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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.

• 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]

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.

• 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]

• 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]

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.

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.

[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]

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.

• 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]

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.