Yellow River Research Articles

Land use dynamics and ecosystem service valuation in the Sanmenxia Reservoir wetland of the Yellow River

The Sanmenxia Reservoir wetland (SRW) serves as a critical ecological buffer in the middle reaches of the Yellow River. Ongoing population growth and changes in land use have placed significant pressure on the wetland’s ecosystems. However, existing research has yet to establish a spatiotemporal analysis method to assess the impact of land use change on the ecosystem service value (ESV). This gap hinders the precise regulation and sustainable development of land resources. To gain a comprehensive understanding of the land use dynamics and ecological functions of the SRW, this study introduced a refined ESV evaluation method. This method revised the equivalent factors from spatial, temporal, and hydrological perspectives, with an emphasis on the impact of sediment discharge. Furthermore, the Patch-level Land Use Simulation (PLUS) model was employed to project the land use structure in 2030, and the corresponding ESV was analyzed. The study revealed the following: (1) Cropland constituted the primary land type in the SRW. Over the last two decades, the build-up area exhibited the most significant single land use dynamics, with the transformation of bare land to cropland spanning the widest range and largest area. (2) From 2000 to 2020, the ESV increased by 0.64 billion CNY, with the water body contributing almost all the increase. (3) The projected ESV for 2030 is 2.94 billion CNY, indicating an increase in ecological functions in the near future. Policy makers should recognizethe impact of land use change on ESV and implement measures to rebalance land use structure. While ensuring the preservation of cropland and the protection of lives and property, it is advisable to consider expanding the water body area to facilitate comprehensive sustainable development within SRW.

Denitrification and Anammox and Feammox in the Yinchuan Yellow River wetland

Denitrification and Anammox and Feammox in the Yinchuan Yellow River wetland

Coupling SWAT and Transformer Models for Enhanced Monthly Streamflow Prediction

The establishment of an accurate and reliable predictive model is essential for water resources planning and management. Standalone models, such as physics-based hydrological models or data-driven hydrological models, have their specific applications, strengths, and limitations. In this study, a hybrid model (namely SWAT-Transformer) was developed by coupling the physics-based Soil and Water Assessment Tool (SWAT) with the data-driven Transformer to enhance monthly streamflow prediction accuracy. SWAT is first constructed and calibrated, and then its outputs are used as part of the inputs to Transformer. By correcting the prediction errors of SWAT using Transformer, the two models are effectively coupled. Monthly runoff data at Yan’an and Ganguyi stations on Yan River, a first-order tributary of the Yellow River Basin, were used to evaluate the proposed model’s performance. The results indicated that SWAT performed well in predicting high flows but poorly in low flows. In contrast, Transformer was able to capture low-flow period information more accurately and outperformed SWAT overall. SWAT-Transformer could correct the errors of SWAT predictions and overcome the limitations of a single model. By integrating SWAT’s detailed physical process portrayal with Transformer’s powerful time-series analysis, the coupled model significantly improved streamflow prediction accuracy. The proposed models offer more accurate and reliable predictions for optimal water resource management, which is crucial for sustainable economic and societal development.

Spatiotemporal Evolution and Simulation Prediction of Ecosystem Carbon Storage in the Yellow River Basin Before and After the Grain for Green Project

Under the background of "dual carbon", the impact of the implementation of the Grain for Green project on the carbon storage of the ecosystem in the Yellow River Basin must be explored, which can serve as an important reference for improving the policy implementation of the new round of the Grain for Green project and improving the carbon sink capacity of the ecosystem in the Yellow River Basin. In this study, 1990, before the implementation of the project, was selected as the starting year of the research period, and 2020, after the implementation of the two rounds of the project, was selected as the end year of the research period. Based on the ecosystem type data from 1990 to 2020, the InVEST model was used to calculate the soil carbon pool, underground carbon pool, below carbon pool, dead organic matter carbon pool, and total carbon storage of ecosystems in the Yellow River Basin and the area where the project was implemented from 1990 to 2020. The results showed that： ① From 1990 to 2020, the area of forest ecosystem in the Yellow River Basin expanded by 26 610.06 km2, and the area of farmland decreased by 46 849.06 km2 after the implementation of two rounds of the project. Spatially, the upper reaches of the Yellow River were dominated by grassland and other ecosystems； the middle reaches of the Yellow River were dominated by farmland, forest, and grassland ecosystems； and the lower reaches of the Yellow River were dominated by farmland ecosystems. ② From 1990 to 2020, the carbon storage in the project implementation area showed a fluctuating and increasing trend, and the total carbon storage reached a peak （219.47×108 t） in 2009 and decreased to 218.59×108 t in 2020 due to the decrease of grassland ecosystem from 2010 to 2020. Spatially, the high-value areas of carbon storage were distributed in Aba Tibetan and Qiang Autonomous Prefecture of Sichuan Province and the southern tip of Gansu Province in the upper reaches of the forest and grass accumulation and in the whole of Shanxi Province and the central and southern parts of Shaanxi Province in the middle reaches. Shangluo City in Shaanxi Province and Alxa League in Inner Mongolia Autonomous Region were prefecture-level cities with the highest and lowest average carbon density. ③ In 2035, the carbon storage loss of the natural development scenario was predicted to be 0.83×108 t, and the other three scenarios would increase this loss. Under the moderate farmland return scenario, the Yellow River Basin ecosystem had the strongest carbon sequestration capacity, and the predicted carbon storage would increase by 2.72×108 t compared with that in 2020, and the deep farmland return scenario was the comprehensive optimal scenario. Therefore, in the future, the Yellow River Basin could refer to the deep farmland return scenario to optimize and adjust the implementation plan of the Grain for Green project, and the predicted value of carbon storage can provide some data support for achieving the dual carbon goal.

Can We Protect China's Northern Coast Wetlands From Tidal Dynamics by Restoring Native Species After Spartina alterniflora Is Eradicated? A Model‐Based Analysis

ABSTRACTIn recent years, the Chinese government has implemented a series of initiatives with the objective of eradicating the invasive Spartina alterniflora along the entire coastline. This has given rise to concerns about the potential for subsequent coastal erosion and salt marsh shrinkage. This study introduces a novel contribution in the form of a model‐based analysis, grounded in fieldwork from the Yellow River Delta, which assesses the potential of native Suaeda salsa as an alternative for coastal protection. Our approach is distinctive in that it not only compares the flow velocity reduction effects of S. alterniflora and S. salsa, but also evaluates the efficacy of three distinct planting patterns in managing tidal dynamics. In this study, we present a significant finding: while both species can mitigate tidal flow velocity, S. alterniflora shows superior performance, which represents a novel point of discussion in the field of coastal wetland management. Furthermore, our research indicates that dense aggregated planting patterns are particularly effective during storm surges, offering a strategic insight for future ecological engineering. However, we recognize the potential limitations of our approach, including the need for continuous management to control the spread of S. alterniflora and the necessity for further research to optimize the restoration potential of S. salsa under varying tidal conditions. Our findings highlight the importance of a balanced approach, suggesting the retention of a portion of S. alterniflora while also emphasizing the strategic planting of S. salsa in high‐density configurations to enhance coastal resilience.

Morphological Characteristics of Constrained Meandering Rivers in the Loess Plateau

In the Loess Plateau of China, loess is widely distributed and forms a unique geomorphic feature of the world. Meanwhile, the Yellow River water and sediment regulation system is under construction. Nonetheless, the morphological characteristics of constrained meandering rivers in the Loess Plateau are still unknown due to the difficulty of extracting the sediment-laden water body. An improved method is proposed based on Landsat 8 imagery, which automatically extracts the multi-band spectral relationship of high-sediment-concentration rivers in valleys. This study analyzes the morphological characteristics of constrained meandering rivers in the middle reaches of the Yellow River Basin, including their sinuosity, periodicity, curvature, and skewness based on the deflection points bend segmentation and continuous wavelet transform methods. These characteristics are then compared with those of other constrained meandering rivers and alluvial meandering rivers. The results show that the sinuosity of the constrained river bends is generally low (with an average of 1.55) due to limitations imposed by the riverbanks, which prevent full development. The average dimensionless curvature radius of the constrained rivers is 18.72, lower than that of alluvial rivers. The skewing angle of the constrained river bends typically inclines upstream, with a proportion reaching 59.44%. In constrained river bends, as the sinuosity increases, the proportion of bends skewing upstream initially increases and then gradually decreases. This indicates that constrained river bends can develop similarly to alluvial bends at lower sinuosity but are limited by the mountains on both sides at medium sinuosity. The analysis of river characteristics in regions with different geological structures reveals the effect of geological structures on the formation of constrained rivers in the Loess Plateau. These findings can provide a reference for selecting reservoir dam sites and are important for the dredging engineering layout in the middle reaches of the Loess Plateau. They also offer quantitative explanations for the meandering characteristics of these rivers.

Spatio-temporal Situation, Regional Differences, and Dynamic Evolution of the Distribution of Ecological Compensation in the Yellow River Basin

In the context of regional coordinated development and modernization of ecological and environmental governance capacity, the spatial collaborative governance of transboundary river basins has received extensive attention, but the ecological compensation of river basins is faced with the intertwined relationship of rights and responsibilities, and the horizontal ecological compensation mechanism has not yet been perfected. Based on the emergy ecological footprint model, the ecological compensation amount of 90 cities in the Yellow River Basin in 2007-2021 was measured, and the spatiotemporal pattern, regional differences, and dynamic evolution characteristics of distribution were explored by combining exploratory spatial data analysis, Dagum Gini coefficient, kernel density estimation, and spatial Markov chain analysis. The results showed that： ① The spatiotemporal pattern of ecological compensation in the Yellow River Basin was different, the ecological compensation amount decreased slightly in the fluctuation and increased from the northwest to southeast gradient in general, and the high-value areas were concentrated in the areas with a superior ecological background or developed economy, and some upstream cities had given up many development opportunities to maintain the ecological security of the Yellow River Basin, however, failed to obtain reasonable ecological compensation. ② A significant positive spatial agglomeration phenomenon was observed in ecological compensation and the overall spatial distribution trend was "cold in the north and hot in the south." The number of low-payment areas and low-compensation areas gradually decreased, showing a gradually shrinking agglomeration layout from the periphery to the center, whereas the number of high-payment areas and high-compensation areas continued to increase and formed a spatial evolution characteristic of the coexistence of scattered distribution and group distribution. ③ The overall regional differences in ecological compensation expanded. The over-variation density was the main source of the overall differences, and the focus on alleviating the intra-regional and inter-regional differences was located in the downstream areas. ④ A slight multi-level differentiation phenomenon was present in ecological compensation. The influence of different neighbors on the horizontal transfer of ecological compensation was quite different. This spatial spillover effect easily formed a "space club convergence" phenomenon within a certain geographical spatial range, but with the expansion of time, the probability of maintaining the original level of ecological compensation in each city decreased, and mobility gradually increased. Therefore, increasing the investment in ecological compensation in different fields, strengthening the coordinated development between regions, and giving full play to the spatial spillover effect are important ways to solve the current spatial imbalance of ecological compensation in the Yellow River Basin.

Spatiotemporal Evolution Characteristics and Influencing Factors of Industrial Carbon Emissions in the Yellow River Basin

Scientific assessment of industrial carbon emissions in the Yellow River Basin and identification of its influencing factors are of great importance for promoting green transformation, ecological protection, and high-quality development of the Yellow River Basin. Considering nine provinces in the Yellow River Basin as the research objects； using relevant data on industrial development and energy consumption in the Yellow River Basin from 2000 to 2019； and with the help of IPCC carbon emission measurement, spatial autocorrelation, and LMDI decomposition, the spatial and temporal evolution characteristics and influencing factors of carbon emissions from industries and industrial sectors in the Yellow River Basin were analyzed. Reasonable suggestions were put forward for reducing the carbon emissions from industries in the Yellow River Basin. The results showed that： ① From 2000 to 2019, industrial carbon emissions in the Yellow River Basin showed a fluctuating growth trend, with a decreasing growth rate. The spatial pattern changed from "low in the upstream and high in the middle and downstream" to "high and low value distribution," and the spatial difference gradually expanded. ② The high carbon industry was the most important source of industrial carbon emissions in the Yellow River Basin, accounting for 96.35% of the carbon emissions between the industries with a continuous growth trend, which was a significant difference. The middle and low carbon industry carbon emissions and the total proportion was low, showing different fluctuations； nine provinces and nine industrial industries had significant spatial variability. ③ Energy structure intensity, economic scale, and population scale promoted the increase in industrial carbon emissions in the Yellow River Basin and energy consumption intensity had an inhibitory effect on the increase in carbon emissions. The economic scale effect was positive and significant, which offset the negative effect of energy consumption intensity. Spatial variability was observed in the contribution value of the influence effect of the factors affecting the carbon emissions of the industry in nine provinces.

Chemical Spatiotemporal Characteristics and Environmental Driving Factors of Groundwater in Hetao Irrigation Area

To explore the chemical characteristics and environmental factors of groundwater in the Hetao Irrigation Area of Inner Mongolia, five irrigation fields, including UulanBuh, Jiefangzha, Yongji, Yichang, and Wulat, were selected as the research area. From 72 groundwater observation wells, a total of 216 groundwater samples were collected throughout three typical periods： the end of freeze-thaw （March）, the middle of irrigation （July）, and the end of autumn watering （November）. Comprehensive methods were utilized, such as statistical analysis, Piper three-line diagram, Gibbs diagram, ion ratio, and principal component analysis, to explore the changes in the groundwater chemical environment and the environmental driving factors of groundwater component formation. The groundwater drinking suitability was evaluated using the water quality index （WQI）, and the irrigation suitability was analyzed using the USSL and Wilcox plots. The results indicated that the groundwater in the research areas was generally saline, and the total anion and cation concentrations in each period in ascending order were as follows： late freeze-thaw stage, late autumn irrigation stage, and mid-irrigation stage, with Na+ and Cl- being the major contributing ions. The chemical type of groundwater was dominated by Cl-Na, followed by Cl·SO4-Ca·Mg and a coexistence with SO4-Ca·Mg, HCO3·Cl-Na, HCO3-Na, and HCO3-Ca·Mg. Based on WQI values, the shallow groundwater in Hetao Irrigation District was mainly classified as Class IV and Class V, and the quality was poor in general. According to the USSL diagram and Wilcox diagram, the comprehensive evaluation results showed that the salinity and sodium concentration of shallow groundwater in the irrigation area were generally high. A total of 80.6% of the water samples during the late freeze-thaw period, 76.1% during the mid-irrigation period, and 77.6% during the late autumn irrigation period lacked irrigation suitability. Two major controlling factors of groundwater chemical characteristics were present in the study area, namely, evaporation and rock weathering, and Na+ and Cl- mainly came from the dissolution and cation exchange of salt rocks. Agricultural irrigation and drought were the chief driving factors of groundwater chemical evolution in the Hetao Irrigation Area. The study provides technical support for optimizing agricultural management measures and a theoretical reference for rational utilization of groundwater resources in the Yellow River irrigation area of Inner Mongolia.

Spatial-temporal Change and Driving Force of Carbon Storage in Three-River-Source National Park Based on PLUS-InVEST-Geodector Model

Exploring the spatial-temporal changes, driving forces, and future development tendency of the carbon sequestration service function of the Three-River-Source National Park ecosystem has great significance for regional ecological protection and sustainable development. Historical land-use data of Three-River-Source National Park from 1990 to 2020 were selected at five-year intervals, and based on the PLUS-InVEST-Geodector model, the spatial-temporal changes of historical carbon storage were analyzed, and the driving forces of spatial-temporal variation were explored combined with multiple factors. The carbon storage of Three-River-Source National Park in 2030 was predicted under the scenarios of natural development and ecological protection. The results showed that： ① The carbon storage of Three-River-Source National Park showed a fluctuating characteristic of increase-decrease-increase-decrease from 1990 to 2020, the carbon storage was increased by 41.85×106 t overall, and the grassland took the largest contribution. ② The spatial distribution characteristics of carbon storage in Three-River-Source National Park had little change between 1990 to 2020, and the evolution of the spatial distribution was relatively stable. The contribution ratio of the Yangtze River source park, Lancang River source park, and Yellow River source park was 7∶1∶2, which was roughly equivalent to the park area. ③ The major driving factors of the spatial-temporal variation of carbon storage in Three-River-Source National Park from 1990 to 2020 were： FVC, soil type, and annual precipitation. The interactive detection of each driving factor showed dual-factor enhancement and nonlinear enhancement. ④ The carbon storage of Three-River-Source National Park was predicted to decrease by 4.87% and 3.98% from 2020 to 2030 under the scenarios of natural development and ecological protection, respectively, and the carbon storage reduction under the ecological protection scenario had a significant inhibitory effect. The findings can provide data support for national spatial planning of Three-River-Source National Park and the enhancement of terrestrial ecosystem carbon storage.

Influence of Typical Regional Land Use/Landscape Pattern on Water TN of the Upper Yellow River

This study aimed to explore the relationship between land use landscape pattern and water quality in the upstream of the Gansu water conservation, water and soil erosion, and ecological fragile areas. Based on the land use data and water quality monitoring section in 2020 in the 200 m, 500 m, 1 km, 2 km, 50 km, and 10 km riparian buffer area, the single-factor index evaluation method, random forest regression model, and BP neural network were used to quantify the response relationship between land use and landscape pattern of the upper Yellow River in Gansu province and water quality index and to carry out the basin water quality prediction based on land use landscape index data. The results showed that： ① through the single-factor index method, the major indicators of the total nitrogen （TN） in July and September, dissolved oxygen （DO）, permanganate index, ammonia nitrogen （NH4+ -N）, total phosphorus （TP）, and other surface indexes met the surface water environment class Ⅲ water quality standard. ② The random forest regression model was used to analyze the influence of land use and landscape index on TN, and the difference in TN in different typical areas was obtained. The land use types with the highest influence on the TN index in water conservation areas, soil and soil erosion areas, and ecological fragile areas were cultivated land, grassland, and construction land, respectively. ③ The BP neural network was used to predict the water quality index based on different typical areas of land use landscape index. The result of water conservation areas was good, the error rate between the predicted value and the actual value was below 10%, and the prediction accuracy was high. The study showed that water quality prediction based on land use and landscape index/water quality quantitative relationship model had a good water quality prediction effect.

Retrieval of total suspended matter concentration in the yellow river estuary offshore area based on QAA-RF model

ABSTRACT Total suspended matter is one of the crucial water quality parameters for both inland and marine environments, and a key role in evaluating the water quality of estuaries and offshore areas. Each year, the Yellow River carries a significant amount of sediment into the semi-enclosed Bohai Sea, results in a prolonged high concentration of total suspended matter in the offshore areas of the Yellow River Estuary. This study focuses on the offshore region of the Yellow River Estuary in China. Utilizing Sentinel-2 satellite imagery data from 2020 to 2023 and in-situ measured data from August 2020 to August 2022, to address the lack of physical mechanisms currently studied in machine learning retrieval methods, a model that integrates the physics-driven Quasi-Analytical Algorithm (QAA) and data-driven Random Forest (RF) is employed for the retrieval of total suspended matter concentration in the study area. The fused model (QAA-RF) is compared and analysed against regression models and standalone machine learning models. The results indicate that the accuracy of machine learning retrieval models is consistently higher than that regression models. The QAA-RF model demonstrates the highest accuracy (R 2 = 0.87, MAE = 5.01 mg L−1, RMSE = 6.39 mg L−1). Based on the QAA-RF model and the imagery data, monthly total suspended matter concentration is conducted in the study area. The retrieval results indicates that: (1) the total suspended matter concentrations is primarily concentrated in the near estuary region, with concentrations decreasing as distance from the estuary increases. (2) the total suspended matter concentration exhibits a distribution pattern with higher values in spring and winter, and lower values in summer and autumn. (3) the concentration of total suspended matter shows relatively small fluctuations at the annual scale from 2020 to 2023.

County-level carbon budget and carbon compensation in the Yellow River Basin: a perspective with balancing efficiency and equity

County-level carbon budget and carbon compensation in the Yellow River Basin: a perspective with balancing efficiency and equity

Transboundary Water Allocation under Water Scarcity Based on an Asymmetric Power Index Approach with Bankruptcy Theory

Cooperative and self-enforceable water allocation is a key instrument to manage geopolitical conflict induced by water scarcity, which necessitates the cooperative willingness of the agents and considers their heterogeneity in geography, climate, hydrology, environment and social economy. Based on a multi-indicator system that contains asymmetric information on water volume contribution, current water consumption, water economic efficiency and efforts for eco-environmental protection, this study proposed a water allocation framework by combining the asymmetric power index approach with bankruptcy theory for solving the transboundary water allocation problem under scarcity. The proposed method was applied to the Yellow River Basin in northern China, which is mainly shared by nine provincial districts and frequently suffers from severe water shortages, and its results were compared with six alternative methods. The results highlight the necessity of quantifying agents’ willingness to cooperate under the condition of asymmetric negotiation power when making decisions on transboundary water allocations. The proposed method allows for transboundary water allocations through simultaneous consideration of the agent’s willingness to cooperate and asymmetric negotiation power, as well as disagreement allocation points, which ensure the stability, fairness and self-enforceability of allocation results. Therefore, it can offer practical and valuable decision-making insights for transboundary water management under water scarcity.

Assessing rural revitalization potential through rural transformation degree and sustainability: A quantitative study of 460 case villages in Lingbao, China

Extensive international experience shows that only villages with sustainable transformation achieve rural revitalization, while those with intense but unsustainable or stagnant transformation struggle to revitalize. However, this cognition lacks robust quantitative substantiation. Therefore, we established a rural revitalization potential assessment framework based on the rural transformation degree and sustainability, employing the Penalty for a Bottleneck (PFB) method and Entropy Function to measure the rural transformation degree and sustainability of 460 villages in Lingbao City, Henan Province, China, from 2000 to 2021, thus evaluating rural revitalization potential. The Mann-Kendall (MK) test was conducted to detect rural transformation thresholds, further quantifying the spatial relationship between rural transformation degree and sustainability through bivariate spatial autocorrelation analysis (BSA). Our findings resonate with the central place theory that villages near those at advanced stages of development struggle to transform sustainably. Additionally, with the optimization of rural population density, and land use structure, these villages demonstrated a discernible upward trajectory in transformation sustainability. Villages with the highest rural revitalization potential were predominantly distributed in the northern of the Yellow River terrace, while those in the southwestern mountainous areas lacked revitalization potential due to low transformation degree. Generally, villages at higher altitudes and steeper slopes exhibited lower rural transformation degree, sustainability, and revitalization potential. With 30 km as the critical point, rural revitalization potential decreased initially and then increased with distance from the county government seat. This study provides essential references for the rational allocation of rural transformation and revitalization resources and for optimizing rural development planning.

Serum calcium improves the relationship between fluoride exposure and hypothalamic-pituitary-testicular axis hormones levels in males—a cross-sectional study on farmers in the lower reaches of the Yellow River

Numerous studies have reported the toxicity of fluoride to the male reproductive system, but epidemiological evidence is limited. We conducted a cross-sectional study in Kaifeng City, Henan Province in 2011 to explore the association between fluoride exposure and hypothalamic-pituitary-testicular (HPT) axis hormones in men. Morning urinary fluoride (UF), serum HPT axis hormones and serum calcium (SC) concentrations were detected. Percent changes and 95% confidence intervals in HPT axis hormones associated with UF were estimated using adjusted linear regression models, and performed subgroup analysis based on SC levels. The restricted cubic spline model was used to fit nonlinear relationships. For every 10% increase in UF, the concentrations of serum GnRH, T, SHBG and TSI decreased by 2.13%, 2.39%, 2.19% and 1.96%, while E2 and FEI increased by 1.11% and 3.33%. Subgroup analysis showed that for every 10% increase in UF, the levels of GnRH, T, TSI and FTI decreased by approximately 3.15%, 5.49%, 4.47% and 5.14%, while the E2 level increased by 2.92% in low-serum-calcium group (LCG). The levels of GnRH and T decreased by approximately 2.97% and 1.82% in medium-serum-calcium group (MCG). In high-serum-calcium group (HCG), serum SHBG levels decreased by 4.70%, while FTI and FEI levels increased by 4.93% and 4.20% as UF concentration increased (P < 0.05, respectively). The non-linear relationship between serum GnRH and UF concentrations presented an approximately inverted U-shaped curve, with a turning point UF concentration of 1.164 mg/L (P < 0.001), and their nonlinear relationship in LCG and MCG were similar to that in the overall subjects. In conclusion, excessive exposure to fluoride can interfere with male serum HPT axis hormones, and a moderate increase in SC alleviates the effect of fluoride. Prospective cohort studies are essential to confirm the causality.

Spatiotemporal evolution and driving factors of the coupling coordination of the population‒land‒water‒industry system in the lower Yellow River

Exploring the interaction and coupling effects within the population‒land‒water‒industry (PLWI) system is conducive to promoting high-quality regional sustainable development. Taking the lower Yellow River during the period from 2000 to 2020 as a research sample, this study used the entropy weight TOPSIS method, the coupling coordination degree (CCD) model and kernel density estimation to synthetically evaluate the CCD of the PLWI system. The GeoDetector model was applied to explore the factors influencing the CCD of the PLWI system considering the nonlinear relationship. The major results can be summarized as follows: (1) From 2000 to 2020, the comprehensive development index (CDI) of the population, land, water and industry subsystems followed a gradual upward trend in the lower Yellow River, increasing by 0.293, 0.033, 0.111 and 0.369, respectively. However, the CDI of the land subsystem varied greatly between regions. Some cities, such as Jinan, Jining and Binzhou, experienced large declines in the CDI of the land subsystem, from 0.433, 0.534 and 0.572 to 0.358, 0.481 and 0.522, respectively. (2) The CCD of the PLWI system in the lower Yellow River showed an upward trend, increasing from 0.481 to 0.678, and became more concentrated during 2000–2020. Most of the region transitioned from near disorder to primary coordination. (3) Factors such as number of health technicians per 10,000 people, average salary, number of college students per 10,000 people, per capita GDP and per capita education expenditure were critical to the coordinated development of the PLWI system, the explanatory powers were 0.644, 0.639, 0.610, 0.498 and 0.455, respectively. Finally, this study proposed three policy recommendations to improve coupling coordination in the lower Yellow River Basin: Improving population quality, promoting green technology and rational land planning.

Mechanism and spatial spillover effect of digital economy on common prosperity in the Yellow River Basin of China

The digital economy has emerged as a new trend in economic development and has profoundly influenced the process of achieving common prosperity. However, current research on the correlation between the digital economy and common prosperity from the perspective of a river basin still needs to be strengthened. Based on this, the present study first theoretically elaborates the conceptual meanings of “digital economy” and “common prosperity”, as well as the mechanism by which the digital economy empowers common prosperity. Subsequently, a scientifically-constructed performance evaluation index system for the digital economy and common prosperity is established. Considering the Yellow River Basin as an empirical case study area, this study investigates the mechanism and spatial spillover effects of the digital economy in empowering common prosperity from 2005 to 2020. The research findings reveal that: (1) The Yellow River Basin exhibits a basin characteristic with downstream > midstream > upstream areas regarding the level of common prosperity and digital economy. It indicates that a distinct spatial correlation exists between the two factors. However, the ongoing decrease in both high-level and very high-level areas reflects the lengthy and challenging journey of enhancing the quality and efficiency of the digital economy in empowering common prosperity. (2) The digital economy not only directly impacts common prosperity, but also fosters its development through spatial spillover effects. Among the control factors, informatization and housing levels have a major stimulating effect. (3) There exists a clear regional heterogeneity in how the digital economy affects common prosperity in the Yellow River Basin. Specifically, common prosperity of downstream cities is significantly impacted by the digital economy. The spatial spillover effects of the digital economy on common prosperity exhibit a pronounced “neighborhood as a moat” characteristic. (4) The digital economy facilitates the achievement of shared prosperity through the implementation of mechanisms centered on sharing, affluence, and sustainability. These research findings illuminate the empowering mechanisms and spatial spillover pathways of the digital economy in promoting shared prosperity, aligning with national strategies for ecological conservation and high-quality development in the Yellow River Basin.

Quantifying the influence of dominant factors on the long-term sandstorm weather - A case study in the Yellow River Basin during 2000–2021

Sandstorm is a disastrous weather phenomenon that often occurs in arid and semi-arid areas, endangering the ecological environment and affecting people's lives and property safety seriously. Since the 21st century, the sandstorm weather in the Yellow River Basin has ameliorated obviously. However, the causes of the long-term trends in sandstorms during 21st century were still unknown. In this study, fifteen influencing factors from five aspects: ecology, meteorology, hydrology, geography and man-made were selected to comprehensively analyze the driving mechanism of sandstorm activities in the Yellow River Basin since the 21st century, and the effect of each influencing factor on sandstorm weather was quantified. The results indicated that ecological, meteorological and geographical factors had dominant impacts on the spatio-temporal variation of sandstorms during 2000–2021, while hydrological and human factors played little role in the long-term variation of sandstorms. Sandstorms frequently occurred in semi-desert or grassland or non-high vegetation covered areas in spring. Vegetation coverage, precipitation, surface pressure, surface roughness, and soil moisture content were negatively correlated with sandstorms, while wind speed, friction velocity, evaporation, and soil temperature were positively correlated with sandstorms. Precipitation, runoff, evaporation, soil moisture content, soil temperature, and surface temperature indirectly acted on normalized brightness temperature dust index (NBTDI) and sandstorms by changing soil texture. Normalized Vegetation Index (NDVI) had direct negative effects on NBTDI, while wind speed 10 m (WS10m), slope of sub-gridscale orography (SOSGO), and forecast surface roughness (FSR) had direct positive effects on NBTDI. This study comprehensively revealed the dominant factors and their driving mechanism of sandstorm weather in the Yellow River Basin since the 21st century, which had practical application value for the prevention of sandstorms.

Comprehensive Assessment of the Ecosystem in Yellow River Basin Based on Pattern-Quality-Service Model

Comprehensive Assessment of the Ecosystem in Yellow River Basin Based on Pattern-Quality-Service Model