Search Results (66)

Accurate estimation of soil organic carbon (SOC) content is crucial for assessing terrestrial ecosystem carbon stocks. Although traditional methods offer relatively high estimation accuracy, they are limited by poor timeliness and high costs. Combining measured data, remote sensing technology, and machine learning (ML) algorithms enables rapid, efficient, and accurate large-scale prediction. However, single ML models often face issues like high feature variable redundancy and weak generalization ability. Integrated models can effectively overcome these problems. This study focuses on the Weigan–Kuqa River oasis (Wei-Ku Oasis), a typical arid oasis in northwest China. It integrates Sentinel-2A multispectral imagery, a digital elevation model, ERA5 meteorological reanalysis data, soil attribute, and land use (LU) data to estimate SOC. The Boruta algorithm, Lasso regression, and its combination methods were used to screen feature variables, constructing a multidimensional feature space. Ensemble models like Random Forest (RF), Gradient Boosting Machine (GBM), and the Stacking model are built. Results show that the Stacking model, constructed by combining the screened variable sets, exhibited optimal prediction accuracy (test set R² = 0.61, RMSE = 2.17 g∙kg⁻¹, RPD = 1.61), which reduced the prediction error by 9% compared to single model prediction. Difference Vegetation Index (DVI), Bare Soil Evapotranspiration (BSE), and type of land use (TLU) have a substantial multidimensional synergistic influence on the spatial differentiation pattern of the SOC. The implementation of TLU has been demonstrated to exert a substantial influence on the model’s estimation performance, as evidenced by an augmentation of 24% in the R² of the test set. The integration of Boruta–Lasso combination screening and Stacking has been shown to facilitate the construction of a high-precision SOC content estimation model. This model has the capacity to provide technical support for precision fertilization in oasis regions in arid zones and the management of regional carbon sinks. Full article

Historically, the Wei River has served as part of the Yongji Canal section of the Grand Canal, playing a crucial role in connecting northern and southern China. However, with the acceleration of urbanization in China, issues such as excessive land development and ecological landscape fragmentation have emerged. Exploring the mechanisms of landscape fragmentation evolution in the Wei River basin and proposing optimization strategies is of significant importance for land use and ecological stability within small- to medium-sized river basins. This study selected land use data from the Weihe River basin between 2000 and 2020, using landscape pattern indices to analyze the trend of landscape fragmentation. The principal component analysis (PCA) and geographical detector methods were employed to explore the distribution characteristics and driving factors of landscape fragmentation. The research results indicate that: (1) The degree of landscape fragmentation in the Wei River basin has progressively intensified over time. The edge density index (ED), the landscape division index (DIVISION), the landscape shape index (LSI), and the Shannon diversity index (SHDI) have increased annually, while the contagion index (CONTAG) and area-weighted mean patch size (Area_AM) have continuously decreased; (2) Landscape fragmentation in the Wei River basin is characterized by stable changes in the source and tributary fragmentation areas, a concentrated distribution of fragmentation in the tributaries, and a significant increase in fragmentation in the main stream; (3) The analysis using the geographic detector method indicates that vegetation coverage (FVC), human activity intensity (HAI), and land use/land cover change (LUCC) are the main driving factors of landscape fragmentation in the Wei River basin. The findings explore the mechanisms of landscape fragmentation in the basin and provide a reference for land use planning and ecological restoration in the region. Full article

Recently, frequent water shortages and reductions in water flow have been observed in the northern segment of the Yellow River within the Beijing–Hangzhou Grand Canal. In response, a water replenishment program has been initiated. This study is focused on the section of the Grand Canal north of the Yellow River and uses the GSFLOW model to examine interaction between surface water and groundwater, as well as the effect of water replenishment. The results indicate that, after the water replenishment, the efficiency of water replenishment was highest in the Xiao Canal (64.30%), followed by the Wei Canal (39.09%), the South Canal (12.11%), and the North Canal, which exhibited the lowest efficiency (5.75%). This variation can be attributed to greater water loss with increasing distance from the replenishment source, leading to lower replenishment efficiency. Surface water recharge to groundwater was extended by 32 days, with replenishment effects persisting even after the water supply ceased. The maximum influence distance on either side of the canal reached 5.73 km, with an average impact distance of 1.48 km, resulting in a total affected area of 974.7 km², accounting for 2.2% of the study area. Water replenishment positively influenced the recovery of groundwater levels along the Grand Canal. Full article

To eliminate the noise interference caused by continuous external environmental disturbances on the rotor signals of a maglev gyroscope, this study proposes a noise reduction method that integrates an adaptive particle swarm optimization variational modal decomposition algorithm with a strategy for error compensation of the trend term in reconstructed signals, significantly improving the azimuth measurement accuracy of the gyroscope torque sensor. The optimal parameters for the variational modal decomposition algorithm were determined using the adaptive particle swarm optimization algorithm, allowing for the accurate decomposition of noisy rotor signals. Additionally, using multi-scale permutation entropy as a criterion for discriminant, the signal components were filtered and summed to obtain the denoised reconstructed signal. Furthermore, an empirical mode decomposition algorithm was employed to extract the trend term of the reconstructed signal, which was then used to compensate for the errors in the reconstructed signal, achieving significant noise reduction. On-site experiments were conducted on the high-precision GNSS baseline of the Xianyang Yuan Tunnel in the second phase of the project to divert water from the Han River to the Wei River, where this method was applied to process and analyze multiple sets of rotor signals. The experimental results show that this method effectively suppresses continuous external environmental interference, reducing the average standard deviation of the compensated signals by 46.10% and the average measurement error of the north azimuth by 45.63%. Its noise reduction performance surpasses that of the other four algorithms. Full article

Solar radiation is the fundamental energy source of climate change, which has a significant impact on the generations of secondary fine particulate matter (PM_2.5) and ozone (O₃) in the atmosphere. Additionally, surface solar radiation is also affected by the concentration of PM_2.5, which in turn affects the generation of O₃. To clarify the relationships among the O₃, PM_2.5 and the total radiation intensity, this study analyzes their temporal and spatial variation trends from 2017 to 2019. Meanwhile, as a common precursor of O₃ and PM_2.5, concentration variations in nitrogen dioxide (NO₂) are discussed as well in this study. The results showed the following: (1) There are significant positive correlations between the O₃-8 h concentrations and the total radiation intensities in critical regions, especially in the “2 + 26” cities, Fen-Wei Plain and Yangtze River Delta. (2) The decrease in PM_2.5 concentrations is in good agreement with the trend of NO₂ concentrations, while the response of O₃ concentration to the NO₂ concentration variation differs in different regions, except in the Pearl River Delta. (3) In addition to the meteorological factors, changes in the concentrations and ratios of precursors such as NO₂ and volatile organic compounds (VOCs) likely contribute to the observed fluctuations in O₃ concentrations in recent years. Full article

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management. Full article

Pasvik State Nature Reserve is situated in the Arctic zone and its chrysophyte flora is poorly studied. The diversity of the golden-brown algae (chrysophytes) from the Paz river, as well as the peat-bog on its bank, has been investigated using light and scanning electron microscopy. Overall, 34 chrysophyte taxa have been recorded. They represent fifteen genera from five orders. A new species of Synura, S. skaloudiorum, has been described. Morphologically, it resembles S. hibernica, a species restricted in its distribution to Ireland and Newfoundland, but differs mainly in size and structure of the apical scales. Nomenclatural issues on the selected chrysophyte taxa are discussed. The name Kephyrion starmachii was invalidly published, and it was validated. The new nomenclatural combination Chrysothecopsis tubulosus has been proposed. Also, Dinobryon sertularia var. annulatum Shi and Wei has been synonymized with D. annulatum Hilliard and Asmund. Full article

Controlling the total amount of river pollutant discharge is an important means of water resource protection and management, and it is also a necessary condition for ensuring the normal functioning of water areas. The total amount of pollutant discharge is closely related to the water environmental capacity (WEC). Shifting from the traditional method of calculating WEC to dynamic analyses and calculations, concerning practical applications, in this paper, a dynamic adaptive calculation method is proposed for the river WEC that considers the changes in adaptive demand and hydrological conditions. In this method, the dynamic WEC is represented by intervals based on dynamic changes in different spatial and temporal scales, various calculation methods, hydrological conditions, and parameters. According to the calculation results for the WEC, a variable interval was formed. Taking the Shaanxi section of the main stream of the Wei River as the research object, with the support of an integrated platform, the dynamic adaptive calculation of the WEC in the Shaanxi section of the Wei River was realized, and a corresponding simulation system was constructed. The verification results show that (1) the dynamic calculation of WEC can be realized by freely combining different model methods and calculation conditions; (2) the WEC is described using a variable interval, which has strong applicability and operability; and (3) the simulation system can quickly adapt to the changing needs of practical applications and provide managers with visual and credible decision support. The research results provide a theoretical basis for river water environment pollution prevention and environmental management decision-making and help in the high-quality development of the river basin. Full article

The Xiao Bei mainstream, located in the middle reaches of the Yellow River, plays a vital role in regulating the quality of river water. Our study leveraged 73 years of hydrological data (1951–2023) to investigate long-term runoff trends and seasonal variations in the Xiao Bei mainstream and its two key tributaries, the Wei and Fen Rivers. The results indicated a significant decline in runoff over time, with notable interannual fluctuations and an uneven distribution of runoff within the year. The Wei and Fen Rivers contributed 19.75% and 3.59% of the total runoff to the mainstream, respectively. Field monitoring was conducted at 11 locations along the investigated reach of Xiao Bei, assessing eight water quality parameters (temperature, pH, dissolved oxygen (DO), chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total phosphorus (TP), permanganate index (COD_Mn), and 5-day biochemical oxygen demand (BOD₅)). Our long-term results showed that the water quality of the Xiao Bei mainstream during the monitoring period was generally classified as Class III. Water quality parameters at the confluence points of the Wei and Fen Rivers with the Yellow River were higher compared with the mainstream. After these tributaries merged into the mainstream, local sections show increased concentrations, with the water quality parameters exhibiting spatial fluctuations. Considering the mass flux process of transmission of the quantity and quality of water, the annual NH₃-N inputs from the Fen and Wei Rivers to the Yellow River accounted for 11.5% and 67.1%, respectively, and TP inputs accounted for 6.8% and 66.18%. These findings underscore the critical pollutant load from tributaries, highlighting the urgent need for effective pollution management strategies targeting these tributaries to improve the overall water quality of the Yellow River. This study sheds light on the spatiotemporal changes in runoff, water quality, and pollutant flux in the Xiao Bei mainstream and its tributaries, providing valuable insights to enhance the protection and management of the Yellow River’s water environment. Full article

Due to the changing climate and human activity, more and more researchers started to focus on non-stationarity in hydrology. In the Wei River Basin, which is the largest tributary of the Yellow River, there is a significant reduction in the total amount of water resources which has been found in past decades. Additionally, the distribution of water resources within the basin is unbalanced, with the lower reaches and southern regions having relatively abundant water resources and other regions lacking these resources. Within this situation, it is important to consider the spatial aspect of water resource management. Four non-stationarity detection methods have been applied to investigate variation in seasonal discharge series. Two meteorological factors have also been analyzed. Based on test results and Köppen Geiger Climate classification, the water resource management has been investigated spatially. As for results, the Baojixia Channel has significant impact on the abrupt change of discharge, while the precipitation and temperature may have an impact on the discharge trend change. In addition, there was no clear evidence to prove that the climate zones impact spatially on the non-stationarity of discharge. Full article

The coordinated development of atmospheric pollution and socio-economic growth plays a core role in the sustainable development of cities and regions. The relationship between socio-economic growth and air pollution can be described using decoupling analysis. The seven key regions of China (168 cities), including Beijing–Tianjin–Hebei and its surrounding areas (BTHSR), the Yangtze River Delta region (YRDR), the Fen-Wei Plain (FWP), the Chengdu–Chongqing region (CCR), the urban agglomeration of the middle reaches of the Yangtze River (MLRYR), the Pearl River Delta region (PRDR), and other provincial capitals and municipalities with specialized plans (OPCCSP) were taken as targets to investigate the spatiotemporal evolution characteristics of AQI values and PM_2.5 concentrations from 2014 to 2022. Then, the decoupling relationship between the AQI/PM_2.5 and the socio-economic growth index (SEGI) in these key regions was deeply researched by the Tapio decoupling model. The main results were as follows: (1) Although the continuous improvement in air quality was observed in these seven key regions in China, the PM_2.5 concentration in the BTHSR and FWP was still higher than 35 μg·m⁻³. The AQI showed a spatial pattern of high in the north and low in the south, and the distribution of PM_2.5 in China was high in the east and low in the west. (2) The decoupling degree between air pollution and socio-economic growth was relatively high in the PRDR and YRDR. In contrast, the degree of decoupling was poor in the FWP and OPCCSP. The decoupling states were primarily influenced by industrial structure, energy consumption, and urbanization. (3) The decoupling of air pollution from socio-economic growth was in a strong decoupling state throughout the majority of the study period, achieving a comparatively ideal decoupling state in 2018. However, the overall decoupling states of the seven regions were not sustainable, and the decoupling stability was relatively poor. During the research period, the decoupling state between socio-economic growth and air pollution changed and was unstable. Full article

Ecological protection in the Yellow River Basin (YRB) is a major strategy for China’s sustainable development. Amid global warming, droughts have occurred more frequently, severely affecting vegetation growth. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) at different time scales from 2003 to 2020, this study employed the linear trend method and the Spearman correlation coefficient method to calculate the trends and correlation coefficients of NDVI and SPEI at different scales at the pixel scale and explored the spatial distribution pattern of the sensitivity of vegetation growth in the YRB to drought. The results show that: (1) NDVI and SPEI are positively correlated in 77% of the area, negatively correlated in 9%, and are positively correlated in the arid and semi-arid areas, while negatively correlated in the humid and subhumid areas. The significant negative correlation between NDVI and drought at high altitudes may be due to the fact that Gramineae vegetation is more sensitive to drought, with heat being more affected than water. (2) Urbanization has a relatively obvious impact on the distribution of drought. Extreme drought mainly occurs in the middle and upper reaches of the Wei River; severe drought mainly occurs in the central area of the Guanzhong Plain centered on Xi’an; the central area of the Loess Plateau; and the surrounding areas of the Zhengzhou-centered Central Plains City Group. (3) The NDVI showed an upward trend from 2003 to 2020, indicating an increase in vegetation density or an expansion of vegetation coverage. From the temporal trend, SPEI decreased at a rate of −0.17/decade, indicating that the entire watershed has a drought trend on an annual scale. (4) Spring NDVI is more sensitive to the water supply provided by SPEI-1, while the positive correlation between SPEI and NDVI begins to rise in June and reaches its peak in July, then starts to decline in August. In autumn and winter, NDVI is more sensitive to 3–6-month accumulated drought. (5) From the dynamic transmission laws of different levels of positive correlation, the positive impact of the 3-month accumulated drought on NDVI is most significant, and the influence of SPEI-1 on the negative correlation between SPEI and NDVI is most significant. This paper aims to clarify the sensitivity of vegetation to different time-scale droughts, provide a basis for alleviating drought in the YRB, and promote sustainable development of ecological environmental protection. The research findings enable us to gain a profound insight into the responsiveness of vegetation growth to drought in the context of global warming and offer a valuable theoretical foundation for devising pertinent measures to alleviate stress on vegetation growth in regions prone to frequent droughts. Full article

The current greenway systems in China are relatively homogenous, whereas recreational groups and their needs are highly diverse. This discrepancy has resulted in increasingly severe behavioral conflicts during greenway recreation. However, scholarly research on behavioral conflicts in greenway recreational activities is lacking. Recreationists’ perceptions of conflict negatively impact their evaluation of the recreational experience, thereby limiting the ecological and recreational benefits of greenways. Therefore, it is crucial to categorize these conflicts, understand their formation mechanisms, and identify influencing factors, so as to put forward targeted management strategies for greenway construction. This study selected urban segments of greenways along the Wei and Feng rivers in Xi’an, Shaanxi Province, China. Field observation, semi-structured interviews, and NVivo 12 three-level coding were used to investigate and analyze the main types of behavioral conflicts perceived by various recreational groups on urban greenways and the factors influencing these perceptions. The results indicate that the primary types of behavioral conflicts are danger perception, space occupancy, environmental damage, and noise disturbance. Younger groups, highly educated individuals, local residents, and those with exercise as their primary recreational purpose are more likely to perceive conflicts. In addition, recreationists also focus on the completeness of greenway infrastructure, the richness of green landscapes, and the adequacy of behavior management. These findings can help greenway managers and planners understand the perception of recreational conflicts, enabling the formulation of targeted design strategies and management measures to mitigate these conflicts in urban greenway recreation. Full article

Water quality is a critical aspect of environmental health, affecting ecosystems, human health, and economic activities. In recent years, increasing pollution from industrial, agricultural, and urban sources has raised concerns about the deterioration of water quality in surface water bodies. Therefore, this study investigated the spatio-temporal distribution of water elements, human health risks of surface water, and pollutant sources at the confluence of the Wei River and the Yellow River. Using 80 samples collected during both wet and dry seasons, the content of the 22 water chemistry indicators was tested. A statistical analysis, Piper diagram, and entropy water quality index were employed to analyze the chemistry indicator content, hydrochemical composition, and water environmental quality of the surface water in the area. Moreover, the health risk assessment model was utilized to evaluate the carcinogenic and non-carcinogenic health risks associated with heavy metal elements in surface water. Finally, correlation heatmaps and a principal component analysis were used to identify potential pollution sources in the study area. The results indicated that $\mathrm{C}\mathrm{r}\left(\mathrm{VI}\right)$ and ${\mathrm{N}\mathrm{H}}_3\text{-}\mathrm{N}$ were the main pollutants during the wet season, while surface water quality during the dry season was mainly influenced by ${\mathrm{F}}^{-}$. The hydrochemical type in the study area was mainly ${\mathrm{S}\mathrm{O}}_4\mathrm{C}\mathrm{l}\text{-}\mathrm{C}\mathrm{a}\mathrm{M}\mathrm{g}$. The health risk assessment revealed a high carcinogenic risk in the study area, with $\mathrm{C}\mathrm{r}\left(\mathrm{VI}\right)$ being the primary heavy metal element contributing to health risks. The correlation and principal component analysis results show that the surface water environment in the study area was influenced by soil characteristics (soils containing ${\mathrm{F}}^{-}$ in the Dalí region, soils containing heavy metals in the Tongguan region), native geological environment (mineral resources and terrain conditions), and industrial activities (ore smelting). This study identified the key pollution indicators, the priority control areas, and the extent of the human health impact of the surface water at the confluence of the Wei River and the Yellow River, guiding targeted management of surface water environments. Full article

Understanding the propagation characteristics and driving factors from meteorological drought to hydrological drought is essential for alleviating drought and for early warning systems regarding drought. This study focused on the Weihe River basin (WRB) and its two subregions (the Jinghe River (JRB) and the middle reaches of the Weihe River (MWRB)), utilizing the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) to characterize meteorological and hydrological drought, respectively. Based on Copula theory and conditional probability, a quantification model for the propagation time (PT) of meteorological–hydrological drought was constructed. The dynamic characteristics of PT on annual and seasonal scales were explored. Additionally, the influences of different seasonal meteorological factors and underlying surface factors on the dynamic changes in PT were analyzed. The main conclusions were as follows: (1) The PT of meteorological–hydrological drought was characterized by faster propagation during the hot months (June–September) and slower propagation during the cold months (December to March of the following year); (2) Under the same level of hydrological drought, as the level of meteorological drought increases, the PT of the drought shortens. The propagation thresholds of meteorological to hydrological drought in the WRB, the JRB, and the MWRB are −0.69, −0.81, and −0.78, respectively. (3) In the dynamic changes in PT, the WRB showed a non-significant decrease; however, both the JRB and the MWRB exhibited a significant increase in PT across different drought levels. (4) The influence of the water and heat status during spring, summer, and winter on PT was more pronounced, while in autumn, the impact of the basin’s water storage and discharge status was more significant in the JRB and the MWRB. Full article