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Copyright of Journal of Anhui Agricultural Sciences is the property of Journal of Anhui Agricultural Sciences 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.)

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography 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.)

Wading projects are likely to bring about changes of the original hydrodynamic conditions of the river, and this may further affect the flood discharge capacity of the river course. Thus, it is of great significance to study the flood risk of the river course with or without the wading projects, so that we can well maintain the project, regulate river course and ensure regional flood control security. Based on the random simulation of four uncertain factors, namely peak flood discharge, initial water level, river course roughness and dike elevation, this paper analyzed the stress of aqueduct under flood action, and then calculated the water surface line of the river. Combined with theforce conditions and water surface line calculation results, the conventional Monte Carlo method and the Monte Carlo method based on Latin hypercube sampling were both used to calculate the flood risk of river course with or without an aqueduct. The results show that: 1 When the water level in Gangqian Aqueduct is 0.5, 1.0, 1.5 and 2.0 m, the flood discharge capacity of Qingfeng Mountain stream, compared with its designed discharge of 1 200 m³/s, respectively decreases by 36.68%, 27.87%, 19.00% and 10.05%. 2 In the case of having no aqueduct in its river course, the flood risk of Qingfeng Mountain stream course is 0.007. In the case of having Gangqian Aqueduct in its river course, when the water level in the aqueduct was 0.5, 1.0, 1.5 and 2.0 m respectively, the flood risk of Qingfeng Mountain stream course is 0.34, 0.045, 0.016, 0.012 in turn. 3 Keep the water level in Gangqian Aqueduct at the highest value within the safe range. When the discharge of Qingfeng Mountain stream exceeds 1 600 m³/s, the flood risk of its river course still rises significantly with the increase in the flood flow. Therefore, in this case, Gangqian Aqueduct would have to be scrapped to ensure the flood discharge capacity of Qingfeng Mountain stream. 4 Both the conventional Monte Carlo method and the Monte Carlo method based on Latin Hypercube Sampling are suitable for assessing the influence of aqueduct on flood risk of river course, and the latter has better convergence. In summary, building adueducts in river courses would have a negative impact on the river courses' flood discharge capacity. It results in the flood discharge capacity of the river course being lower than the designed discharge, and further, led to the flood risk of river course increasing. To a certain extent, raising water level in the aqueduct can reduce the flood risk of river course. The fairness of water use is one of the key factors to be considered in the balanced allocation of water resources. Aiming at the problem that the fairness of water use in the basin is not considered enough in the different industries, an evaluation method based on multi-factor Gini coefficient in different industries is proposed. The Gini coefficient between industry water consumption and industry scale is used to represent industry water fairness. The comprehensive Gini coefficient of water use in the basin is calculated based on the proportion of water consumption in each industry to represent the fairness of water use in the basin. Taking the Yellow River Basin as an example, this paper calculates the Gini coefficient and analyzes the variation of the fairness of water use of different industries in nine provinces of the Yellow River Basin from 1980 to 2020. Take 1995 and 2005 before and after the integrated water regulation of the Yellow River as examples, the impact of integrated water regulation on the fairness of water use in the basin was compared and analyzed. The results show that over the past 40 years, the fairness of water use in domestic, industry, urban public, and agriculture were "highly fair", "relatively fair", from "highly fair" to "relatively fair", and from "relatively fair" to "highly fair", respectively. The proportion of agricultural water use exceeds 70%, and the Gini coefficient of watershed water use is mainly affected by agricultural water use, the comprehensive Gini coefficient of economic and social water use in the basin is 0.16-0.25 from 1980 to 2020, which is in a downward trend, indicating that the fairness of economic and social water use in the basin has gradually improved, changing from "relatively fairness" to "highly fairness" . The fairness of water use for domestic and agriculture is gradually improved, and the fairness of public water use in industry, especially in urban areas, has decreased significantly. This is mainly because the differences in water use quotas for domestic and agriculture between 9 provinces in the basin have decreased, while the differences in water use quotas for the tertiary industry have increased. The integrated water regulation of the Yellow River has effectively controlled the total water use in the basin, promoted the improvement of agricultural water use efficiency and the reduction of water quota differences between provinces, and improved the fairness of agricultural water use and water use in the entire basin. [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography 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.)

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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

In order to provide theoretical support and decision-making basis for improving the level of industrial green development in the Yellow River Basin and promoting the transformation and building industrial green development in the Yellow River Basin, the panel data of nine provinces (regions) in the Yellow River Basin from 2012 to 2021 were used to calculate the level of industrial green development in the Yellow River Basin by using entropy weight-TOPSIS model. The differences were analyzed from spatial distribution, temporal characteristics and provincial levels, and the obstacle factor diagnosis model was used to explore the main obstacle factors affecting the green industrial development in the Yellow River Basin. The results show that the level of industrial green development in the Yellow River Basin shows an over- all upward trend from 2012 to 2021, with the value increasing from 0.378 in 2012 to 0.498 in 2021. The main obstacles to green industrial development in the Yellow River Basin are industrial environmental control and industrial innovation. The main obstacle factors are the proportion of industrial pollution investment in industrial added value, industrial labor productivity, the proportion of industrial wastewater treatment funds in industrial pollution control investment, the number of valid invention patents per household of industrial enterprises above designated size, and the level of innovation capital investment. Finally, the paper put forward some suggestions to improve the level of industrial green development in the Yellow River Basin from three aspects of optimizing industrial structure, strengthening environmental governance and building green innovation system. [ABSTRACT FROM AUTHOR]

By exploring the coupling and coordination relationship between high-quality agricultural development and ecological environment in the Yellow River Basin, and providing scientific reference for ecological protection and high-quality development in the Yellow River Ba- sin, this paper took nine provinces in the Yellow River Basin as the research object, and based on the panel data from 2012 to 2020, adopted the entropy value method, coupling coordination degree, spatial autocorrelation and spatial econometric model to study the coupling and coordination characteristics of high-quality agricultural development and ecological environment, and analyzed the spatial and temporal pattern evolution and driving factors of the coupling and coordination degree between them. The results show that the high-quality development level of agriculture and the ecological environment level in the Yellow River Basin are both on the rise, the regional pattern of the former is mainly "high in the upper and lower reaches and low in the middle reaches". The regional pattern of the latter is mainly "high in the middle and lower reaches and low in the upper reaches". The degree of coupling coordination between high-quality agricultural development and ecological environment is at a relatively low level, higher coupling coordination in the downstream than that of the middle and upper stream, there is a significant spatial agglomeration effect. Scientific and technological innovation and agricultural products trade play a significant role in the coupling and coordination level of high-quality agricultural development and ecological environment in the province (autonomous region), environmental regulation, scientific and technological innovation and agricultural trade have a significant positive space spillover effect, however, the spatial influence degree of each factor is different. In order to promote the improvement of coupling and coordination degree, the following suggestions are put forward; formulating development strategies in accordance with local conditions, strengthening interregional coordination and cooperation, and correctly playing the role of government and market. [ABSTRACT FROM AUTHOR]

In order to quantitatively evaluate the impact of inter-industry water rights transfer on economy and society in the main stream of the Yellow River in Inner Mongolia, the paper analyzed the impact of water rights transfer on agriculture, and the impact of water rights transfer on water use, production and operation, annual income, people's livelihood and economy of all industrial enterprises. The results show that the transfer of inter-industry water rights in the main stream of the Yellow River in Inner Mongolia in 2019-2021 has driven the total investment of industrial projects to 599.58 billion Yuan, created 122 145 new jobs, the gross regional product is 44.709 billion Yuan, the industrial added value is 238.821 billion Yuan, the annual tax revenue is 19.47 billion Yuan, the newly paved road area is 13.161 7 million km², and the new green area is 30.995 million km². The agricultural output value and farmers' income have been significantly increased, local livelihood issues have been effectively solved, and ecological protection and social and economic development along the Yellow River have been promoted. The transfer of water rights between industries in the main stream of the Yellow River in Inner Mongolia has alleviated the bottleneck of water resources of industrial enterprises along the Yellow River, realized the multi-win of farmers' production increase, economic efficiency increase and ecological restoration, and provided strong support for ecological protection and high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In order to promote the implementation of the action of deep water saving and control in the Yellow River Basin and improve the level of intensive utilization of water resources in Shaanxi Province, this paper discussed the definition of deep water saving, using the Fuzzy Analytic Hierarchy Process (FAHP) to establish the evaluation index system of deep water saving level, evaluated the deep water saving level of cities in the Yellow River Basin of Shaanxi Province, put forward the existing problems and countermeasures, and calculated the deep water saving potential according to the deep water saving goal, which had theoretical support for the implementation of deep water saving in Shaanxi Province. The results show that in the current year, the level of deep water saving in Xi'an, Xianyang, Yan'an, Tongchuan, Baoji, Hancheng, Yangling, Yulin, Shangluo and Xixian New District is strong, and the level of deep water saving in Weinan is general. The deep water saving potential of the Yellow River Basin in Shaanxi Province during the 14th Five-Year Plan period is 323.9 million m³, which can increase the water saving potential of 82.7 million m³ compared with the general water saving situation [ABSTRACT FROM AUTHOR]

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

It is essential to adhere to the optimization of national land use development patterns and the green development policy for achieving ecological conservation and high-quality development in the Yellow River Basin. This paper used the undesirable output SBM model to measure the green development efficiency of 36 prefecture-level cities in the restricted development zones of the Yellow River Basin from 2010 to 2019. It also used the Fuzzy-set Qualitative Comparative Analysis (FsQCA) method to explore the complex influence mechanism of the linkage of various influencing factors on the efficiency of green development. The results showed that: ① The green development efficiency of the restricted development zones in the whole basin showed an overall fluctuation and upward trend, and the green development efficiency of various regions in the basin varied significantly. The downstream restricted development zones had the highest green development efficiency, followed by the middle stream restricted development zones, with the upstream restricted development zones having the lowest efficiency. ② The areas with high green development efficiency in the restricted development zones of the whole basin changed from cluster distribution to contiguous distribution, the effective efficiency areas changed from being concentrated in the upper and middle reaches to the middle and lower reaches of the areas, and the green development efficiency of the restricted development zones on the southern bank of the Yellow River was significantly higher than that of the areas on the northern bank. ③ Each of these factors--the level of economic development, urbanization, environmental regulation, degree of trade openness, advanced industrial structure, and investment in science and education--could not singularly become a necessary condition for promoting the formation of high green development efficiency in the restricted development zone of the Yellow River Basin. ④ Four models were identified as those that could promote green development efficiency in the restricted development zones in the Yellow River Basin. In terms of the different types of cities, the 'environmental regulation + export-oriented economy' linkage model could promote the green development efficiency of agricultural cities in the restricted development zones of the Yellow River Basin. The linkage model of 'basic dynamic + environmental regulation + export-oriented economy + industrial upgrading' could promote the green development efficiency of resource-based cities in the restricted development zones of the Yellow River Basin. The two models of 'export-oriented economy + industrial upgrading' linkage and 'basic dynamic + industrial upgrading + science and education investment' linkage could promote the green development efficiency in the old industrial bases in the restricted development zones of the Yellow River Basin. Based on the perspective of configuration association, this paper provides policy suggestions for promoting green development in agricultural cities, resource-based cities, and old industrial base cities in the restricted development zones of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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.)

In order to quantify trade-associated virtual water flows and evaluate their impact on regional water systems, this paper used the multi-region input-output model to reveal the pattern and structure of the virtual water trade inside and outsided of the Yellow River Basin in 2012,2015 and 2017 and used LMDI method to analyze the impact of the virtual water net output of the watershed relative to others, and used the QAP model to analyze the impact factors of the virtual water trade among provinces within the watershed. The results show that a) the Yellow River Basin as a whole presents a virtual water net input state, but the Yellow River Basin net exports virtual water to Beijing, Tianjin, Hebei and other 12 regions. b) The virtual water trade export industry is mainly the production and supply of agriculture, electricity, gas and water. c) Structure effect and intensity effect are important driving factors of virtual water net output in the watershed. d) QAP regression outcomes prove that economic development level, geographic distance and water use intensity differences are the main factors affecting the virtual water trade. [ABSTRACT FROM AUTHOR]

Inclusive finance is an important way to promote farmers’ income increase and adjust farmers’ income structure. This paper uses the panel data of the Yellow River basin from 2011 to 2020 to explore the impact of inclusive finance on the income structure of farmers. The results show that:①The total inclusive financial index has a significant positive impact on the income of rural residents and income from all sources in the whole and all regions of the Yellow River basin, but only has a negative impact on property income in the upstream region, but the negative impact is not significant. ②The inclusive financial coverage index has a significant positive impact on the income of rural residents and income from all sources in the whole and all regions of the Yellow River basin, a significant negative impact on the income of downstream households, and a significant negative impact on downstream property income. ③The depth index of inclusive financial use has a significant positive impact on the per capita net income of rural households and the net income of household management in the whole Yellow River basin, but has no significant positive impact on wage income, while property income and transfer income have a significant negative impact. [ABSTRACT FROM AUTHOR]

Based on the provincial panel data of the Yellow River basin from 2011 to 2020, this paper first calculates the agricultural modernization level of the Yellow River basin using entropy method, and then uses OLS model to empirically analyze the impact of agricultural scientific and technological innovation investment and agricultural modernization in the basin. The results show that:①The average agricultural modernization index of the Yellow River basin is 0. 399, which is in the initial stage, and shows an upward trend in 2011-2018; However, the decline occurred in 2018-2020, which cast a shadow on the development of agricultural modernization in the Yellow River basin. In all regions, the average value of the comprehensive index of agricultural modernization development in the downstream is significantly higher than that in the middle and upstream, and the development index in the upstream is the lowest. Among the provinces and autonomous regions, the average comprehensive development index of agricultural modernization in Shandong Province, Inner Mongolia Autonomous Region and Henan Province is higher than that in other provinces (regions), while the average comprehensive development index of Gansu Province is the lowest. ②The scale of investment in agricultural scientific research has a significant positive impact on the overall and downstream agricultural modernization development of the Yellow River basin, and a significant negative impact on the upstream and midstream; The investment intensity of agricultural research funds has a significant positive impact on the development of agricultural modernization in the Yellow River basin, the upper and middle reaches, and a significant negative impact on the lower reaches; The impact of human investment in agricultural research on agricultural modernization in the Yellow River basin and the upper, middle and lower reaches is significantly positive. [ABSTRACT FROM AUTHOR]

In order to provide reference for the institutional construction of ecological protection and high-quality development in the Yellow River Basin, from a methodological perspective, this paper analyzed the new institutional construction needs for ecological protection and high-quality development in the Yellow River Basin, and the contradiction of the overall requirements of basin governance between fragmented management in reality. On the premise of adhering to ecological priority and green development, and implementing tailored and classified policies, the above issues could be solved by finding the smallest tool unit that covered both ecological protection and high-quality development. Green credit is the minimum common multiple between ecological protection and high-quality development. Establishing a green credit system through laws, regulations and policy regulations is a necessary foundation and logical starting point for basin collaborative governance. Yellow River Conservancy Commission and the nine provinces (regions) in the Yellow River Basin can, in accordance with higher-level laws and relevant policies such as the Yellow River Protection Law, promptly introduce operational norms applicable to the basin and region. [ABSTRACT FROM AUTHOR]

The study of carbon budget and carbon compensation zoning is of great significance in formulating strategies to adapt to the low-carbon development of each region, promoting synergistic management of regional ecological environment, and realizing high-quality develop‐ ment. This paper takes 56 municipal units in the Yellow River Basin as the study area, and by constructing a conceptual structure of carbon income and expenditure as well as carbon compensation zoning of the cities in the basin, it studies the spatio-temporal differentiation law of carbon income and expenditure as well as carbon compensation zoning of the urban agglomerations in the Yellow River Basin by using methods such as the centralization index and the location-con‐ strained multivariate spatial clustering, and then it provides constructive theoretical solutions for the low-carbon development strategy in the process of urbanization. The study shows that: (1) the cities in the Yellow River Basin from 2000 to 2020 are characterized by obvious geographical differentiation of carbon expenditure and revenue, specifically, the carbon expenditure and revenue centralization index of the study area fluctuates up and down around the warning line of 0. 4, and the overall curve shows an obvious fluctuating upward trend. (2) The spatial and temporal variation of carbon income and expenditure among cities in the Yellow River Basin is remarkable, and the data show that carbon emissions in the Yellow River Basin show a structure of "low in the west and high in the east and central parts of the country", with the high-value centres in Gansu, Shaanxi and Shandong provinces in 2000, and then the number of high-value areas of carbon emissions has increased year by year, while at the same time, the absorptive capacity of carbon sinks in each city is roughly equal. (3) Based on the framework of carbon offset zoning, the study area is divided into five types of carbon offset spatial optimization zones, and suggestions are made for green and low-carbon development planning in different types of zones. (4) In the future, the study will refine the spatial scale of the study area, explore the balance of carbon budget and carbon compensation of smaller units, and strive to explore the optimization of the green and low-carbon development mode of small areas, so that the energy conservation and emission reduction and green development of small areas can lead the cities in the region to achieve the dual-carbon goal. [ABSTRACT FROM AUTHOR]

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage 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.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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.)

The water body in the Yellow River basin is complex. Rapid and accurate water extraction in the basin is of great significance to the ecological protection and high-quality development of the Yellow River Basin. However, the existing water body indexes can not meet the requirements of removing the inherent mountain shadow of remote sensing images and accurately extracting complex water bodies. Based on Google Earth Engine (GEE) platform and Sentinel-2 remote sensing images, this paper proposed a Yellow River Basin Water Index (YRBWI), and the effect of water extraction results were compared with the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI) and Shadow Water Index (SWI). The results show that YRBWI achieves an excellent water extraction effect in the Yellow River Basin, specifically: YRBWI can solve the confusion of mountain shadows and accurately extract water bodies with high sediment content; compared with NDWI, MNDWI, and SWI, YRBWI has the largest OA and Kappa values, indicating that YRBWI has the highest water extraction accuracy; the water body extraction accuracy of YRBWI is insensitive to the change of threshold value and has high robustness. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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.)

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research 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.)

In order to provide reference for solving the difficult issue of unbalanced and uncoordinated development of the Yellow River Basin, this paper built a high-quality development evaluation index system of the Yellow River Basin from five dimensions of innovative development, coordinated development, green development, open development and shared development. The paper used the weighted TOPSIS model to measure the high-quality development level of provinces（regions） in the Yellow River Basin from 2010 to 2019. The results show that in 2010-2019, the high-quality development level of the Yellow River Basin is generally low, and there are obvious differences among provinces（regions） in space, showing a continuous upward trend in time, and the inter provincial gap is gradually narrowing. From all dimensions, the levels of innovative development and shared development shows a steady upward trend. The levels of open development and coordinated development both experience a slight decline from 2012 to 2015 and begin to rise significantly in 2016. The level of green development also shows an upward trend but fluctuates greatly. The coordination level of economic, social and ecological environment coupling in the Yellow River Basin is low, and it has been in a state of imbalance for a long time. After 2016, it has changed from a moderate imbalance to a mild imbalance and a near imbalance. Government capacity, the degree of opening to the outside world, the level of education and the degree of medical security have a positive impact on the degree of coupling and coordination. The level of technology and ecological conditions have different effects on the degree of coupling and coordination of the Yellow River. [ABSTRACT FROM AUTHOR]

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Based on the provincial panel data of the Yellow River basin from 2011 to 2020, this paper uses the entropy weight method to evaluate the overall and regional agricultural green development level of the Yellow River basin from four aspects of resource utilization, environmental impact, ecological conservation and economic benefits, and carries out regional difference analysis. The results show that: ① The overall agricultural green development level of the Yellow River basin is not high and shows an overall upward trend, only in 2018 did it decrease. From the perspective of classification indicators, the scores of each classification indicator are quite different. The score of resource utilization is the highest, the score of environmental impact is the lowest, and the score of ecological conservation and economic benefits is lower than that of resource utilization, but the difference between the three is not significant. ② The average comprehensive score of agricultural green development level in the downstream region is the highest, followed by the middle reaches, and the lowest in the upstream region. From the perspective of development trend, the upstream region shows an overall upward trend during the sample period, but there are still fluctuations. Although the average score of agricultural green development level in the relatively stable downstream region is the highest, the volatility of its development trend is significantly greater than that in the upstream and midstream regions. [ABSTRACT FROM AUTHOR]

In order to provide scientific and technological support for the implementation of major national strategies for ecological protection and high-quality development and rural revitalization in the Yellow River Basin, this paper systematically summarized the research results, key technologies and typical models of the coordinated development of ecological governance and ecological economy in the Yellow River Basin over the years, analyzed the current existing and outstanding issues, and put forward corresponding countermeasures and suggestions. Over the years, various regions in the Yellow River Basin have explored a variety of coordinated development models of ecological governance and ecological economy for serious soil erosion. It includes the comprehensive ecological and economic management model with high adaptability of soil and water conservation-geomorphology-ecological economy, the ecological agriculture economic model of soil and water conservation, the integrated development model of soil and water conservation and ecological economy in wind-sand area, the coordinated development model of ecological management and derivative industries in Pisha sandstone area, the virtuous cycle model of rural energy ecology in semi-arid areas, and the governance model of ecological and economic belt of soil and water conservation in the Loess Plateau. At present, the existing outstanding issues include the concept of coordinated development of ecological governance and ecological economy is weak, the synergy between the two is not high, the space for coupling and coordination is unbalanced, and the development model has a single structure and low scale efficiency. The suggestions: To innovate the theory and key technologies of coordinated development of ecological governance and ecological economy; To establish a diversified investment mechanism, create a new model of coordinated development of ecological governance and economy and its production and industrial system with the goal of high-quality development, and explore the promotion mechanism and model of “full trust and full chain”; To build an appropriate technical system, industrial system, management system and talent support system; To establish a pilot demonstration county for the coordinated development of ecological governance and ecological economy, lead and optimize the coordinated development of regional modern ecological governance and economy. [ABSTRACT FROM AUTHOR]

In order to evaluate the sustainable utilization level of water resources in the nine provinces (autonomous regions) of the Yellow River Basin, improve the status of water resources and realize the sustainable utilization of regional water resources, this paper proposed a comprehensive evaluation index of sustainable utilization of water resources suitable for the nine provinces (autonomous regions) of the Yellow River Basin based on the water footprint model. Spearman correlation analysis and multiple linear regression analysis were used to analyze the driving factors of sustainable water resources utilization in the nine provinces of the Yellow River Basin. The results show that the water resources footprint of the nine provinces (autonomous regions) in the Yellow River Basin from 2010 to 2020 increases first and then decreases in a small amplitude, and the water environment footprint shows a decreasing trend, and the spatial distribution of water resources footprint and water environment footprint is very uneven. In the nine provinces (autonomous regions) of the Yellow River Basin, the level of sustainable utilization of water resources has increased to different degrees. The level of sustainable utilization of water resources in the upstream provinces (autonomous regions) is higher, while the level of sustainable utilization in the middle and downstream provinces (autonomous regions) is lower. The main driving factors of sustainable water resources use are population density, wastewater treatment rate and the proportion of secondary industry, followed by per capita water consumption and fertilizer application intensity. [ABSTRACT FROM AUTHOR]

In order to investigate the dynamic evolution and regional differences of quaternity cooperation of water resources-ecology-city-industry in the Yellow River Basin, the paper adopted the synergy model, kernel density estimation, Dagum gini coefficient and its decomposition to estimate it based on the data of 76 major prefecture-level cities in the Yellow River Basin from 2016 to 2020. The results show that the number of cities in primary, intermediate and good coordination is 30, 33 and 13 respectively. The level of synergy among cities is on the rise, but the absolute difference between cities is expanding and the relative difference is narrowing. except for Hu-Bao-E-Yu urban agglomeration, the absolute difference of the coordination degree of the other six urban agglomerations all shows an expanding trend. The internal differences between the upper and lower reaches of the Yellow River show a downward trend, while the internal differences in the middle reaches show an upward trend. The difference between the upper and middle reaches is the largest, and it shows a further expansion trend, and the difference between the upper and lower reaches is gradually narrowing. The difference in Hu-Bao-E-Yu urban agglomeration is the smallest and the difference in Guanzhong urban agglomeration is the largest. The difference between Guanzhong urban agglomeration and Shandong peninsula urban agglomeration is the smallest, and the difference between Jinzhong urban agglomeration and Shandong peninsula urban agglomeration is the largest. In the future, we should further strengthen factor coordination and regional coordination, give play to the dynamic comparative advantages of various regions, and promote the in-depth implementation of ecological protection and high-quality development strategies according to local conditions in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The interaction between water resources utilization and urban development in urban agglomerations in the Yellow River Basin is the key to the high-quality development of urban agglomerations in the basin. There is an urgent need to explore the coupling and coordination relationship between the two under the sustainable development goals, and provide new ideas for exploring the collaborative mechanism of ecological protection and high-quality development of urban agglomerations in the Yellow River Basin. Taking 72 cities and five urban agglomerations in the Yellow River Basin as examples, this paper established an analysis framework for the coupling of water footprint and city development index in 2010-2019 according to the sustainable development goal proposed by the United Nations and the difference of water resources utilization. The Theil variation index method was used to evaluate the spatial differences in coupling coordination results. The results show that the water footprint is decreasing year by year and the city development index is increasing year by year. The coupling relationship between water footprint and city development index is in an unstable state of “rising-falling-rising”. The difference in the level of urban water resources utilization within the urban agglomeration is the main reason for the difference in the level of development, and there are significant differences in the coordination relationship between water resources utilization and urban development in different urban agglomeration development stages. It suggested to build a trans-regional water resources co-governance system, give full play to the regulatory role of public water resources policies in urban agglomerations, and systematically plan the safety pattern of aquatic environment protection and water resources development and utilization among urban agglomerations. [ABSTRACT FROM AUTHOR]

Increasing carbon productivity is an effective means to achieve carbon peak and carbon neutrality. To coordinate the relationship between economic growth and carbon emissions reduction in the Yellow River Basin, the carbon productivity of 9 provinces（regions） in the Yellow River Basin from 2007 to 2017 is calculated. Based on DEA-Malmquist’s total factor carbon productivity model, the spatiotemporal evolution trajectory and spatial distribution pattern of total factor carbon productivity of 9 provinces（regions） is deduced. The potential improvement space of total factor carbon productivity is scientifically decomposed and the influencing factors of the spatiotemporal evolution of carbon productivity is identified. Based on this, the improvement path of carbon productivity in the Yellow River Basin is condensed. The results show that, 1) in the time dimension, the carbon productivity of 9 provinces（regions） rise steadily with the growth of per capita GDP,an increase of 283.3%, while the total factor carbon productivity remains at around 1.000. 2) In the spatial dimension, the regional heterogeneity of carbon productivity and total factor carbon productivity is relatively large affected by economic development and resource endowments, showing a spatial evolution pattern of “downstream significantly higher than midstream, and midstream slightly higher than upstream”. 3) From the point of influencing factors, the midstream and upstream belong to technical efficiency-driven, the role of technological progress is weak, while the downstream is a co-promotion type of technological progress and technological efficiency. Based on this, this paper proposes strategic suggestions such as innovating institutional mechanisms, promoting low-carbon development models, focusing on lowcarbon technology innovation, accelerating energy structure adjustment, strengthening regional integration cooperation, and improving factor allocation efficiency. [ABSTRACT FROM AUTHOR]

In order to clarify the current situation of digital economy and high-quality development in the Yellow River Basin, explore the coupling coordination and interaction between these two aspects and provide a reference for implementing ecological protection and high-quality development strategies in the Yellow River Basin, the interactive mechanism between digital economy and high-quality development in the Yellow River Basin was analyzed theoretically. Based on the panel data 2011 to 2020, a total of 64 prefecture-level cities in the Yellow River Basin were selected. This paper measured the development level of the digital economy and high-quality development level, empirically examined the coupling coordination relationship between these two dimensions by using coupling coordination degree model and explored the interactive relationship between the two through a PVAR model. The results of the study show that a) the development level of the digital economy in the Yellow River Basin has shown improvement during the research period, however, it remains generally lower with significant regional differences, which forms a circle distribution pattern with Jinan, Zhengzhou, Xi’an, Taiyuan and Hohhot as the core cities, and has the spatial distribution characteristics of high in the east and low in the west. b) The imbalance of high-quality development in the Yellow River Basin is prominent, characterized by the polarization and a distinct circle structure. This has resulted in the formation of a high-value area with Jinan, Zhengzhou, Taiyuan, Xi’an, Lanzhou and other provincial capitals as the core cities. c) The coupling coordination degree between the digital economy and high-quality development in the Yellow River Basin has been increasing annually, but the overall coordination level remains insufficient. The current implementation only achieves the transition from the mild imbalance to near imbalance levels, and the coordination degree also illustrates a pattern of lower reaches＞middle reaches＞upper reaches. d) Both the digital economy and high-quality development in the Yellow River Basin are characterized by self-reliance. High-quality development plays a significant role in promoting the digital economy, while the role of the digital economy in enhancing high-quality development needs to be reinforced. [ABSTRACT FROM AUTHOR]

Accelerating the enhancement of green technology innovation competitiveness is an inevitable requirement for achieving high-quality development in Yellow River Basin. Building upon a systematic evaluation of the green technology innovation competitiveness in Yellow River Basin from 2009 to 2020, using vertically and horizontally opening grade method, an in-depth analysis of its spatiotemporal distribution pattern and dynamic evolution features was further conducted through the utilization of kernel density estimation and spatial Markov chain; additionally, an obstacle degree model was employed to analyze the main factors hindering the improvement of green technology innovation competitiveness in Yellow River Basin. The results show that the overall development of green technology innovation competitiveness in Yellow River Basin exhibits a “W”-shaped trend with four stages, including decline period, ascendancy period, re-decline period, and revitalization period; the absolute differences in green technology innovation competitiveness between regions have diminished, yet a significant gradient development characteristic persists, with competitiveness increasing successively from upstream to downstream. There is a transfer inertia of green technology innovation competitiveness between different levels in Yellow River Basin; regions with low competitiveness face severe grade barriers, while regions with high competitiveness exhibit a club convergence phenomenon; under spatial effects, the probability of grade locking in the transfer of green technology innovation competitiveness decreases, but cross-level transitions remain elusive. The obstacles to green technology innovation competitiveness in Yellow River Basin mainly manifest in the aspects of inadequate green development and outcome transformation; factors such as unit GDP energy consumption, energy consumption structure, energy consumption, openness, and the number of green technological papers published are identified as the primary impediments to the enhancement of green technological innovation competitiveness in Yellow River Basin. [ABSTRACT FROM AUTHOR]

The ecological protection and high-quality development of the Yellow River Basin are significant national strategies. The “Yellow River Protection Law of the People’s Republic of China” provides legal guarantees for comprehensive management at the basin level, high-level protection of the Yellow River, high-quality development, and the building of a “Happy River” benefiting the people. The legislative basis of the “Yellow River Protection Law of the People’s Republic of China” includes legislation at the national, local, and basin levels. It addresses the issues of unclear jurisdiction of Yellow River Basin management institutions and the lack of uniformity and coordination among provincial regulations. The paper proposed recommendations for the prompt building of a legal framework system based on the “Yellow River Protection Law of the People’s Republic of China” and the timely promotion and evaluation of the legislation and its implementation. [ABSTRACT FROM AUTHOR]

Based on the panel data of 58 prefecture level cities along the Yellow River from 2010 to 2019, the water resources green efficiency of these cities was studied and analyzed in this paper by using the Super-SBM model. The results show that the water resources green efficiency of cities along the Yellow River is generally improved. The absolute value of the green efficiency level of water resources in the middle and lower reaches is greater than that in the upstream, and the improving rate of the efficiency level in the upstream is greater than that in the middle and lower reaches. Tobit model was also applied in this paper to analyze the impact of the environmental regulation, industrial structure, economic development level, and the degree of openness on the green water resources efficiency. The results show that openness and economic development level have little impact on water resources green efficiency, while the industrial structure has a negative effect and the environmental regulation has a positive influence. Moreover, there are differences among regions in the Yellow River. Policy suggestions are proposed in this paper that the Yellow River Basin should take measures according to local conditions, strengthen water use supervision of upstream cities and collaborative governance of the whole basin, give full play to the agglomeration effect of water resources utilization, accelerate technology spillover and strengthen weak areas, and pay attention to the role of resources allocation in improving green water use efficiency. [ABSTRACT FROM AUTHOR]

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Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)

Copyright of Yellow River is the property of Editorial Board of Yellow River 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.)