Search Results (48)

Land use conflicts represent an increasing challenge to sustainable development, particularly in regions undergoing rapid urbanization. This study investigated the spatiotemporal dynamics of land use conflicts and their ecological implications in Tianshui City from 1980 to 2020. The main objectives were to identify patterns of spatial heterogeneity, explore the driving factors behind these conflicts, and analyze their relationship with the ecological risks. The results indicate the following findings. In terms of spatiotemporal heterogeneity, early land use changes were primarily driven by structural factors, such as topography and climate, with a Nugget/Still ratio of <0.30 observed from 1980 to 2000. After 2000, however, stochastic factors, including an average annual urbanization rate increase of 5.2% and a GDP growth rate of 9.1%, emerged as the dominant drivers, as reflected in a Nugget/Still ratio > 0.36. Regarding conflict intensity, high-conflict areas expanded by approximately 1110 square kilometers between 1980 and 2020, predominantly concentrated in fertile agricultural regions such as the Weihe River Basin and urban core areas. Conversely, non-conflict zones decreased by 38.7%. In terms of ecological risk correlation, bivariate LISA cluster analysis revealed a significant spatial autocorrelation between severe land use conflicts and ecological risks (Moran’s I = 0.62, p < 0.01). High-risk clusters in areas transitioning from arable land to built-up land increased by 23% after 2000. Predictions based on the future land-use simulation (FLUS) model suggest that by 2030, high-intensity conflict areas will expand by an additional 16%, leading to intensified competition for land resources. Therefore, incorporating ecological safety thresholds into land spatial planning policies is essential for reconciling the conflicts between development and conservation, thereby promoting sustainable land use transitions. 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

Groundwater is a vital and invaluable resource on our planet, serving as a critical water supply for human life, industrial activities, and agricultural production. It plays a pivotal role in sustaining human existence and driving societal progress. In this study, we conducted a comprehensive analysis of the hydrochemical characteristics and controlling factors of groundwater in the Upper Weihe River (UWR) using statistical analysis, Piper diagrams, Gibbs diagrams, correlation analysis, and ion ratio analysis. To evaluate the suitability of the regional groundwater for potable use, we employed the entropy weight water quality index (EWQI). Additionally, the sodium adsorption ratio (SAR) and percentage of soluble sodium (Na%) were utilized to evaluate the groundwater’s adaptability to irrigation. Furthermore, this study also assessed the health risks faced by adults and children in the UWR. The findings indicate that the main cations and anions in groundwater are Ca²⁺ and HCO₃⁻, respectively. The hydrochemical types are predominantly HCO₃-Ca, Cl-Ca, and mixed types. The composition of groundwater is primarily influenced by the dissolution of silicate and carbonate minerals, with cation exchange also playing a significant role in shaping its hydrochemical characteristics. The water quality assessment indicates that the majority of groundwater in UWR is classified as “excellent” or “good”, rendering it suitable for human consumption. However, 7.17% of the water samples were of poor quality and unsuitable for drinking; these were primarily located in a few areas in the northern and western parts of the study area. Regarding irrigation, 94.83% of the groundwater is deemed very suitable; however, a small fraction is not appropriate for such use. Additionally, non-carcinogenic risks are generally higher across most parts of the study area for both children and adults, with children exhibiting significantly higher risks than adults. These findings offer crucial insights regarding the sustainable management and environmental conservation of groundwater resources in the UWR. Full article

The wetland ecosystem is one of the most important carbon sinks on Earth, the most biodiverse ecological landscape in nature, and one of the most important living environments for human beings. The Weihe River wetland is located in the Guanzhong Plain urban agglomeration, with extreme climate and urban expansion having a great impact on its dynamic changes. Revealing the characteristics of and trends in wetland dynamics in the Weihe River Basin is the key to protecting and maintaining the healthy development of the Weihe River wetlands. This paper analyzed the changing characteristics of land use types and landscape patterns in the wetlands of the Weihe River Basin using wetland land use data from six periods in the Weihe River wetland from 1980 to 2020 and explored the spatial and temporal distribution characteristics and dynamic changes in wetlands in the Weihe River Basin. The results showed the following: (1) Wetlands in the Weihe River Basin, dominated by rivers, saw area fluctuations with an initial decline followed by an increase. Land use changes followed a slow–fast–slow trend. (2) From 1980 to 2020, frequent conversions among wetland types were observed. The primary transformation was the conversion of marshes into lakes (18.05 km²) and reservoirs/ponds (17.98 km²). Approximately 0.06 km² of lakes were transformed into canals/channels. (3) River patches have the largest area, while canals/channels have the smallest. The patch density (PD) and landscape shape index (LSI) of wetlands fluctuate significantly, and the reduction in area leads to a 3.46% decrease in aggregation index (AI). Shannon’s diversity index (SHDI) has decreased by 5.41%. (4) The centroid of marshes experiences significant changes, while river changes are complex. The centroid changes in reservoirs/ponds are located along the southeast–northwest line. Canals/watercourses remain stable. Lakes exhibit the longest migration. This study provides robust scientific support for wetland ecological protection, policy formulation, and social sustainable development by conducting an in-depth analysis of the dynamic change characteristics of wetlands in the Weihe River Basin. Full article

Temporal and spatial changes in non-point source pollution, driven by significant alterations in land use due to increased human activity, have considerably affected the quality of groundwater, surface water, and soil environments in the region. This study examines the Weihe River basin in greater detail, an area heavily impacted by human activity. The study developed the River Section Potential Pollution Index (R-PPI) model using the Potential Non-Point Source Pollution Index (PNPI) model in order to investigate the dynamic changes in River Section Potential Pollution (R-PP) over a 31-year period and its associated risks, especially those related to land use and land cover change (LUCC). The predominant land uses in the Weihe River Basin are cropland, grassland, and forest, making up around 97% of the basin’s total area. The Weihe River Basin underwent a number of soil and water conservation initiatives between 1990 and 2020, which significantly decreased the potential pollution risk in the river segment. The research separated the R-PP risk values in the area into five different categories using a quantile classification technique. According to the data, there is a polarization of R-PP risk in the area, with downstream parts especially having an increased risk of pollution in river segments impacted by human activity. On the other hand, river segments in the middle and upper reaches of the basin showed a discernible decline in possible pollution risk throughout the study period. The Weihe River Basin’s rapid urbanization and land degradation are to blame for the current increase in R-PP risk. The substantial influence of LUCC on the dynamic variations in R-PP risk in the Weihe River Basin is highlighted by this study. Additionally, it offers crucial information for upcoming conservation initiatives and urban planning guidelines meant to enhance the area’s ecological well-being and environmental standards. Full article

Water quality safety in the water source constitutes a crucial guarantee for public health and the ecological environment. This study undertakes a comprehensive assessment of the water quality conditions within the Jing River Basin of the Loess Plateau, emphasizing the spatial and temporal characteristics, as well as the determinants influencing surface water quality in the Shaanxi section. We utilized data from seven monitoring stations collected between 2016 and 2022, employing an enhanced comprehensive Water Quality Index (WQI) method, redundancy analysis (RDA), and Spearman’s correlation analysis. The results show that the average annual WQI value of the water quality of the Shaanxi section of the Jing River increased from 68.01 in 2016 to 76.18 in 2022, and the river’s water quality has gradually improved, with a significant improvement beginning in 2018, and a series of water quality management policies implemented by Shaanxi Province is the primary reason for the improvement. The river’s water quality has deteriorated slightly in recent years, necessitating stricter supervision of the coal mining industry in the upper section. The river has an average WQI value of 73.70 and is rated as ‘good’. The main pollution indicators influencing the river’s water quality are COD_Mn, COD, BOD₅, NH₃-N, and TP. From the upstream to the downstream, the water quality of the river shows a pattern of increasing and then decreasing, among which S4 (Linjing Bridge in Taiping Town) and S5 (Jinghe Bridge) have the best water quality. The downstream part (S6, S7) of the Jing River near the Weihe River has poor water quality, which is mostly caused by nonpoint source contamination from livestock and poultry rearing, agricultural activities, and sewage discharge. Redundancy analysis revealed that the spatial scale of the 2500 m buffer zone best explained water quality changes, and the amount of bare land and arable land in land use categories was the key influencing factor of river water quality. Full article

Automated water body (WB) extraction is one of the hot research topics in the field of remote sensing image processing. To address the challenges of over-extraction and incomplete extraction in complex water scenes, we propose an encoder–decoder architecture semantic segmentation network for high-precision extraction of WBs called EDWNet. We integrate the Cross-layer Feature Fusion (CFF) module to solve difficulties in segmentation of WB edges, utilizing the Global Attention Mechanism (GAM) module to reduce information diffusion, and combining with the Deep Attention Module (DAM) module to enhance the model’s global perception ability and refine WB features. Additionally, an auxiliary head is incorporated to optimize the model’s learning process. In addition, we analyze the feature importance of bands 2 to 7 in Landsat 8 OLI images, constructing a band combination (RGB 763) suitable for algorithm’s WB extraction. When we compare EDWNet with various other semantic segmentation networks, the results on the test dataset show that EDWNet has the highest accuracy. EDWNet is applied to accurately extract WBs in the Weihe River basin from 2013 to 2021, and we quantitatively analyzed the area changes of the WBs during this period and their causes. The results show that EDWNet is suitable for WB extraction in complex scenes and demonstrates great potential in long time-series and large-scale WB extraction. 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

Recent anthropogenic activities have escalated human exploitation of riparian zones of river ecosystems, consequently diminishing aquatic biodiversity. This intensification of land use is also causing water quality degradation and changes in water environmental factors, evidenced by increased nutrient levels and adversely impacting the community structure and diversity of aquatic organisms. Notably, the Weihe River Basin, the largest tributary of the Yellow River, has demonstrated signs of significant anthropogenic pressure. Despite this, comprehensive investigations examining the effects of land-use intensity on aquatic organism diversity in this watershed remain limited. In this study, the environmental impacts and macroinvertebrate diversity under high-intensity and low-intensity land-use scenarios within the Weihe River Basin were investigated through field surveys conducted during the spring and autumn seasons. Our results demonstrated that areas under high-intensity land use exhibited elevated nutrient concentrations (e.g., total nitrogen) compared to those under low-intensity land use. These environmental changes significantly influenced the macroinvertebrate community structure, reducing functional and phylogenetic diversities in high-intensity land-use watersheds. Hydrological factors (water depth, river width, and discharge) have a significant impact on macroinvertebrate taxonomic diversity. Thus, understanding the effects of land-use intensity on aquatic biodiversity is essential for ecological assessments of impacted watersheds and developing management strategies for the sustainable use and planning of riparian lands in the Weihe River Basin. Full article

Based on Sentinel-2 multispectral image data and existing research results, the comprehensive water quality index (CWQI), NH₄⁺-N, and total phosphorus (TP) in the Weihe River and its tributaries were estimated. Furthermore, a verified model was obtained by fitting the regression using the measured and inverted data. The verified model results show that the average relative error of the CWQI is only 9.80%, the goodness of fit of NH₄⁺-N and TP concentrations is 0.62 and 0.61, respectively, and the average relative errors are 19.40% and 24.70%, respectively. The accuracy of the verified model is relatively high, and it can approximately invert the distribution of the three parameters of the Weihe River and its tributaries. In December 2023, except for the Bahe River between Puhua Town and Sanli Town in Lantian County, most of the water bodies in the Weihe River and its tributaries had good water quality. The study can provide an example of how to monitor water quality information using Sentinel-2 data in similar river basins. 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

Water N-NO₃⁻ (mg L⁻¹) pollution is attracting global concern in the face of combating climate change and human health risks. However, there have been comparatively few comprehensively researched studies on water N-NO₃⁻ pollution with respect to N-NO₃⁻ deposition, soil nitrogen, and land-use changes. We collected a total of 7707 published sampling points on N-NO₃⁻ surface and groundwater during flooding and non-flooding seasons during 2000–2020 in China. The types of water N-NO₃⁻ pollution (>20) can be categorized as point pollution (ΔTN ≤ 0 or > 1.5) and non-point pollution (0 < ΔTN ≤ 1.5), which were then assessed with respect to soil nitrogen (ΔTN g kg⁻¹) and water N-NO₃⁻ changes in this study. We found non-point pollution was concentrated in the Huaihe River Basin and Haihe River Basin with higher urbanization (+6%, +4%), cropland (72%, 45%), nitrogen fertilization (g m⁻² yr⁻¹) (>10), and increased wet N-NO₃⁻ deposition (WND) (kg ha⁻¹ yr⁻¹) (+4.6, +3). The Haihe River Basin was found to have the highest N-NO₃⁻ on its surface (306) and in its groundwater (868) and nitrogen fertilization (32). Point pollution was concentrated in the Songhua and Liaohe River Basin with the highest WND (+7.9) but slow urbanization (+1%). N-NO₃⁻ increased during the flooding season compared with the no-flooding season in serious pollution areas. N-NO₃⁻ increased in the Liaohe River and middle and low Yangtze River but was reduced in the Weihe River. Therefore, stringent criteria and management, especially during the flooding season are urgently required to mitigate the degree of N-NO₃⁻ water pollution that occurs due to intensive agriculture and urbanization with increased N-NO₃⁻ deposition. Full article

Based on the 24 meteorological stations in the Weihe River Basin (WRB) from 1951 to 2013, as well as the runoff data from the mainstream of the Weihe River, the temporal and spatial variations in water balance in the WRB and its relationships with runoff, the drought index, and the climate index were analyzed. The results indicate that the water balance in the WRB has been in a deficit state over the past 63 years, showing a weak declining trend with a decreasing rate of −20.04 mm/decade. Water balance is closely related to potential evapotranspiration (ET₀) and precipitation (P). At the annual time scale, P plays a dominant role in water balance for 6–8 months in the WRB. The distribution of the water deficit (WD) in the WRB is uneven throughout the year, with the largest deficit occurring in June and the smallest values generally occurring in September. Furthermore, there are significant multi-scale correlations between water deficit and climate indices such as Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), and Sea Surface Temperature (SST) in the WRB. In addition, water deficit is also influenced by human activities, such as irrigation, as well as climate factors and socio-economic factors. Studying the temporal and spatial variation characteristics of water deficit and its influencing factors in the WRB is helpful toward deeply understanding the supply and demand dynamics of water resources in the basin and providing a theoretical basis and scientific guidance for the rational utilization of water resources and the high-quality development of the basin. Full article

Model simulation plays a significant role in the water resources cycle, and the simulation accuracy of models is the key to predicting regional water resources. In this research, the Qianhe tributary at the Weihe River basin in Western China was selected as the study area. The tributary was divided into 29 sub-basins and 308 hydrological response units according to the spatial raster data and attribute data of the hydrology, meteorology, topography, land use, and soil types. On this basis, a soil and water assessment tool (SWAT) model for runoff simulation and evaluation of this region was established. A sensitivity test and parameter calibration were then executed on 15 parameters involved with surface runoff, soil flow, and shallow underground runoff. The simulation results demonstrate a calibration and verification error of 3.06–10.08%, with very small uncertainties throughout the simulation, whereas they exhibit relatively large errors in the simulation of the dry period (winter) but, in contrast, quite small errors in the rainy period (summer). In addition, the simulated runoff with a low value is overestimated. When the annual, monthly, and daily runoff are 4–13.5 m³/s, 4–69.8 m³/s, and 40–189.3 m³/s, respectively, the relative error is smaller, and the simulation results are more accurate. The sensitive parameters predominantly affecting the runoff simulation of the basin include soil evaporation compensation, runoff curve coefficient, vegetation transpiration compensation, and saturated hydraulic conductivity in this region. In the case of hypothetical land use change scenarios, we observe a great reduction in simulated runoff in arable land, woodland, and grassland, while we observe an increment in construction and residential land and wasteland. The annual and monthly runoff are increased by above 54.5%. With the increase in cultivated land and forestland, the annual and monthly runoff decrease by 24.6% and 6.8%, respectively. In the case of hypothetical scenarios under 24 climate combinations, if the precipitation remains unchanged, the increase and decrease in temperature by 1 °C leads to a decline and increment of runoff by −0.72% and 5.91%, respectively. With regard to the simulation for the future under the RCP2.6 and RCP8.5 climate scenarios, downscaling was employed to predict the runoff trend of the future. In short, this study provides a method for runoff inversion and water resources prediction in small mountainous watersheds lacking hydrological and meteorological observation stations. Full article

In the era of big data, making full use of remote sensing images to automatically extract surface water bodies (WBs) in complex environments is extremely challenging. Due to the weak capability of existing algorithms in extracting small WBs and WB edge information from remote sensing images, we proposed a new method—Multiscale Fusion SegFormer (MF-SegFormer)—for WB extraction in the Weihe River Basin of China using Landsat 8 OLI images. The MF-SegFormer method adopts a cascading approach to fuse features output by the SegFormer encoder at multiple scales. A feature fusion (FF) module is proposed to enhance the extraction of WB edge information, while an Atrous Spatial Pyramid Pooling (ASPP) module is employed to enhance the extraction of small WBs. Furthermore, we analyzed the impact of four kinds of band combinations on WB extraction by the MF-SegFormer model, including true color composite images, false color images, true color images, and false color images enhanced by Gaussian stretch. We also compared our proposed method with several different approaches. The results suggested that false color composite images enhanced by Gaussian stretching are beneficial for extracting WBs, and the MF-SegFormer model achieves the highest accuracy across the study area with a precision of 77.6%, recall of 84.4%, F1-score of 80.9%, and mean intersection over union (mIoU) of 83.9%. In addition, we used the determination coefficient (R²) and root-mean-square error (RMSE) to evaluate the performance of river width extraction. Our extraction results in an overall R² of 0.946 and an RMSE of 28.21 m for the mainstream width in the “Xi’an-Xianyang” section of the Weihe River. The proposed MF-SegFormer method used in this study outperformed other methods and was found to be more robust for WB extraction. Full article