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• Coupling coordination indicators for pollution and carbon reduction is proposed. • The first time to focus on the issue in cities along the Yellow River Basin. • "East-high and west-low" spatial differentiation characteristics of coupled degree. • "Pollution reduction is hindered and carbon reduction is lagging". • There is a phenomenon of "spatial club" clustering in the coordination degree. 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. [ABSTRACT FROM AUTHOR]

Examining the interplay among water-energy-environment-economy in the Yellow River Basin holds paramount importance for ecological conservation and fostering the high-quality advancement in this region. This research establishes a theoretical framework for understanding the water-energy-environment-economy interplay and proposes a comprehensive evaluation index system targeting for holistic development of the water-energy-environment-economy system. Analyzing data from 57 cities in the Yellow River Basin in 2002–2022, this research employes the coupling coordination model, spatial autocorrelation model, and obstacle model for in-depth analysis. The findings indicate: (1) The overall development of water-energy-environment-economy in the Yellow River Basin demonstrates a steady upward trajectory, with distinct evolution patterns in each subsystem. (2) The coupling coordination degree in water-energy-environment-economy exhibits a gradual improvement, with the coupling coordination values showing the sequence of Lower reaches > Upper reaches > Total average > Middle reaches. (3) Coupling coordination degree reveals a spatial pattern of high values in peripheries and lower values in the central areas, suggesting a certain spatial agglomeration. (4) Water resources per capita emerges as the primary obstacle factor in the Yellow River Basin, with its obstacle degree on the rise. Building upon these insights, the paper presents targeted policy recommendations. • A theoretical framework for relationship among water, energy, environment, and economy is built. • Coupling coordination degree of WEEE in the YRB was evaluated. • Spatiotemporal evolution of WEEE coupling coordination was analyzed. • Obstacle factors of WEEE were identified in the YRB. [ABSTRACT FROM AUTHOR]

• Developed a method to assess synergy and competition in water-energy-food systems. • Energy and food industries face intense competition for water in the Yellow River Basin. • Considering water quality exacerbates competition for water between food and energy and diminishes synergy. • Resource endowment and technological level have significant impact on the degree of competition. Water, as an indispensable component of the water-energy-food (WEF) nexus, plays a pivotal role in shaping its stability and safety. The competition for water between the food and energy systems is accentuated in the concept of the nexus. However, existing quantitative frameworks and assessment mechanisms have limitations as they often neglect to consider water quality in water competition within the WEF nexus. Therefore, a WEF nexus synergy and competition assessment method was proposed by coupling water footprint theory and the Lotka-Volterra model in this paper. This method establishes two scenarios based on the water footprint perspective, namely, water quantity and water quality-quantity. It effectively addresses the deficiencies in quantitative analysis of WEF system trade-offs and synergies. To illustrate the application of the method, this study conducted a case study in the Yellow River Basin (YRB) of China, evaluating the complex competitive and synergistic mechanisms of water use in the energy and food industries. Compared to the water quantity scenario, the results reveals that the inclusion of gray water footprint intensifies the competition for water in the food and energy industries in the YRB from 2000 to 2020, particularly in resource-based and economically developed cities. The spatial distribution characteristics of water resource competition and synergy in the YRB's WEF system align with WEF endowment and economic technology levels. To address water conflicts in the WEF nexus and enhance nexus security, this study proposes a regulatory pathway for WEF system synergistic security based on two aspects (water competition and synergy characteristics and resource endowment). It contributes to a more comprehensive understanding of water competition and synergy in the WEF nexus and provides valuable insights for resource management. [ABSTRACT FROM AUTHOR]

• Digital inclusive finance effectively promotes industrial upgrading in the the Yellow River Basin. • Using advanced, rational, and ecological dimensions to construct an industrial structure evaluation system is reasonable. • Factor flow emerges as a positive influencer in modulating the effect of digital inclusive finance on the enhancement of industrial structure upgrading. • The driving role of digital inclusive finance in upgrading industrial structure is not significant in the midstream regions, directly traversed areas, and provincial capital cities. This paper empirically investigates the impact and pathways of digital inclusive finance on the upgrading of industrial structure, drawing upon data collected from 114 cities in the Yellow River Basin of China spanning the period from 2011 to 2020. The study unveils that the advancement of digital inclusive finance in the Yellow River Basin notably accelerates the upgrading of industrial structure, with discernible regional heterogeneity. Furthermore, factor flow emerges as a positive influencer in modulating the effect of digital inclusive finance on the enhancement of industrial structure upgrading. [ABSTRACT FROM AUTHOR]

• Taking the high-quality development of the Yellow River basin as the background. • Proposing principles for the initial water rights allocation in Yellow River basin. • Analyzing the priority of Industry water use in the Yellow River basin. • Constructing a model for initial water rights allocation with water-use priorities. • Calculated the initial water rights of Hetao Irrigation District. In September 2019, the Chinese government elevated ecological protection and high-quality development of the Yellow River basin to a major national strategy. However, the scarcity and inequitable distribution of water resources in the basin remain a tough and urgent problem. Therefore, this study probed into the initial water rights allocation (IWRA) of Industry in the Yellow River basin driven by high-quality development. First, based on the status quo of water resources in the basin, this study proposed principles of IWRA of Industry were total quantity control, safeguard, fairness, and efficiency. Next, the paper set the Industry water priority based on the configuration rules, constructed a goal programming model for IWRA of Industry, anticipated the ideal value via the gray model(1,1)(GM (1,1)), and suggested IWRA for end-users through both quota method and water-demand proportion. Last, this study calculated that the initial water rights (IWR) for Hetao Irrigation District in Bayannur city of Inner Mongolia should be 4.38 billion m3. Theories and methods put forward in this paper helps enhance water resources management and improve the high-quality development of the Yellow River basin. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper refines a comprehensive index of urban low-carbon innovation based on urban low-carbon innovation concept and an urban low-carbon innovation community structure and function. This index is complemented by an indicator reflecting equity in terms of urban-rural income gap, some indicators of low-carbon knowledge and technology innovation, as well as an indicator of the characteristics of a carbon circular economy, and a further refinement of the indicator of low-carbon innovation system. We use the entropy value method, kernel density analysis, gravity model, and social network analysis to study the low-carbon innovation spatial pattern in urban agglomerations (UAs) of the Yellow River Basin (YRB). Innovations in the findings are: (1) the low-carbon innovation level in the UAs in the YRB decreases in spatial distribution from the downstream to the midstream to the upstream UAs. (2) Reveal the spatial pattern laws of low-carbon innovation levels in different types of UAs in the YRB. The spatial pattern in regional level UAs is more complex and hierarchical than that in area level UAs; but there are still gaps in the hierarchy of spatial patterns of low-carbon innovation levels between UAs at the regional level, as well as between UAs at the area level. The spatial pattern of two regional-level UAs in the YRB is transitioning from a low-carbon innovation point-axis to a low-carbon innovation network structure, and the spatial pattern of one regional-level UAs is at the embryonic stage of the low-carbon innovation point-axis structure. The spatial pattern of one area-level UA is at the embryonic stage of a low-carbon innovation point-axis structure, and the spatial pattern of three area-level UAs is at the stage of low-carbon innovation pole. The spatial pattern of low-carbon innovation becomes more complex and hierarchical as we move from upstream to midstream to downstream UAs. (3) Use social network analysis and the study show that the low-carbon innovation network is dominated by the internal correlations among the UAs in the upstream, midstream, and downstream. The low-carbon innovation linkages between upstream, midstream and downstream UAs are weak. Finally, we put forward corresponding policy recommendations. • Improve concept and comprehensive evaluation index system of urban low-carbon innovation. • Reveal low-carbon innovation spatial patterns in different urban agglomerations in Yellow River Basin. • Using social network analysis study low-carbon innovation spatial correlation pattern in Yellow River Basin urban agglomerations. [ABSTRACT FROM AUTHOR]

• The evaluation index system of water resources intensive use is constructed. • The potential for water conservation and purification phases needs to be tapped. • The structure of spatial association network is sparse on the whole. • The technological element is the main reason for the formation of a spatially linked. 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. [ABSTRACT FROM AUTHOR]

• A framework was proposed for the allocation of PES funds under future scenarios. • The ESV is highest in ecological conservation scenario, while fund is the lowest. • In the future, financial investment in the Qinghai Province needs to be increased. • The exploration of horizontal compensation mechanisms should be encouraged. 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. [ABSTRACT FROM AUTHOR]

[Display omitted] • The equivalent coefficient is revised according to ability and willingness to pay. • The Best-worst method is used to determine the weight of the allocated indicators. • A 10 km buffer calculation strip is established in the compensated payment area. • The overflow of hydrological adjusting is greater than that of erosion prevention. • Ecological compensation in 2010–2020 is higher than that in 2000–2010. 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. [ABSTRACT FROM AUTHOR]

The human settlement environment is the concrete embodiment of measuring the sustainable development of tourism urbanization. Previous studies have preliminarily verified that there is a coupling relationship between tourism urbanization and human settlement environment. However, whether tourism urbanization can effectively improve human settlement environment, especially in the most vulnerable watershed area in China, the Yellow River Basin, is still unclear. Therefore, the purpose of this study is to explore the degree and direction of the impact of tourism urbanization on human settlement environment in 78 prefecture-level cities in the Yellow River Basin from 2005 to 2019 under the influence of nonlinear and spatial spillover effects. This paper uses the PSTR (panel smooth transition regression) model SDM (spatial Durbin) model to reveal the following results: First, tourism urbanization can significantly improve human settlement environment in the Yellow River Basin. After crossing the second threshold (0.434), the nonlinear effect of tourism urbanization on human settlement environment is the strongest, but only a very small number of cities cross the threshold. Secondly, the improvement of the level of tourism urbanization has effectively improved production environment and living environment of the region, but it has had a significant negative impact on ecological environment of the region. Finally, the combined effect of regional geographical proximity and economic interaction is conducive to the positive spatial spillover effect of tourism urbanization on production environment and living environment of surrounding areas of the Yellow River Basin. The current empirical results reveal the key role of tourism urbanization in improving human settlement environment in the Yellow River Basin, and clearly outline that the development of tourism urbanization should be consistent with the national strategy of ecological protection and high-quality development in the Yellow River Basin. [Display omitted] • Tourism urbanization is an effective way to improve human settlement environment. • Tourism urbanization has improved the production and living environment. • Tourism urbanization has a negative impact on ecological environment. • The human settlement environment in the watershed area should be paid attention to. • Tourism urbanization construction should be consistent with policy propositions. [ABSTRACT FROM AUTHOR]

• Environmental pollution factors are taken into account in ULGUE. • There is great potential for the development of ULGUE in the upstream region. • Spatial patterns of ULGUE vary across different regions. • Industrial structure and pollution emissions are increasingly important for ULGUE. • The results will contribute to high-quality sustainable development of the YRB. 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. [ABSTRACT FROM AUTHOR]

China's Yellow River Basin (YRB) has large watershed but scarce water resources. More importantly, most parts of the YRB are located in semi-arid areas of Northwest China, where the ecology and environments are fragile. So, ecological restoration and agricultural production always are the key research topics of the YRB. However, the specific research interest of YRB changed over time and was always closely related to the implementation of government policies. Hence, we conducted a comprehensive analysis of YRB's research topics based on the methods of bibliometrics. The results showed that the number of papers about YRB's research experienced a change from slowly increasing (1998–2010, 83 papers) to rapidly increasing (2011–2015, 128 papers), and then to exponentially rising (2016–2020, 369 papers). Secondly, the main research fields of the YRB included farming, crops, water, soil, environment, and etc. The journal of Agriculture Water Management had the highest global total citations and H-index, even local cited references were the highest among all of the reference papers about the YRB. Through summarizing the most cited papers and references, we found the most important research hotspots about the YRB were: the impacts of climate change and human activities on the amount of sediment in the YRB, the management of soil erosion and vegetation restoration in the YRB, and the relationship between crops and environment and management in the Loess Plateau of China. In addition, " Loess Plateau " was the most frequent keyword in the past ten years and the popularity of " climate change " rose sharply in the past five years. For YRB's research in near future, how to effectively control carbon emissions, greenhouse gas (GHG) emissions, and carbon surplus is becoming an important implication for YRB's agricultural production and ecological restoration in the future. In general, this research is expected to promote a comprehensive and quantitative understanding of the past, present and future of YRB's research. • The research of Yellow River Basin (YRB) has exponentially increase in 2016–2020. • The research interest was closely related to the implementation of government policies. • The main research fields of the YRB included farming, crops, water, soil, environment. • The keyword of "Loess Plateau" was the most frequent keyword in the past ten years. • The carbon emissions, and carbon surplus is becoming an important research direction for YRB. [ABSTRACT FROM AUTHOR]

[Display omitted] • Trying to break out of the stereotypical thinking of inherent study areas. • Use of a three-stage DEA model to make efficiency results more scientific. • Multidimensional identification of differences between strategic areas. • Valuable regionally targeted policy recommendations are made. 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. [ABSTRACT FROM AUTHOR]

As is universally recognized, the eco-efficiency is an important index to evaluate urban ecological civilization construction, and the Yellow River Basin is the main battlefield of national ecological civilization construction. Based on the panel data of the input, expected output and unexpected output of 43 cities along the Yellow River basin from 2007 to 2017, this paper utilizes super-efficiency Data Envelopment Analysis (DEA) based on relaxation variables to measure its eco-efficiency, also discusses the spatial and temporal variation pattern via integrating spatial auto-correlation and other methods, and empirically analyzes the spatial-temporal dynamic evolution and driving factors of the eco-efficiency of cities along the river basin. From 2007 to 2017, the overall eco-efficiency of 43 cities showed a trend of decline first and then rise. Most of the cities had a relatively low level of eco-efficiency and still had a large room for improvement. From the perspective of watershed division, the spatial pattern of ecological efficiency in upper, middle, and lower cities generally shows that the ecological efficiency of middle reaches is higher than that in upper and lower reaches. The Moran's I of the urban eco-efficiency in the study area in the past 10 years shows that the eco-efficiency first presents a spatial negative correlation and then evolves into a spatial positive correlation, and the agglomeration features are enhanced year by year. This paper attempts to summarize general recommendations that are beneficial to urban eco-efficiency and provide scientific support for urban sustainable development and ecological protection. • Expand the evaluation indicators to 11 items, and weigh the eco-efficiency in more detail. • The spatial pattern of eco-efficiency in upper, middle and lower reaches is characterized by "n-shape". • Based on GIS, the relationship between urban ecological efficiency is analyzed from the perspective of space. • Combined with the government policy of city, further explored the influencing factors of urban eco-efficiency. [ABSTRACT FROM AUTHOR]

• The present situation is analyzed by using spatial autocorrelation and spatiotemporal feature distribution. • The entropy weight method and analytic hierarchy process are combined to calculate the weight of each index. • The coupling coordination degree evaluation model of WEF system in the Yellow River basin of Shandong province is established. • The coupling coordination degree of the Yellow River basin in Shandong province is about to reach a good coupling stage. • The PSO-BP model has good applicability in coupling coordination degree prediction. 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. [ABSTRACT FROM AUTHOR]

Water resources is one of the basic resources for human social development. In the context of China's rapid economic development, how to achieve the sustainable development of water resources, social economy and ecological environment has become an urgent issue. Water Resources Carrying Capacity (WRCC) is an important indicator of the degree of coordinated social, economic and ecological development that can be supported by water resources in a certain region. Based on the internal mechanism of WRCC, this paper constructs the evaluation system of WRCC, and estimates WRCC of 9 provinces in the Yellow River Basin (YRB) from 2009 to 2018 by the entropy method. Using the Logarithmic Mean Divisia Index (LMDI) model, we analyze the driving effects of WRCC differences in the YRB from both spatial and temporal aspects. Main conclusions are as follows: (1) There is an inherent mechanism between water resources, social economy and eco-environment, and the coordinated development of the three subsystems can promote the improvement of WRCC; (2) From 2009 to 2018, WRCC of the YRB showed a relatively stable upward trend, in which the sewage treatment effect and the technical effect were the main factors promoting WRCC, while the economic effect had a negative weakening function throughout the research period; (3) There were obvious differences in the WRCC of each province. We choose Shandong and Gansu as the comparison objects, then analyze the factors causing differences of WRCC through the driving effects decomposition analysis. [ABSTRACT FROM AUTHOR]

• Streamflow and sediment patterns significantly influence the benefits of cooperative reservoir operation in the YRB. • The three upstream reservoirs Longyangxia, Liujiaxia, and Wanjiazhai contribute most to the grand cooperation. • Shapley value method is recommended to reallocate the incremental benefits of grand cooperation in the YRB. The complicated relationship between water and sediment in the Yellow River Basin (YRB) makes it imperative for reservoir stakeholders to game with each other to balance the short-term and long-term benefits. This paper proposes an integrated model to analyze the cooperation opportunities for major reservoir stakeholders engaged with the Longyangxia, Liujiaxia, Wanjiazhai, Sanmenxia, and Xiaolangdi reservoirs on the YRB mainstream. Multiple benefits are considered, including flood control, water supply, hydropower generation, and sediment trapping. Non-cooperation and cooperation scenarios are compared in this study. The effect of flow and sediment conditions on the incremental benefit of cooperation is examined, which shows that the systematic incremental benefit is larger when the YRB is dryer and sediment concentration is higher. Basin-wide cooperation is especially beneficial when the inflow peak comes earlier and the streamflow process is more fluctuating. Cooperation of reservoir stakeholders in a normal year (2019) can bring more incremental benefit (i.e., $22.57 million) in contrast to the non-cooperation scenario. Longyangxia, Liujiaxia, and Wanjiazhai reservoirs contribute most to the grand cooperation by implementing optimal operation for downstream stakeholders. Three cooperative game theory methods (Shapley value, Gately point, and Nash–Harsanyi solution) are employed to find possible benefit-sharing solutions. Based on cooperative game theory, the results demonstrate the core of basin-wide cooperation in the Yellow River is negligible due to the negative externality effect, implying more measures are needed by the government or non-profit organization to maintain the stability of grand coalition, i.e., water resources utilization control and external compensation. The results also show that Shapley value could be used to reallocate the incremental benefits in the grand cooperation. [ABSTRACT FROM AUTHOR]

In this paper, a model for the slacks-based measure of super-efficiency in data envelopment analysis (SBM-DEA) was used to measure the green innovation efficiency (GIE) of 79 cities in the Yellow River Basin (YRB) from 2003 to 2018. In addition, the panel threshold model was employed to test the nonlinear relationship between environmental regulation intensity (ERI) and GIE. According to the results, the average GIE in the YRB was 0.68. However, the GIE exhibited a rising and fluctuating temporal trend and the following spatial trend: "lower reaches > upper reaches > middle reaches." Moreover, ERI had a double threshold effect on GIE in the YRB. That is, ERI had a significant positive impact on GIE only when ERI ranged between 0.595 and 0.899. Furthermore, the upper, middle, and lower reaches of the YRB exhibited different nonlinear correlations between ERI and GIE. Therefore, it is essential to implement environmental regulations that are appropriate for the actual conditions of each region. In addition, the per capita income, teacher resources, industrial structure, and actual utilization of foreign capital are significant factors affecting GIE in the YRB. These findings can help governments formulate suitable environmental policies and promote green innovation in the YRB, thereby contributing toward the goal of global sustainable development. • The efficiency of green innovation in the Yellow River Basin increases. • The efficiency of green innovation shows a spatial pattern of "lower reaches > upper reaches > middle reaches". • Regulations have a double threshold effect on the efficiency of green innovation. • The efficiency of green innovation must be improved based on the actual development of each region. [ABSTRACT FROM AUTHOR]

• A new method of dividing datasets based on PSO is proposed. • BNN incorporates Langevin dynamics in the parameter update step (LDBNN). • Integration of LDBNN, CEEMDAN, VMD and the proposed method yield the hybrid model. • The new data dividing method performs better than the traditional dividing method. • The hybrid model yields excellent point and interval predictions. Obtaining accurate point estimates and reliable interval prediction results for rainfall and runoff series is important to aid in water resource decision-making and planning management in a changing environment. In this paper, we propose a two-stage hybrid model (P-CVEE-LDBNN). The model uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD) methods for data preprocessing and a Bayesian neural network (LDBNN) based on Langevin dynamics as a prediction model. Then, a new dataset partitioning method based on a particle swarm optimization algorithm, which is different from the traditional dataset partitioning method, is applied. A one-stage hybrid model (T-CEE-LDBNN) that integrates the CEEMDAN method and the traditional method of partitioning datasets, a one-stage hybrid model (P-CEE-LDBNN) that integrates the CEEMDAN method and the new method of partitioning datasets, and the two-stage hybrid P-CVEE-LDBNN model were compared. These models were applied to monthly runoff and monthly precipitation series from seven hydrological and meteorological stations in the Yellow River basin. The mean absolute error (MAE), absolute root mean squared error (RMSE), Nash–Sutcliffe efficiency (NSE), and correlation coefficient (R) were used to evaluate the predictive ability of the models. The containment ratio (CR), the average bandwidth (IW), and the average asymmetry degree (S) were used to evaluate the interval prediction results of the models. The results show that (1) the subset obtained with the new method of data partitioning considering statistical properties is more favorable for model prediction. (2) The second decomposition approach based on VMD is a reliable method that can significantly improve the prediction accuracy of the final model. (3) Compared with traditional neural networks that can only obtain deterministic point prediction results, Bayesian methods can provide intervals with prediction results, making the results of the two-stage hybrid P-CVEE-LDBNN model highly reliable. [ABSTRACT FROM AUTHOR]

Summary Investigation of drought structure in terms of drought onset, termination, and their transition periods as well as drought duration helps to gain a better understanding of drought regime and to establish a reliable drought early warning system. In this study, a Nonparametric Multivariate Standardized Drought Index (NMSDI) combining the information of precipitation and streamflow was introduced to investigate the spatial and temporal characteristics of drought structure in the Yellow River basin (YRB). Furthermore, the correlations between the El Niño-Southern Oscillation (ENSO) events and NMSDI variations were explored using the cross wavelet technique. The results showed that (1) The variations of NMSDI were consistent with those of 6-month SPI (Standardized Precipitation Index) and SSFI (Standardized Streamflow Index), indicating that the proposed nonparametric multivariate drought index was reliable and effective in characterizing droughts. (2) The preferred seasons of drought onset were spring and summer, and winter was the preferred season of drought recovery in the YRB. The long-term average drought duration in the whole basin was nearly 5.8 months, which was clearly longer than the average drought onset and termination transition periods. (3) Overall, the drought structure in terms of drought duration, onset and termination transition periods in the YRB remained stable, and no appreciable change trend was found. (4) ENSO events exhibited a statistically negative correlation with NMSDI variations, suggesting that they showed strong impacts on drought evolutions in the YRB. Although the YRB was selected as a case study in this paper, the approach/indicator can be applied in other regions as well. [ABSTRACT FROM AUTHOR]

This article evaluated the urban land use efficiency (ULUE) of 57 cities in the Yellow River Basin (YRB) from 2005 to 2017 with the super epsilon based measure (Super-EBM) model, analyzed its difference characteristics and evolution trend by using the Theil index and kernel density function, revealed its spatial correlation by Moran index and LISA clustering, and also explored its influencing factors by the Tobit model. The results show that the ULUE of the YRB first declined and then increased, with the highest in the upstream areas, followed by the downstream areas, while the lowest in the middle reaches of the YRB. The ULUE in the YRB presented the characteristics of continuous distribution, and the ULUE in the cities south of the Yellow River was significantly higher than that in the cities north of the Yellow River. Secondly, the imbalance of ULUE in the YRB was aggravated, and the difference between groups was small while the difference within the group was absolutely dominant. The imbalance of ULUE in the midstream areas of the YRB dominated the whole basin. Thirdly, the ULUE of the YRB had a significant spatial correlation. In 2017, the local spatial correlation was mainly low-low aggregation, and the clustering area was concentrated in resource-based cities in Shanxi Province. Finally, the impact of economic development on ULUE in the YRB presented a "U" curve relationship. The proportion of secondary industry, population density, introduction of foreign capital, innovation level and traffic facilities can significantly promote the ULUE in the Basin, while land urbanization and environmental regulation had a negative impact on the ULUE of the YRB. This paper is important to realize the intensive use of urban land and achieve high-quality development in the YRB. • The urban land use efficiency, its spatial-temporal features and influencing factors of the Yellow River Basin were analysed. • The urban land use efficiency of the Yellow River Basin first declined and then increased during 2005–2017. • The urban land use efficiency had a significant spatial correlation and mainly low-low aggregation in 2017. • The economic development level had a "U" shaped impact on the urban land use efficiency. • Population density, foreign capital, innovation level and traffic facilities positively affect urban land use efficiency. [ABSTRACT FROM AUTHOR]

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

Abstract: Rapid land use change has taken place in many arid and semi-arid regions of China over the past decade, such as in Yellow River Basin. In this paper, changes in the land use pattern of the Yellow River Basin were analyzed using Landsat TM data in 1990, 1995 and 2000. The aim was to improve the understanding of changes in land use with a view to identifying potentially more sustainable systems of land use. Firstly, the mathematical methodology was explored and developed for spatial pattern changes of land use, which include the degree index model of land use dynamic, index model of land use degree, mean center model of land use and transformation model of land use. Based on these models, the changing spatial patterns of land use were calculated and analyzed. During the period 1990–2000, the areas of cropland, built-up land and unused land all increased, the area of cropland increased dramatically by 2917km2, while the areas of grassland and woodland decreased by 4668 and 33km2, respectively. Meanwhile, the spatial pattern of land use also experienced a great change. Then the driving factors of land use change were investigated, the governmental policies on eco-environmental protection, population growth and meteorological conditions were the major factors that caused the land use change in the past decade. [Copyright &y& Elsevier]

The joint operation of reservoirs is a major method of water resource development and management. To ensure the sustainable development of river basins and maintain the health of rivers, it is necessary to establish a comprehensive scheduling and operation method for reservoirs that is unified with the coordination of benefits, disaster reduction and ecology, and consider how to obtain the maximum benefit from different scheduling methods. Therefore, taking benefit as an effective way to evaluate the effect of reservoir combined operation. Based on the multi-disciplinary theories of emergy, economics, hydrology, and ecosystem service functions, this article propose a multidimensional benefits evaluation theory and quantitative method system under the joint application of reservoirs, covering safety (flood damage, sedimentation), socioeconomic (power generation, water supply), and sustainability (ecological environment) benefits. Taking the middle and lower reaches of the Yellow River controlled by the Sanmenxia and Xiaolangdi reservoirs as an example, a large historical flood in 1843 (hydrological frequency of 0.1%) was selected to analyze the multi-dimensional benefits of reservoirs under control and traditional schemes. The results showed that the flood in 1843 was extremely large, resulting in extensive flood damage (control scheme: −212.9 × 108 RMB; traditional scheme: −283.6 × 108 RMB) and the negative sedimentation benefits (control scheme: −268.5 × 108 RMB; traditional scheme: −194.2 × 108 RMB) were relatively large, leading to the comprehensive benefit of both schemes being negative. Although the comprehensive benefit of the control scheme was inferior to that of the traditional scheme, it can effectively mitigate downstream flood damage while satisfying the socio-economic and sustainability benefits; furthermore, the safety benefit has the highest priority in the multi-functional operation of the reservoir. The theory and method system proposed in this paper can quantify the benefits of reservoirs comprehensively, scientifically and effectively, and provide new theories and methods for evaluating the effect of joint operation of reservoirs. A benefit evaluation model covering safety, social economy, and sustainability is helpful for the establishment and implementation of sustainable development strategies for humans and nature. • Identify the safety, socio-economic, and sustainability benefits of reservoir groups. • Propose a multi-dimensional benefit evaluation theory and method system. • Comprehensive assessment of reservoir benefits and scheme optimization. • Reasonable development and utilization of multi-functional reservoirs. [ABSTRACT FROM AUTHOR]

Abstract: In the previous studies, a method was developed to assess soil erosion based on land use information. In this paper, we present another approach that uses environmental data to assess soil erosion. A soil erosion characteristic index EI is proposed, and its value is derived using the Analytic Hierarchy Process (AHP) technique based on standardized environmental information stored in minimum polygons that tile the erodible area under consideration. The approach is applied to a case study of the Yellow River basin, north China, where serious erosion is occurring. To represent different grades of soil erosion, the range of EI is divided into six levels according to standard grades of soil erosion intensity. The application indicates that the method deals properly with data scarcity, with the results giving a satisfactory representation of the characteristics of soil erosion in the Yellow River basin. The spatial–temporal distribution of EI in the Yellow River basin is predicted, and the results interpreted to give the long-term trend and state of soil depletion. Comparisons are given between EI and surveyed soil erosion zoning maps for the Yellow River basin at the end of the 1980s and 1990s. The output reliability and the approach applicability in smaller spatial scales are investigated in a case study of Zhifanggou basin. [Copyright &y& Elsevier]

Summary: Many hydrological models engage spatially distributed measures of ‘potential evapotranspiration’ (ETpot). The reliability and utility of the physically based Penman–Monteith approach to generate ETpot has been recently advocated. Assuming land-surface conditions, spatial surfaces of reference evapotranspiration (ET0) can be generated taking into account the topographic influence of forcing meteorological variables. This was performed in this paper by spatially interpolating maximum (T max) and minimum (T min) air temperatures, wind speed (u) and vapor pressure (e a), using a spline model with a linear sub-model dependency on elevation, and modelling the radiation environment, taking topography (i.e., elevation, slope and aspect) into account, prior to calculating ET0 at each grid-cell. In accordance with previous research, resultant lapse rates showed a strong seasonal pattern; values were steeper in summer than winter and those for T max were steeper than for T min. Monthly mean T max lapse rates varied from −3.01°C km−1 in winter to −7.69°Ckm−1 in summer, with T min lapse rates ranging from −2.79°Ckm−1 in winter, to −6.64°C km−1 in summer. Monthly climatologies of the near-surface elevation-dependence (NSED) for u and e a also showed strong seasonal values. NSED of u varied from 2.01ms−1 km−1 in winter reducing to 0.75ms−1 km−1 in summer. The NSED for e a ranged from −0.08kPakm−1 in winter to −0.64kPakm−1 in summer. For a 252-month sequence from 1980 through 2000, spatial surfaces of ET0 with a 100m resolution for the 113,000km2 study site located in the Loess Plateau, China were generated using an ‘interpolate-then-calculate’ approach. Resultant ET0 values varied from about 20mm month−1 in winter to over 150mm month−1 in summer. In order to assess the reliability of these ET0 surfaces, pan evaporation (E pan) was also spatially interpolated and from these a set of pan coefficient (K pan – a unitless ratio defined as ET0/E pan) surfaces were calculated. Spatio-temporally averaged K pan values for the study site varied from 0.44 in April to 0.65in late summer. K pan values were in agreement with another study using a Chinese 20cm diameter micro-pan, and, as expected, were lower than other values documented using a Class A pan. The influence of topography, especially aspect, was seen on the resultant ET0 and K pan, but not E pan, surfaces. Sensitivity analysis showed that results were particularly stable in the hydrologically active portion of the year extending from March to October, inclusive. This study demonstrated that high spatial resolution monthly surfaces of ET0 can be spatially modelled while taking into account the influence of topography on the forcing variables. [Copyright &y& Elsevier]

The energy-rich area of the Yellow River basin are the major energy producers in China, the energy eco-efficiency (ecological efficiency) of this area has a direct impact on the implementation of ecological protection and high-quality development strategies in the Yellow River Basin due to its huge energy consumption. In this paper, the Stochastic Frontier Model (SFA) was used to estimate the energy ecological efficiency of the study area from 2002 to 2016, the spatial differences in energy eco-efficiency were explored with the use of Spatial Auto-regressive Model (SAR), the Spatial Dubin Model (SDM) is used to analyze the influencing factors. The results show that the average value of each region in 2002 and 2016 is 0.799 and 0.698 respectively; the energy eco-efficiency showing significant spatial aggregation, with the lowest in western regions such as Wuzhong and Zhongwei, and the highest in central regions such as Ordos and Yulin; the spatial pattern of energy eco-efficiency is affected by many factors, such as the proportion of fixed assets investment in gross regional product, industrial added value in gross regional product, and the foreign investment. As a result, the formulation of regional development strategies shall focus on optimization of industrial structure and improvement of regional technical level, which shall also be supported by the establishment of cross-regional coordination organizations, the best play of advantages of all regions, and the improvement of industrial competitiveness, so as to realize the evolution and improvement of the overall energy eco-efficiency in the region. • Calculate and analyze the energy ecological efficiency by SFA and SDM models. • The overall efficiency in the study area is low, presenting a downward trend. • The evolution principle of efficiency is similar in time but difference in space. • R&D, industrial structure and other factors are related to efficiency. [ABSTRACT FROM AUTHOR]