints alone leave vertical-velocity residuals of ~0.8–1.5 mm/yr in several localized areas, including the West Qinling Orogen, the southern Elashan region, the Qinghai–Nanshan region, and areas south of the Lenglongling Fault. Lateral rheological heterogeneity in the mid–lower crust, acting under mantle-flow drag, can better account for these residuals and more accurately reproduce the present 3D velocity field in the basin–range system. We further propose northeastward mid–lower crustal flow along a weak channel; when the flow is impeded by rigid domains (e.g., the Gonghe Basin and the Qinghai Lake Basin), it promotes material accumulation and localized deformation. These results support a hybrid mechanism that combines crustal shortening and mid–lower crustal flow for the Qinghai Lake basin–range system. Full article

Amid accelerating global urbanization, the Qinghai–Tibet Plateau, as a repository of multi-ethnic architectural heritage, plays a crucial role in preserving plateau cultural diversity and sustaining harmonious human–environment relationships. A critical research gap persists, however, in the systematic, comparable, and quantitative assessment of urban architectural character across plateau towns, particularly in high-altitude, ecologically sensitive, and multi-ethnic regions such as Haixi Mongol and Tibetan Autonomous Prefecture. This study takes the Haixi Mongol and Tibetan Autonomous Prefecture as a case to address the specific paradox between the homogenization of urban architectural styles and the erosion of cultural authenticity in plateau towns. We develop and apply an innovative three-dimensional evaluation model—encompassing natural substrate, built environment, and cultural context—to 22 towns. For the first time in research on this region, a chained methodological approach integrating descriptive statistics, principal component analysis (PCA), and cluster analysis is employed to systematically examine the spatial differentiation of architectural character. The analysis reveals three key findings. First, it delineates a regional composite landscape characterized by mountain-basin enclosures, seasonal arid rivers and lakes, small-scale towns with expansive layouts, and multi-ethnic cultural fusion. Second, it identifies a clear ternary differentiation in urban style dominance: nine towns are nature-dominated, nine are human-made (built environment) dominated, and only four are culture-dominated, quantitatively highlighting a significant weakness in the cultural dimension. Third, cluster analysis objectively classifies the towns into eight distinct character groups—for instance, Category I towns exhibit strong architectural regionalism and traditional continuity, whereas Category V towns integrate modern relics with adjacent mountain-water features. Methodologically, this study contributes by providing a replicable, chained quantitative framework that addresses a critical gap in comparative urban studies of high-altitude, underdeveloped regions. Empirically, it reveals the specific “nature > human-made > culture” dominance pattern in Haixi and offers a scientific foundation for formulating differentiated conservation and development strategies tailored to distinct town types in the ecologically fragile areas of western China. Full article

The Mahai Basin (MHB), situated in the northern Qaidam Basin on the Qinghai–Tibetan Plateau, hosts significant Quaternary potash resources. Nevertheless, the sources and evolutionary pathways of potash-forming fluids remain controversial. In this study, a comprehensive multi-isotope dataset and online-first publications spanning the period from 2015 to 2025 were compiled to constrain the end-member characteristics and evolution of brines in the MHB. δD-δ¹⁸O indicates that the initial fluids were derived mainly from Qilian Mountains precipitation and snowmelt, delivered via surface runoff and concentrated through prolonged evaporation under arid, semi-closed conditions, forming a river-lake-brine evolution sequence. δ⁷Li (+7‰ to +40‰) systematically increases with salinity and K content, reflecting long-term low-temperature water–rock interactions and selective ⁶Li adsorption by secondary clays, while deep Ca-Cl brines represent highly evolved endmembers. Elevated ⁸⁷Sr/⁸⁶Sr ratios (0.7113–0.7122) confirm silicate weathering contributions, with intercrystalline brines acting as key intermediate end members. B, S, and Cl isotopes further highlight deep fluid ascent along faults and anticlines, driving K co-enrichment, while sandy–gravel brines inherit highly evolved paleo-lake signatures. These multi-isotope constraints define an integrated evolutionary model involving surface runoff recharge, evaporation-driven concentration with water–rock interaction, deep fluid mixing, lateral migration, and final potash precipitation. Full article

As a vital ecological security barrier and climate regulator in northwestern China, the spatial patterns and evolving formation mechanisms of ecosystem services within the Qinghai Lake basin hold significant strategic value for ecological conservation and national park development in the region. This study selected land use data during 2000–2020, integrating the equivalent factor method, spatial correlation analysis, and the geodetector approach to systematically investigate the spatial heterogeneity characteristics of ESV in the Qinghai Lake basin and its corresponding driving mechanisms. The results indicate the following: (1) During the period 2000–2020, grassland consistently constituted the primary land cover category within the Qinghai Lake Basin, accounting for over 60% of the total area; water bodies (16.67%) and unused land (16.56%) represented the secondary land use categories. Over this twenty-year period, the total ESV exhibited a slight increasing trend, rising from USD 30.30 × 10⁸ to USD 30.75 × 10⁸, representing a growth of 0.31%. Regulating services constituted the primary component of ESV. The highest contribution to ESV originated from water bodies, with grassland ranking second. (2) ESV displayed a spatial arrangement marked by “high values in the lake center and low values in the surrounding areas” and “higher values in the southeast and lower values in the northwest.” Its spatial correlation exhibits a pronounced positive relationship. The number of units classified as high-high clusters (primarily water bodies at low elevations) and low-low clusters (mainly grasslands and unused land at high elevations) both increased over the study period, indicating a continuous intensification of ESV spatial agglomeration. (3) Results from the geographical detector reveal that both natural and anthropogenic factors collectively drive the spatial variation in ESV, with natural factors exhibiting stronger explanatory capacity. Among these, elevation and temperature are identified as the dominant drivers of ESV spatiotemporal differentiation. The combined effect of two interacting factors surpasses the influence exerted by any single factor in isolation. This research clarifies that the spatial distribution of ESV in the Qinghai Lake Basin, which features “high values in the lake center and low values in the surrounding areas” as well as “higher values in the southeast and lower values in the northwest,” is jointly shaped by the combined control of vertical zonality governed by topographic and climatic factors and the spatial differentiation of human activities. In low-altitude lakeshore zones, ESV rose as a consequence of water body expansion and the enforcement of ecological conservation measures, leading to the emergence of high-value clusters. In contrast, ESV improvement in high-elevation regions remained limited, constrained by fragile natural conditions and minimal human intervention. The insights derived from this research offer a scientific foundation for refining the “one core, four zones, one ring, multiple points” functional zoning framework of the Qinghai Lake National Park, as well as for developing tailored management approaches suited to distinct elevation-based regions. Full article

Geothermal water from different orogenic belts, surrounding rock weathering, and salt-forming elements sourced from surface basins jointly shape the hydrochemical characteristics, evaporation evolution sequences, and prospects for subsequent development and utilization of terminal salt lakes. In view of the lack of research on the metallogenic model of a single salt lake in the Qinghai–Tibet Plateau, this paper selects the Nie’er Co Salt Lake, a terminal lake in Northern Tibet, and systematically samples the water, river sediments, and surrounding rocks of the upper reaches of the recharge river, the Xiangqu. The Piper, Gibbs, and Durov, combined with ion ratio analysis, correlation analysis, PHREEQC, quantitative calculations of surrounding rock weathering and tributary contributions to salt-forming elements, were applied to comprehensively characterize groundwater hydrochemistry and surface water system runoff, and clarify the evolution of salt-forming elements in the terminal lake. The driving mechanism of surface runoff and surrounding rock weathering on ion enrichment in the terminal lake was revealed. The Nie’er Co Salt Lake in Tibet evolves from Ca/Na-HCO₃ springs to Na-SO₄²⁻ via dilution, rock leaching, and evaporation. Tributaries contribute 39.6%, 8.2%, and 52.3% of the major ions. Silicate weathering dominates (75%–80%), shifting to evaporite–carbonate inputs. The overall performance is dominated by silicate weathering. The contribution rate of silicate weathering decreases, and the trend of evaporite–carbonate weathering increases. The evolution of surface runoff can be divided into a tributary ion concentration growth section, a mixed ring section (evaporation concentration–TDS increase), and a terminal lake sedimentary section (enrichment evaporation to form the salt lake), revealing that multi-branch superposition and surrounding rock weathering synergistically affect the formation of salt lake hydro-chemical types. Full article

Ancient walled cities represent key material evidence for early state formation and human–environment interaction on the northeastern Tibetan Plateau. However, traditional field surveys are often constrained by the vastness and complexity of the plateau environment. This study proposes an improved deep learning framework, AC-YOLOv11, to achieve automated detection of ancient city remains in the Qinghai Lake Basin using 0.8 m GF-2 satellite imagery. By integrating a dual-path attention residual network (AC-SENet) with multi-scale feature fusion, the model enhances sensitivity to faint geomorphic and structural features under conditions of erosion, vegetation cover, and modern disturbance. Training on the newly constructed Qinghai Lake Ancient City Dataset (QHACD) yielded a mean average precision (mAP@0.5) of 82.3% and F1-score of 94.2%. Model application across 7000 km² identified 309 potential sites, of which 74 were verified as highly probable ancient cities, and field investigations confirmed 3 new sites with typical rammed-earth characteristics. Spatial analysis combining digital elevation models and hydrological data shows that 75.7% of all ancient cities are located within 10 km of major rivers or the lake shoreline, primarily between 3500 and 4000 m a.s.l. These results reveal a clear coupling between settlement distribution and environmental constraints in the high-altitude arid zone. The AC-YOLOv11 model demonstrates strong potential for large-scale archaeological prospection and offers a methodological reference for automated heritage mapping on the Qinghai–Tibet Plateau. Full article