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Scholars have turned their attention to the ecological protection and high-quality development of China's Yellow River Basin in recent years. The basin is a major agricultural production area in China, hence investigating agricultural carbon emission reduction strategies in the basin is crucial. The research object in this article is the agricultural departments of China's nine provinces in the Yellow River Basin from 2005 to 2018. Agricultural carbon emissions are measured using agricultural land usage, rice planting, crop planting, straw burning, and livestock breeding as agricultural carbon sources. In addition, the GTWR model is used to examine the spatiotemporal aspects of the impact of five factors on agricultural carbon emissions in this paper. The findings reveal that the five factors have varying degrees and directions of influence. [ABSTRACT FROM AUTHOR]

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

As one of the national strategies of China, the ecological protection of the Yellow River basin (YRB) is vital for the promotion of the high-quality development (HQD) of the regional economy. This paper uses the data of prefecture-level cities in the YRB from 2004–2019 to analyze the effect of environmental regulation and local government competition on HQD. The findings show the following: (1) Environmental regulation can significantly promote HQD in the YRB, and local government competition can significantly reduce HQD. The interaction effect shows that the promotion effect of environmental regulation on HQD weakens with the intensification of competition between local governments. (2) A heterogeneity analysis shows that environmental regulation has a more significant positive impact on HQD for the lower reaches of the YRB. (3) Using a threshold effect test, it is found that the impact of environmental regulation on the HQD presents a significant nonlinear positive effect with an increase in local government competition. When the local government competition represented by the level of economic catch-up exceeds the threshold value of 3.037, this positive effect decreases significantly. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Wildland Fire Science is the property of Journal of Wildland Fire Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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

High-quality development of socio-economic, ecological environment, tourism industry and natural resources in the Yellow River Basin is a major strategic task for national development. High-quality development in the Yellow River Basin still has a lot of room for improvement, so it is important for the coupled and coordinated development of water resources-socio-economic-ecological environment-tourism industry in the Yellow River Basin region. In this study, we focus on the major strategic issues of high quality development in the Yellow River Basin in the context of the above-mentioned background and the current forms and policies of sustainable development in China, and conduct research on the theory and methods of assessing the sustainable development of regional water resources-socio-economic-ecological environment-tourism industry. However, by analyzing the existing research literature on sustainable development assessment, we find that most of them focus on a single area or two combinations of modal development studies, and focus on exploring micro-coupling mechanisms, so the generality of macro policy support is rather mediocre, which we fill this gap through this study. The study relies on an innovative macroscopic research perspective that draws pioneeringly on the quality function deployment (QFD) theory in the field of product quality management in marketing, which, it is worth stating, allows for a framework of research perspectives from a systematic and holistic perspective. In this framework, we will propose a G1-entropy value method for indicator importance (weight) assessment. It is worth stating that the G1 method used in this paper is different from the traditional G1 method in that we will introduce the identity information weights of experts to improve the reliability of the subjective assignment method. We will also construct an indicator system for studying the regional sustainable development issues in the Yellow River Basin on this basis, so as to complete the ranking and analysis of the nine provinces and the importance of indicators in the Yellow River Basin. This study will provide a comprehensive theoretical basis for Chinese government and related departments to formulate policies for the high-quality development of water resources, socio-economic, ecological environment and tourism industry in the Yellow River Basin, and also provide theoretical and empirical references for the analysis and assessment of similar international regional sustainability cases. [ABSTRACT FROM AUTHOR]

This paper focuses on the spatiotemporal evolution characteristics, as well as the driving factors, of carbon emissions in the prefecture-level cities in the Yellow River Basin (YB). The paper's findings will aid in promoting ecological conservation and high-quality development in the region. The initiatives undertaken in the YB are a significant national strategy towards achieving carbon peaking and carbon neutrality. To fully investigate the spatiotemporal evolution process, as well as the typical characteristics of their carbon emissions, conventional, and spatial Markov transition probability matrices were developed utilizing YB's panel data for 55 prefecture-level cities from 2003 to 2019. The generalized Divisia index decomposition method (GDIM) cleverly uses this data to conduct a complete analysis of the dynamics and driving processes influencing the change in carbon emissions in these cities. However, the evolution of carbon emissions in prefecture-level cities has reached a point of stability that maintains the original state, making it challenging to make meaningful short-term progress. The data indicates that prefecture-level cities in the YB are emitting more carbon dioxide on average. Neighborhood types in these cities significantly influence the transformation of carbon emissions. Low-emission areas can encourage a reduction in carbon emissions, whereas high-emission areas can encourage an increase. The spatial organisation of carbon emissions exhibits a "high-high convergence, low-low convergence, high-pulling low, low-inhibiting high" club convergence phenomenon. Carbon emissions rise with per capita carbon emissions, energy consumed, technology, and output scale, whereas it falls with carbon technology intensity and output carbon intensity. Hence, instead of enhancing the role of increase-oriented variables, prefecture-level cities in the YB should actively engage these reduction-oriented forces. The YB's key pathways for lowering carbon emissions include boosting research and development, promoting and applying carbon emission reduction technologies, lowering output carbon intensity and energy intensity, and improving energy use effectiveness. [ABSTRACT FROM AUTHOR]

How to raise the ecological compensation fund for the Yellow River Basin is one of the key difficulties for executing the ecological compensation mechanism and ensuring the high-quality development of the entire basin. This paper, which is based on systems theory, analyzes the social-economic-ecological compound system of the Yellow River Basin. It makes the point that the goals of human-water harmony, ecological compensation efficiency improvement, and coordinated regional development should be achieved in raising ecological compensation funds. Guided by the raising targets, a two-layer fundraising model based on efficiency and fairness is constructed for ecological compensation. The upper-level model is built to calculate the ecological compensation efficiency of each compensation subject from an input–output perspective. The initial fundraising scheme was further determined to implement the efficiency principle. Within the framework of sustainable development theory, the lower-level model adheres to the fairness principle based on efficiency. The social-economic development level of the compensation subject is considered to discriminate and optimize the initial scheme. Additionally, the two-layer model was utilized to conduct an empirical analysis with the data of the Yellow River Basin from 2013 to 2020. The results show that the optimized fundraising scheme is in line with the actual development level of the Yellow River Basin. This study can provide a reference for the fundraising of horizontal ecological compensation and promote the sustainable development of the whole basin. [ABSTRACT FROM AUTHOR]

For mankind's survival and development, water, energy, and food (WEF) are essential material guarantees. In China, however, the spatial distribution of WEF is seriously unbalanced and mismatched. Here, a collaborative governance mechanism that aims at nexus security needs to be urgently established. In this paper, the Yellow River Basin in China with a representative WEF system, was selected as a case. Firstly, a comprehensive framework for WEF coupling coordination was constructed, and the relationship and mechanism between them were analyzed theoretically. Then, we investigated the spatiotemporal characteristics and driving mechanisms of the coupling coordination degree (CCD) with a composite evaluation method, coupling coordination degree model, spatial statistical analysis, and multiscale geographic weighted regression. Finally, policy implications were discussed to promote the coordinated development of the WEF system. The results showed that: 1) WEF subsystems showed a significant imbalance of spatial pattern and diversity in temporal changes; 2) the CCD for the WEF system varied little and remained at moderate coordination. Areas with moderate coordination have increased, while areas with superior coordination and mild disorder have decreased. In addition, the spatial clustering phenomenon of the CCD was significant and showed obvious characteristics of polarization; and 3) the action of each factor is self-differentiated and regionally variable. For different factors, GDP per capita was of particular importance, which contributed most to the regional development's coupling coordination. For different regions, GDP per capita, average yearly precipitation, population density, and urbanization rate exhibited differences in geographical gradients in an east-west direction. The conclusion can provide references for regional resource allocation and sustainable development by enhancing WEF system utilization efficiency. [ABSTRACT FROM AUTHOR]

The Yellow River Basin assumes an important ecological and economic function in China. The study of carbon emissions from land use in the nine provinces (regions) of the pathway is important to achieve carbon reduction. Based on the dynamic data of land use, energy, and economic changes in nine provinces (regions) for the past 30 years from 1990 to 2018, this study analyzed the spatial and temporal evolution characteristics of land-use carbon emissions by using the carbon emission coefficient method in the IPCC inventory method and evaluating the low-carbon development model of the nine provinces (regions) by land-use carbon emission intensity. Finally, the LMDI model was used to analyze the factors influencing land-use carbon emissions. The results showed that: (1) in the past 30 years, the net carbon emissions have shown a continuously increasing trend, and the difference in the spatial distribution of carbon emissions in different periods was obvious. The carbon sink effect was not significant enough to offset the carbon emissions generated. (2) The continuously decreasing carbon emission intensity values per unit of GDP indicate that the coordination between land-use and economic development was getting better. (3) The factors of population size, economic size, and land-use structure accelerated land-use carbon emissions, whereas land-use efficiency limited land-use carbon emissions. Accordingly, this paper puts forward some corresponding policy suggestions. [ABSTRACT FROM AUTHOR]

As an essential way to enhance farmers’ self-development ability, off-farm employment plays an indispensable role in farmers’ multidimensional poverty reduction in many countries. Employing a survey of 1926 farmers in five provinces of the Yellow River Basin in China, this paper examined the multi-dimensional poverty reduction effect of off-farm employment and the heterogeneous influence of different dimensions of off-farm employment (modes, levels, distances and frequency). The results showed that (1) although absolute poverty in the income dimension was largely eliminated in the Yellow River Basin, the poverty in social resources, transportation facilities, employment security were the key bottlenecks restricting farmers’ self-development. (2) The province with the best multidimensional poverty reduction effect for non-farm employment was Shaanxi, with the largest contribution to employment security. (3) Improving off-farm employment level, distance and time can significantly alleviate the multi-dimensional poverty of farmers. Therefore, to lessen the multi-dimensional poverty of farmers in the Yellow River Basin, it is necessary to focus on the governance of multi-dimensional key poverty-stricken areas, such as the middle and upper courses of the Yellow River, adopting multidimensional poverty alleviation strategy of off-farm employment according to local conditions, working on the farmers’ deficiencies in social resources, mobility, employment security, and deepening the effect of off-farm employment on benefiting farmers and helping the poor. [ABSTRACT FROM AUTHOR]

In the context of promoting high-quality development in the Yellow River Basin (YRB) of China, urgent action is needed to achieve the “Dual Carbon” goal through energy savings, emission reductions, and industrial upgrading. This study measures carbon emissions from eight types of energy consumption across 43 industries from 2000 to 2019. Using the KayaLMDI model, factors affecting carbon emissions are analyzed, and the relationship between industrial structure and carbon emissions is explored through the coefficient of variation (CV). The findings reveal that coal consumption remains significantly higher than other energy sources, and the effect of energy structure adjustment on carbon emission reduction is limited compared to the impact of energy consumption increase on carbon emission growth. Moreover, the economic output effect is identified as the primary driving factor of carbon emissions, while energy utilization rate is crucial in achieving energy savings and emission reductions. Finally, the CV of carbon emissions across 43 industries is increasing. Based on these results, we suggest several policy recommendations, including prioritizing ecological concerns, developing comprehensive and scientifically sound plans, optimizing energy consumption structure, improving energy utilization efficiency, and adjusting industrial structure to promote sustainable development in the YRB. [ABSTRACT FROM AUTHOR]

As the most basic physical geographic elements, basin terrain and river networks have high spatial complexity and are closely related. However, there is little research on the correlation between terrain and river networks. In this paper, the Yellow River Basin was selected as the study area. Topographic factors of multiple dimensions were calculated. The influence of different topographic factors on the river network structure at different scales and their correlation from a multifractal perspective based on geographical detectors and a geographically weighted regression model were determined. The explanatory power of topography on the river network structure at different scales was: multifractal spectrum width > multifractal spectrum difference > slope > average elevation > elevation maximum > elevation minimum, which generally indicated that the topographic factor that has the greatest influence on the river network structure is the complexity and singularity of the terrain. The second-order clustering of regression coefficients from the results of the geographically weighted regression model revealed that the Yellow River basin was divided into three types of high-aggregation areas, which are dominated by the Qinghai-Tibet Plateau, the Loess Plateau, and the Huang-Huaihai Plain, respectively. The clustering results also revealed that the river network structure was affected by different key topographic factors in the different types of areas. This research studies and quantifies the relationship between basin topography and river network structure from a new perspective and provides a theoretical basis for unraveling the development of topography and river networks. [ABSTRACT FROM AUTHOR]

The Yellow River Basin (YRB) is a typical ecologically fragile area in both the Chinese and global contexts. This paper built a sensitivity-resilience-pressure model to evaluate the ecological vulnerability (EV) of the YRB at the grid and prefecture-level regional scales; explored the spatiotemporal characteristics of EV; and scrutinized the impacts of socioeconomic driving factors on EV. The results showed that (1) at the grid and prefecture-level regional scales, EV decreased from the upper to lower reaches, and high vulnerability was observed in the provincial capital city. Mild and severe vulnerability constituted the main EV types in the YRB. (2) The EV index of the YRB decreased from 2.71 to 2.56 in the study period, indicating that the ecological environment improved in the YRB. The slightly and lightly vulnerable areas experienced shrinking-expansion changes, and the overall areas of these two EV types showed expanding trends, while the areal changes and overall trends of the moderately, severely, and extremely vulnerable areas were contrary to those of the slightly and lightly vulnerable areas. (3) The impacts of socioeconomic driving factors on EV dynamically strengthened with the improvement of the socioeconomic level. After considering the interactions of all socioeconomic factors, the explanatory power of the spatial differentiation of EV was enhanced, and the influence of these factors became more prominent. [ABSTRACT FROM AUTHOR]

Horizontal ecological compensation mechanism provides solutions for cross-domain protection of ecological environment, and the key to its implementation depends on the establishment of a suitable incentive mechanism of economic benefits to influence the conservation behavior of each interest body. This article constructs a horizontal ecological compensation mechanism for the Yellow River Basin through indicator variables to analyze the profitability of the participating subjects. Based on data from 83 cities in the Yellow River Basin in 2019, an empirical study was conducted using a binary unordered logit regression model to examine the regional benefits generated by the horizontal ecological compensation mechanism in the Yellow River Basin. The level of urban economic development and ecological environment management significantly affects the profitability of horizontal ecological compensation mechanisms in the Yellow River basin. The heterogeneity analysis finds that the profitability of the horizontal ecological compensation mechanism in the Yellow River basin is stronger in the upstream central and western regions, which are more likely to produce better ecological compensation benefits as recipients of compensation funds. Governments in the Yellow River Basin should strengthen cross-regional cooperation, continuously improve the capacity building and modernization of ecological and environmental governance in the basin, and provide solid institutional guarantees for environmental pollution management in China. [ABSTRACT FROM AUTHOR]

In order to achieve China's carbon peaking and carbon neutrality (double carbon) targets and to advance ecological conservation and high-quality development in the Yellow River Basin, it is essential that China reduces its energy intensity and increases its energy efficiency. This research developed an evaluation index system for energy efficiency and green development in the Yellow River Basin based on panel data collected from 64 of its prefecture-level cities and covering the period from 2011 to 2020. Each city's energy efficiency and green development level index was calculated, and was analyzed together with the characteristics of its spatial pattern progression. The STIRPAT model was then used to investigate the influence mechanism of energy efficiency on green development. The final step in the analysis was to assess the process by which technical innovation influences the rise in energy efficiency from a green development point of view. The findings of this study indicate that: (1) There was a marked improvement in energy efficiency and green development levels across the Yellow River Basin over the study period of 2011 to 2020, but there are notable disparities among prefecture-level cities, with higher levels found in capital cities and cities in the lower reaches of the basin. (2) The improvement in energy efficiency has had a positive impact on the transition to green development, with factors such as human capital, urbanization levels, and the upgrading of industrial structures contributing significantly, while the level of foreign direct investment has had a limited impact. (3) Technological innovation plays a partial role in mediating the relationship between energy efficiency and green development in the Yellow River Basin, and passes the single-threshold test. When technological innovation surpasses the threshold value, the effect of energy efficiency on green development is significantly strengthened. This study indicates that improving energy efficiency, stimulating emerging industries, and enhancing technological innovation capabilities can significantly promote transformative green and high quality development in the Yellow River Basin of China. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The projection of runoff in a large‐scale basin under climate change and human activities is crucial for the future management of water supplies. The impacts of climate change on runoff projections are associated with large uncertainties. In this study, using the optimization and selection of climate models, as well as an uncertainty analysis via the global Bayesian model averaging (BMA) approach, an ensemble projection framework was established to significantly improve the reliability of runoff projections in the future. The global BMA algorithm proposed in this study is an improvement on the BMA algorithm for large basins and is designed to reflect the differences among various models across the basin. In this algorithm, comprehensive BMA weights are obtained by considering the number (N) of stations in a basin. To verify the feasibility and improvement of this method, the runoff in 2050 and 2070 was projected with data from the Yellow River Basin, China. The runoff and its 90% confidence intervals at the six main stations in the Yellow River Basin were obtained. The increased evapotranspiration will exceed the increase in runoff generated by increase in precipitation in the future. The runoff in the upper and middle reaches of the Yellow River in 2050 and 2070 are projected to be 9% and 7% lower, respectively, than those in the reference period. The ensemble projection method proposed in this paper can be used as a widely applicable process in hydrometeorological ensemble projection and provides a basis for water resource management planning. Key Points: An ensemble projection framework was established to significantly improve the reliability of runoff in the futureThe global BMA algorithm is proposed to obtain comprehensive BMA weights by considering number of stations in a basinThe runoff of the Yellow River Basin in 2050 and 2070 will decrease by 9% and 7%, respectively [ABSTRACT FROM AUTHOR]

• 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]

With rapid industrialization and urbanization, the contradiction between the human exploitation of land production and living functions and natural ecosystem service functions has intensified. The issues of how to coordinate the exploitation and conservation functions of land and guide the rational distribution of human activities have become important for global sustainable development, especially considering the realization that multifunctional land use is an effective way to relieve land pressure and improve land use efficiency, that land multifunction has significant spatio-temporal heterogeneity, and that there is a mutual promotion and stress relationship between multifunctional land use. However, few existing studies have discussed the decoupling relationship among land use functions. In this study, a system of 10 sub-functions and 25 indicators was established based on the production function (PDF), living function (LVF), and ecological function (ELF) for 59 cities in the Yellow River Basin (YRB). There are both subjective and objective procedures employed to determine the weights, while an exploratory spatial data analysis is used to analyze the time-based and territorial changes in various functions of land use in the study area from 2000 to 2020. The decoupling relationship between the three functions is detected utilizing the theoretical foundation of the decoupling analysis. The results show that land use is multifunctional, LUFs develop unevenly, and their spatial distribution varies substantially. The results of the decoupling analysis demonstrate that the predominant types of correlations among the land use ELF and PDF and LVF over the research period are strong decoupling and strong negative decoupling correlations, with the former being a dilemma and the latter being a sustainable type of development. [ABSTRACT FROM AUTHOR]

The Yellow River basin (YRB) is China's most critical energy consumption and coal production area. The improvement of carbon emission reduction efficiency in this area is the key for the Chinese government to achieve the 2030 carbon peak and 2060 carbon neutral ("30.60"). Given this, this study first calculates the carbon emission efficiency of YRB from 2005 to 2019 based on the slack-based measured directional distance function (SBM-DDF) model and combined with Malmquist–Luenberger (ML) index and decomposes the carbon emission efficiency of each province. Then, a panel Tobit model with random effect is constructed to measure the influencing factors and their influence degree of carbon emission efficiency of YRB. Finally, the main influencing factors are selected, and policy suggestions on how to improve the carbon emission efficiency of each province are put forward with the help of the coupling coordination degree (CCD) model. The results show that first, the carbon emission efficiency of each province is significantly different, but it shows a fluctuating upward trend on the whole. Second, the reasons for the rise or decline of the ML index in different provinces are different. Therefore, the development strategies of different provinces should be formulated from the perspective of accelerating technological progress and improving technical efficiency. Finally, the calculation results of influencing factors and coupling coordination degrees show that provinces with high coupling coordination degrees should focus on developing per capita power consumption and controlling per capita power consumption to consolidate the actual urbanization process and industrial structure adjustment. Provinces with low coupling coordination degrees should focus on maintaining the urbanization process and increasing the development of the tertiary industry. Therefore, to fundamentally reduce carbon emissions in YRB areas, we need to consider implementing differentiated emission reduction schemes based on national strategic objectives and in combination with the development characteristics of various provinces. [ABSTRACT FROM AUTHOR]

In the pivotal water resource region of the Yellow River Basin in China, precise prediction of water resources is essential for their effective and rational management. This study introduces a novel approach to water resource prediction by employing the Harris Hawks Optimization-Long Short-Term Memory (HHO-LSTM) model. This method overcomes the constraints faced by traditional techniques in processing time series data and various variable factors. It encompasses a comprehensive description of the multi-source hydrological data collection process within the Yellow River Basin, followed by meticulous data preprocessing. The data set for this study includes estimates of four critical water quality parameters, and the efficacy of the model is gauged through the mean squared error (MSE) and root mean squared error (RMSE) metrics. This facilitates the projection of future water quality trends in specific areas by leveraging historical water quality data. The HHO-LSTM model has demonstrated outstanding accuracy and robustness in predicting water quality across diverse temporal scales and water resource variables, marking a significant advancement in water resource management within the Yellow River Basin. This approach not only enhances current management strategies but also contributes valuable insights for ongoing water resource research and decision-making processes. [ABSTRACT FROM AUTHOR]

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

China's digital economy has been expanding rapidly in the past decade. This expansion is having a profound impact on the country's economy. Using panel data on 97 prefecture-level cities in the Yellow River Basin from 2011 to 2020, this study investigates the multifaceted relationship between the digital economy and total-factor carbon emission efficiency. The research yields three key findings: (1) The digital economy positively enhances overall carbon emission efficiency. This conclusion is drawn with robustness tests. (2) Green technology innovation serves as a partial mediator between the digital economy and total-factor carbon emission efficiency, and this mediation role is influenced by government intervention, which negatively moderates the relationship between the digital economy and green technology innovation but positively impacts the mediation role of green technology innovation between the digital economy and total-factor carbon emission efficiency. (3) The positive impact of the digital economy on total-factor carbon emission efficiency is more significant in the upper reaches, lower reaches, and resource-based cities of the Yellow River Basin. These findings provide new perspectives and empirical evidence for better understanding the relationship between digital economy development and total-factor carbon emission efficiency. They also provide policy recommendations for achieving strategic objectives, including digital economy development, carbon emission reduction, carbon peaking, and carbon neutrality. [ABSTRACT FROM AUTHOR]

The Yellow River Basin has been considered to have the most serious soil erosion in the world, and identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. This study used the Universal Soil Loss Equation (USLE) to estimate the spatial and temporal changes in soil erosion from 1985 to 2020 and analyzed the controlling factors. The results indicated that from 1985 to 2020, the average erosion modulus in the Yellow River Basin was 1160.97 t∙km−2∙yr−1, and the erosion modulus in the middle reach was significantly greater than in the lower and upper reaches. Changes in vegetation coverage, rainfall and land use controlled 38.95%, 40.87% and 9.21% of soil erosion changes, respectively. Among them, the area in which soil erosion was decreased due to increased vegetation coverage accounted for 70.77% of the area controlled by vegetation coverage, while the area in which soil erosion was increased due to increased rainfall accounted for 86.62% of the area controlled by rainfall. These results prove the effectiveness of vegetation restoration projects in controlling soil erosion in the Yellow River Basin, but more attention needs to be paid to the impact of rainfall on soil erosion in the future. [ABSTRACT FROM AUTHOR]

Understanding the regional variations and mechanisms of rural hollowing-out in the Yellow River Basin (YRB) is crucial to guiding regional rural revitalization. However, further quantitative evaluation and analysis are essential to address the issue of rural hollowing-out caused by the decrease in rural population and expansion of residential land in the YRB at different spatio-temporal scales. Based on China's census data and residential areas extracted from remote sensing images, the rural hollowing-out in the YRB is classified into five types: smart development type (SDT), human–-land recession type (HRT), population loss type (PLT), land expansion type (LET), and human–land–vacant waste type (HLW). Then, the influential features shaping the spatial diversity of rural hollowing-out types are examined, and the feature importance values at different spatio-temporal scales are assessed using the XGBoost model. The results of rural hollowing-out in the YBR indicate that (1) the geographical types of rural hollowing-out in the YRB are dominated by the HRT type and show significant heterogeneity and distribution at different spatio-temporal scales. At different time stages, the number of counties dominated by HRT in lower reaches accounts for 57% of the total counties, whereas the number of counties in the middle reaches is only 37%. Compared to the rural hollowing-out results from 2000 to 2010, the number of counties dominated by PLT and HLW from 2010 to 2020 in the middle reaches increased by 19% and 16%, respectively. (2) Precipitation had a positive effect on the variability of the rural hollowing-out distribution results based on the feature importance values, whereas agricultural productivity had a negative effect and exhibited a decreasing trend. In the entire study area, economic non-agriculturalization had a negative impact, but the topographic relief was positively correlated with the rural hollowing-out results of regional areas, and the intensity of its effect showed an increased trend from 2000 to 2020. (3) The evaluation results in the entire study area show that the main functional type and the distance from provincial capitals are the most important factors affecting rural hollowing out. Compared to other factors, the level of non-agricultural economic development has a greater impact on the spatio-temporal differentiation of rural hollowing types in different Yellow River basins. Given the significant effect of non-agricultural economic development in the evaluation of regional rural hollowing-out, it can provide methodological and indicator references for the evaluation of rural hollowing-out in different regions. [ABSTRACT FROM AUTHOR]

Understanding ecosystem services(ESs)and their interactions will help to formulate effective and sustainable land use management plans, and clarifying the balance and synergy between watershed ecosystem services can provide a basis for the regulation of the ecological environment in different regions of the watershed and the maximization of overall ecological benefits. This paper takes the Yellow River Basin as the research object and uses the Ecosystem Services and Trade Offs (InVEST)model to evaluate the water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) of the Yellow River Basin. The paper adopts the Carnegie-Ames-Stanford Approach (CASA)model to evaluate the net primary productivity (NPP), draws the spatial distribution map of the five ecosystems, analyzes the trade-off and synergy between the five ecosystems using correlation and binary spatial correlation, and expresses it in space. In addition, it adopts self-organizing mapping (SOM) method to identify ecosystem service clusters. The results show that: (1) ES is generally higher in the upper reaches of the Yellow River, and lower in the middle reaches. (2) WY and NPP, HQ, CS and WY are trade-off relationships, and other ecosystem services are synergistic relationships. Trade-offs and synergy show obvious spatial heterogeneity. (3) The ecosystem services of the Yellow River Basin, driven by different factors, can be divided into three areas, namely WY and SC service leading functional areas, HQ and CS service leading functional areas, and NPP service leading functional areas. Finally, it discusses the driving factors of the spatial heterogeneity of the balance of the ecosystem service functions of the Yellow River Basin and the suggestions of land use management in the basin. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays a key role in water cycle and energy balance, and the construction of large areas of vegetation in the Yellow River Basin (YRB) will cause an increase in regional ET and changes in water use in the basin. Based on GLEAM evapotranspiration products, meteorological stations and land use data, this study used slope trend analysis, Mann-Kendall (M-K) test and partial correlation analysis to analyse changes in evapotranspiration and water use in the YRB before and after reforestation from 1980 to 2019. The results showed that the annual average ET of the YRB from 1980 to 2019 ranged from 363 to 447 mm with an average change rate of 10.2 mm/10a. The actual evapotranspiration/potential evapotranspiration (ET/PET) growth rate of the YRB decreased after the Grain for Green Project (GGP), and the actual evapotranspiration/precipitation (ET/P) decreased extremely significantly. Water use efficiency in the YRB was significantly reduced, and grassland was subjected to greater water stress. This study provides scientific support for future water balance, landscape restoration, ecological protection and quality development of the YRB. [ABSTRACT FROM AUTHOR]

Accurate surface water mapping is crucial for rationalizing water resource utilization and maintaining ecosystem sustainability. However, the diverse shapes and scales of water bodies pose challenges in automatically extracting them from remote sensing images. Existing methods suffer from inaccurate lake boundary extraction, inconsistent results, and failure to detect small rivers. In this study, we propose a dual-stream parallel feature aggregation network to address these limitations. Our network effectively combines global information interaction from the Swin Transformer network with deep local information integration from Convolutional Neural Networks (CNNs). Moreover, we introduce a deformable convolution-based attention mechanism module (D-CBAM) that adaptively adjusts receptive field size and shape, highlights important channels in feature maps automatically, and enhances the expressive ability of our network. Additionally, we incorporate a Feature Pyramid Attention (FPA) module during the advanced coding stage for multi-scale feature learning to improve segmentation accuracy for small water bodies. To verify the effectiveness of our method, we chose the Yellow River Basin in China as the research area and used Sentinel-2 and Sentinel-1 satellite images as well as manually labelling samples to construct a dataset. On this dataset, our method achieves a 93.7% F1 score, which is a significant improvement compared with other methods. Finally, we use the proposed method to map the seasonal and permanent water bodies in the Yellow River Basin in 2021 and compare it with existing water bodies. The results show that our method has certain advantages in mapping large-scale water bodies, which not only ensures the overall integrity but also retains local details. [ABSTRACT FROM AUTHOR]

From the perspective of transaction structure, this paper measured the degree of the marketization of primary land market in 104 cities above the prefecture level of the Yellow River Basin from 2000 to 2016, and analyzed its spatio-temporal pattern evolution by spatial statistical model such as the Global Moran's I and G* i index. Grey correlation analysis model was used to explore the main influencing factors of the spatial- temporal evolution of land marketization level in the study area. The results of this study showed that, from 2000 to 2016, the land marketization level of the Yellow River Basin continued to rise at first and then decreased constantly, presenting a pattern "high level in the east, but low level in the west", which showed significant periodic differences. The land marketization of the whole Yellow River Basin had significant spatial autocorrelation. After accelerated expansion, the hotspots area of land marketization centered on downstream major cities shrank slowly. Several factors, such as the level of economic development, upgrading of industrial structure, investment in fixed assets, government revenue and expenditure ratio, foreign direct investment, and location conditions, influenced the evolution of the spatial- temporal pattern of the land marketization level in the river basin. However, due to the impact of social and economic development of China, the influence degree of various factors significantly changed in different years. [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]

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]

The dependence of water use efficiency (WUE) on changes in land cover types is crucial for understanding of long-term water availability and assessment of water-saving strategies. Investigating the impact of land cover types on ecosystem WUE has important implications when revealing water dynamics and land management. However, the determination of WUE and its dominant factors have always been subject to high data dependency and large calculation consumption within large basins. This paper proposes a framework for processing actual evapotranspiration (AET) and WUE calculation by coupling the Maximum Entropy Production (MEP) method with the Google Earth Engine (GEE). By employing the proposed framework and three data sources available in the GEE platform, results for actual ET and WUE from 2001 to 2020 were obtained in the Yellow River Basin (YRB). The results show that the proposed framework provides an acceptable estimation of actual ET via validation with Eddy Covariance flux sites in the YRB. The calculated WUE values varied greatly in different sub-basins within the YRB, indicating a cumulative growth rate of about 56% during the past 20 years. The dominant factor that led to these changes was the transition from Grasslands into other land-use types. Our results suggest that the use of the GEE platform coupled with the MEP method offers new possibilities for advancing understanding of water exchange and water resource management. [ABSTRACT FROM AUTHOR]

The United Nations Sustainable Development Goals (SDGs) and the rise of global sustainability science have led to the increasing recognition of basins as the key natural geographical units for human–land system coupling and spatial coordinated development. The effective measurement of spatiotemporal patterns of urban connectivity within a basin has become a key issue in achieving basin-related SDGs. Meanwhile, China has been actively working toward co-ordinated regional development through in-depth implementation of the Yellow River Basin's ecological protection and high-quality development. Urban connectivity has been trending in urban planning, and significant progress has been made on different scales according to the flow space theory. Nevertheless, few studies have been conducted on the multiscale spatiotemporal patterns of urban agglomeration connectivity. In this study, the urban network in the Yellow River Basin was constructed using Tencent population migration data from 2015 and 2019. It was then divided into seven distinct communities to enable analysis at both the basin and community scales. Centrality, symmetry, and polycentricity indices were employed, and the multiscale spatiotemporal patterns of urban agglomerations in the Yellow River Basin were identified using community detection, complex networks, and the migration kaleidoscope method. Community connectivity was notably concentrated at the basin scale with a centripetal pattern and spatial heterogeneity. Additionally, there was a symmetrical and co-ordinated relationship in population migration between the eastern and western regions of the basin, as well as between the internal and external parts of the basin. At the community scale, there was significant variation in the extent of central agglomeration among different communities, with few instances of similar-level, long-distance, and interregional bilateral links. The utilization of multiscale spatiotemporal patterns has the potential to enhance the comprehension of economic cooperation between various cities and urban agglomerations. This understanding can aid decision-makers in formulating sustainable development policies that foster the spatial integration of the basin. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can also be used to study the path to achieving carbon neutrality, which can clarify the potential of one region's carbon sink surplus to be compensated to the other areas. Still, there needs to be more research on the carbon compensation potential of the Yellow River Basin. Therefore, this study calculated the carbon compensation potential using the β convergence test and parameter comparison method. With the help of spatial measurement tools such as GIS, GeoDa, Stata, and social network analysis methods, the spatiotemporal pattern and network structure of the carbon compensation potential in the Yellow River Basin were studied from the perspective of urban agglomeration. The results demonstrate the following: (1) The overall carbon compensation rate of the YRB showed a downward trend from 2005 to 2019, falling by 0.94, and the specific pattern was "high in the northwest and low in the southeast". The spatial distribution is roughly spread along the east–west axis, and the distribution axis and the center of gravity keep shifting to the northwest. It also showed a weak divergence and a bifurcation trend. (2) The carbon compensation rate in the YRB passed the spatial correlation and β convergence tests, demonstrating the existence of spatial correlation and a "catch-up effect" among cities. (3) The overall distribution pattern of the carbon compensation potential in the YRB is a "low in the west and high in the east" pattern, and its value increased by 8.86% during the sampled period. (4) The network correlation of carbon compensation potential in the YRB has been significantly enhanced, with the downstream region being more connected than the upstream region. (5) The Shandong Peninsula Urban Agglomeration has the largest network center, followed by the Central Plains Urban Agglomeration, and the Ningxia along the Yellow River Urban Agglomeration has the fewest linked conduction paths. According to the research results, accurate and efficient planning and development suggestions are proposed for urban agglomeration in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

As a vital ecological barrier in China, Yellow River Basin (YRB) is strategically significant for China's national development and modernization. However, YRB has fragile ecosystems, and is sensitive to climatic change. Extreme climate events (e.g., heavy precipitation, heatwaves, and extreme hot and cold) occur frequently in this basin, but the implications (positive and negative effects) of these events on vegetation dynamics remains insufficiently understood. Combing with net primary productivity (NPP), the normalized difference vegetation index (NDVI) and extreme climate indexes, we explored the spatio–temporal characteristics of plants' growth and extreme climate, together with the reaction of plants' growth to extreme climate in the Yellow River Basin. This study demonstrated that annual NPP and NDVI of cropland, forest, and grassland in the study region all revealed a climbing tendency. The multi-year monthly averaged NPP and NDVI were characterized by a typical unimodal distribution, with the maximum values of NPP (66.18 gC·m−2) and NDVI (0.54) occurring in July and August, respectively. Spatially, multi–year averaged of vegetation indicators decreased from southeast to northwest. During the study period, carbon flux (NPP) and vegetation index (NDVI) both exhibited improvement in most of the YRB. The extreme precipitation indexes and extreme high temperature indexes indicated an increasing tendency; however, the extreme low temperature indexes reduced over time. NPP and NDVI were negatively associated with extreme low temperature indexes and positively correlated with extreme high temperature indexes, and extreme precipitation indicators other than consecutive dry days. Time lag cross–correlation analysis displayed that the influences of extreme temperature indexes on vegetation indexes (NPP and NDVI) were delayed by approximately six months, while the effects of extreme precipitation indexes were immediate. The study outcomes contribute to our comprehension of plants' growth, and also their reaction to extreme climates, and offer essential support for evidence–based ecological management practices in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

For decades, the Chinese government has been searching for solutions to cope with the increasing imbalance between the supply and demand of water in the Yellow River Basin. This paper aims at a better understanding of the development of the water allocation regime in the Yellow River Basin between 1950 and 2009, introducing a fresh perspective based on the notion of 'regime transition'. Accordingly, we investigated 1) whether so-called 'Windows of Opportunity for Transition (WOPTs)' emerged, triggering a transition, and whether WOPT(s) resulted in a stable transition towards the new regime; 2) how informal learning processes and epistemic communities have contributed to the regime change. We adapted Kingdon's 'multiple stream model' and identified four WOPTs from the 1950s, analyzing the reconfiguration process of the regime after the onset of the transition. Our examples of two types of informal learning processes demonstrate their contribution to the creation of WOPTs and the reconfiguration of the regime. Furthermore, this study indicates, in a qualitative manner, how epistemic communities contribute to the knowledge base of the regime, and thus to its development. Finally, we have provided a general insight into the further development of the water allocation regime and highlighted potential avenues for further studies. [ABSTRACT FROM AUTHOR]

Understanding the factors affecting irrigation management performance is crucial for sustainable resource use, especially with the decentralized management mode of irrigation systems being implemented in rural China. This paper contributes to the research field by incorporating different categories of social trust and perceived organization support (POS) into the analysis of irrigation management performance, by linking multiple elements that are based on the Institutional Analysis and Development (IAD) framework. We employed principal component analysis (PCA) and ordered probit regression to analyze a database covering 785 households in the upstream of the Yellow River basin. The results suggested that social trust and POS positively affected the irrigation management performance, and social trust strengthened the positive effect of POS on the performance. Furthermore, the results indicated that personal trust and institutional trust, as well as perceived emotional support and physical support, positively affected the performance. In addition, we also found that household characteristics, household cognition, group characteristics, physical conditions, and rules-in-use also had significant impact on the performance. This paper can be used to inform the government that social trust and POS need to be considered in the common-pool resources (CPRs) management. [ABSTRACT FROM AUTHOR]

A series of annual natural runoff recorded at eight hydrological stations in the Yellow River basin (YRB) and distributed at the main channel and two sub-basins (Weihe basin and Fenhe basin) are studied during the period from 1951 to 1998. The trends and the beginning points (or abrupt changes) of these series are detected with Mann-Kendall test (M-K test) and its progressive application. The results show that there are similar trends for different stations. The annual natural runoff series, except for stations of Lanzhou, Hekouzhen, and Longmen, have a downward tendency at some stations whose beginning points of the trend or abrupt changes occurred in the early or mid 1990s. However, their initial years of decrease are different. The decreasing trend of runoff has led to drying-up in lower reaches of the YRB, a water resources scarcity crisis, and a deterioration of the ecosystem. The reasons for the trends have been analyzed in this paper The trends of precipitation in the corresponding regions are similar to those of annual natural runoff It is an important aspect for runoff decrease. In addition, human activities have changed the hydrological cycle and lead to a reduction in runoff to a certain degree. Finally, two countermeasures for the runoff decrease are put forward. One is to develop water savings in irrigation regions, and the other is to plan South-to-North water transfer projects for the YRB. However the conflict between supply and demand will still exist for a long time because of the water scarcity in the future. [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]

The problem of imbalanced urban–rural development in China is becoming increasingly serious. Urban–rural integration (URI) is an inevitable way to narrow the urban–rural gap and promote rural development. The Yellow River Basin (YRB) is an important barrier to China's ecological security and plays a crucial role in promoting ecological protection and in high-quality development strategies. Therefore, this article constructs an evaluation index system for URI from five dimensions: economic integration, social integration, ecological integration, element integration, and spatial integration. The simulated annealing-projection pursuit model and time degree are used to analyze the dynamic urban–rural integration level (URIL) of 373 counties from 2000 to 2019. Building upon this foundation, this study classifies four types of URI zones and proposes development strategies tailored to each zone. The results indicate (1) that the URIL in the YRB continues to increase, and that there has been a significant increase in high-level integration areas since 2010. (2) The URIL exhibits a distinct spatial clustering pattern, characterized by lower levels in the upper reaches, and higher levels in the middle and lower reaches. (3) There exists a spatial disparity between economic development and the ecological environment, and it is particularly noticeable in the lower reaches regions. These results contribute to a better understanding of URI in the YRB and provide a reference for the sustainable development of URI in various regions. [ABSTRACT FROM AUTHOR]

Natural and human factors co-drive changes in vegetation type and distribution. In this study, we constructed an index system covering 17 natural and human activity indicators in six dimensions by using climate data, county-level human activity data, and forest–shrub–grass suitability data from 448 sample counties in the Yellow River Basin of China in 2018. On this basis, we evaluated the influence of human activities and climatic factors on vegetation suitability using multiple regression and relative importance analysis methods. The multiple regression results demonstrate that climatic factors had positive effects on vegetation suitability in the Yellow River Basin, while the influence of human activities on vegetation suitability varied according to the situation. Specifically, economic factors such as per capita disposable income of urban residents and per capita disposable income of rural residents; urbanization factors such as population density, urbanization rate, and construction land area proportion; social development factors such as road density; and agricultural production factors such as the cultivated acreage proportion and the value added of the primary industries proportion all influence vegetation suitability. There is a great regional heterogeneity in the effects of human activities such as economic factors and urbanization factors on vegetation suitability. The relative importance analysis results show that the relative importance of the factors influencing vegetation suitability in the Yellow River Basin was as follows, in order of importance: climatic factors > agricultural production factors > urbanization factors > ecological projects > social development factors > economy factors; however, except for climatic factors, the importance of other influencing factors varied from region to region. This study provides a theoretical basis for optimizing vegetation adjustment schemes and forest and grass ecosystem layout according to regional characteristics. [ABSTRACT FROM AUTHOR]

Ecological security is the state achieved once an ecosystem maintains its stability under external stress. The Yellow River Basin (YRB) is the largest river basin in northwest and north China and an important area for grain and energy production. The assessment and attribution of ecological security in the YRB are important for protecting the natural environment and ensuring sustainable development. Here, the ecological security of the YRB was assessed by the ecological security index (ESI), a comprehensive index based on the oxygen cycle, and its drivers were attributed to climate change, human activities, vegetation, and soil factors. The spatial pattern of ecological security in the YRB showed high heterogeneity. Ecological insecurity occurred mainly in the middle reaches and regions where the major stream of the Yellow River passes through. The ESI decreased at a rate of − 0.82/year since 2000, which indicated the natural environment continued to be improved in the YRB. Climate change dominated the evolution of ecological security in the upper reaches. The level of ecological security has been improved in the middle reaches after a series of ecological restoration projects conducted. With higher intensity of industrial activity, human activities played a more critical role in ecological security in the lower reaches. Our results suggested that government and local people need to adopt different strategies and actions based on the dominant drivers in the upper, middle, and lower reaches to ensure protection of the natural environment and achieve sustainable development targets. [ABSTRACT FROM AUTHOR]

As a critical way to realize the optimal allocation of water environment capacity resources in the basin, emission rights trading faces multiple uncertainties, making it extremely hard and challenging to formulate appropriate decisions and plans. Therefore, this study uses interval two-stage stochastic programming (ITSP) method to model the emission rights trading process with multiple uncertainties. It can promote the secondary optimal allocation of the emission rights between the demander and the supplier after the initial allocation. Externalities caused by environmental problems are internalized through the form of emission rights trading, thereby reducing the transaction costs and promoting the coordination and integrity of water pollution control among governments in a basin. Finally, the Yellow River basin is taken as an example for case analysis. The results show that the net revenue of emission rights system in the transaction status is better than that in the non-transaction status, and the average gap of net income reaches [171.031, 193.056] billion yuan. Under different reduction policies, the average water pollutant emission reduction in transaction status is [451.15, 628.34] thousand tons, which is generally less than [516.57, 670.05] thousand tons in non-transaction status. As policies get stricter and assimilative capacity of water bodies dwindles, reduction shrinks, leading to higher risks and economic loss from being unable to meet the discharge demand. When reduction policies are relatively loose and assimilative capacity is high, emission rights trading volume peaks. At this time, the trading volume of COD reached [29.05, 40.76] thousand tons, and that of NH3-N reached [3.74, 4.31] thousand tons. All these findings will offer insights for decision-makers on how to strike a balance between economic benefits and emission rights trading plans in the Yellow River basin. [ABSTRACT FROM AUTHOR]

Dynamic assessment of the water environment reflects variations in water resources in a basin under the combined influence of nature and humans and is a prerequisite for rational water management. This study provides an integrated assessment of the water environment in a water quantity-quality-soil model. Using the long-term monthly data from hydrological monitoring stations, the water environment of the Yellow River basin is assessed from the year 2006 to 2019. The kernel density estimation and the Dagum Gini coefficient are used to analyze the spatial and temporal imbalances of the water environment. Geographic detectors are used to extract external driving factors of the unbalanced evolution. The study results reveal that (1) the water environment in the basin shows a fluctuating downward trend, which mainly depends on the organic pollution control indicators, with a contribution of 22.85%. Scores of the water environment in the midstream are lower than those in the upstream and downstream due to the heavy pollutant discharges. (2) The spatial imbalance shows a fluctuating downward trend. Inter-regional variation is the primary source of regional variation in the water environment, with an average contribution of 56.02%. (3) The temporal imbalance of the water environment is on the rise, with a degree of multipolarity. The significant left trailing feature of the kernel density curve suggests that there are areas within the basin where the water environment is extremely poor. (4) For the overall basin and upstream, economic development and technological innovation are the main external driving factors influencing the spatial and temporal imbalances of the water environment. For the midstream and downstream, population density and environmental regulations are the main drivers. The interaction of any two factors has a greater impact than the single one. [ABSTRACT FROM AUTHOR]

Tourism has become an indispensable aspect of rural development. For traditional villages with historical and cultural importance, whether the development of tourism had led to traditional villages being restricted or supported needs to be studied. Taking 684 traditional villages in the Yellow River Basin in China as an example, we used Adaptive Cycle Theory to construct an index system and explored the adaptability of Chinese traditional villages in terms of undergoing development for tourism by describing the spatiotemporal coupling and evolution process of village adaptation. Then, we constructed a binary logistic regression model to measure the adaptation differences for villages providing different tourism services. The results showed that from 2000 to 2018, the social adaptability of traditional villages tended to deteriorate and was spatially and regionally different. Compared with the traditional villages without tourism, in villages where tourism has been developed, the adaptability of villages dominated by agriculture is poor. Villages dominated by traditional national culture and ecological leisure agriculture showed higher adaptability. By exploring the adaptation model and evaluating the technological development of traditional villages, we provide support for enhancing the interaction between the external and internal resources of tourism-oriented traditional villages. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems provide crucial ecosystem services to human beings, and their functions are largely dependent on soil moisture availability. Although many studies have evaluated the effects of vegetation and climate changes on soil moisture at the ecosystem scale, changes in ecosystem water limitation remain poorly understood. This study evaluated the spatiotemporal changes of ecosystem water limitation in the Yellow River Basin (YRB)—the second largest river basin of China—during 1982–2016 and identified the major drivers by establishing ecosystem limitation index (ELI) using soil moisture, transpiration, net radiation, and air temperature. The results show a significant and widespread spatiotemporal increase in the water limitation of ecosystems in YRB during the 35‐year study period. Temporally, areas with positive ELI (water‐limited regime) exhibited a significant upward trend (p < 0.01). Spatially, above 75.0% of the total areas showed an upward trend in ELI. Almost all ecosystems showed significant upward trends in water limitation over this period. Further analysis using two different but comparable methods, partial correlation and Lindeman‐Merenda‐Gold, show that vegetation change was the major driver of changes in water limitation, with contributions of more than 35.0%. Air temperature and atmospheric CO2 changes contributed comparably to changes in positive ELI, followed by precipitation changes. These findings improve the understanding of the spatiotemporal pattern and underlying mechanisms of ecosystem water limitation in the greening and warming YRB. Plain Language Summary: Functions of terrestrial ecosystems are largely dependent on soil moisture availability. Plenty of past studies have been conducted to investigate the vegetation and climate effects on soil moisture. However, the ecosystem water limitation and its spatiotemporal changes are rarely explored. We used a correlation difference as the ecosystem limitation index (ELI) to investigate the ecosystem water limitation over the Yellow River Basin (YRB)—the second largest river basin of China during 1982–2016. We found a significant and widespread increase in the water limitation of all ecosystems in YRB during the 35‐year study period. In total, above 75.0% of the total areas showed an upward trend in ELI (increasing water limitation). We used two different methods to attribute ELI and found that vegetation change was the major driver of changes in water limitation, with contributions of above 35.0%. Air temperature and atmospheric CO2 changes contributed comparably to ELI, followed by precipitation changes. The findings highlight the key role of vegetation in ecosystem water limitations in the greening and warming YRB. Key Points: Widespread increasing ecosystem water limitation was found in Yellow River Basin during 1982–2016All ecosystem types showed significant increasing water limitation regimesVegetation was found to be the major driver of the increased ecosystem water limitation [ABSTRACT FROM AUTHOR]

The ecological protection and high-quality development of the Yellow River Basin have become major national strategies in China. Therefore, reducing carbon emissions in the Yellow River Basin through efficient industrial agglomeration is necessary for achieving the goals of carbon peak by 2030 and carbon neutrality by 2060. The Yellow River Basin is an important base for energy, chemicals, raw materials, and industry in China, making it important to study the effects of different industrial agglomeration types on carbon productivity from the perspective of agglomeration externalities. Therefore, taking 2009–2019 panel data for prefecture-level cities in the Yellow River Basin, this study uses a spatial Durbin model to investigate the spatial spillover effects of industrial agglomeration (i.e., specialized, diversified, and competitive agglomeration) on carbon productivity. Furthermore, the moderating effects of urbanization level and environmental regulation are analyzed. The results reveal, first, the existence of spatial correlation in carbon productivity across different cities in the Yellow River Basin. Second, diversified and competitive agglomeration significantly increase carbon productivity, although competitive agglomeration has beggar-thy-neighbor spillover effects. Meanwhile, the effect of specialized agglomeration is not significant. Third, the effects of different types of industrial agglomeration differ significantly between cities in different locations and with different resource endowments. Fourth, urbanization level and environmental regulation have different moderating effects in the relationship between different types of industrial agglomeration and carbon productivity. These findings provide evidence for further developing rational industrial agglomeration patterns to enhance carbon productivity in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The highly non-linear and nonstationary nature of runoff events in changing environments makes accurate and reliable runoff forecasting difficult. We propose a hybrid model by integrating an autoregressive (AR) model, Bayesian inference, a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm, Bayesian optimization, and support vector regression. Two Bayesian inference methods (the No-U-Turn Sampler (NUTS) and variational inference) were used to calculate the parameters of the AR model to obtain a Bayesian AR (BAR) model. Credible intervals were used to analyse the uncertainty of the parameters and model prediction results. The above model is applied to the daily runoff predictions of hydrological stations in the Yellow River basin of China. The results show that (1) the hybrid model can improve the prediction accuracy and (2) the NUTS algorithm-based model provides a narrower reliable interval and performs better in uncertainty analyses. [ABSTRACT FROM AUTHOR]