Search Results (230)

Rapid socio-economic development and the impact of human activities have exerted tremendous pressure on the groundwater system of the Dawen River Basin (DRB), the largest tributary in the middle and lower reaches of the Yellow River. Hydrochemical studies on the DRB have largely centered on the upstream Muwen River catchment and downstream Dongping Lake, with some focusing solely on karst groundwater. Basin-wide evaluations suggest good overall groundwater quality, but moderate to severe contamination is confined to the lower Dongping Lake area. The hydrogeologically complex mid-reach, where the Muwen and Chaiwen rivers merge, warrants specific focus. This region, adjacent to populous areas and industrial/agricultural zones, features diverse aquifer systems, necessitating a thorough analysis of its hydrochemistry and origins. This study presents an integrated hydrochemical, isotopic investigation and EWQI evaluation of groundwater quality and formation mechanisms within the multiple groundwater types of the central DRB. Central DRB groundwater has a pH of 7.5–8.2 (avg. 7.8) and TDSs at 450–2420 mg/L (avg. 1075.4 mg/L) and is mainly brackish, with Ca²⁺ as the primary cation (68.3% of total cations) and SO₄²⁻ (33.6%) and NO₃⁻ (28.4%) as key anions. The Piper diagram reveals complex hydrochemical types, primarily HCO₃·SO₄-Ca and SO₄·Cl-Ca. Isotopic analysis (δ²H, δ¹⁸O) confirms atmospheric precipitation as the principal recharge source, with pore water showing evaporative enrichment due to shallow depths. The Gibbs diagram and ion ratios demonstrate that hydrochemistry is primarily controlled by silicate and carbonate weathering (especially calcite dissolution), active cation exchange, and anthropogenic influences. EWQI assessment (avg. 156.2) indicates generally “good” overall quality but significant spatial variability. Pore water exhibits the highest exceedance rates (50% > Class III), driven by nitrate pollution from intensive vegetable cultivation in eastern areas (Xiyangzhuang–Liangzhuang) and sulfate contamination from gypsum mining (Guojialou–Nanxiyao). Karst water (26.7% > Class III) shows localized pollution belts (Huafeng–Dongzhuang) linked to coal mining and industrial discharges. Compared to basin-wide studies suggesting good quality in mid-upper reaches, this intensive mid-reach sampling identifies critical localized pollution zones within an overall low-EWQI background. The findings highlight the necessity for aquifer-specific and land-use-targeted groundwater protection strategies in this hydrogeologically complex region. Full article

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin. Full article

As an ecological transition zone, the ecosystem of the Qin River Basin in the middle reaches of the Yellow River is of great significance to the regional ecological balance. With the rapid socio-economic development, land use changes are significant, and the spatial and temporal patterns of ecosystems are evolving. Exploring its dynamics and driving mechanisms is crucial to the ecological protection and sustainable development of watersheds. This research systematically examines the spatiotemporal dynamics and driving mechanisms of ecosystem patterns in the middle Yellow River’s Qin River Basin (1990–2020). Quantitative assessments integrating ecosystem transition metrics and redundancy analysis reveal three critical insights: (1) dominance of agricultural land and woodland (74.81% combined coverage), with grassland (18.58%) and other land types (6.61%) constituting secondary components; (2) dynamic interconversion between woodland and grassland accompanied by urban encroachment on agricultural land, manifesting as net reductions in woodland (−13.74%), farmland (−6.60%), and wetland (−38.64%) contrasting with grassland (+43.34%) and built-up area (+116.63%) expansion; (3) quantified anthropogenic drivers showing agricultural intensification (45.03%) and ecological protection measures (36.50%) as primary forces, while urbanization account for 18.47% of observed changes. The first two RDA ordination axes significantly (p < 0.01) explain 68.3% of the variance in ecosystem evolution, particularly linking land-use changes to socioeconomic indicators. Based on these findings, the study proposes integrated watershed management strategies emphasizing scientific land-use optimization, controlled urban expansion, and systematic ecological rehabilitation to enhance landscape stability in this ecologically sensitive region. The conclusions of this study have important reference value for other ecologically sensitive watersheds in land use planning, ecological protection policy making, and ecological restoration practice, which can provide a theoretical basis and practical guidance. Full article

The imbalance between urban and rural development has become a global structural problem that needs to be solved urgently. In this context, the tourism industry, with its strong correlation and cross-regional integration characteristics, provides a key practical entry point and mechanism for systematically promoting integrated development by stimulating factor flow, reconstructing the value chain, and reshaping local identity. Based on the synergetic theory, this paper constructs the theoretical framework of the synergetic evolution of the tourism industry and urban–rural integration, and analyzes the synergetic effect of the tourism industry and urban–rural integration in 58 prefecture-level cities in the Yellow River Basin from 2007 to 2021 and the dynamic characteristics of its spatio-temporal evolution by using the entropy TOPSIS, Haken model, and spatial Markov chain methods. The results show the following: ① As the order parameter of synergistic evolution, the tourism industry dominates the evolution direction of the whole system, mainly showing positive feedback effect, showing a significant stage characteristic in general, and gradually reducing the difference from the initial regional differentiation to the middle stage, finally reaching a higher level of unity. ② The synergic evolution of the tourism industry and urban–rural integration in the Yellow River Basin presents significant temporal and spatial differences in the upstream, midstream, and downstream, with the overall characteristics of “collaborative improvement in the upstream, significant agglomeration in the midstream, and reverse decoupling in the downstream”. ③ The dynamic evolution of the synergistic development of the tourism industry and urban–rural integration in the Yellow River Basin has significant characteristics of spatial interaction and dynamic transfer. Its level has the effect of “path dependence”, showing a good trend of upward transfer, and the spatial neighborhood has a significant impact on the synergetic level transfer. The development trend of each region shows that “the upstream region is upward and stable, the midstream region has significant agglomeration and diffusion effects, and the downstream region is driven by polar nuclei and spatial differentiation”. Full article

Traditional villages possess considerable heritage values. Tourism provides an effective way to protect and revitalize the traditional village heritages. Current research has insufficient consideration of tourism potential when constructing the spatial utilization pattern of traditional villages. This study aims to build a spatial utilization pattern of traditional villages within the Yellow River Basin by assessing the tourism potential of each traditional village via the Combined Weight Method and identifying cultural heritage corridors through the application of the Minimum Cumulative Resistance model. The results indicate the following: (1) The traditional villages situated within the Yellow River Basin demonstrate an uneven spatial distribution, with a notable concentration in the middle and lower reaches. (2) The traditional villages located in the middle and lower reaches possess greater tourism potential compared to those found in the upstream, and they are primarily situated in Shanxi and Henan provinces. (3) In light of the cultural attributes, this study proposes a spatial utilization pattern characterized by “four core areas, seven cultural zones, and a three–tiered corridor system”. These findings promote the development of traditional villages while preserving their heritage values, strengthen the communication and integration of regional cultures, and offer practical guidance towards regional coordination and enduring development. Full article

Understanding the relationship between regional vegetation dynamics and water resources is essential for improving integrated vegetation–water management, enhancing ecosystem services, and advancing the sustainable development of ecological–economic–social systems. As China’s second largest river basin, the Yellow River Basin (YRB) is ecologically fragile and experiences severe water scarcity. Vegetation changes further intensify conflicts between water supply and demand. To investigate the evolution and interaction mechanisms between vegetation and water resources in the YRB, this study uses the InVEST model to simulate annual water yield (Wyield) from 1982 to 2020 and applies the Dimidiate Pixel Model (DPM) to estimate fractional vegetation cover (FVC). The Theil–Sen method is applied to quantify the spatiotemporal trends of Wyield and FVC. A pixel-based second-order partial correlation analysis is performed to clarify the intrinsic relationship between FVC and Wyield at the grid scale. The main conclusions are as follows: (1) During the statistical period (1982–2020), the multi-year average annual Wyield in the YRB was 73.15 mm. Interannual Wyield showed a clear fluctuating trend, with an initial decline followed by a subsequent increase. Wyield showed marked spatial heterogeneity, with high values in the southern upper reaches and low values in the Longzhong Loess Plateau and Hetao Plain. During the same period, about 68.74% of the basin experienced increasing Wyield, while declines were concentrated in the upper reaches. (2) The average FVC across the basin was 0.51, showing a significant increasing trend during the statistical period. The long-term average FVC showed significant spatial heterogeneity, with high values in the Fenwei Plain, Shanxi Basin, and Taihang Mountains, and low values in the Loess Plateau and Hetao Plain. Spatially, 68.74% of the basin exhibited significant increases in FVC, mainly in the middle and lower reaches, while decreases were mostly in the upper reaches. (3) Areas with significant FVC–Wyield correlations covered a small portion of the basin: trade-off regions made up 10.35% (mainly in the southern upper reaches), and synergistic areas accounted for 5.26% (mostly in the Hetao Plain and central Loess Plateau), both dominated by grasslands and croplands. Mechanistic analysis revealed spatiotemporal heterogeneity in FVC–Wyield relationships across the basin, influenced by both natural drivers and anthropogenic activities. This study systematically explores the patterns and interaction mechanisms of FVC and Wyield in the YRB, offering a theoretical basis for regional water management, ecological protection, and sustainable development. Full article

The distortion of energy prices has become an important obstacle to the high-quality development of China’s economy. Moreover, energy price distortions are not merely a domestic issue. They may trigger carbon leakage by diverting emissions-intensive production to countries with cheaper energy. Although the existing literature has extensively examined the effects of energy price distortions, two significant research gaps remain. First, most studies treat energy price distortions merely as an influencing factor, lacking a systematic analysis that places it at the core. Second, the spatial correlation characteristics of energy price distortions are often overlooked. This study measures the degree of energy price distortions across Chinese provinces from 2000 to 2022 and employs methods such as the Global Moran’s I, Local Moran’s I, and kernel density estimation to systematically analyze the spatial correlation, spatial distribution of coordination indices, and dynamic evolution patterns of these distortions. The results reveal that: (1) the overall degree of energy price distortions in China exhibited a trend of rising first and then declining, with significant regional disparities; (2) the regional gap followed an “expansion-contraction” trajectory; (3) there is notable spatial autocorrelation, with high-distortion areas concentrated in Northeast China, the middle reaches of the Yellow River, and Northwest China; and (4) the dynamic evolution suggests that distortion levels in high- and medium-value regions may continue to decline, while those in low-value regions may increase. This study fills a critical gap in the systematic spatial analysis of energy price distortions and provides new empirical evidence and policy insights for advancing market-oriented reforms in energy markets. Full article

Green development stands as an imperative pathway for China’s growth model. Enhancing green economic efficiency is crucial to maintaining sustainable development in the Yellow River Basin. The hierarchical governance structure of China’s economic development system inherently links competition among governments to potential impacts on the basin’s green economic efficiency, yet research in this area remains scarce. This study utilizes a panel data structured dataset containing both temporal and cross-sectional dimensions from nine provinces in the Yellow River Basin to investigate how tax competition among local governments affects green economic efficiency. The empirical results demonstrate that tax competition hinders green economic efficiency in the Yellow River Basin, exhibiting spatial heterogeneity in its inhibitory effect. Specifically, the inhibitory effect on the middle reaches is approximately twice as significant as that observed on the upper reaches, while the inhibitory effect on the lower reaches is found to be facilitative. In addition, the upgrading of industrial structure and industrial agglomeration triggered by tax competition partially alleviate the inhibitory effect on green economic efficiency. Therefore, policymakers can promote the sustainable development of the Yellow River Basin by optimizing the tax system, implementing regional differentiation strategies, optimizing industrial layout, and promoting the development of green clusters. Full article

Flood hazards caused by intense short-term precipitation have led to significant social and economic losses and pose serious threats to human life and property. Accurate disaster risk assessment plays a critical role in verifying disaster statistics and supporting disaster recovery and reconstruction processes. In this study, a novel Large-Scale Flood Risk Assessment Model (LS-FRAM) is proposed, incorporating the dimensions of hazard, exposure, vulnerability, and coping capacity. Multi-source heterogeneous data are utilized for evaluating the flood risks. Soil erosion modeling is incorporated into the assessment framework to better understand the interactions between flood intensity and land surface degradation. An index system comprising 12 secondary indicators is constructed and screened using Pearson correlation analysis to minimize redundancy. Subsequently, the Analytic Hierarchy Process (AHP) is utilized to determine the weights of the primary-level indicators, while the entropy weight method, Fuzzy Analytic Hierarchy Process (FAHP), and an integrated weighting approach are combined to calculate the weights of the secondary-level indicators. This model addresses the complexity of large-scale flood risk assessment and management by incorporating multiple perspectives and leveraging diverse data sources. The experimental results demonstrate that the flood risk assessment model, utilizing multi-source data, achieves an overall accuracy of 88.49%. Specifically, the proportions of areas classified as high and very high flood risk are 54.11% in Henan, 31.74% in Shaanxi, and 18.2% in Shanxi. These results provide valuable scientific support for enhancing flood control, disaster relief capabilities, and risk management in the middle and lower reaches of the Yellow River. Furthermore, they can furnish the necessary data support for post-disaster reconstruction efforts in impacted areas. Full article

The Yellow River Basin in China is the region with the most severe agricultural non-point source pollution. The control of agricultural non-point source pollution is an important task for ecological protection and high-quality development in the Yellow River Basin at present and in the near future. This paper takes the eight provinces located along the Yellow River, except Sichuan, as the research object. This study estimates the total amount, intensity, and structure of agricultural non-point source pollution from 2014 to 2023 by adopting quantitative methods such as the pollutant discharge coefficient method, the equivalent pollution load method, and so on. The results reveal that the total amount of non-point source pollution of the Yellow River Basin has risen from approx. 4.94 million tons in 2014 to approx. 7.45 million tons in 2023. However, the growth rate has decelerated over the past five years, and the pollution intensity has decreased by 15~40% on average. The characteristics of agricultural non-point source pollution presents as follows: chemical oxygen demand (COD) emissions have become the most significant pollutant, accounting for 90% of the total pollution; livestock and poultry breeding has become the main source of pollution; and the key areas of pollution have shifted from the lower reaches to the middle and upper reaches, but the regional differences have been narrowing, as measured by the Gini coefficient. An analysis of the Kuznets curve indicates that most of the provinces in the Yellow River Basin still depend on an extensive growth model characterized by high input, high emission, and low output. Finally, this paper proposes a classified governance and measurement system for regions and sources, aiming to enhance the agricultural non-point source pollution prevention and control system. It also advocates for accelerating the green transformation of agricultural production in the Yellow River Basin to achieve the rapid decoupling of pollution emission from economic growth. Full article

Traditional villages in the Yellow River Basin of China are vital carriers of cultural heritage, ecological sustainability, and socio-economic development. This study employs spatial econometric analysis to examine the distribution patterns and influencing factors of 888 traditional villages in the region. The findings reveal a clustering pattern, with high-density areas in Shanxi and medium-density clusters in Shaanxi and Qinghai, while northern and southern regions remain sparse. Over time, the spatial center of village distribution has shifted along a north–south–north–east–west trajectory. The spatial distribution of traditional villages exhibits distinct regional characteristics and differences, shaped by several key influencing factors. These include elevation, precipitation, river proximity, road density, and the presence of cultural heritage units. Results show that in the upper reaches of the Yellow River Basin, natural factors primarily determine village locations. In contrast, economic development and infrastructure factors play a larger role in shaping village transformation in the middle and lower reaches. Policy interventions, such as cultural heritage protection, have a greater impact on remote upper areas. The influence of these factors varies spatially, highlighting the importance of region-specific conservation strategies. Based on these findings, this study proposes targeted strategies for the conservation and development of traditional villages, including multi-type protection systems, cultural corridor construction, watershed-based governance, and enhanced infrastructure and policy support. These strategies aim to support the sustainable development and long-term preservation of traditional villages in the Yellow River Basin. By integrating geographic, economic, and cultural perspectives, this research provides valuable insights into the spatial evolution of traditional villages and informs policy recommendations for achieving balanced rural development. Full article

Grounded in the theory of new economic geography, this research develops a comprehensive theoretical framework to examine the spatial interaction mechanisms between the Green Finance Index and carbon emissions. Employing a range of econometric techniques—including three-dimensional kernel density estimation, spatial quantile regression, bivariate spatial autocorrelation analysis, and the spatial linkage equation model—the dynamic evolution, spatial pattern shifts, and mutual influences of green finance and carbon emissions in the middle and lower reaches of the Yellow River from 2003 to 2022 are systematically assessed. The findings indicate that (1) both carbon emissions and the Green Finance Index have experienced a trajectory of continuous growth, phased decline, and structural optimization, accompanied by a gradual shift in the regional center of gravity from coastal economic zones towards resource-intensive and traditional industry-concentrated areas; (2) significant spatial clustering is evident for both green finance and carbon emissions, demonstrating a strong spatial correlation and regional synergy effects; (3) a persistent negative spatial correlation exists between green finance and carbon emissions; and (4) green finance exerts a stable negative spatial spillover effect on carbon emissions, suggesting that the influence of green finance extends beyond localities to adjacent regions through spatial externalities, manifesting pronounced spatial transmission and linkage characteristics. By unveiling the bidirectional spatial association between green finance and carbon emissions, this study highlights the pivotal role of green finance in driving regional low-carbon transitions. The results provide theoretical insights for optimizing green finance policies within the Yellow River Basin and offer valuable international references for similar regional low-carbon development initiatives. Full article

How to solve the contradiction between coal mining and soil and water conservation is a key scientific issue in the achievement of high-quality development in the middle reaches of the Yellow River. In this paper, the northern Shaanxi mining area in the middle reaches of the Yellow River is taken as the research area, and the surface loess micro-topography is taken as the entry point. The numerical simulation test and soil loss model calculation are used to reveal the different types of loess natural slope morphology (straight slope, concave slope, convex slope, and composite slope) and the natural slopes (5°, 15°, 25°, 35°, 45°). The influence characteristics and laws of the same mining on the surface loess slope morphology in the coal mining subsidence area are analyzed, and the soil erosion effect on the slope scale is analyzed. The results show that: (1) Coal mining subsidence will lead to an increase in the slope of the loess slope, and the smaller the natural slope, the greater the increase in slope. Among them, the influence of coal mining subsidence on the ‘concave loess slope with natural slope of 15°’ is the most significant, and the natural slope of 15° is the key dividing point for the transformation of the sensitive slope shape of the loess slope in the coal mining subsidence area of northern Shaanxi. (2) Coal mining subsidence will lead to the decrease in slope length of a loess natural slope, and the smaller the natural slope, the greater the decrease in slope length. Among them, coal mining subsidence has the most significant impact on the ‘concave loess slope with a natural slope of 25°’. The natural slope of 25° is the key point of the sudden change rate of the slope length of the loess slope in the coal mining subsidence area of northern Shaanxi. (3) Coal mining subsidence will lead to the increase in the soil erosion modulus on the surface loess slope under the scale of ‘annual erosion rainfall’ and ‘typical field erosion rainfall’, and the smaller the natural slope, the greater the increase in the soil erosion modulus. The natural slopes of 15° and 25° are the key points of the abrupt change in soil erosion intensity on the loess slope in the coal mining subsidence area of northern Shaanxi under the scales of ‘annual erosion rainfall’ and ‘typical erosion rainfall’, respectively. Under the scale of annual erosion rainfall, the increment of the 15° slope was 1.65 times, 1.12 times, 1.11 times, and 1.02 times that of the 5°, 25°, 35°, and 45° slopes, respectively. Under the typical erosion rainfall scale, the increment of the 25° slope was 4.22 times, 1.32 times, 1.04 times, and 1.15 times that of the 5°, 15°, 35°, and 45° slopes, respectively. (4) For the loess subsidence slope with any slope shape, the increase in slope gradient is the main factor for the increase in the soil erosion modulus. Under the annual erosion rainfall scale, the contribution of slope increase was 92.9%. Under the typical erosion rainfall scale, the contribution of slope increase was 79.1%. The research results can provide scientific guidance for soil erosion and control in the northern Shaanxi mining area in the middle reaches of the Yellow River Basin. Full article

Population aging–weakening has become a critical constraint on rural sustainability in China’s Yellow River Basin (YRB), posing substantial challenges to ecological conservation and high-quality development. This study develops a multidimensional evaluation framework categorizing rural aging–weakening into four typologies: general development type (GDT), shallow aging–weakening type (SAT), medium aging–weakening type (MAT), and deep aging–weakening type (DAT). Then, the XGBoost model is used to assess the factors influencing the spatial diversity of aging–weakening types in the rural population at different spatial and temporal scales. The key findings reveal the following: (1) The proportion of aging–weakening areas increased from 65% (2000) to 72% (2020), exhibiting distinct regional trajectories. Upper reaches demonstrate severe manifestations (34% combined MAT/DAT in 2020), contrasting with middle reaches dominated by GDT/SAT (>80%). Lower reaches show accelerated deterioration (MAT/DAT surged from 10% to 31%). (2) Spatial differentiation primarily arises from terrain-habitat conditions, industrial capacity, urbanization, and agricultural income. While most factors maintained stable directional effects, agricultural income transitioned from positive to negative correlation post-2010. Upper/middle reaches are predominantly influenced by geographical environment, with the role of socioeconomic factors gradually increasing. Lower reaches exhibit stronger economic–environmental interactions. (3) This research provides actionable insights for differentiated regional strategies: upper reaches require ecological migration programs, middle areas need industrial transition support, while lower regions demand coordinated economic–environmental governance. Our typological framework offers methodological advancements for assessing demographic challenges in vulnerable watersheds, with implications extending to similar developing regions globally. Full article

Megacities in developing countries are still undergoing rapid urbanization, with different cities exhibiting ecosystem services (ESs) heterogeneity. Evaluating ESs among various cities and analyzing the influencing factors from a resilience perspective can effectively enhance the ability of cities to deal with and react quickly to the risks of uncertainty. This approach is also crucial for optimizing ecological security patterns. This study focuses on Xi’an and Jinan, two important megacities along the Yellow River in China. First, we quantified four ecosystem services for both cities: carbon storage (CS), habitat quality (HQ), food production (FP), and soil conservation (SC). Second, we analyzed the synergies and trade-offs between these ESs using bivariate local spatial autocorrelation and Spearman’s rank correlation coefficient. Finally, we conducted a driver analysis using the Geographic Detector. Results: (1) The spatial and temporal distribution of the four ESs in Xi’an and Jinan is quite different, but both cities show lower ES levels in the urban core area. (2) ESs in Xi’an showed a strong synergistic effect. Among them, CS-HQ had the strongest synergy of 0.93. In terms of space, the north is dominated by low–low clustering, while the south is dominated by high–high clustering. The FP-SC in Jinan showed a trade-off effect of −0.35 in 2000, which gradually weakened over time and was mainly distributed in the northern area of the city where cropland and construction were concentrated. (3) Edge density, patch density, and NDVI have the greatest influence on CS in Xi’an and Jinan. DEM, slope, and patch density have the greatest influence on Xi’an HQ. Temperature, edge density, and patch density have the greatest impact on Jinan HQ. NDVI and temperature have the greatest influence on FP in the two cities. DEM, slope, and edge density have the greatest influence on SC. Landscape fragmentation has a great impact on CS, HQ, and SC in Xi’an and Jinan. Due to insufficient research data, this study focused on only four ESs in Xi’an and Jinan, the megacities in the middle and lower reaches of the Yellow River. However, the research results can provide a new perspective for solving the problem of regional sustainable development and new directions and ideas for follow-up research in this field. Full article