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

In the era of big data transformation, with the emergence of COVID-19, tourism has been given more social responsibilities. Tourism construction in the Yellow River Basin is an indispensable part of tourism construction in China. This paper analyzes the existing eco-tourism resources in Kaifeng City and Shandong Province, as well as the necessity and construction conditions of developing tourism. In this paper, principal component analysis is used to analyze the resource conditions, regional conditions and environmental conditions of the Yellow River tourism resources. The comprehensive evaluation model and index system of tourism resources are constructed. Big data transformation has been realized. The purpose of this paper is to clarify the current situation and potential of tourism in the Yellow River Basin, and to provide reference for the development of tourism in the Yellow River Basin during COVID-19. [ABSTRACT FROM AUTHOR]

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• 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]

Scientific estimation and dynamic monitoring of CO2 emission trends are an important basis for formulating regional differentiated carbon reduction strategies. Using the integrated nighttime light data, this study estimated CO2 emissions in the Yellow River Basin (YRB) and Yangtze River Basin (YZRB) and discussed the similarities and differences of the spatial distribution of CO2 emissions for the two river basins. The results showed that: (1) The CO2 emissions in the two basins continued to rise, but the growth rate decreased from 2000 to 2018, showing an overall convergence trend, but have not yet reached carbon peak. (2) The high emission and high agglomeration areas were located in Shandong Province in the downstream of the YRB, Shanxi, Shaanxi and Inner Mongolia in the midstream and upstream, and the Yangtze River Delta (YRD). (3) Compared with the YRB, the growth rate of CO2 emissions in the YZRB is slower, and the growth rate declines greatly. In the YRB, it had higher CO2 emissions amount, wider area of high carbon emissions and more obvious spatial agglomeration than that in the YZRB. (4) According to CO2 emissions and economic development level, 220 cities of the two river basins were classified three types: low CO2–low development, high CO2–low development and high CO2–high development. [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 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]

Droughts and floods have proven to be threats to food security worldwide. This research used the standardized precipitation index (SPI) to examine the spatiotemporal characteristics of drought and wet events from 1961 to 2020 in the Yellow River basin (YRB). Grain yield data were combined to assess how drought and wet frequency have affected the agricultural system. The occurrence frequency of drought was greater than that of wetness in time, drought frequency decreased, and wetness increased. Spatially, the frequency of drought in all provinces except Shanxi was higher than that of wetness. The grain yield per unit area of the YRB was generally highest in Shandong province and lowest in Gansu province. The grain yield per unit area have shown a significant growth trend in the nine provinces of the YRB since 1961. Drought had a negative effect on the grain yield per unit area in each province, while wetness had a positive effect on the grain yield per unit area in all provinces except Shandong. In general, the influence of drought on grain yield per unit area decreased, while the influence of wetness on grain yield per unit area increased. The results indicate that human activities are effective against preventing and controlling drought and wet disasters and can provide a reference for other parts of the world. [ABSTRACT FROM AUTHOR]