Search Results (228)

The floodplain landscape of the lower Yellow River is jointly shaped by natural water-sediment processes and human activities. With intensified regulation by large reservoirs and increasing human development intensity, the landscape pattern of the floodplain has undergone significant changes. Clarifying the relative contributions of natural and anthropogenic factors, as well as their interactive mechanisms, is crucial for ecological management of the floodplain. Based on 40-year long-term land-use data and hydrological and meteorological observations, this study integrates landscape metrics, the human interference index (HI), grey relational analysis, and partial least squares regression to quantify the spatiotemporal dynamics of landscape pattern in the floodplain of the lower Yellow River and to elucidate the driving mechanisms underlying landscape-pattern evolution. The results indicate that (1) during the study period, the areas of cultivated land and built-up land in the floodplain continuously increased, whereas natural wetlands and grassland decreased accordingly. Taking 2000 as a breakpoint, the rate and direction of landscape change exhibited stage-dependent differences. (2) Landscape pattern metrics changed nonlinearly: the number of patches decreased first and then increased; the patch cohesion index increased first and then declined; and Shannon’s diversity index showed an overall downward trend. These changes suggest a process of landscape consolidation induced by agricultural cultivation, followed by re-fragmentation driven by the expansion of built-up land. (3) Driving-mechanism analysis shows that the HI is the primary driver of the current changes in floodplain landscape pattern. After the operation of the Xiaolangdi Dam, water-sediment conditions tended to stabilize and flood risk in the floodplain decreased, thereby creating favourable conditions for human activities. This study highlights the stage-dependent influences of natural and anthropogenic factors on floodplain landscape evolution under dam regulation and suggests that management strategies should be adapted to the current re-fragmentation phase, prioritizing the strict control of agricultural expansion and the restoration of ecological corridors to mitigate anthropogenic interference under stable dam regulation. Full article

Soil organic carbon (SOC) plays a vital role in regional carbon cycling and ecosystem services. However, previous studies have primarily focused on spatial patterns and environmental drivers, with limited attention to long-term observations, underlying mechanisms, and large-scale modeling. In this study, we collected surface soil samples (0–20 cm) and integrated topography, soil physicochemical properties, climate, vegetation, and MODIS remote sensing data to develop 16 SOC prediction models using linear regression and machine learning approaches. SOC was significantly correlated with latitude, mean annual temperature, and precipitation and negatively associated with several remote sensing indices. The LASSO-selected variable set combined with a support vector machine (SVM) achieved the highest predictive accuracy (R² = 0.53, RMSE = 36.19). From 2001 to 2020, the mean SOC stock in the Yellow River source region was estimated at 1683.98 g C/m², showing higher values in the southeast and lower values in the northwest. Alpine meadow exhibited the highest total stock due to its extensive coverage, whereas the cold temperate wet coniferous forest had higher mean content and unit area value, indicating strong carbon sequestration potential. This study identifies key SOC drivers and mechanisms, provides quantitative estimates of regional SOC content and stock, and offers a scientific basis for grassland carbon management and large-scale digital soil mapping. Full article

As an integrated framework linking resource use and environmental sustainability, the WEF (Water–Energy–Food) system plays a vital role in achieving sustainable agricultural development. Focusing on the irrigation districts in the lower reaches of the Yellow River, this study constructed and applied a Super-Undesirable-SBM (super-efficiency undesirable slacks-based measure) model and a GTWR (geographically and temporally weighted regression) model from a WEF perspective to systematically analyze the spatiotemporal evolution and driving mechanisms of WEFSE (Water–Energy–Food Synergistic Efficiency) from 2000 to 2020. The overall WEFSE exhibited a continuous upward trend, with the spatial pattern gradually shifting from the southwest to the northeast and regional disparities becoming more pronounced. The efficiency demonstrated a significant positive spatial autocorrelation, indicating a stable clustering pattern of “high–high” and “low–low” efficiency areas. In terms of driving mechanisms, WEFSE evolved from being dominated by socio-economic drivers to a composite system jointly influenced by ecological and structural factors. Among these, PD (population density) and WP (proportion of water area) had increasingly positive effects, whereas PRE (precipitation) and NDVI (normalized difference vegetation index) imposed notable constraints. Meanwhile, PCL (proportion of cultivated land), GP (proportion of grassland), and AT (average temperature) exhibited significant spatial differentiation. This study highlights that the assessment of WEFSE and identification of its driving mechanisms using the Super-Undesirable-SBM and GTWR models can help to uncover the spatiotemporal dynamics of agricultural resource utilization, providing methodological support and decision-making insights for optimizing resource allocation and promoting sustainable development in the Yellow River irrigation districts and other complex agricultural systems. Full article

Macrobenthic fauna are vital to the ecological health of the Yellow River Estuary, yet their long-term population drivers are poorly understood. This study used Boosted Regression Tree models to analyze the spatio-temporal distribution of five dominant species: Glycinde gurjanovae, Sternaspis scutata, Moerella jedoensis, Theora fragilis, and Raphidopus ciliatus. Key environmental drivers included ammonia nitrogen, water depth, sand content of sediment, and water temperature. Specifically, S. scutata and R. ciliatus preferred deeper waters, M. jedoensis favored habitats with moderate sand content of sediment, T. fragilis primarily occurred at water temperatures lower than 25 °C, and G. gurjanovae distribution was most influenced by ammonia nitrogen. All species exhibited a preference for lower ammonia nitrogen concentrations. Inorganic nitrogen and freshwater discharge from the Yellow River significantly influenced the distribution of G. gurjanovae, whereas river discharge alone was positively correlated with areas exhibiting a high occurrence probability (>0.5) for M. jedoensis. Future studies that integrate comprehensive seasonal monitoring data, hydrodynamic conditions, and food availability could further enhance predictive accuracy, providing stronger theoretical and technical support for ecological conservation and management in the Yellow River Estuary. Full article

To clarify the multifunctional supply–demand relationship of cultivated land in the Yellow River Basin of Henan Province, and to provide decision-making support for strengthening cultivated land protection and promoting sustainable agricultural and rural utilisation within this basin, this study employs the entropy value method, hierarchical demand theory, and geographically weighted regression (GWR) models. Analyses were conducted at three scales—functional zoning, municipal, and county—to reveal the spatiotemporal evolution of supply and demand for the productive, ecological, social, and landscape functions of cultivated land from 2013 to 2023. This comprehensive assessment evaluates the supply and demand levels of multifunctional cultivated land within the study area and analyses the risks associated with shortages in multifunctional supply and demand. Results indicate: A significant spatial negative correlation exists between the supply and demand levels of multifunctional agricultural land in the Yellow River Basin of Henan Province. The supply level was in the range of [0.08–0.65], exhibiting an overall slight decreasing trend and a spatial pattern of higher values in the east and lower values in the west. The demand level was in the range of [0.11–0.82], showing an overall increasing trend and a spatial pattern of higher values at both ends and lower values in the middle. Between 2013 and 2023, the severity of multifunctional supply–demand scarcity risk gradually improved, exhibiting an overall spatial distribution pattern characterised by scarcity in core and expansion zones, surplus in coordination zones. Risk severity values ranged from −0.08 to 0.02 in core zones, 0.03 to 0.11 in expansion zones, and 0.08 to 0.16 in coordination zones. To optimise the multifunctional supply–demand structure of cultivated land in Henan’s Yellow River Basin, high-risk areas require targeted management and optimisation to mitigate supply–demand risks. The balance between multifunctional supply and demand for cultivated land should be achieved through tailored approaches, such as standardising cross-regional allocation of multifunctional cultivated land resources and establishing a multi-scale, integrated compensation mechanism for protecting cultivated land functions. Full article

The Yellow River Basin (YRB), a vital region for agricultural production in China, is currently grappling with severe rural population shrinkage and variations in the carbon emission intensity across the basin. Based on census data from 2010 to 2020, this study categorized 320 counties by population shrinkage type and applied baseline regression and upper–middle–lower reach heterogeneity analysis to explore population shrinkage’s impact on carbon intensity. The results indicated that population shrinkage in the Yellow River Basin during 2010–2020 was primarily characterized by a rural population decline, which exerted divergent impacts on carbon emissions across the basin. Consequently, the upper reaches were identified as a critical problem area where severe population shrinkage coexisted with a high carbon emission intensity. Based on these findings, targeted and region-specific strategies and policies are proposed. Specifically, High Shrinkage-High Emission (H-H) regions need to focus on promoting ecological migration and the coordinated transformation of industries; High Shrinkage-Low Emission (H-L) regions should strengthen policy coordination in the border areas of the middle and upper reaches; Low Shrinkage-High Emission (L-H) regions should promote the low-carbon technological transformation of traditional industries in downstream counties; and Low Shrinkage-Low Emission (L-L) regions should refine the low-carbon transformation model in the core downstream areas. Full article

This study collected 820 topsoil samples from cultivated lands across Ningxia, covering the Yellow River irrigation area, the central arid zone, and the southern mountainous region. The ordinary kriging were spatially interpolated to analyze As, Hg, Cd, Cr, and Pb heavy-metal pollution spatial patterns. Pollution was evaluated using the Nemerow and geoaccumulation (I_(geo)) indices, and sources quantified via Pearson correlations, PCA (Principal Component Analysis), and PMF (Positive Matrix Factorization). The results indicated that Hg and Cd posed the highest ecological risks. The overall mean concentrations (mg.kg⁻¹) of Hg, Cd, As, Pb, and Cr were 0.04, 0.27, 9.91,23.81, and 57.34, respectively. Compared with the background values, they were 1.90, 2.41, 0.83, 1.14, 2.74 times higher, respectively. Geospatially, regions with higher pollution probabilities for Cd, Cr, Pb, Hg, and As were concentrated in the northern and central parts of Ningxia, whereas the southern region exhibited lower pollution probabilities. pH significantly influenced the accumulation and spatial distribution of heavy metals in soil. Source apportionment identified three primary contributors: transportation and natural parent materials (As, Pb, Cr), industrial activities (Hg), and agricultural practices (Cd). Hg and Cd were identified as the key risk elements requiring prioritized management. These results enhance understanding of the pollution levers of heavy metals in Ningxia cultivated soils, and also provide foundation for developing more scientific and precise soil risk control policies, offering significant practical value for environmental risk management. Full article

The Yellow River Basin faces severe challenges in water security and ecological protection: at the basin scale, complex hydrological processes and fragile ecosystems undermine the water security pattern; at the local scale, waterlogging risks have intensified in Zhengzhou—a core city in the lower reaches—impacting the city itself and also exerting negative effects on the basin’s water security. To address this, mapping the scientific layout of green infrastructure (GI) is urgent. However, existing studies on GI layout at the basin-urban scale have certain limitations: neglect of underlying surface spatial heterogeneity, insufficient integration of natural, hydrological and social factors’ synergies, and lack of research on large-scale basins and cities, especially ecologically sensitive areas with complex hydrological processes. To fill these gaps, this study proposes an integrated framework (SCS–GIS–MCDM) combining the SCS hydrological model, GIS spatial analysis, and multi-criteria decision making (MCDM). The SCS hydrological model is refined via localized parameter calibration for better accuracy; indicator weights are determined through the MCDM framework; and green infrastructure (GI) suitability maps are generated by integrating ArcGIS spatial analysis with fuzzy logic. Results show that (1) 6.8% of Zhengzhou is highly suitable for GI, mainly in riparian areas and the Yellow River alluvial plain; (2) sensitivity analysis confirms flooded areas and runoff corridors as key drivers; (3) spatial validation against government-issued ecological control zone plans demonstrates the model’s value in balancing flood safety and socio-economy. This framework provides a replicable application model for GI construction in cities along the Yellow River Basin, thereby supporting urban planners in making evidence-based decisions for sustainable blue–green space planning. Full article

The dynamic changes in vegetation significantly impact the sustainability, safety, and stability of ecosystems in the source region of the Yellow River. However, the spatiotemporal patterns and driving factors of these changes remain unclear. The MODIS NDVI dataset (1998–2018), together with climatic records from meteorological stations and socio-economic statistics, was collected to investigate the spatiotemporal characteristics of vegetation coverage in the study area. For the analysis, we employed linear trend analysis to assess long-term changes, Pearson correlation analysis to examine the relationships between vegetation dynamics and climatic as well as anthropogenic factors, and t-tests to evaluate the statistical significance of the results. The results indicated the following: (1) From 1998 to 2018, vegetation in the source region of the Yellow River generally exhibited an increasing trend, with 92.7% of the area showed improvement, while only 7.3% experienced degradation. The greatest vegetation increase occurred in areas with elevations of 3250–3750 m, whereas vegetation decline was mainly concentrated in regions with elevations of 5250–6250 m. (2) Seasonal differences in vegetation trends were observed, with significant increases in spring, summer, and winter, and a non-significant decrease in autumn. Vegetation degradation in summer and autumn remains a concern, primarily in southeastern and lower-elevation areas, affecting 25% and 27% of the total area, respectively. The maximum annual average NDVI was 0.70, occurring in 2018, while the minimum value was 0.59, observed in 2003. (3) Strong correlations were observed between vegetation dynamics and climatic variables, with temperature and precipitation showing significant positive correlations with vegetation (r = 0.66 and 0.60, respectively; p < 0.01, t-test), suggesting that increases in temperature and precipitation serve as primary drivers for vegetation improvement. (4) Anthropogenic factors, particularly overgrazing and rapid population growth (both human and livestock), were identified as major contributors to the degradation of low-altitude alpine grasslands during summer and autumn periods, with notable impacts observed in counties with higher livestock density and population growth, indicating that for each unit increase in population trend, the NDVI trend decreases by an average of 0.0001. The findings of this research are expected to inform the design and implementation of targeted ecological conservation and restoration strategies in the source region of the Yellow River, such as optimizing land-use planning, guiding reforestation and grassland management efforts, and establishing region-specific policies to mitigate the impacts of climate change and human activities on vegetation ecosystems. Full article

Yellow River Delta National Nature Reserve plays a critical role in ecological conservation, and assessing its ecosystem service value (ESV) is essential for guiding sustainable management strategies that harmonize development and preservation. This study was motivated by the need to generate actionable insights for adaptive conservation planning in this vulnerable coastal region. We evaluated the spatiotemporal dynamics of ESV from 2000 to 2020 using a combination of remote sensing, geographic information system analyses, and statistical modeling. Primary drivers influencing the spatial heterogeneity of ecosystem service value were identified through geographical detector analysis, and future trends were projected based on historical patterns. The results revealed that (1) ESV showed a clear spatial gradient, with higher values in coastal zones, moderate values along river channels, and lower values inland, and exhibited an overall significant increase over the two decades, primarily driven by improvements in regulating services; (2) wetland area and precipitation were the most influential factors, though socio-economic elements and environmental conditions also contributed to ESV distribution; and (3) future ESV is expected to follow current trends, reinforcing the importance of current management practices. Given that the continuous increase in ESV from 2000 to 2020 was predominantly attributed to water body expansion, future conservation strategies should prioritize the protection and restoration of these water resources. Full article

Frequent channel migrations of the Yellow River, coupled with increasing human disturbances, have driven significant land cover changes in the Yellow River Delta (YRD) over time. Accurate estimation of aboveground biomass (AGB) and clarification of the impact of land cover changes on AGB are crucial for monitoring vegetation dynamics and supporting ecological management. However, field-based biomass samples are often time-consuming and labor-intensive, and the quantity and quality of such samples greatly affect the accuracy of AGB estimation. This study developed a robust AGB estimation framework for the YRD by synthesizing 4717 field-measured samples from the published scientific literature and integrating two critical ecological indicators: leaf area index (LAI) and length of growing season (LGS). A random forest (RF) model was employed to estimate AGB for the YRD from 2001 to 2022, achieving high accuracy (R² = 0.74). The results revealed a continuous spatial expansion of AGB over the past two decades, with higher biomass consistently observed in western cropland and along the Yellow River, whereas lower biomass levels were concentrated in areas south of the Yellow River. AGB followed a fluctuating upward trend, reaching a minimum of 204.07 g/m² in 2007, peaking at 230.79 g/m² in 2016, and stabilizing thereafter. Spatially, western areas showed positive trends, with an average annual increase of approximately 10 g/m², whereas central and coastal zones exhibited localized declines of around 5 g/m². Among the changes in land cover, cropland and wetland changes were the main contributors to AGB increases, accounting for 54.2% and 52.67%, respectively. In contrast, grassland change exhibited limited or even suppressive effects, contributing −6.87% to the AGB change. Wetland showed the greatest volatility in the interaction between area change and biomass density change, which is the most uncertain factor in the dynamic change in AGB. Full article

Agricultural soils near industrial parks in the Yellow River bend region face severe heavy metal pollution, posing a significant to human health. This study integrated field sampling with laboratory analysis and applied geostatistical analysis, positive matrix factorization (PMF) modeling, and health risk assessment models to systematically investigate the pollution levels, spatial distribution, sources, and ecological health risks of heavy metals in the area. The main findings are as follows: (1) The average concentrations of the eight heavy metals (Hg, Cr, Cu, Pb, Zn, As, Cd, and Ni) in the study area were 0.04, 48.3, 54.3, 45.7, 70.0, 22.9, 0.4, and 35.7 mg·kg⁻¹, respectively. The concentrations exceeded local background values by factors ranging from 1.32 to 11.2. Exceedances of soil screening and control values were particularly pronounced for Cd and As. Based on the geoaccumulation index, over 75% of the sampling sites for Cr, Pb, Zn, and Cd were classified as moderately to heavily polluted. Potential ecological risk assessment highlighted Cd as the significant ecological risk factor, indicating considerable heavy metal pollution in the region. (2) Kriging interpolation demonstrated elevated concentrations in the western (mid-upper) and eastern (mid-lower) subregions. Pearson correlation analysis suggested common sources for Cu-Pb-As-Cd and Cr-Zn-Ni. (3) PMF source apportionment identified four primary sources: traffic emissions (38.19%), natural and agricultural mixed sources (34.55%), metal smelting (17.61%), and atmospheric deposition (10.10%). (4) Health risk assessment indicated that the non-carcinogenic risk for both adults and children was within acceptable limits (adults: 0.065; children: 0.12). Carcinogenic risks were also acceptable (adults: 5.67 × 10⁻⁵; children: 6.70 × 10⁻⁵). In conclusion, priority should be given to the control of traffic emissions and agriculturally derived sources in the management of soil heavy metal contamination in this region, while the considerable contribution of smelting activities warrants heightened attention. This study provides a scientific basis for the prevention, control, and targeted remediation of regional soil heavy metal pollution. Full article

Evaluating and enhancing system resilience is essential to strengthen the regional ability to external shocks and promote the synergistic development of environment, economy and society. Taking the Upper Yellow River (UYR) as an example, this paper constructed a resilience evaluation index system for the environment—economy—society (EES) composite system. A three-dimensional space vector model was built to calculate the resilience development index (RDI) of three subsystems and the composite system from 2009 to 2022. Pathways supporting high resilience levels of the composite system were examined using the fuzzy-set qualitative comparative analysis (fsQCA) method from a configuration perspective. The results revealed that (1) the RDI of three subsystems and the composite system in the UYR showed an increasing trend; relatively, the environment and economy subsystems were lower, and their RDI fluctuated between 0.01 and 0.06 for most cities. (2) The emergence of high resilience is not absolutely dominated by a single factor, but rather the interaction of multiple factors. To achieve high resilience levels, all the cities must prioritize both environmental protection and economic structure as core strategic pillars. The difference is that eastern cities need to further consider social development and life quality, while western cities need to consider social development, life quality, and social security. Other cities including Lanzhou, Baiyin, Tianshui, and Ordos should focus on social construction and social security. Exploring the interactive relationship between various influencing factors of the resilience of the composite system from a configuration perspective has to some extent promoted the transformation from a single contingency perspective to a holistic and multi-dimensional perspective. These findings provide policy recommendations for achieving sustainable development in the UYR and other ecologically fragile areas around the world. Full article

Ecotourism is vital for harmonious human–nature coexistence in national parks, making the quantification of its spatial suitability an urgent scientific priority. This study took the Yellow River Estuary National Park (YRENP) as the study area and constructed a multi-criteria evaluation model by interpreting the relationship between Ecotourism Environmental Carrying Capacity (EECC) and Ecotourism Development Suitability (EDS), addressing the critical gap in the integrated land–sea ecotourism suitability assessment for coastal national parks, using the Analytic Hierarchy Process (AHP) to determine indicator weights and ArcGIS for spatial visualization. Multi-source geospatial data, including land use, NDVI, DEM, and socio-economic datasets, were integrated. The results revealed the following: (1) Overall moderate EECC levels with stronger terrestrial capacity contrast with weaker marine capacity—high-carrying zones being limited to nearshore areas; (2) The overall EDS level was favorable, where southern section significantly outperformed northern zones, forming concentrated high-suitability clusters encircling lower-suitability areas; (3) Marine EDS slightly exceeds terrestrial suitability, with optimal coastal zones transitioning landward toward progressively higher suitability. This research provided a replicable methodology for ecotourism suitability assessment in coastal protected areas and supported sustainable spatial planning in land–sea integrated national parks. Full article

Accurate assessment of ecosystem service value (ESV) is crucial for sustainable environmental management, especially in regions with high ecological sensitivity and significant socioeconomic importance. This study focuses on the Yellow River Basin and integrates the land-use transition matrix, equivalent factor method, ecosystem service trade-off and synergy analysis, and the optimized parameters geographical detector to analyze the spatiotemporal evolution and driving mechanisms of ESV from 2000 to 2023. The results show that (1) cropland and grassland are the main land-use types in the Yellow River Basin, and during rapid urbanization, the expansion of construction land mainly comes at the expense of cropland and grassland. (2) the total ESV in the basin has steadily increased, with grassland as the primary contributor among land types; regulating services, particularly hydrological regulation, are the core ecosystem services in terms of supply, regulation, support, and cultural functions. (3) High-ESV areas in the eastern and central parts of the basin have expanded over time, exhibiting a spatial pattern of higher values in the west and lower in the east, distributed mainly along the river, with clustering effects gradually weakening. (4) Ecosystem services demonstrated predominantly synergistic relationships, suggesting potential for integrated ecosystem management. (5) Population density, DEM, mean annual temperature, and slope are the dominant factors influencing spatial variation in ESV, with the combined effects of topography and climate significantly enhancing the explanation of ESV heterogeneity. This study deepens the understanding of the evolutionary mechanisms of ecosystem services in the Yellow River Basin and provides scientific support and decision-making references for regional ecological compensation mechanisms, optimized land resource allocation, and watershed ecosystem management. Full article