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Increasing total factor carbon productivity (TFCP) is crucial to mitigate global climate change and achieve carbon neutrality target. The Yellow River Basin is a critical energy area in China, but its TFCP is relatively low, which results in particularly prominent environmental problems. This paper investigates TFCP using MCPI, Global Moran’s I and kernel density estimation based on panel data of the 9 provinces along this vast basin in 2007–2017. The results demonstrate that: the average value of TFCP fluctuates around 1 and overall TFCP evolution exhibits significant spatial aggregation effect, and technological progress is the dominant impetus for TFCP growth. At regional level, regional heterogeneities of TFCP change and its dynamics exactly exist, with Qinghai the lowest performance and Shandong the highest performance. Moreover, global Moran’s I index reflects there is a significant positive spatial correlation between provincial TFCP, and cumulative TFCP takes on a certain degree of club convergence features. Furthermore, specific and targeted recommendations have drawn from this paper, in particular for the Yellow River Basin, to increase TFCP and achieve sustainable development in the long run.

It has been difficult to revise and adjust the water distribution of the Yellow River in 1987 (1987 water distribution scheme). By gathering data and studies from previous literature, this paper summarized some water distribution ideas, principles and rules in transboundary rivers. We proposed the “synthesis–dynamic–harmonious” water distribution method (SDH), and applied it to the actual conditions of the Yellow River basin. Through the SDH method, we calculated a new scheme for water distribution in the Yellow River and analyzed the results. The key findings of this study are summarized below. Firstly, the water distribution of transboundary rivers required the establishment of advanced water distribution ideas. Secondly, the proposed water distribution method took into account a variety of factors: with the change in distributable water volume, the same ratio changes and meets the minimum water demand and water efficiency constraints. Thirdly, the 1987, the water distribution scheme needed some adjustment. Fourthly, under the new Yellow River basin water distribution scheme (“19ZQT” water distribution scheme), Shandong, Inner Mongolia, and Henan account for 50% of the total water distribution. Sichuan accounts for only 0.3% of the total. Compared with the 1987 water distribution scheme, Hebei and Tianjin reduced the amount of water allocated by 51.2%, while Shaanxi increased it by 24.89%. In this paper, considering the changes in the total distributable water volume, the new Yellow River water distribution scheme (“19ZQT” water distribution scheme) assumed water distribution of 37 billion m3 and 30 billion m3, upon which calculations were performed. This study should provide a scientific and reasonable scheme for water distribution of transboundary rivers, and rational utilization of water resources. It should lay a solid foundation for the high-quality development of the Yellow River basin.

Low-carbon transition is of great importance in promoting the high-quality and sustainable development of urban agglomerations in the Yellow River Basin (YRB). In this study, the spatial Markov chain and Dagum’s Gini coefficient are used to describe the distribution dynamics and regional differences in the carbon emission intensity (CEI) of urban agglomerations in the YRB from 2007 to 2017. Additionally, based on the spatial convergence model, this paper analyzed the impact of technological innovation, industrial structure optimization and upgrading, and the government’s attention to green development on the CEI’s convergence speed for different urban agglomerations. The research results show that: (1) The probability of adjacent type transfer, cross-stage transfer, and cross-space transfer of the CEI of urban agglomerations in the YRB is small, indicating that the overall spatiotemporal distribution type of CEI is relatively stable. (2) The CEI of urban agglomerations in the YRB has decreased significantly, but the spatial differences are still significant, with a trend of continuous increase, and regional differences mainly come from the differences between urban agglomerations. (3) Expanding innovation output, promoting the optimization and upgrading of industrial structure, and enhancing the government’s attention to green development has a significant positive effect on the convergence rate of the CEI of urban agglomerations in the YRB. This paper holds that implementing differentiated emission reduction measures and actively expanding regional collaborative mechanisms will play an important role in reducing the spatial differences in carbon emissions in urban agglomerations in the YRB, realizing the goals of peak carbon and carbon neutrality.

Under the restriction of the national “double carbon” goal, how to realize the coordination between urbanization and low-carbon development in the Yellow River Basin is a problem worthy of attention. In this paper, a new urbanization and ecological carrying capacity evaluation index system is established to evaluate the new urbanization level and ecological carrying capacity of the Yellow River Basin. On this basis, the uncoordinated coupling level of new urbanization and ecological carrying capacity in the Yellow River Basin is measured by using the improved uncoordinated coupling model, and its temporal and spatial characteristics and internal impact mechanism are analyzed. The study shows that the new urbanization and ecological carrying capacity of the Yellow River Basin has a benign development trend as a whole. Shandong province belongs to the low-level uncoordinated coupling type; Gansu Province and Qinghai Province belong to the running-in uncoordinated type; and Shanxi Province, the Inner Mongolia Autonomous Region, Shaanxi Province, and the Ningxia Hui Autonomous Region belong to the antagonistic uncoordinated coupling type. The uncoordinated coupling degree between new urbanization and ecological carrying capacity in the Yellow River Basin has a spatial interaction effect. It presents a low-level cluster centered on Shaanxi Province and Shandong Province and a high-level cluster centered on Gansu Province, Qinghai Province, and the Ningxia Hui Autonomous Region. From the perspective of the internal main impact mechanism, water resources have a two-way impact on the development of the two systems of new urbanization and ecological carrying capacity; the number of permanent residents and the level of scientific and technological investment have a one-way impact on the process of new urbanization; and the green coverage rate of built-up areas has a one-way impact on the development of ecological carrying capacity. The main contributions of this paper are as follows. First, the evaluation index system of new urbanization and ecological carrying capacity has been improved in combination with the new development concept. The evaluation of new urbanization by this index system is more in line with the current national requirements for high-quality development. Second, the impact of potential resources and human regulation has been added to the traditional ecological carrying capacity evaluation index system, and the evaluation of ecological carrying capacity by this index system is more in line with reality. Thirdly, taking the time effect into account, an improved uncoordinated coupling method is proposed. Using this method to evaluate the relationship between systems is conducive to bringing the dynamic relationship within the system into the evaluation system, which is more in line with the reality of system changes. Fourth, from the perspective of problem diagnosis, research on the relationship between new urbanization and ecological carrying capacity will help to find the internal mechanism that affects the coordinated development of new urbanization and ecological carrying capacity in the Yellow River Basin. This method is universal for exploring the internal influence mechanism of the relationship between systems.

This paper contributes to the study of regional economic resilience by analyzing the dynamic characteristics and influence mechanisms of resilience from the perspective of spatial heterogeneity. This paper focuses on the resistance and recoverability dimensions of resilience and analyzed the dynamic changes in economic resilience in China’s Yellow River Basin in response to the 2008 economic crisis. The multi-scale geographical weighted regression model was utilized to examine the effect of key factors on regional economic resilience. Our findings show the following: (1) The resistance of the Yellow River Basin to the financial crisis was high; however, the recoverability decreased significantly over time. (2) The spatial heterogeneity of driving factors was significant, and they had different effect scales on economic resilience. Related variety, government agency, environment, and opening to the global economy had a significant effect on economic resilience only in a specific small range. Specialization, unrelated variety, and location had opposite effects in different regions of the Yellow River Basin. (3) Specialization limited the area’s resistance to shock but enhanced the recoverability. Related variety improved regional economic resilience. Unrelated variety was not conducive to regional resistance to shock and had opposite effects on the recoverability in different regions. (4) Government agency and financial market promoted regional economic resilience. Environment pollution and resource-based economic structure limited regional economic resilience. Opening to the global economy and urban hierarchy limited regional resistance to shock, but strong economic development had the opposite effect of improved regional resistance. The location in the east of the Yellow River Basin enhanced the recoverability; however, the location in the west limited the recoverability.

Grassland is the most important land use/cover type in the Yellow River basin. Studying its ecosystem services and the trade-off and synergistic relationships between its various functions is of great significance to high-quality development and the protection of the ecological environment in the Yellow River basin. This paper evaluates the five typical functions of grassland in the Yellow River basin quantitatively, including water yield, carbon storage, soil conservation, habitat quality, and NPP by adopting the InVEST model and the CASA model. It analyzes changes in the trade-offs and the synergistic relationships between the five ecosystem functions from 1990 to 2018 by adopting the correlation coefficient method. The paper also analyzes and explores the spatial heterogeneity of the trade-offs and synergistic relationships by adopting the bivariate spatial autocorrelation method. The results show that from 1990 to 2018, the average water yield depth, carbon storage, and NPP of the grassland in the Yellow River basin tended to increase, soil conservation and habitat quality showed a decreasing trend, and the spatial distribution of the five functions were clearly in line with zonal law. The five ecological functions were synergistic, the synergistic relationship between water yield and the other functions was relatively weak, and there was a strong synergistic relationship between the other four functions. The trade-offs and synergistic relationships between the five functions demonstrated significant spatial heterogeneity in space. This research provides a scientific basis for determining the optimal utilization and sustainable development of grassland resources.

The basic premise of regional ecological construction would be to scientifically and effectively grasp the characteristics of land use change and its impact on landscape ecological risk. The research objects of this paper are the typical areas of the Yellow River Basin in China and “process-change-drive” as the logical main line. Moreover, this paper is based on multi-period land use remote sensing data from 2000 to 2020, the regional land use change process and influencing factors are identified, the temporal and spatial evolution and response process of landscape ecological risk are discussed, and the land use zoning control strategy to reduce ecological risk is put forward. The results indicated: (1) The scale and structure of land use show the characteristics of “many-to-one” and “one-to-many”, (2) the process of land use change is affected by the alternation of multiple factors. The natural environment and socio-economic factors dominate in the early stage and the location and policy factors have a significant impact in the later stage, (3) the overall landscape ecological risk level and conversion rate show a trend of “high in the southeast, low in the northwest”, shift from low to high and landscape ecological risks gradually increase, and (4) in order to improve the regional ecological safety and according to the characteristics of landscape ecological risk and spatial heterogeneity, we should adopt the management and control zoning method and set different levels of control intensity (from key intensity to strict intensity to general intensity), and develop differentiated land use control strategies.

As human society is entering an era of scarce natural resources, realizing the welfare level of human society is a fundamental requirement to improve sustainable development, while being restrained by the ecological environment. In this paper, we divided ecological welfare performance (EWP) into an ecological economic system and an economic welfare system from the perspective of ecological welfare, and predicted the EWP in the Yellow River Basin Urban Agglomerations (YRBUAs) using the US-NSBM model in two stages. We further explored the dynamic change trend and spatial convergence characteristics in the YRBUAs using the Dagum Gini coefficient, the kernel density estimation method, and the spatial convergence models. The results indicate that there are great spatial variations in EWP in the YRBUAs, where the spatial variation in the downstream is higher than that in the upstream, and the spatial distribution pattern in large- and medium-sized cities is higher than that in small cities. The DEA efficiency could not be realized overall throughout the study period, but it shows an improving trend. At the same time, absolute β convergence and conditional β convergence were observed in the YRBUAs, both overall and between the UAs. This paper provides a basis for analyzing the spatial pattern of EWP and for promoting the coordinated development of urban agglomerations in the YRBUAs, thus serving as a reference for the sustainable development of ecologically sensitive regions in countries across the world.

Ecosystem services are the beneficial goods and services that ecosystems provide to humans. Urbanization is an important feature of human social development. While promoting economic and social development, it also brings about land degradation, resource depletion, environmental pollution and other problems, intensifying the transformation of natural ecosystems into semi-natural and artificial ecosystems, ultimately leading to the loss of ecosystem service functions and declining value. The study of the impact of urbanization on the value of ecosystem services is of critical importance for the conservation of ecosystems and sustainable development. This study examined the spatio-temporal patterns of urbanization’s impacts on ecosystem service value in the Yellow River Basin from the perspective of spatio-temporal heterogeneity. Findings: (1) Both the ecosystem service value (ESV) and urbanization level (UL) in the Yellow River Basin were on the rise on the whole, but they were significantly spatially negatively correlated and mainly characterized by the high–low spatial clustering of “low ESV–high UL” and “high ESV–low UL”. This negative correlation was gradually weakened with the transformation of the urbanization development mode and ecological restoration projects in the Yellow River Basin. (2) The impacts of the five urbanization subsystems on the value of ecosystem services were diverse. Landscape urbanization had a negative impact on the value of ecosystem services in all regions; economic urbanization and innovation urbanization changed from having a negative to a positive impact; and demographic urbanization and social urbanization had both a positive and a negative impact. (3) To promote the coordinated development of ecological environmental protection and urbanization in the YRB, this paper proposes to change the urbanization development model, implement ecological restoration by zoning, and formulate classified development plans. This study compensates for the shortcomings of current studies that ignore the different impacts of urbanization subsystems on ecosystem service value and lack sufficient consideration of the spatio-temporal heterogeneity characteristics of urbanization and ESVs, enriches the theoretical understanding of the interrelationships between natural and human systems in basin areas, and provides a scientific basis for the rational formulation of urban planning and ecological protection policies in the region, which is of great theoretical and practical significance.

As an essential way to enhance farmers’ self-development ability, off-farm employment plays an indispensable role in farmers’ multidimensional poverty reduction in many countries. Employing a survey of 1926 farmers in five provinces of the Yellow River Basin in China, this paper examined the multi-dimensional poverty reduction effect of off-farm employment and the heterogeneous influence of different dimensions of off-farm employment (modes, levels, distances and frequency). The results showed that (1) although absolute poverty in the income dimension was largely eliminated in the Yellow River Basin, the poverty in social resources, transportation facilities, employment security were the key bottlenecks restricting farmers’ self-development. (2) The province with the best multidimensional poverty reduction effect for non-farm employment was Shaanxi, with the largest contribution to employment security. (3) Improving off-farm employment level, distance and time can significantly alleviate the multi-dimensional poverty of farmers. Therefore, to lessen the multi-dimensional poverty of farmers in the Yellow River Basin, it is necessary to focus on the governance of multi-dimensional key poverty-stricken areas, such as the middle and upper courses of the Yellow River, adopting multidimensional poverty alleviation strategy of off-farm employment according to local conditions, working on the farmers’ deficiencies in social resources, mobility, employment security, and deepening the effect of off-farm employment on benefiting farmers and helping the poor. RESUMO: Como uma forma essencial de aumentar a capacidade de autodesenvolvimento dos agricultores, o emprego fora da fazenda desempenha um papel indispensável na redução da pobreza multidimensional dos agricultores em muitos países. Empregando uma pesquisa com 1926 agricultores em cinco províncias da Bacia do Rio Amarelo na China, este documento examina o efeito multidimensional de redução da pobreza do emprego e a influência heterogênea de diferentes dimensões do emprego fora da fazenda (modos, níveis, distâncias e frequência). Os resultados mostram que (1) embora a pobreza absoluta na dimensão da renda tenha sido em grande parte eliminada na Bacia do Rio Amarelo, a pobreza em recursos sociais, facilidades de transporte e segurança no emprego são os principais gargalos que restringem o autodesenvolvimento dos agricultores. (2) A província com o melhor efeito multidimensional de redução da pobreza para o emprego não agrícola foi Shaanxi, com a maior contribuição para a segurança no emprego. (3) A melhoria do nível de emprego fora da fazenda, distância e tempo pode aliviar significativamente a pobreza multidimensional dos agricultores. Portanto, para diminuir esta pobreza é necessário concentrar-se na governança de áreas-chave multidimensionais atingidas, tais como os cursos médio e superior do Rio Amarelo, adotando uma estratégia multidimensional de redução da pobreza de emprego fora da fazenda de acordo com as condições locais, trabalhando nas deficiências dos agricultores em recursos sociais, mobilidade, segurança no emprego e aprofundando o efeito do emprego fora da fazenda em benefício dos agricultores e ajudando os pobres.

The clean utilization of traditional energy and renewable, clean energy utilization are the key points of the energy structure transition in the Yellow River Basin. This paper constructs an evolutionary game model, with the participation of local governments and energy companies, to analyze the dynamic evolution of each game subject. The results from the study highlight three important facts about the energy mix transformation in the Yellow River Basin: (1) the high ratio of traditional clean energy utilization and the low ratio of renewable, clean energy utilization align with the actual energy use in the Yellow River Basin, which can better promote the inclusive development of both types of energy; (2) increasing the capacity to utilize both energy sources can improve the energy system resilience gains of game players, for example, at the immature stage of renewable, clean energy utilization technologies, local government’s willingness to subsidize renewable clean energy utilization is positively related to their energy system resilience gains; and (3) under the premise of ensuring the energy supply, the introduction of penalty parameters can ensure a reasonable share of both types of energy utilization, and an increase in the penalty parameters makes the game participants increase their willingness to implement energy structure transformation policies.

Understanding ecosystem services(ESs)and their interactions will help to formulate effective and sustainable land use management plans, and clarifying the balance and synergy between watershed ecosystem services can provide a basis for the regulation of the ecological environment in different regions of the watershed and the maximization of overall ecological benefits. This paper takes the Yellow River Basin as the research object and uses the Ecosystem Services and Trade Offs (InVEST)model to evaluate the water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) of the Yellow River Basin. The paper adopts the Carnegie-Ames-Stanford Approach (CASA)model to evaluate the net primary productivity (NPP), draws the spatial distribution map of the five ecosystems, analyzes the trade-off and synergy between the five ecosystems using correlation and binary spatial correlation, and expresses it in space. In addition, it adopts self-organizing mapping (SOM) method to identify ecosystem service clusters. The results show that: (1) ES is generally higher in the upper reaches of the Yellow River, and lower in the middle reaches. (2) WY and NPP, HQ, CS and WY are trade-off relationships, and other ecosystem services are synergistic relationships. Trade-offs and synergy show obvious spatial heterogeneity. (3) The ecosystem services of the Yellow River Basin, driven by different factors, can be divided into three areas, namely WY and SC service leading functional areas, HQ and CS service leading functional areas, and NPP service leading functional areas. Finally, it discusses the driving factors of the spatial heterogeneity of the balance of the ecosystem service functions of the Yellow River Basin and the suggestions of land use management in the basin.

High-quality development (HQD) is a positive initiative in China to promote sustainable development. Promoting HQD in the Yellow River Basin (YRB) is a major national strategy for China. The YRB is an important ecological barrier and economic zone in China, which comprises nine provinces, including Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan and Shandong. The objective of this paper is to provide a comprehensive evaluation of the HQD of the nine provinces in the YRB. It clarifies the basic connotation of HQD and constructs a comprehensive evaluation index system for HQD according to the principles of comprehensiveness, distinctiveness, openness, refinement and feasibility. The comprehensive evaluation index system includes four dimensions: economic development, technology innovation, society and livelihood, and ecological security, which contain 28 secondary indicators. The combined method of coupling development and entropy weight termed the “technique for order preference by similarity to an ideal solution (TOPSIS)” was selected to make a comprehensive evaluation of the HQD of the nine provinces in the YRB from the time dimension and the space dimension, respectively. It was found that there are still problems, such as the differentiation of HQD, the low comprehensive development degree (CDD), and the low development coupling degree (DCD) in some provinces.

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

The Yellow River Basin plays an important role in economic and social development and ecological security; therefore, its ecological protection and high-quality development are vital. In order to understand the level of synergistic development between environment and industry in the Yellow River Basin, and to understand the change in synergy degree through spatial and temporal analysis, and finally to propose suggestions to provide a basis for the policy formulation of environmental protection and industrial development, informing the initiatives of the relevant parties—companies and residents, so as to ensure the high-quality development and sustainable development of the Yellow River Basin, this paper is based on the theory of synergetic and dissipative structure, and it expounds the synergetic mechanism by constructing the compound system of environment and industry in the Yellow River Basin and revealing their internal and external interactions. Based on the panel data of 57 prefecture-level cities in the Yellow River Basin from 2010 to 2020, the synergy degree of environment and industry in the Yellow River Basin and its temporal and spatial characteristics are discussed by using the synergy model of compound systems. The results show that: (1) the overall degree of environmental and industrial synergism in the Basin develops from mildly non-synergistic to mildly synergistic, but the level is still low; there are significant temporal and regional differences in synergy degree in the upper, middle and lower reaches of the Basin and among cities. (2) The number of cities in the basin that are in mild synergy is increasing; the synergy degree shows an overall positive global spatial autocorrelation.

Examining the convergence characteristics of energy eco-efficiency in the Yellow River Basin (YRB) is of great significance for the sustainable development of China. It fulfills the international commitment to carbon peak and carbon neutrality. Based on the Super-EBM model and ML index, this paper measures the energy eco-efficiency of 60 cities in the YRB during 2006–2018, and then spatial and temporal patterns are both analyzed before the final investigation of the convergence in the YRB. The results show the following: (1) From 2006 to 2018, the energy eco-efficiency of the YRB showed a significant upward trend, but there was still a 25.61% improvement compared with the production frontier. (2) The spatial differentiation of the energy eco-efficiency in the YRB was significant, and the inter-regional differences were the main reason for this. (3) There was no σ-convergence in energy eco-efficiency in the YRB during 2006–2018, but absolute and conditional β-convergence did occur. (4) Although the significant factors in the convergences were different, the levels of energy eco-efficiency in the different reaches all developed towards stable levels, and the catch-up effects in the less-developed regions were significant.

Promoting new-type urbanization with the concept of green development has become an inevitable requirement for high-quality development in the Yellow River Basin. Grasping the development trend and influencing factors of green urbanization level in the Yellow River Basin is of great significance for implementing the international conventions on environmental protection and participating in global environmental governance. This paper selects the green urbanization level panel data of nine provinces in the Yellow River Basin from 2006 to 2018. Then, principal component analysis and factor analysis are applied to measure and evaluate the green urbanization level of each province. Furthermore, this paper constructs a dynamic panel estimation model and uses differential generalized method of moments (DIF-GMM) model and system generalized method of moments (SYS-GMM) model to explore the influencing factors. The results show that the overall level of green urbanization in the Yellow River Basin has steadily and rapidly increased, and there are significant spatial differences. The green urbanization level of eastern provinces is significantly higher than that of central and western provinces. In addition, the overall level of green urbanization shows a convergence trend. From the perspective of influencing factors, the factors that have significant positive effects on the level of green urbanization include economic development level, technological innovation level, and urban size. Industrial structure, foreign direct investment (FDI), and education level counteract the level of green urbanization. However, environmental regulation strength and opening degree fail to pass the significance test. Therefore, it is necessary to promote and upgrade industrial transformation, improve the quality of opening up, and strengthen cooperation in technological innovation and environmental governance. There are requirements that the government control the urban size and population scientifically and implement the environmental access system strictly in order to improve the level of green urbanization in the Yellow River Basin. It is more possible to achieve harmonious economic and ecological environment development.

To clarify the evolution of “production-living-ecological” function coupling in the Yellow River Basin, coordinating the spatial allocation of resources, development management and layout optimization, is an important means for achieving ecological protection and high-quality development in the region. In this paper, we conducted an empirical analysis and ARIMA prediction of the coupled production-living-ecological function coordination level in the Yellow River Basin of China from 2008 to 2018, and found that: (1) In terms of temporal evolution, the production-living-ecological function and coupling coordination level of each province and region in the Yellow River Basin generally shows a sharp and then slow upward trend, with the living functions changing more than the production and ecological functions; (2) in terms of spatial pattern, the production and living functions of each province and region show the trend of functional level increasing from east to west over time; the ecological functions, contrary to production and living functions, show a “high-low” aggregation, midstream shows “low-low” aggregation, and downstream shows “low-high” aggregation; (3) According to the regression results of the spatial Dubin model, the environmental governance level, technological research and development level, and social security level and resource dependence degree have positive promoting and spillover effects on the coupling coordination level of the “production-living-ecological” function in the region. However, population density and carbon emission intensity will hinder the development of regional coupling coordination level; (4) from the ARIMA prediction, the coupling coordination level of “production-living-ecological” in the Yellow River Basin continues the development trend of 2008–2018 in the short term, the overall coordination level is at a high level, and the variability of coupling coordination level among provinces and regions is further reduced. Finally, corresponding development countermeasures and suggestions are given to different provinces and regions based on the spatial and temporal evolution characteristics, influencing factors and development trend of the “production-living-ecological” function in the Yellow River basin.

As the most basic physical geographic elements, basin terrain and river networks have high spatial complexity and are closely related. However, there is little research on the correlation between terrain and river networks. In this paper, the Yellow River Basin was selected as the study area. Topographic factors of multiple dimensions were calculated. The influence of different topographic factors on the river network structure at different scales and their correlation from a multifractal perspective based on geographical detectors and a geographically weighted regression model were determined. The explanatory power of topography on the river network structure at different scales was: multifractal spectrum width > multifractal spectrum difference > slope > average elevation > elevation maximum > elevation minimum, which generally indicated that the topographic factor that has the greatest influence on the river network structure is the complexity and singularity of the terrain. The second-order clustering of regression coefficients from the results of the geographically weighted regression model revealed that the Yellow River basin was divided into three types of high-aggregation areas, which are dominated by the Qinghai-Tibet Plateau, the Loess Plateau, and the Huang-Huaihai Plain, respectively. The clustering results also revealed that the river network structure was affected by different key topographic factors in the different types of areas. This research studies and quantifies the relationship between basin topography and river network structure from a new perspective and provides a theoretical basis for unraveling the development of topography and river networks.

In the context of global climate governance, the study of land-use carbon emissions in the Yellow River Basin is crucial to China’s “dual-carbon” goal in addition to ecological conservation and the high-quality developments. This paper computed the land-use carbon emissions of 95 cities in the Yellow River Basin from 2000 to 2020 and examined its characteristics with respect to spatio-temporal evolution and driving mechanisms. The findings are as follows: (1) The overall net land-use carbon emissions in the Yellow River Basin rose sharply from 2000 to 2020. (2) From a spatial perspective, the Yellow River Basin’s land-use carbon emissions are high in the middle-east and low in the northwest, which is directly tied to the urban development model and function orientation. (3) A strong spatial link exists in the land-use carbon emissions in the Yellow River Basin. The degree of spatial agglomeration among the comparable cities first rose and then fell. “Low–Low” was largely constant and concentrated in the upper reaches, whereas “High–High” was concentrated in the middle and lower reaches with an east-ward migratory trend. (4) The rates of economic development and technological advancement have a major positive driving effect. Moreover, the other components’ driving effects fluctuate with time, and significant geographical variance exists. Thus, this study not only provides a rationale for reducing carbon emissions in the Yellow River Basin but also serves as a guide for other Chinese cities with comparable climates in improving their climate governance.

Precise decoupling of CO2 emission and economic development holds promise for the sustainability of China in a post-industrialization era. This paper measures the energy-related CO2 emissions of 57 cities in the Yellow River Basin (YRB) during 2006–2019 and analyzes their decoupling states and dynamic evolution paths based on the derived general analytical framework of two-dimensional decoupling states to decompose their decoupling index using the LMDI method. The results show that (1) from 2006 to 2019, the economic growth and CO2 emissions of cities along the YRB are dominated by weak decoupling at an average contribution of 53.2%. Their dynamic evolution paths show fluctuations of “decoupling–recoupling” states, while the evolution trend is relatively ideal. (2) The factors of economic output, energy intensity and population scale inhibit the decoupling in most cities, which contribute 39.44%, 19.34%, and 2.75%, respectively, while the factors of industrial structure, carbon emission coefficient, and energy structure promote the decoupling in most cities in the YRB, with average contributions of −12.63%, −8.36%, and −0.67%, respectively. (3) The significant increase in the contribution of energy intensity is the main reason for the “Worse” path of cities, while the industrial structure and energy structure factors promote to the “Better” path of cities. This work satisfies the urgent need for the ecological protection of the YRB and opens new avenues for its high-quality development.

With the gradual networking of inter-city relations and the increase in acute impact and chronic stress, the measurement of the resilience of urban network structures is particularly prominent. Based on the construction of the urban network by passenger train trips in the Yellow River Basin, this paper analyzes and assesses the characteristics of the structural resilience of the urban network, and probes into the network resilience and urban response under the circumstances of node failure and line failure in Zhengzhou. The main conclusions are as follows: (1) The urban network in the Yellow River Basin was clearly hierarchical, with a significant spatial distribution of “low in the north and high in the south”, and the overall characteristics of “robustness” in small areas and “fragility” in large areas. The network connection forms were diversified and open. The network transmission efficiency was high, and the edge cities depended on the core cities with prominent characteristics, and the risk load of regional core cities rose. (2) The network structure was “robust” as it maintained high operational efficiency and connectivity under random attacks. Under deliberate attacks, the city network operated efficiently with a small increase in connectivity before the 60% threshold, and after the threshold, the overall network started to split into many sub-networks, and the network fragmentation gradually increased until the network collapsed. (3) Zhengzhou node failure and line failure states in the Yellow River Basin urban network were resilient, in the sense that when suffering important nodes and lines going down it could still maintain good network operation efficiency, and the core nodes in the impact of natural disasters could adapt to the destructive nature of the network through the urban network structure self-regulation.

Globally, nations and regions have pushed for “green development (GD)”, a sustainable development strategy that considers the integrated growth of “economy–environment–society”. As it is an area of China that provides an ecological function and is an important energy base, it is necessary to explore the current situation and factors influencing GD in the Yellow River Basin (YRB). Therefore, first, this paper constructs a GD indicator system from a multi-dimensional perspective, measures the GD of 79 prefecture-level cities in the YRB from 2006 to 2019 by using the entropy method, and analyzes the evolution of time series according to the results. We found that the YRB’s GD showed an overall increase during the study period, rising from 0.1261 to 0.2195, but the level was low. Second, we analyzed the spatial characteristics of the YRB’s GD using a spatial analysis method and concluded that GD varied significantly across cities in the YRB. The YRB presented spatial distribution characteristics with obvious “quad-core pieces”, and there was a high intensity of spatial correlation and agglomeration. The spatial center of gravity of GD moved toward the southeast year by year. Third, we examined the influencing factors of the GD of the YRB through the spatial Durbin model. The study found that the spatial spillover effect on GD in the YRB was obvious, and the reasons affecting the GD of the YRB were heterogeneous. Finally, according to the conclusions of this research, we propose differentiated policies that are suitable for GD in the YRB.

To analyze the spatial distribution characteristics of water resource value in the agricultural system of the Yellow River Basin, this paper takes the Yellow River Basin as its research object and studies the spatial distribution characteristics and influencing factors of water resource value in the agricultural system using the emergy theory and method, the spatial autocorrelation analysis method, and the spatial regression model. The results show the following. (1) The value of water resources in the agricultural system ranges from 0.64 to 0.98 $/m3, and the value in the middle and lower reaches of the basin is relatively high. (2) The Moran index of the water resource value in the agricultural system is 0.2772, showing a positive spatial autocorrelation feature. Here, ‘high-high (high value city gathering)’ is the main aggregation mode, which is mainly concentrated in the middle and lower reaches of the basin. (3) The spatial error model, moreover, has the best simulation effect. The cultivated land area, total agricultural output value, agricultural labor force, and total mechanical power have a significant positive impact on the agricultural production value of water resources in the Yellow River Basin; the altitude, annual average temperature, and agricultural water consumption have a negative impact. Overall, this study shows that guiding the distribution of water resources according to their value and increasing agricultural water use in the middle and lower reaches of the basin will help improve the overall agricultural production efficiency of water resources in the basin. HIGHLIGHTS Spatial distribution analysis provides a basis for the formulation of water resources management policies.; Water resource value in the agricultural system is quantified based on the emergy theory.; The spatial autocorrelation analysis method is used to analyze the spatial distribution of water resources value.; The spatial regression model is used to identify the main influencing factors of water resources value.

As one of the national strategies of China, the ecological protection of the Yellow River basin (YRB) is vital for the promotion of the high-quality development (HQD) of the regional economy. This paper uses the data of prefecture-level cities in the YRB from 2004–2019 to analyze the effect of environmental regulation and local government competition on HQD. The findings show the following: (1) Environmental regulation can significantly promote HQD in the YRB, and local government competition can significantly reduce HQD. The interaction effect shows that the promotion effect of environmental regulation on HQD weakens with the intensification of competition between local governments. (2) A heterogeneity analysis shows that environmental regulation has a more significant positive impact on HQD for the lower reaches of the YRB. (3) Using a threshold effect test, it is found that the impact of environmental regulation on the HQD presents a significant nonlinear positive effect with an increase in local government competition. When the local government competition represented by the level of economic catch-up exceeds the threshold value of 3.037, this positive effect decreases significantly.

In order to promote the sustainable development of a social economy and ecology, the social–economic–natural compound ecosystem (SENCE) conceptual framework was used to construct the water environmental carrying capacity index system. Taking the Gansu section of the Yellow River basin as an example, 18 indexes were selected from the 3 subsystems of social, economic, and natural ecology. Based on the unascertained measure theory and the obstacle factor model, the comprehensive level of water environmental carrying capacity in the Gansu section of the Yellow River basin from 2015 to 2020 was empirically evaluated, and the obstacles that hindered the water environmental carrying capacity were identified and analyzed. The results showed that the comprehensive level of water environmental carrying capacity fluctuated and increased overall, and it was grade III (critical load) from 2015 to 2017 and in 2019 and grade IV (weak load) in 2018 and 2020. Considering the ranking of the obstacle degree of each index, the obstacle factors were concentrated in the natural ecological subsystem, among which the obstacle factors were the discharge of wastewater, the population density, the urbanization rate, and the water resources development and utilization rate, which should be examined in the future. The research results and methods described in this paper could provide a theoretical reference for the evaluation of water environmental carrying capacity for other rivers and lakes.

The Yellow River Basin (YRB) is a significant area of economic development and ecological protection in China. Scientifically clarifying the spatiotemporal patterns of carbon emissions and their driving factors is of great significance. Using the methods of spatial autocorrelation analysis, hot-spot analysis, and a geodetector, the analysis framework of spatiotemporal differentiation and the driving factors of carbon emissions in the YRB was constructed in this paper from three aspects: natural environment, social economy, and regional policy. Three main results were found: (1) The carbon emissions in the YRB increased gradually from 2000 to 2020, and the growth rates of carbon emissions in the different river reaches were upper reaches > middle reaches > lower reaches. (2) Carbon emissions have an obvious spatial clustering character from 2000–2020, when hot spots were concentrated in the transition area from the Inner Mongolia Plateau to the Loess Plateau. The cold spots of carbon emissions tended to be concentrated in the junction area of Qinghai, Gansu, and Shaanxi. (3) From 2000 to 2020, the driving factors of spatial differentiation of carbon emissions in the YRB and its different reaches tended to be diversified, so the impacts of socioeconomic factors increased, while the impacts of natural environmental factors decreased. The influence of the interactions of each driving factor showed double factor enhancement and nonlinear enhancement. This study will provide a scientific reference for green and low-carbon development, emphasizing the need to pay more attention to environmental protection, develop the green economy vigorously, and promote the economic cycle, so as to achieve green development and reduce carbon emissions.

In the context of the global pandemic, the development of tourism in the Yellow River Basin is constrained by the dual mechanisms of the decline in the quality of public service and the deterioration of the ecological environment. In order to promote the high-quality development of the ecological environment in the Yellow River Basin, this paper studies the coordinated development of tourism, the ecological environment and public service in the Yellow River Basin by treating tourism, the ecological environment and public service as a whole. Based on the coupling coordination function GM (1,1) grey prediction method and PVAR model, we discuss the characteristics of spatio-temporal differences, evolutionary trends and the interaction mechanism of the coupling coordination degree (CCD) of tourism-ecological environment-public service in nine provinces along the Yellow River Basin in China from 2008 to 2019. The results show that tourism and public service in the Yellow River Basin are closely related, and the protection of the ecological environment and tourism development are not contradictory. In terms of time, the overall trend is stable and upward from the perspective of the CCD of the three systems; in terms of space, Henan, Shandong, and Sichuan provinces have a relatively high level of CCD. While Qinghai, Gansu, Ningxia, Inner Mongolia, Shaanxi and Shanxi provinces have a lower level of CCD, which shows an upward trend from upstream to downstream in the space. The evolutionary trend of the CCD of the three systems in the basin will be upward in all provinces except for the Shandong province in the next five years. Tourism can promote both the ecological environment and public service from the perspective of the mutual influence mechanism.

Understanding the factors affecting irrigation management performance is crucial for sustainable resource use, especially with the decentralized management mode of irrigation systems being implemented in rural China. This paper contributes to the research field by incorporating different categories of social trust and perceived organization support (POS) into the analysis of irrigation management performance, by linking multiple elements that are based on the Institutional Analysis and Development (IAD) framework. We employed principal component analysis (PCA) and ordered probit regression to analyze a database covering 785 households in the upstream of the Yellow River basin. The results suggested that social trust and POS positively affected the irrigation management performance, and social trust strengthened the positive effect of POS on the performance. Furthermore, the results indicated that personal trust and institutional trust, as well as perceived emotional support and physical support, positively affected the performance. In addition, we also found that household characteristics, household cognition, group characteristics, physical conditions, and rules-in-use also had significant impact on the performance. This paper can be used to inform the government that social trust and POS need to be considered in the common-pool resources (CPRs) management. Understanding the factors affecting irrigation management performance is crucial for sustainable resource use, especially with the decentralized management mode of irrigation systems being implemented in rural China. This paper contributes to the research field by incorporating different categories of social trust and perceived organization support (POS) into the analysis of irrigation management performance, by linking multiple elements that are based on the Institutional Analysis and Development (IAD) framework. We employed principal component analysis (PCA) and ordered probit regression to analyze a database covering 785 households in the upstream of the Yellow River basin. The results suggested that social trust and POS positively affected the irrigation management performance, and social trust strengthened the positive effect of POS on the performance. Furthermore, the results indicated that personal trust and institutional trust, as well as perceived emotional support and physical support, positively affected the performance. In addition, we also found that household characteristics, household cognition, group characteristics, physical conditions, and rules-in-use also had significant impact on the performance. This paper can be used to inform the government that social trust and POS need to be considered in the common-pool resources (CPRs) management.

A good grasp of the carbon emission efficiency (CEE) of the provinces in the Yellow River basin (YRB) in China, and its influencing factors, can help promote the sustainable development of the region and smooth realization of the national carbon emission reduction target. Based on stochastic frontier analysis (SFA), this paper calculates the CEE of nine provinces in the YRB from 2005 to 2019, and then, analyzes its spatial and temporal characteristics. The spatial Durbin model (SDM) with two-way fixed effects is selected to investigate the influencing factors of the CEE in the YRB. The results suggest that: (1) the overall CEE of the YRB shows a slow upward trend, and although the gap in CEE between provinces is large, it is slowly narrowing; (2) there is a significant negative spatial autocorrelation in the CEE of the provinces in the YRB; and (3) technological innovation capability, energy consumption structure, population density, and urban greening level are the most significant factors affecting the CEE of the YRB. Both population density and urban greening level have a positive effect on the improvement of the CEE of the provinces themselves and of the whole YRB, and there is also a spatial spillover effect on the improvement of CEE due to population density. Technological innovation capability and energy consumption structure had a negative impact on the overall CEE of the province and the basin during the research period. This study may have some reference value for improving the CEE of the YRB.

The research on high-quality development of the manufacturing industry (HQDMI) in the Yellow River Basin is in the exploratory stage, and little literature has systematically analyzed its influencing factors. Based on the grounded theory, this paper makes an exploratory analysis of the influencing factors of the HQDMI in the Yellow River Basin. This study finds that the influencing factors of the HQDMI mainly include six aspects: innovation capability, organization construction, industry resources, institutional environment, industry collaboration, and market demand. By using the HQDMI’s endogenous and exogenous factors as the core, the realization mode of the HQDMI in the Yellow River basin is put forward, and the influencing factors and action model of the HQDMI in the Yellow River Basin are constructed. The findings have significant reference value for promoting the HQDMI in the Yellow River Basin and are helpful for improving the HQDMI research.

Identifying and extracting check dams is of great significance for soil and water conservation, agricultural management, and ecological assessment. In the Yellow River Basin, the check dam, as a system, generally comprises dam locations and dam-controlled areas. Previous research, however, has focused on dam-controlled areas and has not yet identified all elements of check dam systems. This paper presents a method for automatically identifying check dam systems from digital elevation model (DEM) and remote sensing images. We integrated deep learning and object-based image analysis (OBIA) methods to extract the dam-controlled area’s boundaries, and then extracted the location of the check dam using the hydrological analysis method. A case study in the Jiuyuangou watershed shows that the precision and recall of the proposed dam-controlled area extraction approach are 98.56% and 82.40%, respectively, and the F1 score value is 89.76%. The completeness of the extracted dam locations is 94.51%, and the correctness is 80.77%. The results show that the proposed method performs well in identifying check dam systems and can provide important basic data for the analysis of spatial layout optimization and soil and water loss assessment.

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

Baseflow is crucial to maintaining river flow during low-rainfall periods. The baseflow estimation is important to water supply and ecological environmental protection in the Yellow River Basin (YRB), China. This paper comprehensively assessed the applicability of four single-parameter digital filtering, recursive digital filtering, and HYSEP (streamflow hydrograph separation) methods across four typical catchments in the Yellow River Basin: the Zuli River Basin, the Kuye River Basin, the Tuwei River Basin, and the Jingle sub-basin. We also investigated annual and monthly variations in baseflow. We found the standard deviation and coefficient of variation of baseflow index through recursive digital filter were relatively small. And the baseflow process line was smoother and more reasonable in typical year and typical storm-flood events, which conformed to the damping and hysteresis effect of the underlying surface. Thus the recursive digital filter method had the best performance, which was recommended for baseflow separation in the YRB. The estimated baseflow index of typical basins were between 0.354 and 0.502. In addition, inter-annual baseflow showed a decreasing trend and intra-annual baseflow was characterized by uneven distribution, which was subject to the characteristics of each basin. HIGHLIGHTS The evolution of baseflow in the typical catchments in the YRB was investigated by various methods.; The recursive digital filter method is an effective method for baseflow separation in the YRB.

The dual problems of the public crisis from the global epidemic and the deterioration of the ecological environment constrain the economic development in the Yellow River Basin. To promote the sustainable and balanced development in the Yellow River Basin, this paper takes public health, ecological environment, and economic development, as a whole, to study the coordinated development of the Yellow River Basin. Based on coupling coordinated theory, we use the SMI-P method to evaluate the coordinated development index of public health, the ecological environment, and economic development in the Yellow River Basin. Moreover, we use the coordinated regulation and obstacle factor diagnosis to identify the main influencing factors and design regulation methods to optimize the coordinated development index. The results found that (1), during the research period, there is spatiotemporal heterogeneity in the coordinated development level in the Yellow River Basin. From 2009 to 2019, the overall development index increased steadily, while the regional disparity in the coordinated development level was obvious. (2) The ecological environment indicators contribute more to the relevance and obstacle factors, such as the average concentration of fine particulate matter, per capita arable land area, afforestation area, etc. (3) After regulating the overall development level of the Yellow River Basin, we prove that Path 4, which comprehensively considers the relevance and obstacle factors, performs better.

How to realize the sustainable use of land resources is extremely important for environmental protection and sustainable development in ecologically fragile regions. Nevertheless, the logic of achieving sustainable land use (SLU) in ecologically fragile regions and the corrective mechanisms for the implementation of land use efficiency systems are not fully revealed in theory. The Yellow River Basin is an important ecological barrier in China, and it holds an important position in China’s economic and social development, as well as for ecological safety. However, the basin is also ecologically vulnerable. Therefore, investigating eight central cities in the Yellow River Basin of China and using municipal-level panel data from 2009 to 2018, this paper constructs a multidimensional index system and is dedicated to carrying out a comprehensive evaluation of SLU and the diagnosis of obstacle factors in ecologically fragile regions. The study found the following: (1) From 2009 to 2018, the SLU level in the central cities of the Yellow River Basin evolved from the “Unsustainable Level” to the “Initial Sustainable Level” and then to the “Basic Sustainable Level”. The overall development trend was positive, and the level of SLU also rose. (2) From 2009 to 2018, there was significant geographical variation in spatial disparities in SLU in the central cities of the Yellow River Basin. In 2018, the average comprehensive score of SLU showed a pattern of downstream > upstream > midstream. (3) The obstacle factors of SLU in the Yellow River Basin of these cities in 2009 were concentrated on resource and environmental sustainability, while those in 2018 were concentrated on social acceptability. (4) In terms of the transfer process of land use types in these Yellow River Basin cities, the transfer from cultivated land to other types of land use played a major role, while construction land showed a significant expansion over the past ten years.

Realizing the decoupling development between the economic expansion and carbon dioxide emissions of the transport sector is of great importance if the Yellow River basin is to achieve green and low-carbon development. In this paper, we adopt the Tapio decoupling index to examine the decoupling relationship within the transport sector in the Yellow River basin, and then introduce the standard deviational ellipse to dynamically analyze the spatial heterogeneity of carbon emissions and economic growth at the provincial level. Furthermore, based on the decoupling method, we expand the traditional logarithmic mean Divisia index decomposition (LMDI) model to decompose the decoupling index into eight sub-indices, and we identify the impact of each factor on the decoupling relationship. The results indicate that the carbon emissions of the transport sector in the Yellow River basin show the non-equilibrium characteristics of “upstream region < midstream region < downstream region”. The decoupling state of the transport sector shows obvious spatial differences. The less-developed regions are more likely to present non-ideal decoupling states. The growth rate of carbon emissions in Sichuan, Qinghai, and Shandong provinces is relatively fast, and the azimuth of the transport sector’s carbon emissions shows a clockwise trend. Moreover, the inhibitory effects of urbanization on decoupling in the Yellow River basin are much greater than the non-urbanization factors. In addition to the effect of urbanization, the transport structure has a major negative effect on decoupling development in the upstream and midstream regions, while energy intensity and energy structure are key to realizing a decoupled status in the downstream region. Finally, we propose some differentiated policy recommendations.

The urban development in the Yellow River basin (YRB) varies widely. Therefore, it is necessary to choose a development path that fits the characteristics of each city to achieve high-quality development. The purpose of this paper is to address the problem of how to choose a characteristic path for high-quality development and clarify its suitability for YRB cities. Firstly, based on data from 50 YRB cities from 2011 to 2020, the suitability evaluation was carried out from the perspective of an ecological niche, followed by the measurement of sub-dimensional niche breadth and overlap. The results confirmed the great diversity of development between cities and the intense competition for resources. Then, based on the classification approach using the k-means method, this study proposes a method for selecting a suitable path for high-quality development. It classifies the suitable paths into 3 major types with 7 minor types and recommends policies for the suitable paths for YRB cities. The systematic thinking and specific path selection method for the high-quality development of YRB cities is not only of practical significance for implementing city classification strategies but also provides a reference for the sustainable development of basin cities in other countries.

Analyzing the spatial difference and convergence of ecological common prosperity (ECP) in the Yellow River Basin (YRB) will be beneficial for the environmental governance and multi-regional economic coordination. Based on the panel data of 97 cities in the YRB from 2003 to 2019, this paper measured and analyzed the index of ECP, the Gini coefficient of ECP, and the convergence of ECP. The results indicate that the ECP of YRB shows a steady growth trend (with an average growth rate of 4.71% yearly) and the overall differences are low (average Gini coefficient is 0.1509 from 2003 to 2019). In different areas, the Gini coefficient between the medium-stream and downstream of YRB is the largest (average value of Gini coefficient is 0.1561). From the decomposition of the overall differences of ECP, the contribution degree of the density of transvariation is the highest for annual average, with a contribution rate of 43.37%, the rate of intra-regional and the inter-regional differences are 31.86% and 24.77%, respectively. The results indicate that the overall differences of ECP in YRB are getting smaller because of cooperation and governance, but the differences between and within regions exist because of geographical feature. There is a significant spatial β convergence trend of ECP, the convergence rate in the upstream and downstream area is faster under the economic geographical matrix than others, and the rate in the medium-stream area is faster under the administrative adjacency matrix. Therefore, strengthening economic and environmental cooperation between and within regions is more beneficial to achieve a better quality of life, as well as the long-term goals of 2035.

The Yellow River Basin assumes an important ecological and economic function in China. The study of carbon emissions from land use in the nine provinces (regions) of the pathway is important to achieve carbon reduction. Based on the dynamic data of land use, energy, and economic changes in nine provinces (regions) for the past 30 years from 1990 to 2018, this study analyzed the spatial and temporal evolution characteristics of land-use carbon emissions by using the carbon emission coefficient method in the IPCC inventory method and evaluating the low-carbon development model of the nine provinces (regions) by land-use carbon emission intensity. Finally, the LMDI model was used to analyze the factors influencing land-use carbon emissions. The results showed that: (1) in the past 30 years, the net carbon emissions have shown a continuously increasing trend, and the difference in the spatial distribution of carbon emissions in different periods was obvious. The carbon sink effect was not significant enough to offset the carbon emissions generated. (2) The continuously decreasing carbon emission intensity values per unit of GDP indicate that the coordination between land-use and economic development was getting better. (3) The factors of population size, economic size, and land-use structure accelerated land-use carbon emissions, whereas land-use efficiency limited land-use carbon emissions. Accordingly, this paper puts forward some corresponding policy suggestions.

Establishment of a watershed ecological compensation mechanism between multiple subjects is an effective means to realize the collaborative governance of water pollution and maintain the security of water ecology. This paper breaks through the conventional upstream and downstream perspectives of watershed ecological compensation design research and combines them with uncertainty factors. The watershed ecological compensation mechanism for the mainstream and branches was established based on the evolutionary game and the random process. Then, taking the midstream of the Yellow River as an example, some constraint conditions and influencing factors were explored. Results show that: (1) The branch government (i.e., the Shanxi provincial government) is the key to establishing an ecological compensation mechanism between the river mainstream and branches. (2) The proportion of pollution transferred by other branches, the initial probability and the random factors are the main factors affecting the decision-making of branch governments (Shanxi and Shaanxi provincial governments). (3) The compensation and reward of the mainstream government to the branch government and the compensation of the branch government to the mainstream government are the main factors affecting the decision-making of mainstream and branch governments (Shanxi–Henan provincial governments, Shaanxi–Henan provincial governments). The study may provide scientific guidance for the construction of a watershed ecological compensation mechanism between mainstream and multiple branches.

Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle (ATC) model and the Normalized Difference Vegetation Index (NDVI). The Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature-Vegetation Drought Index (TVDI), which are four typical remote sensing drought indices, were calculated. Then, the air temperature, precipitation, and soil moisture data were used to evaluate the applicability of each drought index to different land types. Finally, this study characterized the spatial and temporal patterns of drought in the Yellow River Basin from 2003 to 2019. The results show that: (1) Using the LST reconstructed by the ATC model to calculate the drought index can effectively improve the accuracy of drought monitoring. In most areas, the reconstructed TCI, VHI, and TVDI are more reliable for monitoring drought conditions than the unreconstructed VCI. (2) The four drought indices (TCI, VCI, VH, TVDI) represent the same temporal and spatial patterns throughout the study area. However, in some small areas, the temporal and spatial patterns represented by different drought indices are different. (3) In the Yellow River Basin, the drought level is highest in the northwest and lowest in the southwest and southeast. The dry conditions in the Yellow River Basin were stable from 2003 to 2019. The results in this paper provide a basis for better understanding and evaluating the drought conditions in the Yellow River Basin and can guide water resources management, agricultural production, and ecological protection of this area.

Understanding the response of vegetation to drought is of great significance to the biodiversity protection of terrestrial ecosystem. Based on the MOD13A2 NDVI, GOSIF, and SPEI data of the Yellow River Basin from 2001 to 2020, this paper used the methods of Theil–Sen median trend analysis, Mann–Kendall significance test, and Pearson correlation analysis to analyze whether the vegetation change trends monitored by MODIS and GOSIF are consistent and their sensitivity to meteorological drought. The results showed that NDVI and SIF increased significantly (p < 0.001) at the rate of 0.496 × 10−2 and 0.345 × 10−2, respectively. The significant improvement area of SIF (66.49%, p < 0.05) is higher than NDVI (50.7%, p < 0.05), and the spatial distribution trend of vegetation growth monitored by NDVI and SIF is consistent. The negative value of SPEI-12 accounts for 65.83%, with obvious periodic changes. The significant positive correlation areas of SIF-SPEI in spring, summer, and autumn (R > 0, p < 0.05) were 7.00%, 28.49%, and 2.28% respectively, which were higher than the significant positive correlation areas of NDVI-SPEI (spring: 1.79%; summer: 20.72%; autumn: 1.13%). SIF responded more strongly to SPEI in summer, and farmland SIF was significantly correlated with SPEI (0.3424, p < 0.01). The results indicate that SIF is more responsive to drought than NDVI. Analyzing the response of vegetation to meteorological drought can provide constructive reference for ecological protection.

Land use/cover change is the main reason for the variation of ecosystem carbon storage. The study of the impact of land use on carbon storage has certain reference values for realizing high-quality development in the Yellow River Basin. In this paper, the InVEST model was used to simulate the variation of carbon storage in the Yellow River Basin in 2000, 2005, 2010, 2015, and 2020, and to predict the carbon storage in 2030 in combination with the CA-Markov model, as well as to discuss the impact of land use on carbon storage. The results showed that: (1) The variation trend of carbon storage for different land use types in the Yellow River Basin was different and was mainly manifested as a decrease of cultivated land and unused land, and an increase of forest land, grassland, water, and construction land. The carbon storage in the provincial key development prioritized zone, national development optimized zone, and provincial development optimized zone showed decreasing trends, while the national key development prioritized zone and national major grain producing zone presented a fluctuating downward trend. (2) The ecosystem carbon storage function weakened after 2000, and part of the carbon sink area transformed into a carbon source area. The area with low carbon storage was distributed in the west of the provincial key ecological function zone, and the area with high carbon storage was concentrated in the south and middle of national key ecological function zone and the east of the provincial key ecological function zone. (3) The carbon loss was largest in the urban expansion scenario (UES), followed by the natural development scenario (NDS) and ecological protection scenario (EPS). The carbon storage of different scenarios presented significant positive correlations with land use intensity.

The emergence of houses is a social revolution around the world. Over the past several decades, Chinese archaeologists have excavated many Neolithic to Bronze Age houses, but there is still a great amount of uncertainty about the social and environmental factors driving the differences between these house structures in the Yellow River Basin. In this paper, we summarize data from excavation reports on the shape and size of Neolithic-Bronze Age houses in the upper, middle and lower reaches of the Yellow River, respectively, to identify some social and environmental factors that may have affected the development of house structures across northern China. Our results show that the shape and size of the houses developed at a different pace, but in general followed a similar developmental sequence: (1) 10–8 ka BP, the bud of settlements emerged in the middle and lower reaches of the Yellow River, (2) 8–7 ka BP, people started to construct small pithouses without walls, (3) 7–6 ka BP, people made medium-sized pithouses with low walls, and surface buildings were made with a wood skeleton and mud walls, (4) 6–5 ka BP, ultra-large houses emerged, (5) 5–4 ka BP, house form became more varied, including pithouses, cave dwellings and surface buildings with a wood skeleton mud wall, rammed earth wall, piled mud-grass mixed walls and adobe walls, and (6) 4–3 ka BP, original palaces emerged. Our analyses indicate that the environment played an essential role in determining the house changes over time and that the early to middle Holocene’s warm and humid climate provided excellent conditions for the emergence of settlements throughout the region. Due to the shortage of trees, people chose to change their house construction methods to accommodate the growing lumber shortage. In conclusion, the rapid shift in house construction methods reflects the changing ecological condition as well as a feedback cycle between the environment and social practices driven by resource limitations.

The dependence of water use efficiency (WUE) on changes in land cover types is crucial for understanding of long-term water availability and assessment of water-saving strategies. Investigating the impact of land cover types on ecosystem WUE has important implications when revealing water dynamics and land management. However, the determination of WUE and its dominant factors have always been subject to high data dependency and large calculation consumption within large basins. This paper proposes a framework for processing actual evapotranspiration (AET) and WUE calculation by coupling the Maximum Entropy Production (MEP) method with the Google Earth Engine (GEE). By employing the proposed framework and three data sources available in the GEE platform, results for actual ET and WUE from 2001 to 2020 were obtained in the Yellow River Basin (YRB). The results show that the proposed framework provides an acceptable estimation of actual ET via validation with Eddy Covariance flux sites in the YRB. The calculated WUE values varied greatly in different sub-basins within the YRB, indicating a cumulative growth rate of about 56% during the past 20 years. The dominant factor that led to these changes was the transition from Grasslands into other land-use types. Our results suggest that the use of the GEE platform coupled with the MEP method offers new possibilities for advancing understanding of water exchange and water resource management.

Based on the data of 59 prefecture-level cities in the Yellow River Basin from 2011 to 2019, this paper uses the Slack Based Measure-Global Malmquist Luenberger (SBM-GML) model to measure green total factor productivity (GTFP) of the cities. Under the space–time concept of the Basin, heterogeneity analysis of the upper, middle and lower reaches of the Yellow River Basin is conducted. On this basis, a panel Tobit model is constructed to analyze the impact of environmental regulation on GTFP in the whole basin, upstream region, middle region and downstream region. The results show that the intensity of environmental regulation in the Yellow River Basin increases gradually, which is the highest in the lower reaches, followed by the middle reaches; spatially, the intensity of environmental regulation shows a certain aggregation trend. The green economic growth is realized in the whole basin, and the green technology progress effect is the driving factor of GTFP. The GTFP distribution in the upstream region is relatively concentrated, showing a slow upward trend. The distribution of GTFP in the middle reaches is discrete, and the annual difference is large. In the downstream region, it shows a trend of decline first and then increase. Environmental regulation promotes GTFP in the whole basin, upper, middle and lower reaches, accompanied by certain spatial differences. The Yellow River Basin breaks through the cost effect brought by environmental regulation and triggers technological innovation, thereby enhancing GTFP; the “Porter hypothesis” has been verified in the Yellow River Basin.

With the imminent need of regional environmental protection and sustainable economic development, the concept of virtual water is widely used to solve the problem of regional water shortage. In this paper, nine provinces, namely Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan, and Shandong in the Yellow River Basin (YRB), are taken as the research objects. Through the analysis of input-output tables of 30 provinces in China in 2012, the characteristics of virtual water trade in this region are estimated by using a multi-regional input-output (MRIO) model. The results show that: (1) The YRB had a net inflow of 17.387 billion m&sup3, of virtual water in 2012. In interprovincial trade, other provinces outside the basin export 21.721 billion m&sup3, of virtual water into the basin. In international trade, the basin exports 4334 million m&sup3, of virtual water to the international market. (2) There are different virtual flow paths in the basin. Shanxi net inputs virtual water by interprovincial trade and international trade, while Gansu and Ningxia net output virtual water by interprovincial trade and international trade. The other six provinces all net output virtual water through international trade, and obtain the net input of virtual water from other provinces outside the basin. (3) From the industrial structure of the provinces in the basin, the provinces with a relatively developed economy, such as Shandong and Shanxi, mostly import virtual water in the agricultural sector, while relatively developing provinces, such as Gansu and Ningxia, mostly import virtual water in the industrial sector. In order to sustain the overall high-quality development of the YRB, we propose the virtual water trade method to quantify the net flow of virtual water in each province and suggest the compensation responsibility of the virtual water net inflow area, and the compensation need of the virtual water net outflow area, in order to achieve efficient water resources utilization.

Given the substantial impacts that are expected due to climate change, it is crucial that accurate rainfall–runoff results are provided for various decision-making purposes. However, these modeling results often generate uncertainty or bias due to the imperfect character of individual models. In this paper, a genetic algorithm together with a Bayesian model averaging method are employed to provide a multi-model ensemble (MME) and combined runoff prediction under climate change scenarios produced from eight rainfall–runoff models for the Yellow River Basin. The results show that the multi-model ensemble method, especially the genetic algorithm method, can produce more reliable predictions than the other considered rainfall–runoff models. These results show that it is possible to reduce the uncertainty and thus improve the accuracy for future projections using different models because an MME approach evens out the bias involved in the individual model. For the study area, the final combined predictions reveal that less runoff is expected under most climatic scenarios, which will threaten water security of the basin.

For this paper, according to the statistics of water resources amounts and utilization needs, we carried out a water resources security preliminary evaluation from the following points of view: water consumption balance analysis, available water resources analysis, supply-demand water resources balance analysis, and overall water resources security analysis for the Yellow River Basin in 2009. The results of the research show that the consumption rate in 2009 was 75.5% for the Yellow River Basin. The total amount of local water in the Yellow River Basin was 58.210 billion m3, but both the supply water and the amount of available water are very low. Meanwhile, from the point of view of net water consumption, the deficit water resource amounts to16.763 billion m3, and in view of the size of the water supply, the deficit water resources amounts to 16.12 billion m3. The current deficit has been created by over-exploiting groundwater, squeezing ecological water consumption, re-using wastewater, and utilizing brackish water, sea water. Therefore, the water supply in the Yellow River Basin is not sustainable, and so it is not secure. As there exist issues in terms of the water resource and in terms of socioeconomic security and ecological security in the Yellow River Basin, we can conclude that the present Yellow River water resource is not reliable, which means that this water resource may not be able to meet future normal demands for living, production, and ecology maintenance.