Search

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.