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The Yellow River Basin plays a crucial role as both an ecological barrier and an economic development area in China. However, achieving synergistic development between the environment and industry in the coastal provinces remains challenging. Conducting in-depth studies on the synergy between these two aspects can provide valuable guidance for the development of each province. This paper employs the Topsis method to assess the development level of the industrial and environmental systems in the Yellow River Basin. Additionally, it utilizes the Harken model to analyze the synergy between the environment and industry in the coastal provinces of the Yellow River Basin from 2011 to 2021. Furthermore, the overall distribution of the level of synergistic development between the industry and environment in the Yellow River Basin is analyzed using kernel density estimation. The empirical findings reveal the following: 1. The development level of both environmental and industrial systems in each province of the Yellow River Basin has exhibited a consistent increase over the study period. 2. The average synergy between environment and industry in the Yellow River Basin has shown a declining trend from 2011 to 2021. In 2021, the synergy level follows the pattern of "upstream

Urbanization and cultivated land use have presented a complex and dynamic relationship. This study aims to reveal the coupling and coordination relationship between urbanization and cultivated land use ecological efficiency, together with the driving factors behind it. The statistical data was collected from the 88 prefecture-level cities (states and leagues) in the Yellow River Basin from 2005 to 2020. The comprehensive evaluation was then adopted to measure the urbanization development level using the SBM-Undesirable model, and the coupling coordination degree model. The cultivated land use ecological efficiency and the coupling coordination degree were achieved after evaluation. The results show that: (1) The development level of urbanization increased steadily, but there was a much more outstanding feature of spatial differentiation. The first echelon of urbanization was gradually distributed in the downstream coast of the Yellow River, the middle and upper reaches of the northern part of the Yellow River; The ecological efficiency of cultivated land use was significantly improved with the imbalance of "high in the middle and low in the surroundings" in the local areas. (2) It continued to rise the coupling coordination degree between urbanization and cultivated land use ecological efficiency. But there was no reach in the advanced level of coordination. The extreme situation of "high in the east and low in the west" in the spatial distribution gradually evolved into the polycentric "high in the middle and low in the surroundings" pattern of differences. The overall spatial differences were gradually narrowing to evolve into the "high in the middle and low in the surroundings" pattern. Two types of coupling coordination were the "high-high" and "low-low" agglomeration. Among them, the "high-high" agglomeration was concentrated mainly in the downstream areas, such as Shandong and Henan Provinces. While the "low-low" agglomeration was mainly concentrated in the upstream areas of Gansu Province. (3) There were the influencing factors on the coupling coordination degree between urbanization and cultivated land use ecological efficiency, such as the scale of cultivated land operation, the income level of farmers, the government's agricultural support, the elevation, the average annual precipitation, and the average annual temperature. There was a non-linear and two-factor enhancement of the interaction among the driving factors. Therefore, much effort should be continued to narrow the gap between the development level of urbanization and the cultivated land use ecological efficiency among regions. In addition, breakthroughs and upgrades should be promoted in the level of coordination between urbanization and the cultivated land use ecological efficiency. The demonstration and leadership were found in the "high-high" agglomeration areas. Finally, it is necessary to take the regional background as the primary determinant of urbanization development and arable land use. While the interaction and complementary enhancement of each factor can be fully considered to synergistically improve the coordinated development of regional urbanization and arable land use. [ABSTRACT FROM AUTHOR]

Introductions: Since the reform and opening up, the inflow of foreign direct investment (FDI) has provided a steady stream of capital, technology, talent and other resources for the development of the Yellow River basin, while caused problems such as environmental pollution, ecological fragility and industrial structure upgrading difficulties to some extent. Environmental regulation is a pivotal initiative to achieve mutual harmony between ecological environment and economic development, which could enhance the quality of the introduction of FDI and accelerate the green transformation of the development mode. Methods: Based on urban panel data from 2006-2019, this study empirically examined the impact of FDI and environmental regulation on industrial structure upgrading in the Yellow River Basin. Moreover, taking environmental regulation as a threshold variable, a panel threshold model was established to further explore the role of environmental regulation in the impact of FDI on industrial structure upgrading in the Yellow River Basin. Results: (1) The relationship between FDI and industrial structure upgrading in the Yellow River Basin is not a simple linear relationship, but an inverted "U"-shaped relationship that rises first and then falls, and the results of this inverted "U"-shaped relationship are still robust after replacing key indicators. (2) The environmental regulation policy has a driving effect on the upgrading of industrial structure in the Yellow River Basin. (3) Environmental regulation has a positive role in the influence of FDI on the industrial structure upgrading in the Yellow River basin, and the positive role increases gradually as the intensity of environmental regulation increases moderately, but if the intensity of environmental regulation is too high, it will have a negative impact on the upgrading of industrial structure in the Yellow River basin to some extent. Discussion: In the future, policymakers should make reasonable and effective use of FDI and improve the quality of FDI; reasonably formulate environmental regulation policies; coordinate the intensity of FDI and environmental regulation; thus, bring into play the promotion effect of FDI and environmental regulation on industrial structure upgrading, and then realize the win-win of ecological protection and high-quality economic development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban–rural transition affects PM2.5 are warranted within the framework of urban–rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban–rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban–rural transformation and PM2.5. The results are as follows: (1) The level of urban–rural transformation shows an obvious upward trend with time. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban–rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted "N-shaped" curve of negative–negative–changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. An inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land transformation (LT) has a "U-shaped" curve for its effect on PM2.5. This study provides a new perspective on the topic of PM2.5 and its connection to urban–rural integration, which is crucial to understanding the dynamics of this shift. To achieve the goal of high-quality development, this study supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, the results of this study can provide a reference for decision-makers in the world's densely populated areas that suffer from serious air pollution. [ABSTRACT FROM AUTHOR]

Ecological protection and high-quality development in the Yellow River Basin have become a major national strategy in China. This paper explores the impact and mechanisms of new infrastructure on high-quality industrial development in the Yellow River Basin, considering the current context of vigorous development of new infrastructure and the industrial development status of the region. This study finds that new infrastructure promotes high-quality industrial development in the Yellow River Basin, and the enhancement of digital literacy strengthens this positive impact. New infrastructure facilitates high-quality industrial development in the Yellow River Basin by driving labor transfer from the supply side and consumption upgrading from the demand side. This positive influence is particularly pronounced in the upstream cities, central cities, and urbanized areas of the Yellow River Basin. Further research indicates that there is a "pain period" in promoting the construction of new infrastructure, and only when the level of high-quality industrial development exceeds a certain threshold can its efficiency be further improved. The conclusions of this paper provide theoretical references and policy inspiration for the coordinated promotion of new infrastructure construction to empower high-quality industrial development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In order to provide reference for the integrated protection of organisms and habitats in the Yellow River Basin from the level of the rule of law and the building of a unified and synergistic biodiversity conservation management system and regime, the current status of biodiversity in the Yellow River Basin was analyzed. It was pointed out that the legal regulation system of biodiversity protection in the Yellow River Basin was not systematic and complete, the comprehensive management system was not perfect, the administrative functions and responsibilities of the government for biodiversity protection were not matched, and the coordination mechanism of environmental justice had shortcomings. The implementation of the Yellow River Protection Law provides a framework for the rule of law for the protection and restoration of biodiversity in the Yellow River Basin, and then puts forward the countermeasures for the rule of law for the integrated protection of biodiversity in the Yellow River Basin, integrating and improving the legal normative system of biodiversity protection, perfecting the mechanism for the participation of pluralistic subjects in the management of the system, setting up a legal system that promotes the effective fulfillment of the responsibility of the local government for the protection of biodiversity and building the multidimensional judicial collaboration mechanism. [ABSTRACT FROM AUTHOR]

In order to reveal the spatial and temporal characteristics of agricultural water use efficiency in the Yellow River Basin and to pro- vide a theoretical basis for the efficient management of agricultural water resources, this study employed the stochastic frontier production function to measure the agricultural water use efficiency of 79 prefecture-level cities in the Yellow River Basin from 2000 to 2021. Combined with Stata 15.0 and ArcGIS 10.7 software, deeply analyzed the spatial and temporal evolution of agricultural water use efficiency, and its re- gional differentiation status. The results show that during the study period, the overall level of agricultural water use efficiency in the Yellow River Basin is low, but it shows a steady growth trend, and the difference value between prefecture-level cities is basically maintained in a relatively stable state. The spatial differentiation characteristics of agricultural water use efficiency are significant. Medium and low efficiency prefecture-level cities are mainly located in the upper and middle reaches of the Yellow River, while high efficiency cities are primarily con- centrated in Shandong and Henan provinces. The distribution of efficiency kernel density is generally consistent with the distribution of major grain-producing areas in China. Notably, the agricultural water use efficiency of some prefecture-level cities in the Hetao irrigation area, western Henan, and the Guanzhong area has significantly improved during the study period. There are significant differences in agricultural water use efficiency between the upper, middle, and lower reaches of the Yellow River Basin and among provinces (regions). The order of agricultural water use efficiency between basins is downstream > midstream > upstream, and among provinces, it is Shandong > Henan > Shaanxi > Inner Mongolia > Shanxi > Gansu > Qinghai > Ningxia. However, the order of efficiency improvement is the opposite. [ABSTRACT FROM AUTHOR]

[Objective] This research aims to explore the temporal and spatial status of the ecological quality evolution and the main driving factors of its evolution in the Loess Plateau, and to provide the theoretical basis for the improvement of regional ecological quality and sustainable development in the Yellow River Basin. Methods] Based on the 'Driving Force-Pressure-State-Impact-Response' (DPSIR) model, 14 indexes reflecting the social and economic situations, natural environment and ecological governance were selected to build the comprehensive evaluation index system. The weight of each index was defined by the analytical hierarchy process (AHP), and the comprehensive evaluation indexes were calculated by the weighted average. The Ridge Regression Model was used to quantitively assess the driving factors of the ecological quality evolution. [Results] The ecological quality of the Loess Plateau in the Yellow River Basin exhibited a distinctive spatiotemporal heterogeneity, with the high-quality areas concentrating in the midstream and low quality areas in the upstream, showing the unique spatial pattern of high-quality in the southeast and low- quality in the northwest'. The medium-quality areas and above increased from 40.56% in 2000 to 70.36% in 2020. The ecologically improved areas in the past 2 decades took up 94.44% of the total research area, and the ecologically improved counties accounted for 91.57% of the total counties. The Ridge Regression Model explained 99.4% of the ecological evolution, demonstrating the relatively higher contributions from the vegetative cover and the annual precipitation to such evolution. [Conclusion] The ecological quality in the Loess Plateau was improved, and the spatiotemporal evolution of ecological quality was mainly driven by vegetative cover and annual precipitation. It is recommended that the spatial pattern of ecosystems is further optimized on the basis of a scientific and rational increase in vegetation cover. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the coupling and coordination of environmental protection and economic development in the Yellow River Basin and its influencing factors, so as to provide a theoretical reference for the high-quality development of the whole basin. [Methods] Based on the coupling coordination model, Dagum Gini coefficient, Markov chain and geographically weighted regression model, the spatiotemporal coupling dynamic evolution of carbon reduction-pollution reduction-green expansion- economic growth in the Yellow River Basin from 2009 to 2020 and its influencing factors were studied and analyzed. [Results] (1) The coupling coordination degree of carbon reduction-pollution reduction-green expansion-economic growth in the Yellow River Basin showed generally a fluctuating upward trend. The coupling coordination degree was the largest in the lower reaches, followed by the middle reaches, and the least in the upper reaches. (2) The intraregional gap in the coupling coordination level of the upper reaches was significantly higher than that in the middle and lower reaches of the region. The gap between regions followed the order: upper and middle upper and lower middle and lower. The gap among regions and intensity of transvariation was the major source of the overall gap. (3) The coupling coordination degree of carbon reduction-pollution reduction-economic green expansion-economic growth system had the low fluidity, which had the stability of maintaining the original state. It was difficult to achieve leapfrog development evolution in a short period. (4) Industrial structure optimization can effectively promote the coupling coordinated development of the Yellow River Basin. Government intervention has an obvious role in promoting the coupling coordinated development of most provinces and regions. The effective combination of market demand and technological achievements can further improve the coupling coordination degree of the Yellow River Basin. Conclusion The overall spatiotemporal coupling of carbon reduction-pollution reduction-green expansion-economic growth in the Yellow River Basin is on the rise. The factors affecting the coordination degree of this system coupling are relatively complex. In the future, efforts should be made to optimize the industrial structure, to strengthen the transformation of technological achievements, and to promote the coordinated development of carbon reduction-pollution reduction-green expansion-economic growth in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the temporal and spatial evolution characteristics of land ecological security in the Yellow River Basin, to clarify its deductive law, and to help accelerate the construction and development of ecological civilization in the Yellow River Basin. [Methods] Based on the statistical data from 2012 to 2021, 58 cities in the Yellow River Basin were selected as the research unit. system of evaluation index was established, integrated entropy weight TOPSIS method and Moran index were used to explore the temporal and spatial evolution law, and grey prediction GM(1.1) model was used to explore future trend. [Results] (1) In terms of time, the whole level of land ecological security was not high in Yellow River Basin, but showed a trend of good development year by year, and experienced an improvement from sensitive level' to good level'. (2) From the spatial distribution point of view, the land ecological security presented the characteristics of large cohabitation and small aggregation' which always showed a step-shaped distribution pattern of 'the highest level in downstream was, the medium level in the middle reaches, and the lowest level in upper reaches'. (3) The land ecological security of the Yellow River Basin had obvious positive correlation in space and significant agglomeration characteristics, Locally, the high safety values (H-H) were clustered in Shandong and Henan, the low safety value are clustered in Qinghai, Gansu and Shaanxi of the middle and upper reaches. (4) From 2022 to 2025, the land ecological security level will maintain a steady rise, and the land ecological security level will remain at 'good level'. [Conclusion] The level of land ecological security in the Yellow River Basin continues to improve, but the overall level is not high, and land ecosystem governance and joint protection in the areas along the basin should be continually promoted. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to characterize the changes in net primary productivity (NPP) at different time scales, and to reveal the impact of climate factors on vegetation NPP in Yellow River Basin. [Method] The NPP was estimated month by month using the CASA model from 2000 to 2020 based on remote sensing data and meteorological data, and the trend analysis and partial correlation analysis were used to investigate the temporal and spatial variations of NPP and its response to climate factors at annual and seasonal scales. [Results] The annual NPP in the Yellow River Basin showed significant upward trend with a rate of 1.68 g/ (m²·a) from 2000 to 2020, and the NPP in the middle reaches was the highest and grew fastest. The summer NPP was the highest and had the fastest growth rate, especially in the middle reaches. Annual NPP was affected by precipitation most widely, accounting for 31.95% of the total area, and precipitation had a longer lag period than temperature and sunshine duration. The relationships between precipitation and NPP in summer and autumn were mainly positive, with a ratio of more than 70%. About 75% of area showed that temperature and sunshine duration positively influenced NPP in winter. [Conclusion] Vegetation NPP in the Yellow River Basin presented obvious spatial heterogeneity and seasonal variation, and the influence of climate factors on vegetation NPP had different lag periods. Therefore, vegetation protection and restoration in the Yellow River Basin should be considered from both spatial and temporal aspects. [ABSTRACT FROM AUTHOR]

Objectively and accurately identifying the spatial structure and protection scope of intangible cultural heritage and constructing intangible cultural heritage corridors are crucial for the comprehensive systematic protection of intangible cultural heritage and the synergistic development of the region. However, the current research on intangible cultural heritage is limited to the protection and development of intangible cultural heritage in specific locations or specific areas. Thus, systematic and holistic research perspectives are relatively limited. Therefore, this study employs geographic information system spatial analysis and the minimum cumulative resistance model to construct an intangible cultural heritage corridor in the Yellow River Basin. This study aims to establish a systematic protection method and framework for intangible cultural heritage. The results show the following: (1) The intangible cultural heritage in the Yellow River Basin has a large-scale centralized distribution and small-scale scattered distribution, which provides an important spatial basis for the construction of intangible cultural heritage corridors. (2) Overall, intangible cultural heritage corridors can be more effectively constructed in the eastern region of the Yellow River Basin than in the western region, with 84.6% of the area being suitable and 15.4% being unsuitable. (3) Based on the suitability analysis, the "18 + N" corridor system of intangible cultural heritage in the Yellow River Basin, distributed across the eastern, central and southern regions, is constructed. The major corridor has a suitable width of 60–100 km, a total length of 11,935 km, and an area of 625,976 km2–919,942 km2, and can connect 634–711 intangible cultural heritage sites in series. On this basis, this study proposes a multilevel construction system for intangible cultural heritage corridors in the Yellow River Basin that integrates the "network structure–spatial scope" and "element–axis–region" levels. This approach culminates in a pattern of intangible cultural heritage protection and development in the Yellow River Basin characterized by "connecting points into lines, distributing in groups, and linking regions." This study reveals that combining geographic information system spatial analysis tools with a minimum cumulative resistance model effectively identifies potential heritage corridor networks and clarifies the hierarchical relationships of heritage element protection in the study area. This approach provides a reference model for the comprehensive protection and systematic development of intangible cultural heritage in the Yellow River Basin. Furthermore, the effectiveness and universality of this framework make it applicable to the protection and development of other similar international heritage areas. [ABSTRACT FROM AUTHOR]

The spatial distribution pattern of rural settlements in the Yellow River Basin is scattered and numerous. It is of great significance to study the discrete distribution of rural settlements for achieving high-quality development and promoting rural revitalization strategy. In this paper, we propose an enhanced evaluation model for assessing the spatial distribution dispersion of rural settlements, incorporating the weight of road grade (the road grade refers to the ranking of traffic capacity and importance of a particular type of road, indicating varying levels of time accessibility). We investigate the dispersion characteristics of rural settlements in the Yellow River Basin in 2020, focusing on both county and city scales. Furthermore, we conduct a comprehensive analysis of the spatial differentiation and scale effects of dispersion evaluation outcomes and their driving forces. Our findings reveal the following insights: (1) The road grade significantly influences the dispersion evaluation. When considering road grade in the dispersion calculation, the results align more closely with the actual situation. (2) The dispersion of rural settlements in the Yellow River Basin exhibits a decreasing trend from west to east. Specifically, the dispersion is higher in the upper reaches compared to the middle and lower reaches. Both city and county scales show spatial autocorrelation in dispersion, with a positive spatial correlation observed. High dispersion values cluster in the west, while low values concentrate in the east. Notably, the agglomeration degree is more pronounced at the county scale than at the city scale, highlighting more localized patterns of agglomeration and dispersion. (3) The multiscale geographically weighted regression model emerges as the optimal model for analyzing the driving forces of dispersion. At the city scale, factors such as river density, road density, and rural economy negatively impact dispersion. However, at the county scale, average elevation and rural economy positively affect dispersion, whereas river density, road density, and rural population density have a negative influence. By incorporating the weight of road grade into our evaluation model, we provide a more nuanced understanding of the spatial distribution dispersion of rural settlements in the Yellow River Basin. Our findings offer valuable insights for policymakers and planners seeking to optimize rural settlement patterns and promote sustainable rural development. [ABSTRACT FROM AUTHOR]

The level of coordination between cultural, ecological, and economic systems directly affects the sustainable development of the Yellow River Basin (YRB). However, researchers have neglected the importance of cultural elements in the social-ecological system and have paid insufficient attention to the interaction of cultural, ecological, and economic systems in the YRB. Therefore, a framework of coupled cultural-ecological-economic (CEE) systems was constructed based on service-dominant logic, and the spatiotemporal distribution, evolutionary trends, and factors influencing the coupled coordination of different systems in 76 major cities in the YRB were analyzed by using an entropy-weighted TOPSIS model, coupled coordination model, spatial Markov chain, and panel spatial Dubin model. The results were as follows: (1) the cultural, ecological, and economic systems of the YRB showed a growing trend, the economic system grew faster than the cultural system and the ecosystem, and the ecosystems dominated sustainable development in the YRB. (2) From 2011 to 2022, the type of coupled CEE system coordination in the YRB was mainly in a state of slight incongruity, with the different regions showing temporal consistency and synchronized growth, with the upstream area mainly in a state of moderate incongruity, the midstream area mainly in a state of slight incongruity, and the downstream area concentrating in general coordination. (3) The spatial coordination level of CEE system coupling in the YRB showed the characteristic of "gradually converging to coordination from upstream to downstream" and exhibited upstream low-value agglomeration and downstream high-value agglomeration. Meanwhile, there was a clear trend of spatial spillover in terms of balanced regional development, and 67.11% of the cities in the region and neighboring areas maintained stable development. (4) Tourism development (TD), foreign trade (FT), the human environment (HE), government control (GC), and other factors significantly positively impacted the sustainable development in the YRB. In the future, the focus should be on improving the transregional infrastructure and transportation service systems in the YRB, to enhance cooperation and exchanges between different regions. This research provides new insights and methods for the coordinated development of cultural, ecological, and economic systems at a watershed scale. [ABSTRACT FROM AUTHOR]

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Assessing and monitoring the green total factor energy efficiency (GTFEE) of cities while considering technology heterogeneity is crucial for the development of energy-conservation and emission-reduction policies. Considering that the heterogeneity of production technologies encompasses several dimensions, this paper proposes a 3E3S (Economy-Environment-Energy-Society-Science-Space) heterogeneity framework and integrates it with the improved meta-frontier global SBM-undesirable to analyze GTFEE and its decomposition. Empirical analysis of cities in the Yellow River Basin of China (YRBC) highlights the following: (1) The 3E3S heterogeneity framework facilitates the classification of all cities into three distinct groups, a finding that contrasts significantly with previous outcomes documented in the literature that relied solely on criteria such as geographic location. (2) The three groups identified under the meta-frontier exhibit substantial energy-saving potentials of 24.49%, 35.17%, and 52.46%, respectively. Additionally, there are spatiotemporal variations in GTFEE, with cities located in the central part of YRBC, particularly those in Shanxi province, demonstrating poor GTFEE performance. (3) The decomposition analysis of GTFEE indicates that technological progress plays a pivotal role in enhancing GTFEE on the whole, albeit with varying approaches for improving GTFEE depending on individual cities. [ABSTRACT FROM AUTHOR]

Improving the green electricity efficiency (GEE), is an important issue for China's high-quality economic development. This study presents a spatial correlation network of urban GEE in the Yellow River Basin from 2012 to 2021, constructed using an improved gravity model. Social network analysis and the quadratic assignment procedure method are employed to analyze the spatial correlation characteristics and influencing factors. The findings indicate that urban GEE in the Yellow River Basin exhibits complex and stable network characteristics. The spatial network analysis reveals that Jiayuguan City, Dongying City, Dingxi City, Zibo City, and Shizuishan City occupy central positions within the network. The results indicate that spatial adjacency, GDP per capita, industrial structure, and the level of science and technology expenditure are positively related to urban GEE, while environmental regulation and average temperature are negatively related. The findings of the study have led to policy recommendations aimed at enhancing urban GEE in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In recent years, non-point source pollution (NPSP) has become prominent in the Yellow River Basin (YRB) of China and seriously affects human survival and sustainable development. The Henan section was selected as an example region of the YRB in China, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model has been used to quantitatively evaluate nitrogen (N) and phosphorus (P). The results show that (1) the cultivated land (CL), grassland (GL), and unused land (UL) decreased, while forest land (FL), water areas (WAs), and built-up areas (BAs) increased in 2000-2020, and precipitation increased from the northeast to the southwest in 2000-2020; (2) the N export was much more than P export in 2000, 2010, and 2020, and the N and P exports increased in 2000-2020; the spatial distribution of N and P export changes was different in the whole basin in 2000-2010, 2010-2020, and 2000-2020; (3) the N and P exports decreased in 2000-2010, 2010-2020, and 2000-2020 with increasing precipitation; and (4) the N and P exports on CL and BAs were more than those on the other land-use types, and the overall change trends of N and P exports on all land-use types increased from 2000 to 2020. [ABSTRACT FROM AUTHOR]

This study investigates the Dynamic Coupling between Land Use Economic Efficiency (LUEE) and Urban Ecological Resilience (UER) in the Yellow River Basin (YRB). This exploration is pivotal for elucidating the interaction mechanisms between economic growth and ecological governance. Furthermore, understanding this relationship is essential for fostering high-quality, sustainable urban development in the YRB. Utilizing panel data from 56 cities spanning 2003 to 2020, this study employed the coupling coordination degree (CCD) model, spatial correlation analysis, Kernel density estimation, convergence model, and Geodetector to systematically analyze the spatio-temporal distribution, dynamic trend, and determinants of the CCD between LUEE and UER in the YRB. The findings indicate that: (1) A general upward trend in both LUEE and UER, accompanied by a steady improvement in their CCD. (2) Significant spatial disparities in their CCD, with higher levels in the lower reaches. (3) Marked positive spatial autocorrelation, predominantly characterized by clusters where high (low) values are surrounded by high (low) values. (4) Regarding the impact of individual factors, government fiscal budget expenditure demonstrates the most robust explanatory power for the CCD within the YRB. Concerning the effects of two-factor interactions, the interplay between industrial structure upgrading and government fiscal budget expenditure emerges as the most significant determinant in influencing the CCD between LUEE and UER. This study enhances our comprehensive understanding of the interplay between economic and ecological systems. It offers scientific insights and strategic direction for harmonizing ecological governance with urban economic growth at both the regional and global scales. [ABSTRACT FROM AUTHOR]

Ecological well-being performance (EWP) is a key indicator of sustainable development and has garnered significant research attention. This study measures the overall and stage-by-stage efficiency of the urban agglomerations in the Yellow River Basin based on the ends–means framework of steady-state economics. This study then delves into the spatiotemporal transfer characteristics of EWP through Moran's I, and spatial Markov chains. Additionally, this research investigates the factors influencing EWP using a random forest model. The findings indicate a notable enhancement in EWP in the urban agglomerations in the YRB from 2006 to 2021, showing clear spatial agglomeration patterns. The shift in EWP types displays a "path dependence" effect, with distinct evolutionary paths influenced by spatial lag effects. Ecological input emerges as a key internal driver of EWP, while urbanization and technological advancements are highlighted as significant external factors. Industrial agglomeration and industrial structure also contribute to improving EWP. The findings of this study help to clarify the spatial and temporal characteristics of ecological welfare performance and its driving mechanisms in the urban agglomerations of the Yellow River Basin. This is conducive to the achievement of high-quality urban transformation and regional green development, and it provides a reference for the construction of an ecological civilization. [ABSTRACT FROM AUTHOR]

Based on the panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this manuscript measures the agricultural low-carbon production efficiency scientifically through the Super-SBM model. In addition, the deviation degree of agricultural industry is used as the index of structural adjustment. Finally, the spatial Durbin model is used to analyze the effect direction and degree of structural adjustment, financial support, and their synergistic effect on agricultural low-carbon production efficiency. The results show that ① the agricultural low-carbon production efficiency in the Yellow River Basin shows a trend of fluctuating downward and a spatial distribution pattern of "high in the east and low in the west". ② Structural adjustment in local region and adjacent areas has a significantly negative impact on agricultural low-carbon production, and the inhibitory effect in adjacent areas is more obvious, and the negative spatial spillover effect is strong. Financial support has a significantly positive impact on agricultural low-carbon production, but the spatial spillover effect of adjacent areas is not obvious. ③ By region, structural adjustment has a significantly negative impact on low-carbon agricultural production in the midstream and downstream regions, while financial support has a significantly positive impact on low-carbon agricultural production in the upstream region. The impact of control variables on agricultural low-carbon production varies from region to region. ④ The synergistic effect of structural adjustment and financial support in the whole and midstream region shows a significantly positive impact on agricultural low-carbon production, indicating that financial support has a certain correction effect on structural adjustment. The coefficient between the upstream and downstream regions is positive but not significant. The conclusions have important reference significance for promoting the ecological protection and high-quality development and agricultural low-carbon development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

China is the world's largest producer and consumer of plastic products, and the densely populated Yellow River Basin underscores the critical importance of water quality safety. Based on extensive research on micro-plastic pollution in the Yellow River Basin, we systematically summarized the current status of micro-plastic pollution, including its sources, shapes and sizes, spatial and seasonal distribution characteristics. In-depth analysis was conducted by considering variations in population density, geographical environment, and seasonal changes across different regions. Furthermore, a comparison with micro-plastic pollution in other major rivers in China was made. The results indicate that the abundance of micro-plastics in the Yellow River Basin generally shows a west-to-east gradient, with most micro-plastics in the main stream of the Yellow River having a particle size concentration below 200 µm, and higher abundance during low-flow periods compared to high-flow periods. Additionally, the biological toxicity of micro-plastics and advances in remediation technologies are systematically discussed. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the current water use situation of the Yellow River Basin and to assess the scale of future water demand. Based on water consumption data from 1988 to 2021, the current water consumption situation in the Yellow River Basin was analyzed, and the Holt linear trend method, the GM(1,1) grey prediction model, the quota method and the multiple linear regression method were used to forecast the water demand in the Yellow River Basin in 2035. The results show that the growth of total water use in the Yellow River Basin from 1988 to 2021 shows three stages of a substantial reduction stage (1988-2003), a rapid growth stage (2004-2015) and a slow reduction stage (2016-2021); The structure of water use in the basin has changed significantly, with the proportion of water used in agriculture and industry declining significantly, with an average annual decline rate of 0.83% and 0.53% respectively; Among the four prediction methods, the multiple linear regression prediction is better, with a predicted water demand of 53.741 billion m³ in 2035. The increase in water demand may lead to greater pressure on water supply and pose a threat to the sustainability of water resources. [ABSTRACT FROM AUTHOR]

Taking the Yellow River Basin as the empirical object, the dissipative structure characteristics, formation and evolution of the innovative ecosystem were explored. The formation process of the dissipative structure of the innovative ecosystem were deduced according to dissipative structure theory, and the dissipation level measure formula was derived from the Brusselator translation model, combined with the entropy weight Topsis method to measure and depict the dissipation level and evolution of innovative ecosystem in the Yellow River Basin from 2011 to 2020. The results show that the dynamic evolution of innovative ecosystems meets the conditions for the formation of dissipative structures. Although the dissipation level of the innovative ecosystem in the Yellow River Basin shows a trend of increasing year by year, no dissipation structure has been formed during the study period. Compared with innovation investment, the innovation landscape is more important for its level of dissipation. The dissipation level of the innovative ecosystem in the Yellow River Basin shows a hierarchical distribution pattern of "downstream leading, midstream following and upstream catching". [ABSTRACT FROM AUTHOR]

By exploring the coupling and coordination relationship between high-quality agricultural development and ecological environment in the Yellow River Basin, and providing scientific reference for ecological protection and high-quality development in the Yellow River Ba- sin, this paper took nine provinces in the Yellow River Basin as the research object, and based on the panel data from 2012 to 2020, adopted the entropy value method, coupling coordination degree, spatial autocorrelation and spatial econometric model to study the coupling and coordination characteristics of high-quality agricultural development and ecological environment, and analyzed the spatial and temporal pattern evolution and driving factors of the coupling and coordination degree between them. The results show that the high-quality development level of agriculture and the ecological environment level in the Yellow River Basin are both on the rise, the regional pattern of the former is mainly "high in the upper and lower reaches and low in the middle reaches". The regional pattern of the latter is mainly "high in the middle and lower reaches and low in the upper reaches". The degree of coupling coordination between high-quality agricultural development and ecological environment is at a relatively low level, higher coupling coordination in the downstream than that of the middle and upper stream, there is a significant spatial agglomeration effect. Scientific and technological innovation and agricultural products trade play a significant role in the coupling and coordination level of high-quality agricultural development and ecological environment in the province (autonomous region), environmental regulation, scientific and technological innovation and agricultural trade have a significant positive space spillover effect, however, the spatial influence degree of each factor is different. In order to promote the improvement of coupling and coordination degree, the following suggestions are put forward; formulating development strategies in accordance with local conditions, strengthening interregional coordination and cooperation, and correctly playing the role of government and market. [ABSTRACT FROM AUTHOR]

In order to provide theoretical support and decision-making basis for improving the level of industrial green development in the Yellow River Basin and promoting the transformation and building industrial green development in the Yellow River Basin, the panel data of nine provinces (regions) in the Yellow River Basin from 2012 to 2021 were used to calculate the level of industrial green development in the Yellow River Basin by using entropy weight-TOPSIS model. The differences were analyzed from spatial distribution, temporal characteristics and provincial levels, and the obstacle factor diagnosis model was used to explore the main obstacle factors affecting the green industrial development in the Yellow River Basin. The results show that the level of industrial green development in the Yellow River Basin shows an over- all upward trend from 2012 to 2021, with the value increasing from 0.378 in 2012 to 0.498 in 2021. The main obstacles to green industrial development in the Yellow River Basin are industrial environmental control and industrial innovation. The main obstacle factors are the proportion of industrial pollution investment in industrial added value, industrial labor productivity, the proportion of industrial wastewater treatment funds in industrial pollution control investment, the number of valid invention patents per household of industrial enterprises above designated size, and the level of innovation capital investment. Finally, the paper put forward some suggestions to improve the level of industrial green development in the Yellow River Basin from three aspects of optimizing industrial structure, strengthening environmental governance and building green innovation system. [ABSTRACT FROM AUTHOR]

Green credit and technological progress play an important role in curbing carbon emissions. In order to provide a reference for the nine provinces (autonomous regions) in the Yellow River Basin to reduce carbon emissions as soon as possible and develop with high quality, the panel data of the nine provinces (autonomous regions) in the Yellow River Basin from 2008 to 2020 were presented. Based on the geographical distance matrix and economic distance matrix between provinces (regions), the global Molan index of carbon emissions was calculated, and a spatial Dubin econometric model was constructed to analyze the spatial and synergistic effects of green credit and technological progress on carbon emissions in nine provinces (regions) of the Yellow River Basin. The results show that: a) There is a spatial correlation between carbon emissions in the nine provinces (regions) of the Yellow River Basin, mainly showing "low-low" agglomeration and "high-high" agglomeration. Green credit and energy use technology progress have significant spatial effects on carbon emissions; b) Green credit has a significant inhibitory effect and spatial spillover effect on carbon emissions. The broad sense of technological progress has little effect on carbon emissions in the nine provinces (autonomous regions) of the Yellow River Basin, and the progress of energy use technology has a long-term inhibitory effect on carbon emissions in the province (autonomous region) and neighboring provinces (autonomous regions); c) Technological progress in energy use and green credit have a synergistic effect on promoting carbon reduction in the nine provinces (autonomous regions) of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

As one of the most vital ecological regions in China, the well-being of the Inner Mongolia section of the Yellow River Basin directly hinges upon comprehending the variations in its ecosystem. The current research puts emphasis on the analysis of single-factor ecological indicators within the Mongolian section of the Yellow River and lacks summarization and analysis regarding the overall state of the ecosystem within the Mongolian section of the Yellow River. This study, using methods such as remote sensing interpretation and model simulation, combined with ground surveys, analyzes the macrostructure, quality status, service functions, and driving factors of the ecosystem in the Inner Mongolia section of the Yellow River Basin from 2000 to 2020. The results indicate that (1) in 2020, the ecosystem structure in the Inner Mongolia section of the Yellow River Basin was predominantly composed of forest, grassland, and other types of systems. (2) From 2000 to 2020, the Normalized Difference Vegetation Index (NDVI), Fractional Vegetation Cover (FVC), and net primary productivity (NPP) all showed increasing trends in the Inner Mongolia section of the Yellow River Basin, with NPP showing a slightly greater increase compared to the NDVI and FVC. (3) Over the past two decades, the overall rate of decrease in the wind erosion modulus per unit area was 1.675 t hm−2. (4) An analysis of the drivers of ecosystem changes revealed that while climate change has exerted an influence, human activities have likewise had a substantial effect on the ecosystem over the past 20 years. This study contributes to a comprehensive understanding of the current status and changes in the ecosystem, providing a decision-making basis for subsequent ecological protection and management projects. [ABSTRACT FROM AUTHOR]

Reservoir construction and operation profoundly alter the hydrological, hydrodynamic, and carbon and nitrogen cycling processes of rivers. However, current research still lacks a systematic understanding of the characteristics of greenhouse gas (GHG) emissions from reservoirs in arid/semi-arid regions. This study integrates existing monitoring data to discuss the characteristics of GHG emissions from reservoirs in the Yellow River Basin and illustrate the controlling factors and underlying mechanism of these processes. The results indicate that while CO2 emission flux from reservoirs is lower than that from river channels, the emission fluxes of CH4 and N2O are 1.9 times and 10 times those from rivers, respectively, indicating that the emission of GHG with stronger radiative effect is significantly enhanced in reservoirs. Compared to the reservoirs in humid climates (e.g., the Three Gorges Reservoir), reservoirs in the Yellow River Basin exhibit relatively lower emissions of CO2 and CH4 due to lower organic matter concentrations, but significantly higher N2O emissions due to higher nitrogen loads. Monte Carlo simulations for 237 reservoirs in the Yellow River Basin showed that total emission of the three GHGs is 3.05 Tg CO2-eq yr−1, accounting for 0.39% of the total emission from global reservoirs and lower than the area percentage of the basin (0.53%). This study has important implications on revealing the GHG emission characteristics and control mechanisms of reservoirs in arid/semi-arid regions. [ABSTRACT FROM AUTHOR]

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios. [ABSTRACT FROM AUTHOR]

Understanding the responses of water yield (WY) to climate change and vegetation greening is crucial for water resources management. However, quantifying the feedback relationships among climate, vegetation, and WY remains challenging. In this study, we developed a system feedback assessment framework based on Integrated Valuation of Ecosystem Services and Tradeoff (InVEST), gravity center model, and structural equation model to reveal these relationships. The framework involves identifying land cover transfer projects, assessing spatio-temporal variations in climate, vegetation, and WY, and quantifying their system feedback relationships, which was applied in the Yellow River Basin (YRB) with significant climate change and vegetation greening. The results demonstrated that precipitation, Normalized Difference Vegetation Index (NDVI), and WY showed significant increasing trends (p < 0.05) at rates of 2.92 mm/a, 0.004 /a and 0.71 mm/a, respectively, during 1991–2020. The areas of significant increase in precipitation, NDVI, and WY were primarily concentrated in the source and midstream of the YRB. The gravity centre of WY moved southwest from 1991 to 2000 and then northeast from 2000 to 2020 in the YRB. Precipitation changes and ecological restoration were identified as key driving factors affecting the variation of WY. Our findings highlight the possible negative effects of ecological restoration on WY variation and provide important information for developing adaptation strategies for land use management in the YRB or other regions. [ABSTRACT FROM AUTHOR]

The uneven distribution of global navigation satellite system (GNSS) continuous stations in the Yellow River Basin, combined with the sparse distribution of GNSS continuous stations in some regions and the weak far-field load signals, poses challenges in using GNSS vertical displacement data to invert terrestrial water storage changes (TWSCs). To achieve the inversion of water reserves in the Yellow River Basin using unevenly distributed GNSS continuous station data, in this study, we employed the Tikhonov regularization method to invert the terrestrial water storage (TWS) in the Yellow River Basin using vertical displacement data from network engineering and the Crustal Movement Observation Network of China (CMONOC) GNSS continuous stations from 2011 to 2022. In addition, we applied an inverse distance weighting smoothing factor, which was designed to account for the GNSS station distribution density, to smooth the inversion results. Consequently, a gridded product of the TWS in the Yellow River Basin with a spatial resolution of 0.5 degrees on a daily scale was obtained. To validate the effectiveness of the proposed method, a correlation analysis was conducted between the inversion results and the daily TWS from the Global Land Data Assimilation System (GLDAS), yielding a correlation coefficient of 0.68, indicating a strong correlation, which verifies the effectiveness of the method proposed in this paper. Based on the inversion results, we analyzed the spatial–temporal distribution trends and patterns in the Yellow River Basin and found that the average TWS decreased at a rate of 0.027 mm/d from 2011 to 2017, and then increased at a rate of 0.010 mm/d from 2017 to 2022. The TWS decreased from the lower-middle to lower reaches, while it increased from the upper-middle to upper reaches. Furthermore, an attribution analysis of the terrestrial water storage changes in the Yellow River Basin was conducted, and the correlation coefficients between the monthly average water storage changes inverted from the results and the monthly average precipitation, evapotranspiration, and surface temperature (AvgSurfT) from the GLDAS were 0.63, −0.65, and −0.69, respectively. This indicates that precipitation, evapotranspiration, and surface temperature were significant factors affecting the TWSCs in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Abstract Objectively and accurately identifying the spatial structure and protection scope of intangible cultural heritage and constructing intangible cultural heritage corridors are crucial for the comprehensive systematic protection of intangible cultural heritage and the synergistic development of the region. However, the current research on intangible cultural heritage is limited to the protection and development of intangible cultural heritage in specific locations or specific areas. Thus, systematic and holistic research perspectives are relatively limited. Therefore, this study employs geographic information system spatial analysis and the minimum cumulative resistance model to construct an intangible cultural heritage corridor in the Yellow River Basin. This study aims to establish a systematic protection method and framework for intangible cultural heritage. The results show the following: (1) The intangible cultural heritage in the Yellow River Basin has a large-scale centralized distribution and small-scale scattered distribution, which provides an important spatial basis for the construction of intangible cultural heritage corridors. (2) Overall, intangible cultural heritage corridors can be more effectively constructed in the eastern region of the Yellow River Basin than in the western region, with 84.6% of the area being suitable and 15.4% being unsuitable. (3) Based on the suitability analysis, the "18 + N" corridor system of intangible cultural heritage in the Yellow River Basin, distributed across the eastern, central and southern regions, is constructed. The major corridor has a suitable width of 60–100 km, a total length of 11,935 km, and an area of 625,976 km2–919,942 km2, and can connect 634–711 intangible cultural heritage sites in series. On this basis, this study proposes a multilevel construction system for intangible cultural heritage corridors in the Yellow River Basin that integrates the "network structure–spatial scope" and "element–axis–region" levels. This approach culminates in a pattern of intangible cultural heritage protection and development in the Yellow River Basin characterized by "connecting points into lines, distributing in groups, and linking regions." This study reveals that combining geographic information system spatial analysis tools with a minimum cumulative resistance model effectively identifies potential heritage corridor networks and clarifies the hierarchical relationships of heritage element protection in the study area. This approach provides a reference model for the comprehensive protection and systematic development of intangible cultural heritage in the Yellow River Basin. Furthermore, the effectiveness and universality of this framework make it applicable to the protection and development of other similar international heritage areas.

Abstract Improving the green electricity efficiency (GEE), is an important issue for China's high-quality economic development. This study presents a spatial correlation network of urban GEE in the Yellow River Basin from 2012 to 2021, constructed using an improved gravity model. Social network analysis and the quadratic assignment procedure method are employed to analyze the spatial correlation characteristics and influencing factors. The findings indicate that urban GEE in the Yellow River Basin exhibits complex and stable network characteristics. The spatial network analysis reveals that Jiayuguan City, Dongying City, Dingxi City, Zibo City, and Shizuishan City occupy central positions within the network. The results indicate that spatial adjacency, GDP per capita, industrial structure, and the level of science and technology expenditure are positively related to urban GEE, while environmental regulation and average temperature are negatively related. The findings of the study have led to policy recommendations aimed at enhancing urban GEE in the Yellow River Basin.

Abstract This study investigates the Dynamic Coupling between Land Use Economic Efficiency (LUEE) and Urban Ecological Resilience (UER) in the Yellow River Basin (YRB). This exploration is pivotal for elucidating the interaction mechanisms between economic growth and ecological governance. Furthermore, understanding this relationship is essential for fostering high-quality, sustainable urban development in the YRB. Utilizing panel data from 56 cities spanning 2003 to 2020, this study employed the coupling coordination degree (CCD) model, spatial correlation analysis, Kernel density estimation, convergence model, and Geodetector to systematically analyze the spatio-temporal distribution, dynamic trend, and determinants of the CCD between LUEE and UER in the YRB. The findings indicate that: (1) A general upward trend in both LUEE and UER, accompanied by a steady improvement in their CCD. (2) Significant spatial disparities in their CCD, with higher levels in the lower reaches. (3) Marked positive spatial autocorrelation, predominantly characterized by clusters where high (low) values are surrounded by high (low) values. (4) Regarding the impact of individual factors, government fiscal budget expenditure demonstrates the most robust explanatory power for the CCD within the YRB. Concerning the effects of two-factor interactions, the interplay between industrial structure upgrading and government fiscal budget expenditure emerges as the most significant determinant in influencing the CCD between LUEE and UER. This study enhances our comprehensive understanding of the interplay between economic and ecological systems. It offers scientific insights and strategic direction for harmonizing ecological governance with urban economic growth at both the regional and global scales.

Abstract Studying the carbon effect of land use in watersheds is important for mitigating global warming, promoting coordinated emission reduction in different regions within the watersheds, and realizing high-quality development of the watersheds. Although a number of scholars have carried out relevant studies in the past, they mainly focused on carbon emissions, rarely involved the carbon balance formed by carbon sources and sinks, and lacked relevant studies on the development of low-carbon economy sub-region. Based on this, this study takes the Yellow River Basin as an example, explores the spatial and temporal evolution of carbon emissions from land use in counties in the Yellow River Basin from 1980 to 2020, and predicts the spatial pattern of carbon income and expenditure from land use under natural conditions in 2030 and 2060 using the PLUS model; and then superimposes on the main functional area planning, divides 735 counties in the Yellow River Basin into six low-carbon economic development subregions, and analyzes their economic development The model of their economic development is analyzed. The results show that: (1) the spatial and temporal differentiation of land use carbon balance in the Yellow River Basin has changed greatly over the past 40 years, (2) the spatial distribution pattern of land use carbon balance in the natural context in 2030 and 2060 is more similar to that in 1990, (3) the carbon emission reduction potentials and pattern optimization of the different low-carbon economic development subregions differ greatly, and they have different low-carbon economic development patterns. The results of this study provide a theoretical basis for scientifically and rationally formulating economic policies for low-carbon development in the counties of the Yellow River Basin, and also provide an important reference for related studies in other similar basins or regions in the world.

The capabilities of 23 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 were evaluated for six extreme precipitation indices from 1961 to 2010 using interannual variability and Taylor skill scores in the Yellow River Basin and its eight subregions. The temporal variations and spatial distributions of extreme precipitation indices were projected from 2021 to 2050 under the shared socioeconomic pathway scenarios (SSP2–4.5 and SSP5–8.5). The results show that most GCMs perform well in simulating extreme values (1-day maximum precipitation (RX1day) and 5-day maximum precipitation (RX5day)), duration (consecutive dry days), and intensity index (simple daily intensity index (SDII)), and perform poor in simulating the threshold indices (precipitation on very wet days (R95p) and number of heavy precipitation days (R10mm)). The projected changes in extreme precipitation indicate that under the SSP2-4.5 scenario, future extreme precipitation will increase by 15.7% (RX1day), 15.8% (RX5day), 30.3% (R95p), 1d (R10mm), and 6.6% (SDII), respectively, decrease by 2.1d (CDD). The aforementioned changes are further enhanced under the SSP5-8.5 scenario. Extreme precipitation changes widely in Hekou Town to Longmen, in the northeastern part of the region from Longmen to Sanmenxia, below Huayuankou, and in the interflow basin. HIGHLIGHTS The study evaluated the biases of 23 global climate models (GCMs) from observations and the spatial distribution of the biases.; Interannual variability score, Taylor diagram, and Taylor skill score were used to evaluate CMIP6 GCMs.; The future changes of the Yellow River Basin and its subregions extreme precipitation under SSP2-4.5 and SSP5-8.5 scenarios were projected by using six ETCCDI indices.;

[Objective] The study on the spatial-temporal change characteristics of land use/cover is of great significance for the protection and rational development of land resources in the Yellow River Basin, and can provide an important reference for the implementation of ecological protection and high-quality development strategy in the Yellow River Basin. [Methods] Based on the annual land use/cover data of the Yellow River Basin from 1980 to 2021, the characteristics of land use/cover change in the Yellow River Basin in recent 40 years were investigated by using Mann-Kendall and sliding t-test, geographic information TUPU standard deviation ellipse and gravity shift model. [Results] (1) From 1980 to 2021, forest land, shrub, water area, and construction land increased significantly, while the cultivated land, grassland, and wetland decreased significantly. (2) The periods of land use/cover change in the basin can be divided into 1980—1992, 1993—2001, 2002—2012, and 2013—2021, and the quantitative structure gradually presented by rapid changes, and the changes of construction land, wetland and water area were sensitive. The balance of land-use structure was gradually increased, and the stage changes showed a high correlation with the implementation of major strategic measures, and more consistent with the divided stage. (3) In the middle and upper reaches of the basin, the main changes were from 2012 to 2021 and intermittent changes, and the main changes were from 2001 to 2012 and from 2012 to 2021, and the main changes were from 2001 to 2012 and from 2012 to 2021, and the main changes were from arable land to construction land and grassland. The basin changed frequently in northern Ningxia, eastern inner Mongolia and some areas along the Yellow River system. (4) The centers of gravity of wetland, water and construction land moved westward, showing concentrated distribution to the southwest, east and northwest, respectively. [Conclusion] The overall trend of land use structure becomed better under the guidance of policies. In the future, we should pay more attention to wetlands and areas with frequent land use changes.

Abstract The watershed system has a complex game relationship between the benign operation and coordinated development of various elements of flood-sediment transportation, eco-environment, and socio-economy (FES). With the increasing breadth, depth, and intensity of human activities in watersheds, it is urgent to coordinate the FES. The relationship of water–sediment in the Yellow River Basin (YRB) is complex, with a prominent contradiction in water supply and a fragile ecosystem. This research tries to build a comprehensive evaluation model for FES and explore the complex interaction between FES in the YRB from 2000 to 2020. The results demonstrated that (1) the comprehensive flood-sediment transportation index (CFTI) and comprehensive eco-environment index (CEI) presented fluctuating growth. In contrast, the comprehensive socio-economy index (CSI) revealed a linear growth trend. The CFTI of Sanmenxia, CEI of Toudaokuan, and CSI of Ningxia had the highest growth rates, with 36.03%, 6.48%, and 107.5%, respectively. (2) FES's positive and negative effects were alternating, with heterogeneity in both time and space. (3) The coupling coordination degree (CCD) in the YRB indicated an increasing trend, ranging from 0.53 to 0.87, from reluctantly coordinated development to good coordinated development. The lagging subsystem was CFTI (2000–2001 and 2008–2020) and CSI (2002–2007), and the CEI was not lagging. (4) Exploratory Spatial Data Analysis (ESDA) demonstrated significant differences in the CCD of the YRB, and areas with similar CCD within the basin tend to be centrally distributed in space. At the same time, there was negative spatial autocorrelation in coordination. The results provide a scientific theoretical and methodological framework for strategic research on the YRB system's governance, protection, and management.

Studying the carbon effect of land use in watersheds is important for mitigating global warming, promoting coordinated emission reduction in different regions within the watersheds, and realizing high-quality development of the watersheds. Although a number of scholars have carried out relevant studies in the past, they mainly focused on carbon emissions, rarely involved the carbon balance formed by carbon sources and sinks, and lacked relevant studies on the development of low-carbon economy sub-region. Based on this, this study takes the Yellow River Basin as an example, explores the spatial and temporal evolution of carbon emissions from land use in counties in the Yellow River Basin from 1980 to 2020, and predicts the spatial pattern of carbon income and expenditure from land use under natural conditions in 2030 and 2060 using the PLUS model; and then superimposes on the main functional area planning, divides 735 counties in the Yellow River Basin into six low-carbon economic development subregions, and analyzes their economic development The model of their economic development is analyzed. The results show that: (1) the spatial and temporal differentiation of land use carbon balance in the Yellow River Basin has changed greatly over the past 40 years, (2) the spatial distribution pattern of land use carbon balance in the natural context in 2030 and 2060 is more similar to that in 1990, (3) the carbon emission reduction potentials and pattern optimization of the different low-carbon economic development subregions differ greatly, and they have different low-carbon economic development patterns. The results of this study provide a theoretical basis for scientifically and rationally formulating economic policies for low-carbon development in the counties of the Yellow River Basin, and also provide an important reference for related studies in other similar basins or regions in the world. [ABSTRACT FROM AUTHOR]

Conservation and restoration of wetlands have become a global priority as awareness of their importance increases. At present, efforts to restore wetlands have primarily focused on enhancing water quality and biodiversity, with little attention paid to analyzing the recovery of the food web. We investigated the differences in food web attributes between natural and restored wetlands in Qingtongxia wetlands on the upper reaches of the Yellow River, China. Our results showed that there were no significant differences in the community structure of aquatic organism (fish, macroinvertebrates, zooplankton, phytoplankton and macrophytes) and water parameters (TP, TN, DO, et al.) between natural and restored wetlands. Restored wetlands had higher total system throughput and primary productivity compared to natural wetlands, which increased the proportion of the detritus food chain in the energy supply. However, energy transfer at the system level was less efficient than in natural wetlands. Indices of cycling, path length and network analysis showed that the restored wetland was less mature but more stable than the natural wetland. Given the inconsistency of food web recovery with water variables and aquatic assemblages, integrating community and food web approaches in future wetland restoration will be critical to refining restoration goals and enhancing conservation efforts. [ABSTRACT FROM AUTHOR]

Based on the camping sites in the Yellow River Basin published by Amap, this study examines the spatial distribution pattern of camping sites using various indices, including the average nearest neighbor index, geographical concentration index, disequilibrium index, and kernel density estimation. The research findings are as follows: (1) Camping sites exhibit a highly significant agglomeration distribution, and the spatial scale presents a non-equilibrium characteristic of "east dense west sparse". The distribution density of camping sites shows clear hot and cold spots, forming a general pattern of "one belt, one mass, two points". The locations of these camping sites commonly follow the rule of "backing mountains, along roads, and accompanied by scenery". (2) The spatial distribution of camping sites is influenced by both natural factors, such as elevation and air quality, and social factors, such as highway mileage and the number of high-level scenic spots. The impact of social factors is found to be more substantial than that of natural environmental factors. [ABSTRACT FROM AUTHOR]

In order to quantitatively evaluate the impact of inter-industry water rights transfer on economy and society in the main stream of the Yellow River in Inner Mongolia, the paper analyzed the impact of water rights transfer on agriculture, and the impact of water rights transfer on water use, production and operation, annual income, people's livelihood and economy of all industrial enterprises. The results show that the transfer of inter-industry water rights in the main stream of the Yellow River in Inner Mongolia in 2019-2021 has driven the total investment of industrial projects to 599.58 billion Yuan, created 122 145 new jobs, the gross regional product is 44.709 billion Yuan, the industrial added value is 238.821 billion Yuan, the annual tax revenue is 19.47 billion Yuan, the newly paved road area is 13.161 7 million km², and the new green area is 30.995 million km². The agricultural output value and farmers' income have been significantly increased, local livelihood issues have been effectively solved, and ecological protection and social and economic development along the Yellow River have been promoted. The transfer of water rights between industries in the main stream of the Yellow River in Inner Mongolia has alleviated the bottleneck of water resources of industrial enterprises along the Yellow River, realized the multi-win of farmers' production increase, economic efficiency increase and ecological restoration, and provided strong support for ecological protection and high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Current hydrological prediction model studies lack analysis of the differential selection of modeling parameters for neural networks in different watersheds, and the adaptability of the model is low, which is not conducive to the promotion and application of the model. In this study, three sub-basins of the Yellow River Basin were selected as the research objects, and the parameter differences of hydrological stations in different characteristic sub-basins were modeled based on the discrete wavelet algorithm and Long Short-Term Memory (LSTM) model. The aim was to improve the adaptability of hydrological prediction models. The results show that for hydrological stations with good periodicity of historical flow and less human influence, a prediction model can be built based on the historical flow of the station. For mainstream hydrological stations with greater influence from upstream flow, the predictive power of the model based solely on the historical flow of the station is lower. Combining the upstream flow, it can improve the prediction accuracy of the model. Moreover, the farther the upstream hydrological station considered is from the predicted hydrological station, the longer the flow can be predicted by the model. For basins with small river flow and significant influence from groundwater and precipitation, the predictive power of the model based solely on the historical flow of the station is lower, but incorporating rainfall can improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

In order to promote the implementation of the action of deep water saving and control in the Yellow River Basin and improve the level of intensive utilization of water resources in Shaanxi Province, this paper discussed the definition of deep water saving, using the Fuzzy Analytic Hierarchy Process (FAHP) to establish the evaluation index system of deep water saving level, evaluated the deep water saving level of cities in the Yellow River Basin of Shaanxi Province, put forward the existing problems and countermeasures, and calculated the deep water saving potential according to the deep water saving goal, which had theoretical support for the implementation of deep water saving in Shaanxi Province. The results show that in the current year, the level of deep water saving in Xi'an, Xianyang, Yan'an, Tongchuan, Baoji, Hancheng, Yangling, Yulin, Shangluo and Xixian New District is strong, and the level of deep water saving in Weinan is general. The deep water saving potential of the Yellow River Basin in Shaanxi Province during the 14th Five-Year Plan period is 323.9 million m³, which can increase the water saving potential of 82.7 million m³ compared with the general water saving situation [ABSTRACT FROM AUTHOR]

In order to explore the mechanism of digital economy enabling high-quality development in the Yellow River Basin and provide reference for the full implementation of major national strategies for ecological protection and high-quality development in the Yellow River Basin, based on the theoretical analysis of the relationship between digital economy and high-quality development, the evaluation index systems of high-quality development level and digital economy development level were built respectively. Based on the panel data of 60 cities along the Yellow River from 2011 to 2020, the entropy method was used to measure the digital economy development level index and high-quality development level index in the Yellow River Basin. Then, taking the high-quality development level as the explained variable, the digital economy development level as the core explanatory variable, the industrial structure upgrading and green technology innovation as the mechanism variables, and the environmental level and employment level as the control variables, the benchmark measurement model and the mechanism test model were built. Through the model regression, the mechanism of digital economy promoting the high-quality development of the Yellow River Basin was empirically analyzed, and the empirical analysis results were endogenous and robust. The results show that the high-quality development of the Yellow River Basin empowered by the digital economy is significant, and its internal mechanism is to promote the upgrading of industrial structure and green technology innovation. There are spatial differences in the high-quality development of the Yellow River Basin enabled by the digital economy. Its role is most obvious in the middle reaches of the Yellow River and relatively smaller in the upper and lower reaches. It puts forward policy suggestions such as comprehensively promoting the development of digital economy in the Yellow River Basin and further enabling high-quality development, promoting the upgrading of industrial structure, improving the level of green technology innovation, implementing regional differentiation development strategy, and promoting regional integration development. [ABSTRACT FROM AUTHOR]

Expanding the breadth and depth of research on high-quality development, further improving the measurement system and research paradigm for high-quality development, and providing reference for the comprehensive and deepening implementation of the major national strategy of ecological protection and high-quality development in the Yellow River Basin, building a high-quality development system evaluation index system based on the new development concept, and making innovative development, coordinated development, green development, open development, and shared development as the five sub-systems of high-quality development, using the period from 2010 to 2020 as the research period and 62 prefecture level cities along the Yellow River as sample cities, the entropy weight method was used to calculate the development index of 5 sub-systems and the comprehensive index of high-quality development systems. Then, the equilibrium level of each subsystem of high-quality development was measured by the equilibrium entropy model, the dynamic evolution of the equilibrium level of the high-quality development system in the Yellow River Basin was analyzed by the kernel density estimation method, and the influencing factors of the equilibrium level of the high-quality development system in the Yellow River Basin were detected by the geographic detector. The results show that a) the balance level and comparative advantages of various sub-systems of high-quality development in the Yellow River Basin are shifting towards a positive direction. Most prefecture level cities have good balance in high-quality development systems, while a few prefecture level cities have systemic imbalances. The middle reaches of the Yellow River have the highest balance level of high-quality development systems, while the downstream areas have the lowest balance level of high-quality development systems. b) The comprehensive level of high-quality development system and the equilibrium level of the sub-systems in the Yellow River Basin are mismatched. The comprehensive level of high-quality development system in most cities in the middle and upper reaches is relatively lower, while the equilibrium level of each sub-system is relatively higher, indicating low-level equilibrium. The comprehensive level of high-quality development system in most cities in the downstream is relatively higher, while the equilibrium level of each sub-system is relatively lower, indicating high-level imbalance. c) There are significant spatial differences in the overall balance level of high-quality development systems in the Yellow River Basin, as well as in the upper, middle, and lower reaches. At the same time, there is a phenomenon of "club convergence" in all regions, and the polarization phenomenon within each region is gradually weakening. d) The driving effects of innovative development, coordinated development, green development, open development, and shared development on the balanced level of high-quality development system in the Yellow River Basin have spatial differentiation, and the mutual influence between the two has an enhancing effect. Suggestions have been put forward for the dual development of quantity and quality in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Dongping is an important area in the Yellow River Basin, with important geographical position and prominent ecological functions. Local cultural resources are extremely rich. In the context of the rural revitalization strategy, Dongping County vigorously develops cultural tourism and strengthens the construction of agricultural industry in order to achieve synergistic benefit between them. On the basis of phased results of Dongping cultural and tourism integration development to promote rural revitalization, this paper deeply explores the reasons behind the difficulties. Specific suggestions are put forward from the aspects of infrastructure construction, personnel training, experience projects, featured product development, to promote the implementation of rural revitalization strategy in Dongping County. [ABSTRACT FROM AUTHOR]

Introduction: The Yellow River Basin is an important national energy base and ecological protection area, and it is of great significance to promote the coordinated development of high-quality development and eco-environmental carrying capacity in the region. Methods: Taking the 73 prefecture-level cities along the Yellow River as the study unit, this paper measures the changes of high-quality development level and eco-environmental carrying capacity of municipalities from 2005 to 2020, using the coupling coordination degree model and fuzzy logic algorithm. Results and discussion: 1) The capital city and its surrounding cities have a high level of high-quality development, with the lower and middle reaches of the Yellow River having higher levels than the upper reaches. From 2005 to 2020, the level of high-quality development showed an upward trend. 2) The eco-environmental carrying capacity of cities in the lower reaches is higher than that in the upper reaches. From 2005 to 2020, the eco-environmental carrying capacity of cities in the lower reaches of the Yellow River increased first and then decreased. 3) The provincial capital cities have a high degree of coupling coordination, with cities in the lower reaches having a higher level than those in the middle and upper reaches. A high degree of coupling coordination reduces spatial differences, but dominated by primary coordination. 4) From 2005 to 2020, the eco-environmental carrying capacity tended to be coordinated with the high-quality development, close to a high level and system optimization. In the end, we conclude with policy recommendations to promote high-quality urban development and harmony between people and nature in the region. [ABSTRACT FROM AUTHOR]