Search Results (23)

Climate change intensifies hydrological cycles, leading to an increased variability in terrestrial water storage anomalies (TWSAs) and a heightened drought risk. Understanding the spatiotemporal dynamics of TWSAs and their driving factors is crucial for sustainable water management. While previous studies have primarily attributed TWSAs to regional factors, this study employs wavelet coherence, partial correlation analysis, and multiple linear regression to comprehensively analyze TWSA dynamics and their drivers in the Hengduan Mountains (HDM) region from 2003 to 2022, incorporating both regional and global influences. Additionally, dry–wet variations were quantified using the GRACE-based Drought Severity Index (GRACE-DSI). Key findings include the following: The annual mean TWSA showed a non-significant decreasing trend (−2.83 mm/y, p > 0.05), accompanied by increased interannual variability. Notably, approximately 36.22% of the pixels in the western HDM region exhibited a significantly decreasing trend. The Nujiang River Basin (NRB) (−17.17 mm/y, p < 0.01) and the Lancang (−17.17 mm/y, p < 0.01) River Basin experienced the most pronounced declines. Regional factors—particularly precipitation (PRE)—drove TWSA in 59% of the HDM region, followed by potential evapotranspiration (PET, 28%) and vegetation dynamics (13%). Among global factors, the North Atlantic Oscillation showed a weak correlation with TWSAs (r = −0.19), indirectly affecting it via winter PET (r = −0.56, p < 0.05). The decline in TWSAs corresponds to an elevated drought risk, notably in the NRB, which recorded the largest GRACE-DSI decline (slope = −0.011, p < 0.05). This study links TWSAs to climate drivers and drought risk, offering a framework for improving water resource management and drought preparedness in climate-sensitive mountain regions. Full article

It is crucial to simulate land use change and assess the corresponding impact on ecosystem services to develop informed land management policies and conservation strategies. To comprehensively simulate the patterns of land use change under different management policies and evaluate the corresponding ecological service values (ESV), a method for coupling the Generalized Multi-Objective Programming (GMOP) model and Patch-generating Land Use Simulation (PLUS) model is proposed in this study. First, the GMOP model is used to obtain optimized land use solutions under different scenarios. Then, the PLUS model is used to analyze the mechanism driving land expansion, explore land conversion patterns, and, ultimately, achieve spatial expression of land use quantity changes. The uncertain parameters in the coupled model are processed by intuitionistic fuzzy numbers. The coupled model successfully integrates the outstanding spatiotemporal dynamic simulation capability of the PLUS model and the multiobjective optimization advantages of the GMOP model, effectively overcoming the limitations of applying a single model in land use analysis. Finally, four different scenarios are established for land use change, namely, business as usual (BAU), economic efficiency priority (RED), ecological protection priority (ELP), and coordinated economic and ecological development (EEB), to predict land use change trends and ecological service values. A case study of the Ningxia Hui Autonomous Region demonstrates that the area of agricultural land exhibits a stable growth trend in the four different scenarios, with the majority of the expansion occurring through the conversion of grassland. Concurrently, the rate of expansion of construction land is highest in the BAU scenario at 31.72%, compared with the area in 2020. This is notably higher than the rates observed in the RED (10.10%) and EEB (9.47%) cases. With the expansion of construction land, the ESV decreased by 3.485 billion, 1.514 billion, and 1.658 billion yuan in the BAU, RED, and ELP scenarios, representing 41.72%, 24.96%, and 34.05% decreases in ESV, respectively. The proposed integrated methodology accounts for various spatial constraints and land conversion behaviors, thereby ensuring a true and accurate reflection of land use dynamics. This methodology supports the quantification of ESV under different land management strategies, thereby providing policymakers with effective support for data-driven sustainable land use planning and conservation. Full article

The dynamic alterations in intestinal microbiota can provide insights into the adaptive relationships between these microorganisms and their hosts in response to environmental changes. Schizothorax nukiangensis is widely distributed throughout the Nujiang River and exhibits numerous unique adaptations. In this study, we collected samples of S. nukiangensis across different seasons and regions within the Nujiang River to comprehensively elucidate the diversity and composition of its intestinal microbiota using metagenomic technology. The results indicated that Firmicutes and Proteobacteria predominated at the phylum level, while Priestia, Bacillus, and Aeromonas were the most abundant genera identified. Notably, the relative abundance of these microorganisms varied significantly across different seasons and regions. From autumn through spring and into summer, the predominant microorganisms shifted from Firmicutes to Proteobacteria. Biomarker analysis revealed that Firmicutes (including the class bacilli and the genera Priestia and Bacillus) exhibited a higher relative abundance within the upstream group, where categories related to amino acid metabolism and carbohydrate metabolism were significantly enriched. Conversely, Proteobacteria (including several potential pathogens, such as Saezia, Pantoea, Lelliotia, and Aeromonas genera) showed an increased relative abundance within downstream groups, where disease-related categories exhibited significant enrichment. Our findings significantly enhance our understanding of how S. nukiangensis adapts to its environment, providing valuable data support for the conservation of S. nukiangensis and for ecological security assessment of the Nujiang River. Full article

Yunnan Province, as a critical ecological security barrier in China, has long been highly susceptible to drought events. Characterizing the spatiotemporal distributions of drought and identifying its driving factors is crucial. Due to the complexity of drought occurrence, linear correlation analysis alone is insufficient to quantify drought drivers and their interactions. This study used the Standardized Precipitation Evapotranspiration Index (SPEI) as a drought indicator to analyze the spatiotemporal trends of drought across Yunnan and its six major river basins. The geographic detector model (GDM) and random forest (RF) were utilized to quantify the impacts of meteorological, topographical, soil, and human activities on drought, as well as the interactions among these factors. The results showed that 63.61% of the study area exhibits a significant drying trend (p-value < 0.05), with the Jinsha River Basin (JSRB) experiencing the highest frequency of extreme drought events. Precipitation (PRE), temperature, potential evapotranspiration (PET), vapor pressure deficit (VPD), and relative humidity (RH) were identified as the primary controlling factors of drought, with factor interactions displaying nonlinear enhancement effects. PRE plays a dominant role in driving drought across Yunnan, whereas elevation primarily influenced drought severity in the JSRB, Lancang River Basin (LCRB), and Nujiang River Basin (NJRB). The RF-based SPEI prediction model demonstrated superior performance in simulating short-term drought (SPEI_1, R² > 0.931, RMSE < 0.279), particularly in the JSRB (R² = 0.947 RMSE = 0.228). These findings provide a scientific basis for regional water resource management applications and drought early warning systems, offering a robust framework for understanding and mitigating drought impacts in ecologically sensitive regions. Full article

The Qinghai–Tibet Plateau (QTP) is a unique ecological area that has faced issues like diminishing ecosystem stability and increasing pressures on resources and the environment. These issues have arisen as a result of the combined impact of global warming and human activities in recent times. The study of the growth and distribution patterns of schizothoracinae fishes can support guiding policy decisions about the conservation of aquatic species and ecological habitats in the QTP. The investigation on fish resources was carried out in the QTP section of the Nujiang River during the spring and autumn seasons of 2017, 2018, and 2019. A total of seven sampling sites were established based on variations in elevation. According to length–weight relationship (LWR) analysis, Schizothorax nukiangensis mainly displayed a negative allometric growth while Ptychobarbus kaznakovi and Schizopygopsis thermalis mainly showed near isometric growth or positive allometric growth in the QTP section of the Nujiang River. Due to temperature and food abundance, the three schizothoracinae fishes showed better growth performance in autumn than spring. Spatial heterogeneity exhibited a greater influence on the LWR of S. nukiangensis and P. kaznakovi than seasonal variation. In contrast, seasonal variation on S. thermalis showed greater influence than spatial heterogeneity. According to the linear mixed effect model (LMM), both spatial factors and seasons had influence on fish growth in the QTP. Schizothorax nukiangensis was identified as the predominant species from CWL to BS, spanning an altitude range of 1800 to 2700 m. Ptychobarbus kaznakovi was identified as the main species at LL, BB, and BR, occupying an altitude range of 2700 to 3800 m. Schizopygopsis thermalis is primarily distributed at altitudes beyond 4000 m and along the tributary river Yuqu. Principal coordinates analysis (PCOA) and nonmetric multidimensional scaling (NMDS) divided schizothoracinae fish populations into three clusters by spatial differences. Redundancy analysis (RDA) and Monte Carlo Permutation analysis revealed that habitat elevation and water temperature had a significant impact on schizothoracinae fish distribution. This article enhances our understanding of the distribution and environmental adaptation of indigenous fish in the Qinghai–Tibet Plateau. Full article

Estimating the spatiotemporal variations in natural grassland carrying capacity is crucial for maintaining the balance between grasslands and livestock. However, accurately assessing this capacity presents significant challenges due to the high costs of biomass measurement and the impact of human activities. In this study, we propose a novel method to estimate grassland carrying capacity based on potential net primary productivity (NPP), applied to the source area of the Nujiang River and Selinco Lake on the Tibetan Plateau. Initially, we utilize multisource remote sensing data—including soil, topography, and climate information—and employ the random forest regression algorithm to model potential NPP in areas where grazing is banned. The construction of the random forest model involves rigorous feature selection and hyperparameter optimization, enhancing the model’s accuracy. Next, we apply this trained model to areas with grazing, ensuring a more accurate estimation of grassland carrying capacity. Finally, we analyze the spatiotemporal variations in grassland carrying capacity. The main results showed that the model achieved a high level of precision, with a root mean square error (RMSE) of 4.89, indicating reliable predictions of grassland carrying capacity. From 2001 to 2020, the average carrying capacity was estimated at 9.44 SU/km², demonstrating a spatial distribution that decreases from southeast to northwest. A slight overall increase in carrying capacity was observed, with 65.7% of the area exhibiting an increasing trend, suggesting that climate change has a modest positive effect on the recovery of grassland carrying capacity. Most of the grassland carrying capacity is found in areas below 5000 m in altitude, with alpine meadows and alpine meadow steppes below 4750 m being particularly suitable for grazing. Given that the overall grassland carrying capacity remains low, it is crucial to strictly control local grazing intensity to mitigate the adverse impacts of human activities. This study provides a solid scientific foundation for developing targeted grassland management and protection policies. Full article

Geohazards that have developed in densely vegetated alpine gorges exhibit characteristics such as remote occurrence, high concealment, and cascading effects. Utilizing a single remote sensing datum for their identification has limitations, while utilizing multiple remote sensing data obtained based on different sensors can allow comprehensive and accurate identification of geohazards in such areas. This study takes the Latudi River valley, a tributary of the Nujiang River in the Hengduan Mountains, as the research area, and comprehensively uses three techniques of remote sensing: unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR), Small Baseline Subset interferometric synthetic aperture radar (SBAS-InSAR), and UAV optical remote sensing. These techniques are applied to comprehensively identify and analyze landslides, rockfalls, and debris flows in the valley. The results show that a total of 32 geohazards were identified, including 18 landslides, 8 rockfalls, and 6 debris flows. These hazards are distributed along the banks of the Latudi River, significantly influenced by rainfall and distribution of water systems, with deformation variables fluctuating with rainfall. The three types of geohazards cause cascading disasters, and exhibit different characteristics in the 0.5 m resolution hillshade map extracted from LiDAR data. UAV LiDAR has advantages in densely vegetated alpine gorges: after the selection of suitable filtering algorithms and parameters of the point cloud, it can obtain detailed terrain and geomorphological information on geohazards. The different remote sensing technologies used in this study can mutually confirm and complement each other, enhancing the capability to identify geohazards and their associated hazard cascades in densely vegetated alpine gorges, thereby providing valuable references for government departments in disaster prevention and reduction work. Full article

The Three Rivers Lateral Collision Zone (TRLCZ), situated at the southeastern margin of the Tibetan Plateau, is a crucial frontier where materials from the plateau flow southeastward. This study extensively investigated the hydrochemical characteristics and origin of helium and carbon isotopes in 73 thermal springs within the TRLCZ. The analysis revealed dominant processes, including carbonate and silicate interactions, resulting in elevated concentrations of HCO₃⁻ and Na⁺. The impact of Ca/Mg-rich minerals, particularly dolomite, influenced the cation composition. Additionally, gypsum dissolution, notably in the Lancangjiang Fault and Weixi–Qiaohou Fault, was highlighted through Ca/SO₄ ratios. The positive correlation between SO₄²⁻ and Cl⁻ indicated dilution by shallow cold water, explaining the lower SO₄²⁻ content in the Jingshajiang–Zhongdian Fault and Nujiang Fault compared to the Weixi–Qiaohou Fault and Lancangjiang Fault. The circulation depth of thermal spring water varied, with the northern Weixi–Qiaohou Fault exhibiting the shallowest circulation depth (~3 km), while the Jingshajiang–Zhongdian Fault and southern segments of the Nujiang Fault displayed deeper depths—ranging from 4 to 7 km. A positive correlation between the circulation depth and fault activity was also observed. The Rc/Ra ratios of free gas samples, predominantly indicating crustal origin, varied from 0.01 Ra to 0.53 Ra. Elevated Rc/Ra ratios in the research area suggested potential minor additions of mantle helium through faults and fractures. Crustal limestone was identified as the primary source of CO₂-rich samples, with δ¹³C_CO2 values ranging from −1.6‰ to −7.2‰, while trace amounts of mantle CO₂ were found. The spatial distribution of the H₂ concentration, CO₂ concentration, He concentration, and mantle He proportions in gases indicated that higher values of He concentration and mantle He% always occur near sampling points with deeper circulation depths. However, no similar correlation was observed for H₂ and CO₂. Most earthquakes of magnitude 5 or greater occurred near the regions with high values of mantle source He release, highlighting the critical role of mantle fluids in the occurrence of earthquakes in the region. In this study, a fluid circulation model was developed to describe the process of fluid (water and gas) circulation migration and earthquake generation in the TRLCZ. Full article

Carbon plays an important role in global climate change. The mechanisms of carbon sources and carbon sinks have also received wide attention from society, and the physical and chemical characteristics of riverine ions can reflect the chemical weathering of rocks and carbon sink capacity of river basins. Based on the data on river, rainwater, and rock samples from 2019, this study used various methods, such as ion ratio diagrams and ternary diagrams, to analyze the chemical characteristics of water; the chemical weathering and carbon sink effects of rocks were also calculated while assuming three scenarios based on the main sources of ions in the Naqu River. The results showed that for the whole catchment, the main ion sources in the river were: carbonate rock chemical weathering > silicate rock chemical weathering > evaporite dissolution > atmospheric precipitation input. According to the calculations, in the three scenarios, the carbonate weathering rates were 16.84, 11.32, and 14.08 t/km²/yr, and the carbon sink capacities were 66.47, 121.13, and 93.80 mol/km²/yr, respectively; the evaporite weathering rates were 2.20, 9.63, and 5.92 t/km²/yr, respectively. The silicate chemical weathering rate and carbon sink capacity did not change significantly in either scenario, with 6.82 t/km²/yr and 248.6 mol/km²/yr, respectively. This study quantified the ion sources in the Naqu River basin and accurately analyzed their chemical genesis, which helps in understanding the role of the rivers of the Qinghai–Tibet Plateau in the global carbon cycle and global climate change, in addition to providing a reference for the scientific development of the Nujing River. Full article

In the analysis of rock slope stability and rock mass hydraulics, the dominant partitioning of discontinuities of rock masses is a very important concept, and it is still a key for establishing the three-dimensional (3-D) network model of random discontinuities. The traditional graphical analysis method is inadequate and greatly influenced by subjective experience. A new method using density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed for the dominant partitioning of discontinuities of rock mass. In the proposed method, we do not need to determine the centers of every cluster before clustering, and the acnodes or outliers can be eliminated effectively after clustering. Firstly, the spatial coordinate transformation of the discontinuity occurrence is carried out and the objective function is established by using the sine value of the angle of the unit normal vector as the similarity measure standard. The DBSCAN algorithm is used to establish the optimal clustering centers by searching the global optimal solution of the objective function, and the fuzzy C-means clustering algorithm is optimized and the mathematical model of the advantage grouping of rock discontinuities is established. The new method and the fuzzy C-means method are compared and verified by using the artificially randomly generated discontinuity occurrence data. The proposed method is a better method than the fuzzy C-means method in general cases, and it can provide more accurate results by eliminating the acnodes or outliers. Finally, the proposed method is applied to discontinuity orientation partition data at Maji dam site, Nujiang River, and there is good agreement with the in situ measurement. Full article

In order to investigate the influence of the high-altitude aquatic environment on indigenous fish metabolites, metabolomics studies were applied in this study. Widespread throughout the main stem of the Nujiang River of Schizothorax nukiangensis, we established sampling sites at high (3890 m) and low (2100 m) altitudes and selected six S. nukiangensis at each location, each weighing approximately 150 g and looking healthy. Then, metabolomics analysis was performed to compare the various metabolites of the two groups. Low concentrations of amino acids, dipeptides, eicosapentaenoic acid, docosahexaenoic acid, pentadecanoic acid, Thioetheramide-PC, 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine, 1-Stearoyl-sn-glycerol-3-phosphocholine, 1-Myristoyl-sn-glycero-3-phosphocholine and 1-Palmitoyl-sn-glycero-3-phosphocholine, high concentrations in S-Methyl-5’-thioadenosine, creatine, D-mannose-6-phosphate, D-mannose-1-phosphate, oleic acid and myristoleic acid were found in high-altitude fish liver. These differentially accumulated metabolites were involved in oxidative stress, energy metabolism, carbohydrate metabolism and lipid metabolism. mTOR signaling pathway, apoptosis and lysosome were the KEGG pathways that were enriched between different groups to ensure energy supply and limit tissue damage of fish at high altitudes. All these results contributed to the understanding of the high-altitude adaptation of S. nukiangensis in the Nujiang River. Nicotine and methoprene, two organic pollutants, performed differently in fish at different altitudes. Overall, our findings advanced the fundamental understanding of fish responses to high-altitude environments, adaptive mechanisms and organic contaminants pollution in the Nujiang River. Full article

At present, landslide susceptibility assessment (LSA) based on landslide characteristics in different areas is an effective measure for landslide management. Nujiang Prefecture in China has steep mountain slopes, a large amount of water and loose soil, and frequent landslide disasters, which have caused a large number of casualties and economic losses. This paper aims to understand the characteristics and formation mechanism of regional landslides through the evaluation of landslide susceptibility so as to provide relevant references and suggestions for spatial planning and disaster prevention and mitigation in Nujiang Prefecture. Based on the grid cell, this study selected 10 parameters, namely elevation, slope, aspect, lithology, proximity to faults, proximity to road, proximity to rivers, normalized difference vegetation index (NDVI), land-use type, and precipitation. Support vector machine (SVM), certainty factor method (CF), and deterministic coefficient method–support vector machine (CF-SVM) were used to evaluate the landslide susceptibility in Nujiang Prefecture. According to these three models, the study area was divided into five landslide susceptibility grades, including extremely high susceptibility, high susceptibility, moderate susceptibility, low susceptibility, and very low susceptibility. Receiver operating characteristic curve (ROC) was applied to verify the accuracy of the model. The results showed that CF model (ROC = 0.865), SVM model (ROC = 0.892), CF-SVM model (ROC = 0.925), and CF-SVM model showed better performance. Therefore, CF-SVM model results were selected for analysis. The study found that the characteristics of high and extremely high landslide-prone areas in Nujiang Prefecture have the following characteristics: intense human activities, large density of buildings and arable land, rich water resources, good economic development, perfect transportation facilities, and complex topography and landform. In addition, there is a finding inconsistent with our common sense that the distribution of landslide disasters in the study area does not decrease with the increase of NDVI value. This is because the Nujiang River basin is a high mountain canyon area with low rock strength, barren soil, and underdeveloped vegetation and root system. In an area with large slope, the probability of landslide disaster will increase with the increase of NDVI. The CF-SVM coupling model adopted in this study is a good first attempt in the study of landslide hazard susceptibility in Nujiang Prefecture. Full article

Constructing an ecological security pattern is vital to guaranteeing regional ecological security. The terrain and geomorphology of the alpine valley are complex and sensitive, meaning it is difficult to construct ecological security patterns. Therefore, the study takes Nujiang Prefecture as the study area and builds an “Importance–Sensitivity–Connectivity” (Importance of ecosystem service, eco-environmental sensitivity, and landscape connectivity) framework to carry on the comprehensive evaluation of the ecological security and identification of ecological sources. Furthermore, we constructed an ecological resistance surface using land-use type. Using the minimum cumulative resistance (MCR) model, the study identifies the ecological corridors and nodes to build ecological security patterns to optimize the ecological spatial structure of Nujiang Prefecture. The results showed that (1) the importance of ecosystem services was higher in the west and lower in the east. The high-sensitive areas of the ecological environment were distributed discontinuously along the banks of the Nujiang and the Lantsang River, and the areas with high landscape connectivity were distributed in patches in the Gaoligong Mountain Nature Reserve and the Biluo Snow Mountain. (2) The overall ecological security was in a good state, and the ecologically insecure areas were primarily distributed in Lanping County and the southeast region of Lushui City. (3) The primary ecological source area was identified to be 3281.35 km² and the secondary ecological source area to be 4224.64 km². (4) In total, 26 primary ecological corridors, 39 secondary ecological corridors, and 82 ecological nodes were identified. Full article

Rivers play an essential role in the global matter transport and hydrogeochemical cycle. Hydrogeochemical research is significant to developing and protecting water resources in the Qinghai-Tibet Plateau and its lower reaches. This study aimed to identify the hydrochemical characteristics and controlling factors of Daqu River and Gaqu River in Dingqing County, two tributaries of the upper Nujiang River. This study used spatial analysis, trilinear diagram analysis, and ion ratio analysis of hydrochemical indexes to investigate the hydrochemical characteristics and controlling factors. Results show that Ca²⁺ and Mg²⁺, and HCO₃⁻ and SO₄²⁻ are the main cations and anions of these two rivers. HCO₃·SO₄-Mg·Ca and HCO₃·SO₄-Ca·Mg are the primary hydrochemical types for the surface water of Daqu and Gaqu Rivers, respectively. The influence of atmospheric precipitation and anthropogenic activities is weak. The carbonated water–rock reaction is the main Ca²⁺, Mg²⁺, and HCO₃⁻ source, and hot springs act as the primary source of SO₄²⁻ and supplements Ca²⁺, Mg²⁺, and HCO₃⁻. Mg²⁺ from magnesite dissolution exists in the Daqu River basin. Weak reverse cation exchange occurs in both rivers. Daqu River receives more low-mineralized glacier meltwater along the flow, whereas Gaqu River receives more high-mineralized hot spring water. Full article

Topographic factors are critical for influencing vegetation distribution patterns, and studying the interactions between them can enhance our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000–2019), combined with the Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Qinghai-Tibet Plateau (QTP) in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000–2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the entire basin and each sub-basin. During 2000–2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with variations in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with higher NDVI in the southern regions NDVI than those in the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation. Our results confirmed the importance of topographic factors on vegetation growth processes and have implications for understanding the sustainable development of mountain ecosystems. Full article