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Collaborative efforts to reduce pollution and carbon emissions are a notable feature of the current era. Achieving the “pollution reduction” and “carbon reduction” dual-driven new development model is the inevitable requirement and significant practical measure for building a new development pattern and realizing a comprehensive green transformation of economic and social development. The synergistic effects between pollution reduction and carbon reduction (PRCR) have been demonstrated. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of PRCR have not received enough attention. Therefore, the evaluation index system was constructed based on the scientific connotation of PRCR, and the CCD of PRCR in cities along the Yellow River Basin (YRB) from 2009 to 2018 was measured quantitatively by constructing the coupling coordination model in this paper. In addition, we comprehensively investigated its spatial pattern, distribution characteristics, and evolution trend using ESDA, Kernel density estimation, and Markov chain. The primary findings can be summarized as: (1) PRCR levels and their CCD fluctuated and increased in the YRB, with “east-high and west-low” spatial differentiation characteristics, and the coupling phenomenon of “pollution reduction is hindered and carbon reduction is lagging”. (2) There is a phenomenon of “spatial club” clustering in the coordination degree of PRCR in the YRB, with most cities in the downstream areas belonging to the type of high-high clustering, while the middle and upstream areas had the opposite type. (3) The CCD of PRCR in the whole and upper reaches of the YRB have transformed from low-level divergence to high-level convergence. (4) Spatial geographic factors have a significant spillover effect on the evolution of the CCD of PRCR, and there is a phenomenon of the “Matthew effect”. This paper provides a comprehensive framework for analyzing the synergistic effects between PRCR, and the research findings can also provide insights for other regions.

[Objective] The purpose of this paper is to explore the impact path of technological innovation on carbon productivity, give full play to the carbon reduction and efficiency enhancement capabilities of technological innovation, and provide a reference for promoting regional high-quality development and the realization of the dual carbon goals. [Methods] Taking the Yellow River Basin and the Yangtze River Economic Belt as research regions, this study examined the influence path of technological innovation on carbon productivity and the mediation effect of digital finance by constructing a stochastic impacts by regression on population, affluence, and technology (STIRPAT) model and a mediation effect model respectively. [Results] The results show that: (1) Technological innovation of cities can improve regional carbon productivity levels, and the impact of technological innovation on carbon productivity exhibits regional heterogeneity. The impact of technological innovation on carbon productivity is stronger in the Yangtze River Economic Belt than in the Yellow River Basin. (2) Digital finance can partially mediate the impact of technological innovation on carbon productivity. Technological innovation can improve regional carbon productivity through digital finance. The mediation effect of digital finance is stronger in the Yangtze River Economic Belt than in the Yellow River Basin. (3) Improving the level of urbanization and economic development can promote the improvement of carbon productivity in the Yellow River Basin, and improving the level of urbanization and economic development and accelerating the upgrading of industrial structure can promote the improvement of carbon productivity in the Yangtze River Economic Belt. [Conclusion] This study suggests that local governments should enhance the technological innovation capabilities of cities, promote the deep integration of digital finance and traditional industries, strengthen regional industrial technology exchange and cooperation, promote the green transformation of industries in the Yellow River Basin and the Yangtze River Economic Belt, and ultimately achieve regional low-carbon and sustainable development.

Improving the efficiency of agricultural technology innovation is an inevitable requirement for ecological protection and sustainable agricultural development in the Yellow River Basin. Under the background of prominent water resources constraints in the Yellow River Basin, the actual level and regional differences of agricultural technology innovation efficiency in the basin are analyzed, which will provide theoretical basis and data reference for the development plan of agricultural modernization in the Yellow River Basin. The construction of evaluation index system and the choice of method are the main factors that affect the measurement results. Therefore, this paper first selects input indicators such as water-saving technology level and output indicators such as total agricultural output value to construct an innovative evaluation index system of agricultural technology innovation efficiency in the Yellow River Basin under the consideration of water resources constraints. Secondly, the three-stage DEA model was used to eliminate the interference of external environmental variables, and the overall and regional agricultural technology innovation efficiency of the Yellow River Basin during 2011–2020 was measured with the data of prefecture-level cities under the constraint of water resources. Finally, from the perspective of the whole and the region, the spatio-temporal dynamic evolution law is analyzed and evaluated. The results show that: on the whole, the agricultural technology innovation efficiency in the Yellow River Basin is good and rising in a wave trend, the adjusted pure technology efficiency increases, while the scale efficiency decreases. From the regional perspective, although there is regional heterogeneity, the overall development trend is good, and the lower Yellow River has the highest efficiency, followed by the upper reaches and the middle reaches. From the perspective of the change law, the spatio-temporal evolution distribution shows a multi-polarization trend, and the different regions in the upper, middle and lower reaches show great differences. Therefore, promoting the innovation of water-saving technology and the integration of agricultural science and technology, promoting the integration of production, study and research, and strengthening the regional linkage mechanism are helpful to improve the competitiveness of agricultural science and technology and achieve sustainable agricultural development in the Yellow River Basin.

Water resources are crucial for the development of ecosystems and humanity. The Yellow River Basin (YRB), as an important ecological area in China, is facing significant challenges in ecological protection and high-quality development due to global climate change and intense human activities. In order to alleviate the water resources crisis in the YRB, it is necessary to calculate the resilience of the water resources system and identify the main influencing factors. This paper considered the factors of water resources, social economy, and ecological environment, then constructed an evaluation framework of the water resources system resilience (WRSR) from three aspects: resistance, restoration, and adaptability. Taking nine provinces along the YRB as a case study, the WRSR was measured by using the entropy weight TOPSIS model, and its driving factors were analyzed with Geographical Detectors (GD). The results showed that: (1) From 2010 to 2022, the WRSR in the Yellow River Basin and various provinces was showing a fluctuating increasing trend, in which Ningxia had the highest average WRSR (0.646), while Shanxi had the lowest (0.168). (2) From three dimensions, the development trends of resistance, restoration, and adaptability in the YRB and various provinces from 2010 to 2022 were relatively stable. Shandong’s resistance level far exceeded that of other provinces, having the highest average resistance value (0.692), and Ningxia had the highest average value of restoration (0.827) and adaptability (0.711). However, Gansu had the lowest average value of resistance (0.119), Sichuan had the lowest average value of restoration (0.097), and Shandong had the lowest average value of adaptability (0.110). (3) In terms of impact factors, the development and utilization rate of water resources (C13) and the development and utilization rate of surface water resources (C14) in the restoration subsystem consistently ranked in the top two of influencing factors. Similarly, the water consumption per 10,000 yuan of GDP (C26) in the adaptability subsystem consistently ranked within the top ten. On the other hand, the natural population growth rate (C6) in the resistance subsystem, as well as the impact of ammonia nitrogen emissions (C9) and total precipitation (C2) in wastewater, exhibited an upward trend. Based on these, this paper provides relevant suggestions for improving the WRSR in the YRB.

Abstract Climate change has become an unavoidable problem in achieving sustainable development. As one of the major industries worldwide, tourism can make a significant contribution to mitigating climate change. The main objective of the paper is to assess the development level of low-carbon tourism from multi-aspect, using the Yellow River Basin as an example. Firstly, this study quantified tourism carbon dioxide emissions and tourism economy, and analyzed their evolution characteristics. The interaction and coordination degree between tourism carbon dioxide emissions and tourism economy were then analyzed using the improved coupling coordination degree model. Finally, this study analyzed the change in total factor productivity of low-carbon tourism by calculating the Malmquist–Luenberger productivity index. The results showed that: (1) the tourism industry in the Yellow River Basin has the characteristics of the initial environmental Kuznets curve. (2) There was a strong interaction between tourism carbon dioxide emissions and tourism economy, which was manifested as mutual promotion. (3) The total factor productivity of low-carbon tourism was increasing. Based on the above results, it could be concluded that the development level of low-carbon tourism in the Yellow River Basin has been continuously improved from 2000 to 2019, but it is still in the early development stage with the continuous growth of carbon dioxide emissions.

Reservoir operation optimization is a technical measure for flood control and is beneficial owing to its reasonable and reliable control and application of existing water conservancy and hydropower hubs, while ensuring dam safety and flood control, as well as the normal operation of power supply and water supply. Considering the beneficial functions of reservoirs, namely flood control and ecological protection, this paper firstly established a two-objective optimal operation model for the reservoir group in the middle reaches of the Yellow River. We aim to maximize the average output of the cascade reservoir group and minimize the average change in ecological flow during the operation period under efficient sediment transport conditions, with the coordination degree of water and sediment as the constraints of reservoir discharge flows. The paper aims to construct an evaluation index system for reservoir operation schemes, apply a combined approach of objective and subjective evaluations, and introduce the gray target and cumulative prospect theories. By uniformly quantifying the established scheme evaluation index system, screening the reservoir operation schemes with the fuzzy evaluation method, and selecting the recommended scheme for each typical year, this paper provides a new scientific formulation of the operation schemes of reservoirs in the middle reaches of the Yellow River. The selected schemes are compared with actual data, demonstrating the effectiveness of joint reservoir operation and for multidimensional benefits in terms of power generation, ecology, and flood control.

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

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

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

Coordinated governance and horizontal ecological compensation are important ways to realize ecological protection and high-quality development in the Yellow River basin. Taking the middle and lower reaches of the Yellow River as the research object, this paper analyses the compensation relationship and amount of cities along the line in Shaanxi, Shanxi, Henan and Shandong provinces. Firstly, the spillover value of regulation of water flows and erosion prevention of 32 counties along the Yellow River in Shaanxi and Shanxi provinces were calculated during 2000–2010 and 2010–2020 from the perspective of land use/cover change (LUCC). Secondly, the compensation accounting index system was established based on the classification of ecological services given the beneficiaries' individual preferences, and each indicator's weights were determined based on the Best-worst method. Finally, setting the water ecological service value of the 10 km buffer zone on both sides of the Yellow River as the accounting scope, this paper calculated the amount of ecological compensation paid by 16 cities in Shandong and Henan provinces. The results show that: (1) The spillover value of Shaanxi and Shanxi provinces in 2010–2020 is greater than that in 2000–2010, and the values of erosion prevention in both stages are lower than that of regulation of water flows; (2) From the perspective of providers, the highest is 3.68e + 08 yuan in Lvliang from 2000 to 2010, while the highest is 3.60e + 09 yuan in Yulin from 2010 to 2020; (3) From the perspective of beneficiaries, Zhengzhou has the highest amount of compensation in Henan province, which is 2.28e + 08 yuan in 2000–2010 and 9.41e + 08 yuan in 2010–2020 respectively. In Shandong province, Heze pays the highest value of 1.27e + 08 yuan from 2000 to 2010, and Jinan pays the highest value of 9.56e + 08 yuan from 2010 to 2020. The ecological compensation scheme obtained in this paper is more sustainable than the vertical compensation and expands the scope of the existing ecological compensation standards, which can effectively stimulate the enthusiasm for ecological protection, and reduce the financial pressure on the central government.

Measuring industrial eco-efficiency (IEE) is essential to improve environmental quality and industrial restructuring. However, most studies ignore the influence of embeddedness on industrial eco-efficiency and lack analysis of the pathways of influence factors. Therefore, this study assesses industrial eco-efficiency in the Yellow River Basin (YRB) using a super-efficiency model slacks-based measure (Super-SBM) that considers non-desired outputs, outlines the social embeddedness of IEE, and empirically analyzes the driving mechanism of IEE from the perspective of embeddedness by constructing hierarchical linear modeling (HLM) to address the pathways of action of the influencing factors of industrial eco-efficiency. The results showed that 50.79% of the overall differences in IEE in the YRB were caused by social embeddedness. Economic development level, industrial agglomeration, and environmental regulation (ER) are significant direct influencing factors. Increasing cognitive and cultural embeddedness will enhance the positive relationship between economic development level and IEE. Political and relational embeddedness significantly moderates the positive relationship between industrial agglomeration and eco-efficiency. Cultural embeddedness can significantly and directly affect industrial eco-efficiency and weaken the positive relationship between ERs and industrial eco-efficiency. Therefore, improving IEE should consider both fundamental and embedded factors. Our findings are conducive to promoting high-quality development in the YRB and support the government in formulating differentiated policies. In addition, this paper tries to establish an empirical analysis method suitable for social embeddedness theory, and the empirical results help to improve the situation due to the lack of empirical analysis of social embeddedness theory.

Achieving the efficient, synergistic and sustainable utilization of water resources is a necessary precondition and an important means through which to protect the ecological environment of the Yellow River Basin (YRB) and promote the high-quality development of the basin's economy. This paper innovatively defines water-intensive utilization efficiency (WIUE) and constructs an appropriate evaluation index system. A superefficiency network slacks-based measure (SBM) model is introduced for measurement. The gravity model is improved, and the spatial clustering and spatial association network characteristics of water use efficiency (WUE) and water conservation and purification efficiency (WCPE) are analysed using exploratory spatial data analysis (ESDA) and social network analysis (SNA). Finally, the formation mechanism of the spatial network of WCPE is explored by using quadratic assignment procedure (QAP) regression. The following conclusions are obtained. (1) The WIUE of the YRB shows a divergent trend over time, with fluctuations in the water conservation and purification stage being the main factors influencing WIUE changes in each province. (2) Currently, the spatial association network structures of WUE and WCPE are sparse. However, with the government's basin-wide water conservation policy, the spatial relationships within the basin have gradually become more closely linked. The local clustering effect of WUE in space and the communication of technical elements in the WCPE stage in the basin are the main reasons for this network formation. Focusing on the WCPE stage, this study not only proposes policy suggestions to improve the efficiency of water resource intensification in the YRB by promoting the exchange of factors but can also be used as a reference for other basins with great regional differences.

In this paper, we investigate the features of spatiotemporal change in fractional vegetation cover (FVC) throughout the Yellow River Basin between 2000 and 2022 and identify the driving factors behind the change using the MODIS normalized difference vegetation index (NDVI) as a data source. On that basis, our research involves trend analysis and the center migration model to examine the correlation between vegetation cover changes and various factors, such as climates, topographies, soils, and human activities. In this way, we aim to uncover how such correlation contributed to the reduction in suspended sediment concentration (SSC) in surface runoff. Results suggest that (1) the FVC of the Yellow River Basin has been trending upward over the past 23 years, and vegetation growth has been remarkably improved; (2) the center of medium-high and denser vegetation cover has progressively migrated from the upper reaches of the Yellow River down to its middle-lower segments; (3) soil erosion control measures are critical to improve vegetation cover, given the great impact of the shifting natural elements on vegetation cover changes on a local basis; (4) an improvement in vegetation cover leads to considerable positive change in the runoff and SSC of the Yellow River mainstem. This study has yielded noteworthy contributions in correctly understanding the current vegetation changes and related factors in the Yellow River Basin. Furthermore, it has laid the groundwork for further research in improving the accuracy of basic data and deepening the correlation between factors.

Reasonable payments of Ecosystem Services (PES) standards are crucial to provide eco-environment management countermeasures. However, existing research on the unified coordination of future PES from the overall perspective is insufficient. This paper proposes a framework derived from the patch-generating land-use simulation (PLUS) model and the ecosystem services value (ESV) assessment method for allocation PES funds. The Yellow River Basin (YRB) was taken as a case study, which is a highly integrated and interconnected entity. The PLUS model was used to analyze various land-use situations from 2010 to 2020, and predict future land-use status under different development scenarios including natural development (ND), cropland conservation (CC) and ecological conservation (EC). The ESV approach was applied to calculate the ESV in nine provinces of the YRB, and propose optimized fund distribution schemes. The results showed that (1) The most significant land-use changes during 2010–2020 were impervious, forests, grasslands, and croplands, where the impervious increased by 22.47 % (4642 km2) and the forest increased by 9 % (7623 km2). (2) The total ESV in the YRB will be highest under EC scenario in 2030, at 729.16 billion CNY, and Qinghai, Sichuan, Gansu and Shandong will have the highest ESV under EC scenario. (3) The funds will reach lowest under EC scenario, at 13.35 billion CNY, while reach highest under CC scenario, at 13.58 billion CNY. (4) In any scenario, Qinghai and Gansu province will get the highest PES funds among nine provinces, and financial investment in the Qinghai Province needs to be increased. Based on our results, it is recommended to foster the exploration of horizontal compensation between the downstream provinces of Henan and Shandong, and the upstream provinces of Qinghai, Sichuan, and Gansu, in order to enhance the protection of the eco-environment. The findings can provide scientific guidance for improvement of the PES funds allocation in the YRB, and methodological references for other river basins.

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.

The Yellow River, a critical water resource, faces challenges stemming from increasing water demand, which has led to detrimental effects on hydropower generation and ecological balance. This paper will address the complex task of balancing the interests of hydropower generation, water supply, and ecology within the context of cascade reservoirs, specifically Longyangxia and Liujiaxia reservoirs. Employing a systemic coupling coordination approach, we constructed a multi-objective synergetic model of the upper Yellow River in order to explore synergies and competitions among multiple objectives. The results reveal that there is a weak competitive relationship between hydropower generation and water supply, a strong synergy between hydropower generation and ecology, and a strong competitive relationship between water supply and ecology. The Pareto solution set analysis indicates a considerable percentage (59%, 20%, and 8% in wet, normal, and dry years, respectively) exhibiting excellent coordination. The probability of excellent coordination decreases with diminishing inflow. The optimization scheme with the highest coupling coordination demonstrates significant improvements in power generation, water supply, and ecological benefits in the upper Yellow River without compromising other objectives, fostering the sustainable operation of hydropower generation, water supply, and ecology in the upper Yellow River.

Water market development in the Yellow River Basin (YRB) unfolds new opportunities for alleviating water scarcity and improving water productivity. However, the further development of an effective water market in the basin faces challenges such as unclear water rights, regulatory deficiencies, market deficiencies, and insufficient compensation to third-parties, among others. Studying water market development in Western countries provides useful insights for addressing similar challenges, thus providing useful case studies despite the different cultural, economic, institutional, and political settings. This paper investigates water markets in the Murray–Darling Basin in Australia, the western United States, and Chile to synthesize cases of water market development that could potentially contribute to overcoming the challenges encountered in the YRB. After analyzing these cases, recommendations are made for enhancing the YRB’s water market development from the perspectives of water rights systems, as well as the roles of the government and market, legal system, and third-party effects.

[Objective] This study aimed to examine the boundary of ecological security level of resource-based cities in the Yellow River Basin, and analyze the transfer rule and convergence characteristics of ecological security level reflected in different time and space, in order to provide a reference for the high-quality development of resource-based cities. [Methods] The ecological security evaluation system of resource-based cities in the Yellow River Basin was established based on the state-stress-immunity (SDI) model, and the ecological security class boundary of these cities was estimated by the fuzzy matter-element model. The spatial and temporal distribution characteristics were analyzed based on the kernel density curve and Moran’s I index, the spatiotemporal transfer rules were analyzed by the Markov chain and spatial Markov chain, and the convergence characteristics were studied by convergence and absolute test. [Results] This paper defines the boundary value of ecological security level of resource-based cities in the Yellow River Basin. The ecological security level of resource-based cities in the Yellow River Basin still has a large space for improvement, and it presented a V-shaped development trend temporally and a high-low-high distribution pattern spatially. The transfer of ecological security level of these cities were path-dependent and showed a lock-in effect, and the change of ecological security usually occurred between adjacent levels. The difference of ecological security of resource-based cities in the Yellow River Basin showed obvious catch-up effect, which was more prominent in the lower reaches and the medium-value areas. [Conclusion] Based on the current situation that the ecological security level of resource-based cities in the Yellow River Basin is generally low, development policies should be formulated in different areas considering differences in development stage. Based on the transfer pattern of ecological security level of these cities, attention should be paid to the leading role of cities with higher ecological security level. Based on the catch-up effect of ecological security of these cities, complementary development of resource-based cities should be realized on the basis of strengthening regional coordinated development.

Evapotranspiration is an important part of water cycle, and the study of evapotranspiration is conducive to understanding the spatio-temporal variation of regional water resources. The Yellow River Basin (YRB) is located in an arid and semi-arid region, and water resources are sparse and uneven in spatio-temporal distribution, and the water issues are prominent. Analyzing the response of evapotranspiration to the changing environment in the YRB and revealing the hydrologic and water resources effects of climate change, vegetation seasonality and phenological variations are of great theoretical and practical significance for the sustainable development and planning and management of regional water resources. Based on the Multivariate Adaptive Regression Splines(MARS) non-parametric model, this paper analyzes the correlation between the water-energy coupling control parameter ϖ and environmental variables under the Budyko framework by using the third generation normalized differential vegetation index datasets(NDVI3g) developed by Global Inventory Modelling and Mapping Studies, meteorological data, soil data, land use/cover data and topographic and geomorphic data of 30 sub-basins in the YRB. The influence mechanism of changing environmental variables on evapotranspiration is discussed. The results show that (1) the spatial variation of the water balance relationship is significantly correlated with the water-energy coupling seasonality, the spatial variability of geomorphology, and the precipitation seasonality (average storm depth and coefficient of variation of precipitation). (2) On the inter-annual scale, a) the water and energy synchronicity is the most important climate seasonality that affects the inter-annual water balance: as water and energy synchronicity increases, the evapotranspiration ratio decreases and runoff yield increases; b) the more concentrated the precipitation, the higher the annual variation and the more obvious the seasonal precipitation, suggesting the smaller the evapotranspiration ratio; c) vegetation seasonality is an important factor affecting the catchment water balance: the stronger the vegetation growth and the longer the growing season, suggesting the larger the evapotranspiration ratio and the smaller the runoff yield coefficient. (3) There is a strong auto-correlation among environmental variables, which co-evolve and act on evapotranspiration.

Carbon attainment and carbon neutrality are inherent requirements for promoting high-quality development, and the carbon emission efficiency of cities in the Yellow River Basin(YRB) directly affects the high-quality development of the Yellow River Basin. In this paper,we measures the carbon emission efficiency of 61 cities in the YRB from 2004 to 2018 using the super-efficiency Slack-Based Measure model (super-efficient SBM model), and explores the spatial and temporal heterogeneity and spillover effects of the new carbon emission efficiency values by combining empirical orthogonal functions and spatial autoregressive models. The results show that: (1) The spatial pattern of cities in the YRB has changed from “pretty high in the centre and low in the surroundings” to “agglomeration in high-value zones as well as dispersion in low-value zones”. (2) GDP per capita and government involvement are positively related to carbon emission efficiency, while GDP per capita squared, energy intensity and industrial structure are negatively correlated with carbon emission efficiency. (3) Reducing the proportion of fossil energy consumption, strengthening government regulation and optimising​ industrial structure are effective ways to improving the efficiency of carbon emissions in the YRB.

Study region: The Yellow River basin (YRB) Study focus: Runoff plays an important role in ecology and hydrology, which can be affected by climate change and human activities. The fractional vegetation cover can reflect the influence of human activities on underlying surface to some extent. However, the attribution research on future runoff changes is not sufficient. Using the CMIP6 global climate model with Delta-downscaling, Budyko equation, and empirical orthogonal function method, the effects of climate change and underlying surface change on runoff in the YRB from 2022 to 2100 are analyzed in this paper. New hydrological insights for the region: The trend of runoff increased uniformly on the YRB except for the upstream of the YRB and some areas of the source region of the YRB. Runoff is negatively correlated with potential evapotranspiration and underlying surface change but positively correlated with precipitation, according to the Budyko equation. And the increase in the concentration of emissions will amplify the impact of climate change particularly precipitation on runoff. In most areas of the basin, precipitation changes will be the dominant factor in runoff changes between 2022 and 2100, and their contribution rate will increase over time. On the source region of the YRB, however, the potential evapotranspiration dominated runoff changes. This study will help formulate appropriate soil and water conservation and ecological protection strategies in ecologically vulnerable areas of the YRB in the context of climate change.

Under the current social background of green, sustainable, and high-quality development, countries and regions have increasingly begun to regard green development as a major goal of their economic and social development plans. If the evaluation of urban land use efficiency continues to be based only on economic and social outputs, such research will not conform to the current social development situation. Therefore, this paper introduces negative impacts, such as environmental pollution, into the evaluation system, using the Super-EBM model to measure the urban land green use efficiency (ULGUE) of the Yellow River Basin (YRB) based on panel data from 2011 to 2019. Exploratory spatial data analysis, kernel density estimation, and trend surface analysis were used to study the spatial–temporal evolution characteristics of ULGUE, and the GTWR model was used to explore potential driving mechanisms. The overall ULGUE remained relatively flat from 2011 to 2015, before showing a climbing growth in the post-2015 period; at the sub-basin level, the ULGUE in the midstream area was significantly higher than that in the downstream area, and slightly higher than that in the upstream area, but the rate of ULGUE increase in the upstream area was significantly higher than that in other areas. The spatial aggregation degree of ULGUE showed an increasing trend followed by a decreasing trend, but at the end of the study period, it was still slightly higher than its initial level. The overall ULGUE showed a “polarization–non-differentiation–polarization” trajectory, with the highest efficiency area gradually shifting from the northwest to the central region. Although the driving factors vary between different cities, in general, the roles of technology input and pollution emission factors have gradually increased. This research provides a scientific reference for high-quality development of the YRB and supports the optimal allocation of land resources and regional coordinated development.

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.

ABSTRACT: 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.

The Yangtze River Economic Belt and the Yellow River Basin are important economic regions and ecological barriers in China. Promoting the development of the Yangtze River Economic Belt and promoting ecological protection and high-quality development in the Yellow River Basin are major regional strategies implemented by the Chinese government, and the green growth of the two regions is important for the high-quality sustainable development of the whole China. To investigate the regional differences in green growth efficiency of the same type of geographical units, this paper measures the green growth efficiency and decomposition indicators of the Yangtze River Economic Belt and the Yellow River Basin from 2010 to 2020 using a three-stage DEA model and the Malmquist index method and establishes a panel Tobit model to identify the influencing factors of green growth efficiency. The results show that: ①After using the three-stage DEA model to remove the influence of external environment and stochastic factors, the mean values of green growth efficiency of Yangtze River Economic Zone and Yellow River Basin from 2010 to 2020 are 0.996 and 1.089, respectively. The change of green growth efficiency of Yangtze River Economic Zone is slightly higher than that of Yellow River Basin. ②The Malmquist indexes of the Yangtze River Economic Belt and the Yellow River Basin have generally increased, with the Technological Progress Index, which characterizes technological innovation, being the main endogenous driver of green growth efficiency in the Yellow River Basin, while the technical efficiency index, which characterizes factor mix and management level, is more significant in the Yangtze River Economic Belt. ③The Tobit model regression results show that the factors influencing green growth efficiency are also different in the two regions. Among them, the urbanization rate has a significantly positive effect on the two regions, while the effects of environmental regulation and research intensity are not significant. External openness has a suppressive effect on green growth efficiency in the Yangtze River Economic Belt, while the level of financial development and human capital negatively affect green growth efficiency in the Yellow River Basin. Therefore, green development in the new era should pay attention to the differences between different regions, and make appropriate development policies according to the local conditions of the development status of different regions.

Water resources, energy, and food are important basic resources for high-quality regional development. In the process of rapid development of regional economy, how to coordinate the development of basic resources has become one of the most serious challenges to the high-quality development of the Yellow River basin and even the whole Yellow River basin in Shandong province. Previous studies have produced few such analyses and evaluations for cities in the Yellow River basin, and there is a lack of research on multi-scale analysis, evaluation and prediction of urban coupling and coordinated development level. Hence, in this study, we propose an indicator system consisting of 24 indicators for the water resources, energy, and food system based on panel data for 9 cities in the Yellow River basin in Shandong Province for 2011–2020. Spatial autocorrelation analysis and temporal and spatial distribution analysis were used to determine the current state of water resources, energy, and food systems at multiple scales; combined weighting, comprehensive evaluation, and coupling coordination quantification were used to formulate the coupling coordination relationships of water resources–energy–food and identify the spatiotemporal formation and development of the water resources–energy–food system. A particle swarm optimization–back propagation model (PSO-BP) was used to predict the coupled and coordinated changes in the water resources–energy–food system for the next five years. The study results show that: (1) The composite index of the water resources–energy–food system showed an increasing trend, and the composite index of the food subsystem increased relatively quickly. (2) In 2020, the coupling coordination degree for eight of the nine cities in the Yellow River basin in Shandong Province was 0.70. Jinan, the exception, was at a critical stage of transitioning from low to moderate coupling, and the other eight cities were at the moderate stage of coupling coordination. (3) The coupling coordination of the water resources–energy–food system is increasing; it has transitioned from low to moderate and is about to transition to the stage of good coupling coordination. (4) The PSO-BP model predicted that the coupling coordination of water resources–energy–food systems in the Yellow River basin in Shandong Province will reach the stage of good coupling coordination in 2023. The research results presented in this paper can provide a theoretical basis for formulating policy recommendations in the Yellow River basin in Shandong Province.

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.

As a national strategy, the development of the Yangtze River Economic Belt (YREB) and the ecological protection and high-quality development (HQD) of the Yellow River Basin (YRB) are of great significance for promoting the HQD of the regional economy. Based on the panel data in the YRB and the YREB from 2006 to 2019, this paper constructed an evaluation index system of HQD with five dimensions of “innovation development, coordination development, green development, openness development, and sharing development”, and we used the entropy weight method, kernel density method, and Tobit panel model to analyze the differences in the HQD and the similarities and differences of the influencing factors between the two regions. The research findings were as follows: (1) The HQD of the YRB and the YREB was consistent with the national trend, showing a fluctuating upward trend. The HQD of the YRB was always lower than that of the YREB. The kernel density curves in both regions had a rightward trailing pattern, with polarization and unbalanced development. (2) From the perspective of the spatial distribution pattern, the HQD of the YRB presented a spatial distribution characteristic of “high at both ends and low in the middle”. In contrast, the HQD of the YREB maintained the characteristic of “high in the east and low in the west”. (3) The level of human capital, the level of foreign direct investment, and the economic scale played a significant positive role in improving the HQD of the YRB. The level of human capital, urbanization, foreign direct investment, and economic scale significantly improved the HQD of the YREB.

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.

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.

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.;

Most cities in the Yellow River Basin are located in the central and western regions of China. Restricted by historical evolution, natural environment, resource endowments and other conditions, the economic and social development model of the Yellow River Basin region is outdated, and the level of economic and social development is relatively lagging, which hinders its coordinated development of ecology and economy. This paper uses the coupling coordination degree model, GIS spatial analysis method, NAR neural network model, spatial autoregression, and geographically weighted regression model to investigate the coupling coordination level, spatial differentiation characteristics, future development trend, and coupling driving factors of eco-environmental protection and high-quality development in the Yellow River Basin. The results show that From 2003 to 2018, the level of eco-environmental protection and high-quality development in most areas of the Yellow River Basin gradually improved, presenting a spatial imbalance characteristic of “high in the east and low in the west. The coupling coordination degree of eco-environmental protection and high-quality development in various regions of the Yellow River Basin increased year by year during the survey period. In 2018, most cities had been transformed into intermediate coordinated development areas, and most cities in Inner Mongolia and the middle and lower reaches south of the Yellow River have been upgraded to a well-coordinated development stage. The coupled and coordinated development relationship between eco-environmental protection and high-quality development in the Yellow River Basin has significant spatial agglomeration characteristics, and the local spatial positive correlation gradually increases. From 2019 to 2023, the average level of coupling coordination between eco-environmental protection and high-quality development in the Yellow River Basin during the forecast period is 0.802, 0.807, 0.809, 0.813, and 0.816, respectively, all of which have entered a stage of well-coordinated development. The coupled driving factors of ecological protection and high-quality development in the Yellow River Basin are ranked from strong to weak: energy utilization, urbanization, water resources development, and industrialization. Among them, the degree of energy utilization is the root of the differentiation of coupling coordination between eco-environmental protection and high-quality development in 74 regions of the Yellow River Basin. This study puts forward two strategic suggestions based on the optimal utilization strategy of energy and water resources and the coordinated promotion strategy of industrialization and urbanization, which has great practical and scientific significance for promoting the coordinated development of ecological environment protection and high-quality development in the Yellow River Basin.

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 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.

Based on a detailed analysis of the impact mechanism of industrial restructuring on carbon dioxide emissions in the Yellow River Basin, this paper first calculated the carbon dioxide emission data of 57 prefecture-level cities in the Yellow River Basin from 2009 to 2019 and constructed indicators from two dimensions: the advancement and the rationalization of the industrial structure. Then, the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model was used to empirically analyze the influencing factors of industrial structure adjustments on carbon dioxide emissions in the Yellow River Basin. Consequently, changing carbon dioxide emission trends in the Yellow River Basin under various scenarios were predicted. The research observed the following: (1) the eastern part of the Shandong Peninsula Urban Agglomeration and the Energy Golden Triangle have higher carbon dioxide emissions; (2) the advancement of industrial structures in the Yellow River Basin has a better emission reduction effect than the rationalization of industrial structures; (3) increased foreign investment will lead to an increase in carbon dioxide emissions in the Yellow River Basin, and a “Pollution Refuge Effect” will emerge; (4) accelerated industrial transformations and upgrades, high-quality economic development, and a moderate population growth rate are consistent with future development trends.

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.

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.

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.

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.

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.

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.

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.