Search Results (21)

To address the environmental evolution and management needs of emerging contaminants in the Yellow River Basin (Henan Section), China, nine typical functional cross-sections, covering industrial outfalls, sewage treatment plant (STP) effluents, human activity-dense areas, and baseline tributaries, were selected to systematically investigate the occurrence, potential sources, and multi-dimensional risks of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) in surface water. The results indicated a 100% detection rate of the target pollutants across all sites, with PFOA (0.45–7.46 ng/L) being the absolute dominant analogue. The spatial distribution exhibited an evident industrial point-source-driven pattern, where the pollution loads at the Jili District industrial outfall (S7) and STP effluent (S5) were significantly higher than those in non-point sources and natural baseline waters. Source apportionment suggested that direct wastewater discharge and secondary release from regional industrial clusters were likely key contributors to PFAS spatial heterogeneity. Multi-dimensional risk assessments revealed that the current ecological risk quotients (RQ < 0.01) for aquatic organisms and the human health risk values (HR < 0.1) via drinking water ingestion for various age groups were well within safe and controllable ranges. However, PFOS contributed significantly more to the ecological risk than PFOA, and children exhibited slightly higher health exposure vulnerability than adults. Although the overall risk is minimal, PFOA concentrations at high-load cross-sections have exceeded the latest stringent maximum contaminant level (4.0 ng/L) mandated by the US EPA in 2024. This study suggests an urgent need to establish a dynamic, life-cycle monitoring network for PFASs in the basin and to prioritize targeted deep-reduction strategies for high-risk industrial point sources. Full article

Cultural heritage in major river basins serves as an important spatial carrier of historical civilization evolution, and the spatial differentiation characteristics and influencing factors of its activation level are closely related to heritage conservation, utilization, and sustainable development. This study focuses on the Henan section of the Yellow River Basin and selects 344 cultural heritage sites as the research objects. A comprehensive evaluation system for cultural heritage activation was constructed from three dimensions—culture, society, and economy. By integrating GIS-based spatial analysis with the GWR model, the study reveals the spatial differentiation characteristics of cultural heritage activation levels and their influencing factors. The results indicate that the activation level of cultural heritage exhibits a dual-core-dominated and multi-level spatial agglomeration pattern. Zhengzhou and Luoyang function as dual high-density core clusters with elevated heritage activation levels, while a continuous cultural heritage corridor has gradually formed along Sanmenxia, Luoyang, Zhengzhou, Jiaozuo, Hebi, and Puyang. Furthermore, heritage agglomeration, heritage spatial radiosity, per capita GDP, transportation accessibility, terrain relief, and NDVI on the activation level of cultural heritage demonstrate significant spatial heterogeneity. Based on the identification of spatial heterogeneity, this study proposes a core–corridor–node spatial pattern and a factor-adaptive targeted strategy for cultural heritage activation. These findings provide a scientific basis for differentiated conservation and precise activation of cultural heritage under the national strategy of ecological protection and high-quality development in the Yellow River Basin, while also offering valuable insights for the collaborative governance of cultural heritage in major river basins worldwide. Full article

Addressing national goals for ecological conservation in the Yellow River Basin, this study focuses on its Henan segment (HYRB). We developed a VOR-SQ assessment framework by augmenting the classic Vitality–Organization–Resilience model with ecosystem services and an enhanced ecological quality indicator. Using multi-source remote sensing and statistical data, we examine the spatiotemporal evolution of ecosystem health in the HYRB from 2000 to 2020. The XGBoost-SHAP algorithm was applied to identify nonlinear drivers and threshold effects. Key findings indicate (1) a persistent “high west, low east” health gradient with an overall declining trend; western mountains remain healthy, while eastern plains, urban, and intensive agricultural areas show degradation. (2) Natural factors—evapotranspiration (ET), elevation, NDVI, and slope—dominate health dynamics, with critical thresholds (~1153 mm, ~457 m, ~0.76, ~10.5°, respectively) beyond which their impacts shift markedly. (3) Anthropogenic factors (GDP, population/road density) contribute less globally but cause strong local negative disturbances in plains. For instance, road density > 434 km/km² or population density > 159 persons/km² reverses their effects from positive to negative. Accordingly, we propose tailored strategies: western conservation, central farmland optimization, and eastern development control. By coupling the VOR-SQ framework with XGBoost-SHAP, this study offers a robust diagnostic tool for ecosystem health and adaptive governance in fragile socio-ecological systems. Full article

Soil erosion undermines the sustainable development of land—a vital resource for human survival. Research into the spatiotemporal dynamics of soil erosion is therefore crucial for formulating effective soil and water conservation strategies and advancing ecological protection efforts. In the domain of soil erosion research, the Universal Soil Loss Equation and Revised Universal Soil Loss Equation (USLE/RUSLE) model represent the dominant approach for quantifying soil erosion volumes. While this methodology yields reliable outcomes, it fails to incorporate an assessment of the relative significance of the factors embedded within the model. This study selected the Henan section of the Yellow River Basin as the research area, using monthly remote sensing data from 2010 to 2025 as the main data source. Taking into account factors such as rainfall, slope, elevation, vegetation coverage, and hydrological conservation measures, the RUSLE model was used to calculate and combine Geographic Information System (GIS) geographic detectors for quantitative analysis of soil erosion factors. The results showed the following: (1) The average soil erosion modulus in the study area from 2010 to 2025 was mainly micro and mild erosion. (2) Soil erosion exhibits a certain periodicity, with a year of significant soil erosion occurring every 3–4 years. The overall trend of soil erosion is a decrease. (3) Geographic detector analysis shows that slope has the greatest impact on soil erosion, with larger slopes leading to more severe soil erosion. The influence of each factor ranges from large to small as slope > water conservation measures > rainfall > vegetation coverage > elevation. (4) The interaction between factors can enhance the influence on soil erosion, and the interaction between vegetation cover factors and other factors significantly increases the influence; after interacting with various factors, the slope factor will significantly increase the influence of soil erosion. The research results can provide technical support and decision-making basis for ecological protection in the Yellow River Basin, such as through soil and water conservation, returning farmland to forests, and slope greening; The dominant factors and obvious interaction factors in the research area can provide a scientific basis for subsequent scholars to optimize the parameters of regional models. Full article

Advancing ecological civilization in the Yellow River Basin requires a nuanced understanding of the spatiotemporal evolution of ecosystem service value (ESV) and its underlying drivers, which are fundamental to regional sustainable development. This study examines the Henan section of the Yellow River Basin, applying the equivalent factor method to estimate ESV in 2020 at three grid scales: 3 km × 3 km, 5 km × 5 km, and 10 km × 10 km. Spatial patterns of land-averaged ESV at each scale are characterized using autocorrelation analysis, while the geodetector model is employed to identify and quantify the influence of driving factors on ESV spatial heterogeneity. The findings reveal that (1) ESV displays both consistent and variable spatial patterns, with higher values in the west and north, lower values in the east and south, and a distinct high-value belt along water bodies; (2) strong spatial positive correlation and aggregation of ESV are observed at all grid scales, though these effects weaken as grid cell size increases; and (3) human activities exert a significant influence on regional ESV, with the interaction of multiple factors providing robust explanatory power for ESV variation, which diminishes with increasing scale. These results offer insights for optimizing ecosystem management and promoting sustainable development in the Yellow River Basin. Full article

To accurately grasp the land and ecological dynamics in the Henan section of the Yellow River Basin (YRB) and provide detailed local data for the ecological protection of the YRB, this article takes the Henan segment within the YRB as the research area, explores the spatio-temporal evolution of land use (LU) and landscape ecological risks (LERS), and predicts LU and LERS under various scenarios in the future based on the PLUS model. We found that: (1) From 2000 to 2020, object types in research area were given priority with cultivated land, forest land, and construction land, with construction land and cultivated land experiencing the largest changes of 5.71% and −6.34%, respectively. Changes in other land types varied within a ±3% range. The expansion of construction land principally encroached upon cultivated land, indicating significant urban sprawl. (2) The high-ecological-risk areas were clustered in the area centered in Zhengzhou, and the low-ecological-risk areas were distributed in the edge of the study area. As risk levels increased, the risk center gradually shifted towards the central regions, particularly around Luoyang and at the junction of Luoyang, Zhengzhou, and Jiaozuo. (3) The LU status in 2030 was projected using the PLUS model under three varied scenarios. The Kappa coefficient of the model was 0.81, and the overall accuracy was about 88.13%. Cultivated land, forest land, and construction land still accounted for the main part, and the area of cultivated land and construction land changed significantly. Based on this analysis of LERS prediction, the distribution of risk levels in different scenarios was different, but in general, high-ecological-risk areas and higher-ecological-risk areas accounted for the main part, while the study area’s edges were where low-ecological-risk zones were situated. Research can offer scientific and technological support for the sensible utilization and administration of resources, along with the protection of the ecological environment and regional sustainable development. Full article

This research has been performed to optimize the management of cultivated land fragmentation in the Henan Section of the Yellow River Basin, (“the research area”), coordinate the contradiction between increasing food demand and environmental constraints, maintain regional food security, and promote agricultural and rural modernization. The spatial and temporal evolution characteristics have been summarized by calculating the fragmentation index of the cultivated land landscape, and the driving factors explored with geographical detectors. Results show the following: (1) between 2000 and 2023, the landscape fragmentation index of cultivated land in the research region exhibited a pattern of initial decline followed by a subsequent rise. It decreased by 69.33% from 2000 to 2015 and increased by 138.42% from 2015 to 2023. Over the period from 2000 to 2023, the cultivated land landscape fragmentation index in the study area saw an overall reduction of 26.87%. (2) ”The reduction in cultivated land area and the decrease in landscape fragmentation” index accounted for 82.46% in the county unit. (3) The kernel density curve of the cultivated land landscape fragmentation index showed a unimodal distribution, but the shape was flat. The regions with a fragmentation index mainly range from 4 to 6. The regional cultivated land fragmentation distribution was more dispersed. (4) The average altitude, the distance from the Yellow River, the proportion of the construction land area and population density are the main driving factors. The combined impact of the proportion of the construction land area and population density contributes more than 46% to the cultivated land landscape fragmentation index. The interaction among various factors exerts a more pronounced effect than any individual factor alone. The intensity of the main interaction factors reaches above 0.67. The findings of this study can serve as a theoretical foundation for the sustainable utilization and development of cultivated land resources, as well as for ecological protection and construction in the Henan segment of the Yellow River Basin. Full article

Ecological security patterns (ESPs) are fundamental to safeguarding regional ecological integrity and enhancing human well-being. Consequently, research on conservation and restoration in critical regions is vital for ensuring ecological security and optimizing territorial ecological spatial configurations. Focusing on the Henan section of the Yellow River Basin, this study established the regional ESP and conservation–restoration framework through an integrated approach: (1) assessing four key ecosystem services—soil conservation, water retention, carbon sequestration, and habitat quality; (2) identifying ecological sources based on ecosystem service importance classification; (3) calculating a comprehensive resistance surface using the entropy weight method, incorporating key factors (land cover type, NDVI, topographic relief, and slope); (4) delineating ecological corridors and nodes using Linkage Mapper and the minimum cumulative resistance (MCR) theory; and (5) integrating ecological functional zoning to synthesize the final spatial conservation and restoration strategy. Key findings reveal: (1) 20 ecological sources, totaling 8947 km² (20.9% of the study area), and 43 ecological corridors, spanning 778.24 km, were delineated within the basin. Nineteen ecological barriers (predominantly located in farmland, bare land, construction land, and low-coverage grassland) and twenty-one ecological pinch points (primarily clustered in forestland, grassland, water bodies, and wetlands) were identified. Collectively, these elements form the Henan section’s Ecological Security Pattern (ESP), integrating source areas, a corridor network, and key regional nodes for ecological conservation and restoration. (2) Building upon the ESP and the ecological baseline, and informed by ecological functional zoning, we identified a spatial framework for conservation and restoration characterized by “one axis, two cores, and multiple zones”. Tailored conservation and restoration strategies were subsequently proposed. This study provides critical data support for reconciling ecological security and economic development in the Henan Yellow River Basin, offering a scientific foundation and practical guidance for regional territorial spatial ecological restoration planning and implementation. Full article

The Henan section of the Yellow River Basin (3.62 × 10⁴ km², 21.7% of Henan Province), a vital agro-industrial and politico-economic hub, faces frequent rainfall-induced geohazards. The 2021 “7·20” Zhengzhou disaster, causing 398 fatalities and CNY 120.06 billion loss, highlights its vulnerability to extreme weather. While machine learning (ML) aids geohazard assessment, rainfall-induced geological hazard susceptibility assessment (RGHSA) remains understudied, with single ML models lacking interpretability and precision for complex disaster data. This study presents a hybrid framework (IVM-ML) that integrates the Information Value Model (IVM) and ML. The framework uses historical disaster data and 11 factors (e.g., rainfall erosivity, relief amplitude) to calculate information values and construct a machine learning prediction model with these quantitative results. By combining IVM’s spatial analysis with ML’s predictive power, it addresses the limitations of conventional single models. ROC curve validation shows the Random Forest (RF) model in IVM-ML achieves the highest accuracy (AUC = 0.9599), outperforming standalone IVM (AUC = 0.7624). All models exhibit AUC values exceeding 0.75, demonstrating strong capability in capturing rainfall–hazard relationships and reliable predictive performance. Findings support RGHSA practices in the mid-Yellow River urban cluster, offering insights for sustainable risk management, land-use planning, and climate resilience. Bridging geoscience and data-driven methods, this study advances global sustainability goals for disaster reduction and environmental security in vulnerable riverine regions. Full article

As economic development and urbanization continue to accelerate, the Yellow River Basin experiences increasing challenges in balancing land use with ecological environmental protection. Understanding their interactions is crucial for sustainable regional development. This study adopts an integrated evaluation system and a coupling model to examine the dynamic interactions between land use functions and ecological quality in the Yellow River Basin section of Henan Province, China, from 2000 to 2020. The primary findings are as follows: (1) Land use functions improved from 0.276 to 0.303, with high-land-use-function areas expanding eastward. (2) Ecological quality initially declined but subsequently improved, with areas having good and excellent ecological quality increasing from 44.47% to 72.61%. (3) Coupling coherence stabilized, with moderate coordination covering 69.80% of the area by 2020. (4) The fractional vegetation cover and leaf area index were identified as critical influencing factors. Overall, these results highlight the importance of balanced land use planning and targeted ecological conservation strategies. This study provides valuable insights for policymakers aiming to enhance sustainable regional development, emphasizing the importance of integrating ecological security with economic growth in rapidly urbanizing areas. Full article

The Yellow River Basin is rich in coal resources, but the ecological environment is fragile, and the ecological degradation of vegetation is exacerbated by the disruption caused by high-intensity mining activities. Analyzing the dynamic evolution of vegetation in the Henan section of the Yellow River Basin and its mining areas over the long term run reveals the regional ecological environment and offers a scientific foundation for the region’s sustainable development. In this study, we obtained a long time series of Landsat imageries from 1987 to 2023 on the Google Earth Engine (GEE) platform and utilized geographically weighted regression models, Sen (Theil–Sen median) trend analysis, M-K (Mann–Kendall) test, coefficient of variation (CV), and the Hurst index to investigate the evolution of vegetation cover based on the kNDVI (the normalized difference vegetation index). This index is used to explore the spatial and temporal characteristics of vegetation cover and its future development trend. Our results showed that (1) The kNDVI value in the Henan section of the Yellow River Basin exhibited a trend of fluctuating upward at a rate of 0.0509/10a from 1987 to 2023. The kNDVI trend in the mining areas of the region aligned closely with the overall trend of the Henan section; however, the annual kNDVI in each mining area consistently remained lower than that of the Henan section and displayed a degree of fluctuation, predominantly characterized by medium–high variability, with areas of moderate and high fluctuations accounting for 73.5% of the total. (2) The kNDVI in the study area showed a significant improvement in vegetation cover and its future development trends. We detected a significant improvement in the kNDVI index in the area; yet, significant improvement in this index in the future might cause vegetation degradation in 87% of the study area, which may be closely related to multiple factors such as the intensity of mining at the mine site, anthropogenic disturbances, and climate change. (3) The vegetation status of the Henan section of the Yellow River Basin shows a significant positive correlation with distance from mining areas, accounting for 90.9% of the total, indicating that mining has a strong impact on vegetation cover. This study provides a scientific basis for vegetation restoration, green development of mineral resources, and sustainable development in the Henan section of the Yellow River Basin. Full article

Vegetation plays a crucial role in terrestrial ecosystems, and the FVC (Fractional Vegetation Coverage) is a key indicator reflecting the growth status of vegetation. The accurate quantification of FVC dynamics and underlying driving factors has become a hot topic. However, the scale effect on FVC changes and driving factors has received less attention in previous studies. In this study, the changes and driving factors of FVC at multiple scales were analyzed to reveal the spatial and temporal change in vegetation in the Henan section of the Yellow River basin. Firstly, based on the pixel dichotomy model, the FVC at different times and spatial scales was calculated using Landsat-8 data. Then, the characteristics of spatial and temporal FVC changes were analyzed using simple linear regression and CV (Coefficient of Variation). Finally, a GD (Geographic Detector) was used to quantitatively analyze the driving factors of FVC at different scales. The results of this study revealed that (1) FVC showed an upward trend at all spatial scales, increasing by an average of 0.55% yr⁻¹ from 2014 to 2022. The areas with an increasing trend in FVC were 10.83% more than those with a decreasing trend. (2) As the spatial scale decreased, the explanatory power of the topography factors (aspect, elevation, and slope) for changes in FVC was gradually strengthened, while the explanatory power of climate factors (evapotranspiration, temperature, and rainfall) and anthropogenic activities (night light) for changes in FVC decreased. (3) The q value of evapotranspiration was always the highest across different scales, peaking notably at a spatial scale of 1000 m ($q$ = 0.48). Full article

Hydrographic connectivity stands as a crucial indicator for analyzing the structural dynamics within river and lake systems. Nevertheless, the impact of changes in hydrographic connectivity, including structural and functional connectivity within extensive river basins, on the progression of agriculture, industry, and habitation remain scarcely explored. To bridge this gap, Henan province in China, traversed by the Yellow River, was selected as a case study. The extraction of water information was facilitated by employing a remote sensing-based Modified Normalized Difference Water Index (MNDWI), while Set Pair Analysis was utilized to construct a hydrographic connectivity evaluation system for the study area spanning the preceding two decades (2000–2020). The results revealed that for structural connectivity, agricultural land covers over 50% and prevails as the primary land-use type; reservoir and lake areas initially increased before subsequently decreasing. Human activities have exerted a profound influence on these changes. Meanwhile, the structural form of the water system has gradually improved, exhibiting an increasing complexity of river networks and a stabilizing connectivity configuration. As for functional connectivity, the natural function remains well-preserved, while the social function demonstrates a positive correlation with the expansion of industrial activities, eventually achieving an excellent level from a moderate level. Overall, agriculture dominated the water usage structure, with residential water consumption steadily increasing, thereby positively impacting hydrographic connectivity in the studied area. Full article

Rational differentiated utilization of cultivated land can effectively coordinate the contradiction between ecological protection, cultivated land utilization, and urban development. Therefore, this article adopts the southern section of the Yellow River Basin as an example, starting with vulnerability and resilience and then formulating an index system for evaluating farmland ecological vulnerability and farmland resilience. Moreover, this article combines Future Land-Use Simulation–Urban Growth Boundaries (FLUS–UGBs) to conduct urban development boundary simulations, which take the urban development boundary as restrictions and comprehensive division and determine the differentiated utilization zoning strategies for cultivated land to achieve coordinated development between ecological protection, cultivated land use, and urban development. The following results are presented: (1) The ecological vulnerability of the research area mainly involves low-to-medium vulnerability; the western and middle sections of the research area demonstrate high and low ecological vulnerability, respectively. (2) Areas with high resilience of cultivated land are mainly located in the mid-eastern part of the research area, and those with low resilience mainly involve the western mountains. (3) The four-quadrant method, the PLUS model, and the FLUS-UGB module are employed to determine differentiated usage zones for cultivated land to achieve rational allocation and effective use of resources. Full article

(1) Background: The Henan section of the Yellow River Basin plays an important role in the economic zone of the middle reaches of the Yellow River. However, ecological environmental geological problems such as soil erosion have seriously affected the lives of residents and economic development, resulting in increasingly prominent conflicts between humans and the environment. Therefore, this paper made use of remote sensing images and other reference data, integrated image classification, remote sensing inversion and statistical analysis methods to explore the ecological environmental geological problems and their causes in the Henan section of the Yellow River Basin. (2) Results: the main eco-environmental geological problems in the Sanmenxia–Zhengzhou section are serious soil erosion, degradation of water conservation function and being prone to geological disasters. The main eco-environmental geological problems in the Zhengzhou–Puyang section are poor water and soil conservation function, degradation of water conservation function and poor biodiversity maintenance function. In the last 19 years, the eco-environmental geological problems in the Henan section of the Yellow River Basin have shown a significant improvement trend as a whole. Along the main stream of the Yellow River in Sanmenxia, Luoyang, Jiyuan, Jiaozuo, Zhengzhou and other areas, the eco-environmental geological problems are still prominent; altitude, vegetation and rainfall are the key driving factors of eco-environmental geological problems in the Sanmenxia–Zhengzhou section and rainfall, vegetation and land-use type are the key driving factors in the Zhengzhou–Puyang section. (3) Conclusions: This study comprehensively considered the three aspects of ecology, environment and geology in a total of five research topics. The temporal and spatial distribution characteristics and driving factors of ecological environmental geological problems in the Yellow River Basin were analyzed, which could provide technical support for ecological environmental protection and high-quality development in the Yellow River Basin. Full article