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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.)

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.)

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.)

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.)

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.)

Due to the influence of environment and other factors, there are often abnormal data in dam monitoring data and the detection of abnormal data plays an indispensable role in the normal operation of the dam. However, the accuracy of traditional anomaly detection algorithms for dam monitoring data often fails to meet the requirements. In this paper, an anomaly detection algorithm based on Prophet GMM was proposed. The better fitting performance of Prophet algorithm was used to fit the dam data and the residual sequence was obtained from the fitting data and the actual data. Then, the residual sequence was clustered by GMM algorithm to accurately identify the abnormal value. The test results show that the method proposed in this paper can accurately identify outliers for different types of dam monitoring data. Compared with the traditional detection algorithm, it has significantly improved the detection indicators of precision, recall and accuracy. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the assessment method of urban water resources vulnerability too subjective and not taking into account the finite rationality of natural person and the psychological behavior characteristics of regret avoidance, which resulting in the distortion of the evaluation results, this paper proposed an urban water resources vulnerability assessment method based on OWA operator empowerment and regret theory. The DPSIR model was used to construct 29 evaluation indexes from the following five aspects including driving force, pressure, state, influence and response. OWA operator was used to reorder the decision data, which fully considered the location and size of data, so as to weaken the negative effect of extreme decision data on weight. The difference between the utility value of decision data and the ideal utility value in the regret theory was selected as the basis to evaluate the subjectivity of experts, so as to realize the objectification of the subjective data of decision making and improve the objectivity of the evaluation results. Finally, this paper evaluated the water resources vulnerability of Zhengzhou from 2017 to 2022, and compared the evaluation results with those of AHP and regret theory, OWA operator and fuzzy mathematics. The results show that the evaluation results of urban water resources vulnerability assessment method based on OWA operator empowerment and regret theory are basically consistent with the evaluation results of other methods, all of which are considered as severely vulnerable water resources in Zhengzhou City. However, the evaluation results of this method have less relative error and are more close to the actual situation, which can be better used for the assessment of urban water resources vulnerability. [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 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.)

Aqueduct is a typical space thin-walled structure, which is very sensitive to external temperature changes. Surface insulation measures can effectively improve the temperature stress distribution of the structure and prevent surface cracks. Although the calculation method of surface insulation capacity commonly used in dam construction is of reference significance to aqueduct insulation issue, it cannot be directly applied, so the aqueduct insulation issue needs to be studied separately. Therefore, based on the temperature load of aqueduct structure, this paper put forward a calculation method of aqueduct insulation design based on the temperature and temperature stress analysis of concrete structure. The calculation results show that the stress state of the groove body can be greatly improved by laying 5.0 cm thick polyurethane foam insulation material on the outer surface of the straight wall section and the arc section of 0°-45°. When the temperature rises, the inner wall circumferential and longitudinal tensile stress does not appear. When the temperature drops, the circumferential and longitudinal stress of the outer wall is reduced, and the stress state of the inner and outer walls of the groove body meets the design requirements. The project case study shows that the calculation method of thermal insulation design proposed in this paper can be applied to the thermal insulation design of aqueduct during operation, and then the key parameters of thermal insulation design such as laying range and insulation layer thickness can be determined. [ABSTRACT FROM AUTHOR]

The water quality data of the river basin has dual dependencies in time and space. Based on the fact that most of the existing water quality prediction models are only based on the time dimension and cannot make effective use of the spatial correlation of water quality, a spatiotemporal prediction model based on graph convolution neural network GCN and long short-term memory network LSTM was proposed in this paper. Firstly, the whole watershed was constructed into the topology of station-to-station connection, and the distance along the river between stations was taken as the indicator of connectivity between stations. For each input time, an independent GCN was used to capture the spatial relationship between stations, and then the temporal variation characteristics were captured by LSTM. Finally, the multi-step prediction results were obtained by multi-layer perceptron (MLP). The south source of Qiantang River was selected as the research object, multi step prediction experiments were carried out on three water quality prediction tasks of pH, DO and CODMn at 15 monitoring stations in the basin. The results show that in the three water quality prediction tasks, the average percentage error MAPE of GCN-LSTM model compared with LSTM model is decreased by 15.29%, 11.77% and 9.8% respectively. Compared with some classical time series models, the model proposed in this paper can better capture the spatial relationship of watershed water quality, improve the accuracy of water quality prediction and provide a new method for watershed water environment quality prediction. The connections between monitoring points have differences, and using distance to represent the strength of the connections between monitoring points can make water quality prediction results more accurate. [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 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.)

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 promote the green, low-carbon and high-quality development of agriculture, this paper adopted the super-efficiency SBM model and the entropy method to measure the agricultural carbon emission efficiency and the high-quality development level of agriculture in the Yellow River Basin, and discussed the interaction between the two by using VAR model. The results show that a) the agricultural carbon emission efficiency in the Yellow River Basin is on the rise as a whole. The agricultural carbon emission efficiency of Gansu and Shanxi, Sichuan, Shandong, Henan, Shaanxi and Qinghai, Ningxia and Inner Mongolia is at a lower, medium and higher level respectively. b) The overall level of high-quality agricultural development shows a fluctuating upward trend. Shaanxi, Shanxi, Ningxia and Inner Mongolia, Qinghai and Gansu, Henan, Sichuan and Shandong are at a lower, medium and higher level respectively. c) The improvement of agricultural carbon emission efficiency has a significant effect on the promotion of high-quality agricultural development, while the improvement of high-quality agricultural development has no significant effect on agricultural carbon emission efficiency. Based on the research results, some suggestions were put forward to improve the efficiency of agricultural carbon emissions and promote the high-quality development of agriculture in the Yellow River Basin from the aspects of green and sustainable development. [ABSTRACT FROM AUTHOR]

Clarifying the relationship between hydrological connectivity and flood probability is an important basis for scientific development of flood management measures. In this paper, the hydrologic connectivity index (RIC) of the Kuye River (KYH) catchment was measured by using a modified hydrologic connectivity model based on hydrologic observations and remote sensing data. Advanced spatial analysis tools and statistical tests, including the Theil-Sen Median and Mann-Kendall methods, were employed to analyze the spatial-temporal evolution patterns of RIC. An ordered logistic regression model was then used to examine the influence of RIC on flood probability. The results indicate a significant decline in the yearly average RIC value. Significant reductions in RIC are primarily observed in specific regions. Spatially, RIC concentrations with high-high agglomeration are in the downstream rock mountainous areas of KYH. Notably, low-low aggregation is found in the Ulan Mulun River catchment, particularly in the Kangbashi and Yijinhuoluo. The trend of long-term significance change is dominated by highly significant decrease and significant decrease. Floods in KYH are mainly concentrated in the summer, with their frequency and annual maximum instantaneous streamflow (AMS) showing a significant downward trend. The mutation point of AMS is found to be in 1998 by the Mann-Kendall test in KYH. The RIC significantly contributes to the probability of flood occurrence. Specifically, when all other variables are fixed and unchanged, for each unit increase in the RIC, the probability of a flood becoming a larger magnitude increases by 5.999 times. [ABSTRACT FROM AUTHOR]

Accurately predicting the flood peak discharge increase phenomenon in the Yellow River during the period of water and sediment regulation is not only an urgent need for reservoir dispatch and flood control, but also a new topic for hydraulics and river dynamics research. This paper took the value-added ratio as the dependent variable, the sediment concentration peak, the average rate of increase during the peak period of the sediment concentration, the base flow before the sediment concentration rises, the particle size of suspended sediment at Xiaolangdi Station as the independent variables and the correlation analysis was conducted. As a result, the sediment concentration peak at Xiaolangdi Station and the average rate of increase during the peak period of the sediment concentration are filtered out, as the prediction parameters for the flood peak discharge increase. The study proposes that the flood peak discharge increase phenomenon may occur in the Lower Yellow River when the average increase rate during the peak period of the sediment concentration at Xiaolangdi Station exceeds 22.9 kg/m³h, and the value-added interval can be predicted on the basis of the correlation between the peak sediment concentration and the value-added ratio of flood peak discharge. By tracking the real-time water and sediment conditions at Xiaolangdi Station during the water and sediment regulation in 2023, prediction and forecasting of the flood peak discharge increase phenomenon was carried out, the prediction results are basically consistent with the measured results. [ABSTRACT FROM AUTHOR]

The major national strategy of ecological protection and high-quality development in the Yellow River Basin has been proposed for nearly five years. During this period, the levels of ecological protection, governance, and development in the Yellow River Basin have been rapidly improved. However, the issues of the Yellow River are longstanding and highly complex, far from being resolved overnight. Given the current situation and unresolved challenges in the Yellow River Basin, there is an urgent need to systematically summarize the research and achievements of the past five years, and to provide prospects for future development. This article systematically summarized the research and contributions made by various sectors of society to the Yellow River since the proposal of the major national strategic plan, focusing on scientific research projects, academic papers, academic monographs, and research platforms. Based on in-depth study of the major national strategic ideology and theories such as systems theory, dialectical materialism, and the theory of harmony, and combined with the current situation of the Yellow River Basin and the urgent major issues that need to be addressed, the article presented five prospects for the future development of the Yellow River Basin; multi-disciplinary integration, multi-department collaborative governance, multi-level joint research, multi- platform talent training, multi-approach protection and governance. [ABSTRACT FROM AUTHOR]

As the mother river of China, the Yellow River Basin serves as a crucial ecological domain and economic zone, as well as a vital source of food and energy. It plays an indispensable role in the political, economic, and cultural development of the nation. The ecological protection and high-quality development of the Yellow River Basin have become a major national strategy in China. Yet, the Yellow River is among the most complex and challenging rivers in the world. Throughout China's long history, especially since efforts began to regulate the river, significant achievements have been made in its management and ecological protection. However, many critical issues still need to be addressed. This paper explored the rich history of the Yellow River Basin management and successes, examined the current situation and challenges, and provided recommendations and strategies for achieving long-term stability, sustainability, and high-quality development in the Yellow River Basin, such as constructing the water resources security system of the basin, realizing the restoration and protection of the ecological environment in the key areas in the basin, and improving the engineering system of flood control, ice-flood prevention and water-sediment regulation in the basin, etc. [ABSTRACT FROM AUTHOR]

Land cover change is a direct driver of the carbon cycle in terrestrial ecosystem. In order to evaluate the carbon sequestration ability of the terrestrial ecosystem and explore the response relationship between land cover change and ecosystem carbon storage, based on InVEST model, the paper analyzed and predicted the temporal and spatial variation characteristics of carbon storage in Heihe River Basin. We quantified the influence of land cover change to the ecosystem carbon storage. The result shows as follows: The carbon storages in 1992, 2000, 2010 and 2020 are 764.49 million tons, 769.85 million tons, 773.31 million tons and 769.90 million tons respectively in Heihe River Basin, showing increasing first and then decreasing. The carbon storage has increased 5.41 million tons from 1992 to 2020 and decreased from the southwest to the northeast in space. The main reasons for the increase of carbon storage in the basin are the conversion of bare areas to cropland, sparse vegetation and grassland, the conversion of mosaic vegetation and grassland to forest, which make the increases of vegetation coverage and canopy density. [ABSTRACT FROM AUTHOR]

Based on domestic high-resolution remote sensing images, this paper carried out remote sensing monitoring of human activities in the scope of management and protection of hydraulic engineering works and downstream flood channels. On this basis, it analyzed the interactive relationship between human activities and the security of engineering flood control and proposed the risk assessment methods and models of human activities in hydraulic engineering works. Lastly, an application demonstration was shown by using Hekoucun Reservoir as an example. The monitoring results show that there are less human activities within the scope of the reservoir management and protection, but more human activities within the scope of the downstream Qinhe River management and protection. After the completion and acceptance of the project, human activities within the scope of the reservoir management and protection are decreased, while human activities within the scope of the downstream Qinhe River management and protection are increased. Before and after the flood season, there is no significant change in human activities within the scope of the reservoir management and protection, but in the scope of downstream Qinhe River management and protection, human activities are affected by heavy rainfall, and the occupied area changed. After calculation, the average interference index of the reservoir is 17.6, and that of Qinhe River is 67.22. After the completion and acceptance of the project, the interference index of the reservoir is decreased significantly, while the interference index of Qinhe River is increased slightly. Before and after the flood season, the interference index of human activities in Hekoucun Reservoir remains unchanged, and the interference index of Qinhe River human activity fluctuates to a certain extent. Application demonstration proves that remote sensing technology can effectively monitor the risk sources of human activities in water conservancy projects during operation, and can quantitatively assess the impact of risk sources of human activities on flood control of hydraulic engineering works. [ABSTRACT FROM AUTHOR]

Based on the panel data of each city and prefecture in Qinghai Province from 2007 to 2021, the index system was built. The paper used AHP-entropy weight TOPSIS to measure the high quality development level of Qinghai Province and made a comprehensive analysis with the help of coupling coordination degree, standard deviation ellipse, Dagum Gini coefficient, Kernel function and other models, the overall coordination and spatial-temporal evolution characteristics were comprehensively analyzed, and the obstacle factors were identified. The results show that the average high-quality development index of Qinghai Province from 2007 to 2021 is 0.434 1, which is at a medium level. Among the cities and prefectures, Xining City has the highest high-quality development level, with an average index value of 0.568 4. The high quality development level of Qinghai Province is in a state of fluctuating improvement. The largest contribution from the five dimensions is innovation and development, with an average contribution of 29.43%. The coordination of the high-quality development system in Qinghai Province is at the level of imbalance, with an average coordination index of 0.290 7. The level of high-quality development presents spatial imbalance and regional differences, and the differences mainly come from inter-regional differences, with an average contribution rate of 50.87%. The criterion-level obstacle factor that affects the high-quality development level of Qinghai Province is innovation and development (the average degree of obstacle is 28.75%), and the largest index-level obstacle factor is scientific and technological investment (the average degree of obstacle is 8.95%). [ABSTRACT FROM AUTHOR]

In order to improve the flood disaster prevention and mitigation capacity, taking Henan Province as the study area, the paper built a comprehensive flood disaster bearing capacity evaluation index system covering disaster prevention capacity, disaster resistance capacity, disaster relief capacity and recovery capacity, and assessed the comprehensive flood disaster bearing capacity of Henan Province by using AHP-entropy combination assignment method and comprehensive evaluation index model. The results show that a) the comprehensive flood disaster bearing capacity of Henan Province shows certain regular changes, and the distribution characteristics of comprehensive disaster bearing capacity and disaster relief capacity are basically the same, overall the central region > southwest region > northeast region > east region > southeast region northwest region. South region has the strongest disaster prevention capacity, while the north and central regions have weaker disaster prevention capacity; cities in the southwest-northeast regions have stronger disaster resilience, while cities in the north- west-southeast regions are weaker; recovery capacity basically decreases from northwest to southeast. The area with medium and above comprehensive disaster-bearing capacity accounts for 66.67% of the total area, and the area with lower medium capacity accounts for 33.33% of the total area. b) In terms of the disaster-bearing capacity of each city (pilot area), Xinyang City has the strongest disaster prevention caрасity and the pilot area of Jiyuan has the weakest disaster prevention capacity and disaster relief capacity. Zhengzhou City has the strongest disaster prevention capacity, disaster relief capacity and recovery capacity, and Sanmenxia City has the weakest disaster relief capacity. Zhumadian City has the weakest recovery capacity. The comprehensive disaster bearing capacity of flood disaster in Henan Province is at a medium and low level on the whole, so it is necessary to formulate reasonable strategies to improve the comprehensive disaster bearing capacity of flood disaster. [ABSTRACT FROM AUTHOR]

In 2021, the Yellow River experienced the most serious autumn flood since 1949. The Sanmenxia Reservoir played an important role in the autumn flood control, but there was 1.04 billion cubic meters difference between the inflow and outflow of the flood volume. In order to identify the cause of the above water imbalance, this paper took Tongguan-Sanmenxia reach as the study area, and digital elevation model, land use, soil type, meteorological and hydrological data were used to drive a HEC-HMS distributed hydrological model for flood processes simulation. The results show that the bias of simulated flood peak in 11 floods are all less than 20.0%, the average coefficient of determination of the simulations is 0.725, and the pass rate of the results is 90.9%. The model accurately simulates the water inflow process in the Tongguan-Sanmenxia reach during the autumn flood season in 2021, and the contribution of different tributaries to the total flood amount of the reach is quantified. [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 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]