Search Results (508)

Lake eutrophication and water quality deterioration are increasingly jeopardizing both ecological integrity and human health. As a typical eutrophic shallow lake on plateaus, Yilong Lake currently faces the primary issue of excessive COD_Cr levels. Through systematic sampling and analysis, as well as static release of COD_Cr from sediment experiments, we have categorized the release process of COD_Cr and identified factors that are highly correlated with COD by using RDA and random forest analyses. The aim is to investigate the release patterns of COD_Cr in Yilong Lake, explore the primary factors influencing COD_Cr, and understand the causes of water quality pollution in the lake. The principal findings of this study are as follows: the static release of COD_Cr from sediment experiments was conducted to estimate the COD_Cr release flux from the sediments of Yilong Lake using Fick’s first law, and the release process was divided into three stages: initial release, intermediate adsorption, and late equilibrium. The RDA results indicate that SedpH and SedTP are positively correlated with both COD_Cr and COD_Mn; COD_Mn is statistically most closely related to SedAP; and COD_Cr exhibits the strongest synergy with SedpH. The random forest model output demonstrates that BOD₅ is the factor most highly correlated with COD_Cr, followed by SedAP. The results of the submerged plant humic degradation experiments show that the organic matter released during the humic degradation process of submerged plants has a significant impact on COD_Cr in water bodies, and that algal activity also affects COD_Cr. These findings provide a scientific basis for environmental protection and pollution control in Yilong Lake and similar lakes. Full article

The increasing frequency and magnitude of glacial lake outburst floods pose a severe threat to the safety of downstream communities. However, Interference from glacier shadows and mountain shading reduces the accuracy of remote sensing-based glacial lake detection. We propose a two-level nested framework that integrates global spatiotemporal aggregation and local adaptive enhancement. At the global level, the 80th temporal percentile (P80) of multi-temporal AWEI imagery is used to construct a stable water-background composite and suppress short-term seasonal noise. Multi-source physical constraints, including the Normalized Difference Snow Index (NDSI), a DEM-derived slope constraint (slope < 10°), and red-band reflectance thresholds (0.3 < BandRed < 1.6), are applied to suppress interference from land, terrain shadows, snow, and glaciers. At the local scale, an adaptive dynamic segmentation strategy is proposed by establishing an equal-area buffer for each individual lake, where the temporal occurrence frequency of MNDWI is computed to build a stable water probability composite, and the Otsu algorithm is applied to independently derive lake-specific optimal thresholds. Using Landsat imagery and meteorological data from 1990 to 2025, we quantified the spatiotemporal dynamics of typical glacial lakes in the central Himalayas, and explored the driving mechanisms of climate factors on lake area changes. Over the past 35 years, the number and area of lakes have exhibited a pronounced expansion trend under a climatic regime characterized by rising temperatures, increasing precipitation, and decreasing relative humidity. During 1990–2020, lake area variations were primarily governed by strong interactions between temperature and wind speed. Summer variability exerted a more pronounced impact than winter variability. The proposed framework provides an effective approach for glacial lake extraction in the study area and may provide useful technical support for long-term monitoring of alpine lakes. Full article

The Qinghai Lake Basin (QLB) serves as a crucial ecological barrier on the Qinghai–Tibet Plateau, making high-precision mapping of land use/land cover (LULC) essential for eco-hydrological research within the basin. In this study, multitemporal Sentinel-1 radar and Sentinel-2 optical imagery from 2024, DEM-derived terrain information, and features derived from these sources were used to produce a 10-m resolution LULC map for the QLB using a support vector machine classifier. The Level-1 and Level-2 LULC datasets of QLB (QLBLC-10) achieved sample-based apparent overall accuracies (OAs) of 91.95% and 91.24%, respectively, and kappa coefficients of 0.90 for both. In contrast, the area-weighted apparent overall accuracy (OA_w) decreased to 81.50 ± 2.09% (95% confidence interval), indicating that class-area imbalance and small-area classes affect map-level performance. The ablation study confirms the contribution of multisource temporal information and terrain constraints to alpine LULC classification. The OA increased from 77.07% with single-temporal Sentinel-2 to 91.24% when multitemporal Sentinel-1/2 data and DEM-derived features were added, while the kappa coefficient increased from 0.75 to 0.90. The comparison with existing products shows that QLBLC-10 outperforms existing global and regional LULC datasets in representing alpine land cover patterns in the QLB. The LULC system proposed in this study is tailored to the QLB, and the presented LULC classification strategy enhances discrimination among major alpine vegetation types, including temperate and alpine steppes, alpine meadows, and alpine shrublands. It provides an up-to-date (2024) LULC dataset for ecosystem monitoring and land management across the QLB. Full article

High-altitude rock slides frequently occur in the high-mountain canyon regions of the eastern Tibetan Plateau, posing significant disaster risks. The Baige landslide catastrophically failed in October 2018, blocking the Jinsha River and forming a major landslide-dammed lake. However, quantitative understanding of the spatiotemporal evolution and environmental control mechanisms remains insufficient, particularly regarding stage-dependent driving mechanisms. This study investigates the Baige landslide using mall Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR), Seasonal-Trend decomposition based on Loess (STL) time-series decomposition, Principal Component Analysis–Independent Component Analysis (PCA-ICA) signal analysis, and slope-unit spatial statistics. Results indicate that: (1) deformation exhibited three stages separated by October 2018: slow pre-slide deformation, post-slide residual creep, and long-term sustained acceleration; (2) instability caused systematic restructuring of the deformation field, with valid pixels decreasing from 2766 to 560, deformation changing from slight positive line-of-sight (LOS) displacement to pronounced negative LOS displacement, and global standard deviation increasing from 21.40 mm to 40.55 mm, with stronger disturbances in the steep front zone; and (3) the driving mechanism shifted from short-term multi-factor control to a temperature-dominated long-term environmental control regime after failure, while gravity-driven creep and post-failure structural adjustment remained important background controls. Slope fragmentation and structural reorganization likely contributed to this transition. Full article

This study investigated the contamination characteristics, sources, and ecological risks of organochlorine pesticides (OCPs) in surface sediments from three plateau lakes in southwestern China (Qilu Lake, Dianchi Lake, and Yangzonghai Lake). Significant differences in OCP pollution levels were observed among the three lakes. Hexachlorocyclohexanes (HCHs) were identified as the dominant contaminants, reflecting historical technical HCH input and subsequent long-term aging, whereas dichlorodiphenyltrichloroethanes (DDTs) exhibited generally low concentrations and originated primarily from historical technical use, with predominantly aerobic degradation. Principal component analysis (PCA) revealed that agricultural non-point source pollution was the main contributor to OCP residues. Ecological risk assessment demonstrated that most OCPs posed low or negligible risk; however, γ-HCH (lindane) ubiquitously presented moderate risk across all lakes, with one site exceeding the high-risk threshold. Endrin derivatives and methoxychlor further elevated combined risks at specific sites. Notably, the unique hydrological characteristics of plateau lakes may enhance OCP retention and accumulation in sediments. These findings provide a scientific basis for ecological risk management and pollution control in plateau lakes. Full article

The proglacial lakes of the Qinghai-Xizang Plateau serve as natural laboratories for studying microbial adaptation to extreme environments. However, research on the composition and functional characteristics of microorganisms in these settings remains limited. In this study, three typical high-altitude proglacial lakes in southern Xizang (Qudengnima proglacial lake, Gangbugou proglacial lake, and Qiangyong proglacial lake) were selected as research subjects. Bacterial community structure, diversity in the water and sediment of these lakes were analyzed using 16S rRNA sequencing. The results showed that Pseudomonadota, Actinomycetota, and Bacteroidota were highly abundant across all samples. The relative abundances of Cyanobacteriota and Acidobacteriota, however, exhibited distinct habitat preferences: Cyanobacteriota was enriched in the water, whereas Acidobacteriota was predominantly found in sediment. Alpha diversity analysis showed that both species diversity and richness in Qiangyong proglacial lake were significantly higher than those in the other proglacial lakes, and within the same lake, both diversity and richness in sediment were higher than in the water. Beta diversity analysis indicated that the bacterial community structures in sediment were similar across different proglacial lakes, whereas those in water varied considerably among the lakes. LEfSe analysis identified 94 biomarkers that exhibited significant differences among the different proglacial lake environments at an LDA score threshold of 4. Redundancy analysis revealed that pH, total phosphorus, and ammonium nitrogen were the physicochemical factors significantly influencing the bacterial community structure in the water, while total carbon was the key driver for the community in sediments. This study preliminarily characterized the bacterial community structure and diversity in high-altitude proglacial lakes on the southern Qinghai-Xizang Plateau, which lays a theoretical foundation for exploiting microbial resources and understanding their ecological functions in such extreme environments. Full article

Excessive fluoride intake from drinking water remains a public health concern in geogenic high-fluoride regions, yet direct evidence linking environmental fluoride levels to internal exposure in remote high-altitude areas is limited. This study integrated environmental monitoring with human biomonitoring to assess fluoride exposure and health risks in the Taruo Lake region of the Tibetan Plateau. Surface water (n = 45 for Taruo Lake; n = 8 for its tributaries) and groundwater samples (n = 4) were collected and analyzed for fluoride concentrations, and blood ionic fluoride (BIF) levels were measured in 122 local residents (47 adults, 75 children). The results showed that fluoride concentrations in most surface water tributaries of Taruo Lake and groundwater sources were below China’s drinking water standard, whereas those in Taruo Lake exceeded this limit (routine monitoring mean 2.54 mg/L; multi-site mean 2.79 mg/L). BIF levels were significantly higher in adults (0.126 ± 0.041 mg/L) than in children (0.075 ± 0.032 mg/L) and showed a positive correlation with age (r = 0.533, p < 0.001). Notably, 23.4% of adults and 1.3% of children exceeded 0.15 mg/L, an empirical threshold typical for healthy populations in non-endemic areas. Based on the hazard quotient (HQ) model recommended by the US EPA, most drinking water sources posed acceptable non-carcinogenic risks (HQ < 1). In contrast, Taruo Lake water presented an elevated risk (HQ > 1) in 2024 primarily due to the regional geological background, and although not used for daily drinking, this finding offers an indicative reference for local water management and risk prevention. This preliminary monitoring and biomonitoring assessment provides baseline data for future studies and underscores the necessity of continuous surveillance and evaluation of total dietary fluoride intake to protect the health of this vulnerable high-altitude population. Full article

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

Small and medium-sized (SMS) lakes in cold–arid regions are highly sensitive to climate change and play critical roles in regional hydrological and ecological processes. However, their long-term dynamic evolution along aridity–humidity gradients remains insufficiently understood. This study aims to reveal the spatiotemporal variations in SMS lakes on the Inner Mongolia Plateau and clarify their climatic driving mechanisms. Based on Landsat imagery and meteorological data (1984–2021) on the Google Earth Engine (GEE) platform, this study quantified the spatiotemporal variations in SMS lakes and adopted an ecological–geographical zoning framework to characterize lake responses across aridity–humidity gradients. Results indicate that, from 1984 to 2021, the total area of SMS lakes showed an insignificant linear trend but a net increase of 117% (396.50–860.33 km²), while the lake number increased by 155%, with 59 new lakes. The dynamics followed four stages: expansion (1984–1993), fluctuation (1994–2002), low-level stability (2003–2011), and recovery (2012–2021). Notably, recovery levels remained below the pre-2003 peak, with 2003 identified as a critical turning point. Lake numbers responded to climatic stress earlier than area changes. Spatially, lake variations in arid regions were primarily controlled by energy-related factors (e.g., temperature and potential evapotranspiration), while lake changes in semi-humid regions were dominated by precipitation-regulated water availability. Semi-arid regions presented transitional characteristics constrained by both energy and water factors. Although extreme weather events did not dominate long-term lake evolution, they significantly exacerbated short-term lake fluctuations. Overall, the controlling mechanism of SMS lakes shifted from energy limitation to water regulation under ongoing climate warming, highlighting pronounced regional differences in climate–lake interactions. Full article

Accurate lake boundary extraction from optical remote sensing imagery remains challenging in high-altitude regions such as the Tibetan Plateau due to ice cover, snow, shadows, and spectrally similar backgrounds. Although recent deep learning models achieve strong region-overlap performance, they often fail to ensure stable shoreline localization. To address this issue, we propose a Global–Local Residual Refinement Network (GLR-Net) for boundary-aware lake extraction from remote sensing imagery. The proposed framework first captures large-scale semantic context through a global branch and subsequently performs patch-level residual refinement to improve local shoreline geometry. A global-to-local guidance mechanism is further introduced to incorporate structural priors into local refinement. Experiments on a manually annotated Tibetan Plateau lake dataset demonstrate that the proposed method achieves competitive region-level segmentation performance while improving geometric shoreline accuracy. Compared with representative semantic segmentation baselines, including U-Net, SegFormer-B0, SegFormer-B4, and OCRNet, the proposed method achieves the highest Boundary F1 score of 0.811 under a 3-pixel tolerance and the lowest mean BDE of 13.19 pixels. The results indicate that conventional overlap-based metrics alone are insufficient for evaluating shoreline delineation quality in complex alpine environments. Full article

Lake depth is a fundamental parameter for estimating lake storage, analyzing basin morphology, and understanding the evolution of plateau lakes. Compared with typical shallow lakes, Tibetan Plateau lakes are characterized by high elevation, strong radiation, pronounced inter-lake and inter-annual variability, and in some cases considerable basin depth, which limits the accuracy, stability, and generalization ability of existing bathymetric inversion methods based on single-source optical imagery. Meanwhile, although ICESat-2 can provide sparse but high-precision along-track bathymetric constraints, a unified framework suitable for plateau-lake scenarios is still lacking. To address this issue, this study proposes TabKAN, a bathymetric inversion framework for Tibetan Plateau lakes under joint constraints from hyperspectral imagery and ICESat-2 data. TabKAN constructs tabular input features from hyperspectral reflectance, water indices, imaging geometry, and environmental variables; employs TabNet for feature selection and encoding; and introduces a KAN regression head to enhance nonlinear bathymetric mapping. A joint-supervision and bias-correction mechanism is further designed to incorporate ICESat-2 samples, thereby improving model robustness across lakes and acquisition dates. To enhance the temporal coverage of training samples, multi-year sample expansion based on stereo-mapping data is introduced, and a stripe-aware self-supervised learning strategy is developed for hyperspectral image restoration and pretraining. Experiments on five Tibetan Plateau lakes, including Anglaren Co, Caiduo Chaka, Cuoe, Geren Co, and Qixiang Co, show that the proposed method outperforms benchmark methods in both overall accuracy and depth-stratified evaluation, while providing more stable recovery of basin morphology and depth gradients. These results demonstrate that combining hyperspectral information, ICESat-2 laser constraints, and stripe-aware pretraining can effectively improve the accuracy and robustness of bathymetric inversion for Tibetan Plateau lakes and provide a new technical route for storage estimation and change monitoring of cold inland lakes. Full article

Revegetation serves as a critical ecological safeguard, while these interventions have added complexity to the evapotranspiration processes and water balance. Dalinor Lake basin (DLB), located in the southeast of Inner Mongolia Plateau, serves as a vital habitat for migratory birds and plays an important role in the ecological security of northern China. To enhance biodiversity, numerous ecological restoration projects have been carried out in this area in recent years. Dalinor Lake, a large inland lake within the basin, has experienced persistent shrinkage. Although existing studies have explored its driving factors, the potential influence of revegetation activities on lake shrinkage remains unclear. In this study, we used remote sensing imagery, combined with supervised classification and visual interpretation methods, to extract changes in the surface areas of lakes within the DLB (i.e., Dalinor Lake and Ganggeng Lake), and analyzed the effects of total terrestrial evapotranspiration (ET_t), precipitation (PPT), runoff, soil moisture content, and the vapor pressure deficit on these changes. Results showed that the Dalinor Lake’s area decreased by 18.68% from 2000 to 2020, and was mainly influenced by ET_t, with the Normalized Difference Vegetation Index (NDVI) contributing the most to ET_t (54.02%). In contrast, Ganggeng Lake expanded by 5.68% and was strongly driven by PPT. Compared with Ganggeng Lake, there have been more revegetation activities around Dalinor Lake, resulting in significant increases in NDVI and ET_t, together with widespread declines in soil moisture in its surrounding areas, suggesting that revegetation exerted non-negligible water pressure on Dalinor Lake. These findings can provide valuable information for policymakers to balance large-scale ecological restoration with sustainable water management in semi-arid regions. Full article

To elucidate the solute sources, migration and enrichment mechanisms of water bodies in the endorheic lake region of the Qiangtang Plateau on the Tibetan Plateau and clarify the hydrogeochemical cycling patterns in alpine arid environments, this study focuses on two core scientific objectives: quantitative identification of the multi-source contributions of aquatic solutes, and revelation of the key processes governing the enrichment of strategic elements including lithium (Li) and boron (B). To achieve these goals, we conducted systematic hydrogeological field investigations and collected 28 multi-type water samples, covering springs, rivers, thermal springs, freshwater lakes, salt lake brines, atmospheric precipitation, and glacial meltwater. The physicochemical properties, major ions, and trace elements of all samples were comprehensively analyzed. On this basis, the hydrogeochemical characteristics, evolutionary processes, and solute origins of regional waters were systematically explored. Combined with PHREEQC numerical simulation, principal component analysis (PCA), and Pearson correlation analysis, the dominant controlling factors of water geochemistry were quantified, and a conceptual hydrogeochemical evolution model was established. The results reveal a clear hydrogeochemical evolutionary gradient across the study area: water bodies evolve from low-salinity HCO₃-Ca recharge end-members and transitional HCO₃·SO₄-Ca(Mg) type water to highly mineralized Cl-Na (SO₄·Cl-Na) salt lake brines, accompanied by synchronous enrichment of Li, B, arsenic (As), and other characteristic elements. Solute accumulation in regional waters is governed by the ternary coupling effects of evaporative concentration, rock weathering and leaching, and deep geothermal fluid input, while cation exchange and mineral dissolution–precipitation reactions further modulate ionic composition and ratios. Elements including As, Li, B, and chloride (Cl⁻) exhibit conservative migration behaviors in non-hydrothermal waters, whereas thermal springs possess unique geochemical signatures driven by deep fluid recharge. PCA results indicate that evaporative concentration serves as the primary controlling factor with a contribution rate of 55.39%; rock weathering provides the basic solute load (17.09%); and the coupled processes of deep fluid mixing and carbonate precipitation regulate elemental fractionation (14.21%). These findings systematically clarify the hydrogeochemical evolution laws and multi-source coupling mechanisms of inland lake waters in the Qiangtang Plateau. Furthermore, this study establishes a conceptual framework of “multi-source recharge–water–rock interaction–evaporative concentration”, advances the understanding of alpine hydrological cycling under climate change, and provides a solid scientific foundation for hydrological cycle research and green exploration of strategic mineral resources in endorheic salt lake regions. 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