There is independence and integration between water supply and sediment reduction in sediment-laden river reservoirs. How to maintain effective storage capacity and meet water supply requirements for a long time is one of the issues to be solved in the efficient operation of sediment-laden river reservoirs. In this paper, Dongzhuang Reservoir of Jinghe River was taken as the research object. Through the analysis of measured data and mathematical model calculation, the measured hydrological sediment and cross-section erosion and deposition in the lower reaches of Jinghe River and Weihe River were analyzed. The reservoir sediment discharge flow index which was beneficial to reduce the sediment deposition in the lower reaches of Weihe River and maintain the effective reservoir capacity for a long time was studied, and the joint regulation mode of reservoir runoff and sediment was put forward. The outcomes show that during the main flood season for the sediment interception period from July to September, when the inflow is greater than 600 m³/s and the sediment concentration is greater than 300 kg/m³, the Dongzhuang Reservoir is open for sediment discharge. As the normal operation period, during the main flood season from July to September, when the inflow exceeds 300 m³/s, the Dongzhuang Reservoir will open for sediment discharge. The reservoir cannot supply water during the sediment discharge period. The joint regulation of the Dongzhuang Reservoir and the surrounding four storage reservoirs can reduce the deposition of the lower reaches of the Weihe River by 11 million tons per year, increase the guarantee rate of agricultural irrigation from 30% to 50%, and increase the guarantee rate of industrial water supply from 57% to 95%.

In order to provide references for landslide hazard prevention and research on the sensitivity of landslide-causing factors, the Longyangxia-Jishixia section of the upper Yellow River basin was selected as the study area, and 16 factors such as elevation, slope, terrain roughness and lithology were taken as typical landslide hazard factors. The collinearity test was carried out by Spearman correlation coefficient method to select landslide hazard factors with strong correlation. GIS was used to reclassify landslide disaster-causing factors and analyze their weights with geographic detectors. The geographic detection model results were coupled with random forest model to obtain landslide prediction probabilities under different causative factors. ROC curve was used to verify the accuracy of prediction results. The results indicate that a）the explanatory power of the interaction between causative factors is greater than that of individual factors, with the synergistic effect of elevation and other topographic parameters being particularly significant. b）The importance of drainage density, topographic roughness, and profile curvature is nearly zero, suggesting that these features may not have a direct or significant correlation with landslide occurrence. c）There are notable differences in the contribution of causative factors to the prediction results, with the elevation-slope combination being the core driving unit for landslide development in the study area. d）The AUC value ofrandom forest model has achieved 0.93, indicating strong classification performance.

In order to investigate the effect and mechanism of digital economic development on carbon emission in the Yellow River Basin, based on the panel data of 76 prefecture-level cities in the Yellow River Basin from 2011 to 2020, we measured the level of digital economic development, the total amount of carbon emission and the intensity of carbon emission in the Yellow River Basin, and built an individual and time two-way fixed-effects model to conduct empirical analysis, and conducted robustness tests on the results of the lagging effect of digital economic development, changing the sample capacity, and substitution variables. The empirical results are tested for robustness such as lagged effect of digital economic development, changing sample capacity, and substitution of variables, the mechanism of technological progress and industrial structure upgrading, and the heterogeneity of location and heterogeneity of resource endowment of carbon emission reduction effect of digital economic development. The results show that a) the digital economic development has a significant inhibitory effect on carbon emission intensity and total carbon emission in the Yellow River Basin. b) Technological progress and industrial structure upgrading are important mechanisms for digital economic development to promote carbon emission reduction in the Yellow River Basin. c) There is significant location heterogeneity and resources endowment heterogeneity in the inhibitory effect of digital economic development on carbon emission in the Yellow River Basin, and the inhibitory effect on carbon emission in the middle and upstream areas of the Yellow River is significantly better than that in the downstream areas, and the inhibitory effect on carbon emission in the middle and downstream areas is significantly worse. The inhibition effect on the total carbon emissions in the middle and upper reaches of the Yellow River is significantly better than that in the lower reaches, the inhibition effect on the carbon emission intensity in the upper reaches has not yet appeared, and the inhibition effect on the carbon emissions of non-resources cities is significantly greater than that of resources cities. Countermeasures and suggestions are put forward to coordinate the coordinated development of the digital economy in the Yellow River Basin, strengthen the promotion of green and low-carbon technological innovation, accelerate the transformation and upgrading of the industrial structure, implement differentiated digital economy development strategies, and effectively curb carbon emissions.

In order to explore the realistic path of new quality productivity to empower urban economic resilience in the Yellow River Basin, and provide a reference for the implementation of the major national strategy of ecological protection and high-quality development in the Yellow River Basin, based on the panel data of 99 sample cities in the nine provinces (autonomous regions) of the Yellow River Basin from 2011 to 2022, the entropy method was adopted to measure the level of new quality productivity and the urban economic resilience index. Moreover, the two-way fixed effect model and the mediating mechanism model were used to empirically analyze the impact of new quality productivity on the urban economic resilience of the Yellow River Basin and its mechanism of action. The results show that on the whole, the new quality productivity has a significant role in promoting the urban economic resilience of the Yellow River Basin, and its internal mechanism is to promote the upgrading of industrial structure and improve the level of infrastructure construction. The effect of new quality productivity is heterogeneous, especially in the middle reaches of the Yellow River Basin, small-scale and high-intensity environmental regulation cities are stronger. Some policy suggestions are proposed, such as actively cultivating and developing new quality productive forces, promoting the upgrading of industrial structure in the Yellow River Basin and implementing differentiated regional development strategies.

In response to the issue that natural disaster knowledge graphs for single disaster types had a narrow coverage of information, making it difficult to extract knowledge from massive and complex information, this study proposed a method for building a natural disaster knowledge graph for the Yellow River Basin oriented toward loss assessment. The natural disaster knowledge graph consisted of a data resources layer, a knowledge extraction layer (including a schema layer and a data layer), and an application service layer. The schema layer was built by using a top-down approach, centered on ontological models of natural disaster events, fundamental geographic information, and disaster loss assessment. Multi-source heterogeneous data were collected, including natural disaster event data, basic geographic information data, and disaster loss data, and the data layer was built by using a bottom-up approach, enabling knowledge extraction, knowledge fusion, and knowledge storage from these diverse data sources. The application situations show that the knowledge graph supports efficient spatial-temporal relationship queries and rapid identification of regional concurrent disasters. The analysis of 160 major disaster events in the Yellow River Basin from 1981 to 2018 reveals an increasing frequency of disasters over time, with floods being the most common disaster type. Additionally, 37 instances of concurrent disasters are identified. This map breaks through the limitations of the traditional single disaster knowledge system and improves the efficiency of disaster loss assessment.

In order to explore the influencing factors and spatial differences of the green development of agriculture (GDA) in the Yellow River Basin (YRB), and to provide theoretical support and decision-making basis for the high-quality development of agriculture in the YRB, an evaluation index system for the level of GDA was established, which included three dimensions of high efficiency of development, ecological friendliness and resources conservation. Based on the panel data of 68 prefecture-level cities in the YRB from 2011 to 2021, the global entropy method (GEM) was applied to assess the level of GDA in the YRB, and the Moran index was used to analyze the spatial and temporal patterns of its differentiation. On this basis, six indicators were set up in economic, social and natural aspects, including industrial structure, planting structure, industrialization level, urbanization level, topographic relief and annual precipitation, and a multi-scale geographically weighted regression (MGWR) model was used to empirically analyze the influencing factors of the GDA in the YRB and its spatial differences. The results show that a) the level of GDA in the YRB shows an upward trend from 2011 to 2021, but the overall level at the end of the study period is still low, with the level of GDA in the lower reaches significantly higher than that in the middle and upper reaches, the development of efficient dimensions in the upper reaches and lower reaches showing a clear upward trend, and the ecologically friendly and resources-saving dimensions showing a smaller increase in the study period. b) There is an obvious positive spatial correlation between the level of GDA in the YRB, with a relatively large number of H-H agglomeration and L-L agglomeration prefecture-level cities. c) The spatial heterogeneity of the factors influencing the GDA is significant and the intensity of influence is different, among which the spatial differences in the influence of industrial structure, planting structure, industrialization level and topographic relief are small and the spatial difference in the influence of urbanization and annual precipitation is large. Industrial structure, industrialization level and topographic relief have negative effects, while planting structure, urbanization level and annual precipitation have positive effects. The intensity of influence is topographic relief > industrialization level > urbanization level > industrial structure > planting structure > annual precipitation. Some suggestions are put forward, such as changing the concept of agricultural development, strengthening regional cooperation and implementing differentiated agricultural green development strategies.

The Xiaolangdi Reservoir is a key project for controlling water and sediment of the Yellow River. Studying its sediment discharge law and regulation indicators is of great significance for maintaining effective storage capacity in the long term. Based on the analysis of measured data and the practice of water and sediment regulation, 34 sediment discharge processes in the Xiaolangdi Reservoir from 2010 to 2023 were selected, and the reservoir sediment discharge law and its influencing factors were analyzed, in the meantime the regulation indicators which were useful to reducing reservoir silt were proposed. The results show that, during water and sediment regulation in pre-flood season, sediment discharge is mainly caused by flushing of clear water discharged by the Sanmenxia Reservoir. The sediment discharge amount is positively linear correlated with the inflow volume and negatively linear correlated with the storage volume of the Xiaolangdi Reservoir. During water and sediment regulation in flood season, the sediment discharge ratio is negatively correlated with the degree of reservoir damming and the ratio of inflow and outflow flow, which is a power function relationship. The quantitative expressions of sediment discharge amount during water and sediment regulation in pre-flood season and sediment discharge ratio during water and sediment regulation in flood season are established, and the water level of the reservoir can be reduced and then maintained to 215 m and 223 m respectively during water and sediment regulation in pre-flood and flood season are proposed, in which the annual sediment discharge ratio can reach 125%.

Due to its complex terrain and special climate, Qinghai Province is prone to sudden and destructive mountain floods. In order to provide a basis for the monitoring and prevention of mountain floods in the region, taking the Longyangxia-Jishixia section of the upper reaches of the Yellow River in Qinghai Province, where mountain flood disasters were relatively severe, as the study area, 10 influencing factors of mountain flood disasters were initially selected. Based on the data of 115 historical flood disaster points in the study area from 1958 to 2000, four factors with strong correlations were eliminated through Pearson correlation test. The remaining six influencing factors were classified. GIS spatial analysis technology was used to obtain the classified data of the six influencing factors. The entropy index method was adopted to calculate the weights of each factor and identify the main disaster-causing factors. The research results show that elevation, annual precipitation, terrain roughness, NDVI, distance from the river course, and aspect are the disaster-causing factors of mountain floods in the study area (with the weights of 0.571 6, 0.144 8, 0.107 9, 0.094 8, 0.071 9 and 0.009 0 respectively), among which, elevation, annual precipitation and terrain roughness are the main disaster-causing factors. According to the classification of the main disaster-causing factors, 91.30% of the historical mountain flood disasters in the study area occur in the areas with an elevation lower than 3 091 m, 99.14% occur in the areas with an annual precipitation greater than 317 mm, and 98.26% occur in the areas with a terrain roughness less than 1.10.

In order to address climate change and water resources pressures, and to achieve sustainable regional water resources utilization under the carbon neutrality target, the InVEST model was employed to assess carbon storage and water yield in the Qinhe River Basin from 2000 to 2020. The study also used geographical detectors to explore the driving factors and explanatory power, and spatial autocorrelation analysis to examine the spatial relationship between the two. The results show that: a) Water yield in the Qinhe River Basin has shown a fluctuating increasing trend, rising from 1.020 billion m³ in 2000 to 1.167 billion m³ in 2020. This change aligns with the trend in precipitation, with carbon storage and potential evapotranspiration being the main driving factors. b) Carbon storage decreases from 167.566 7 million tons in 2000 to 167.110 5 million tons in 2020, following a trend similar to soil carbon storage, with potential evapotranspiration and water yield being the primary driving factors. c) The global Moran’s index of water yield and carbon storage is -0.2, showing no significant spatial distribution overall. Spatially, there is a pattern of high water yield-low carbon storage and low water yield-high carbon storage.

In order to explore the influence mechanism of new quality productivity to the carbon emissions in the Yellow River Basin, and then provide references for developing new quality productivity and promoting carbon reduction and emission reduction in the Yellow River Basin, this paper took 2013-2022 as the study period and nine provinces in the Yellow River Basin as the measurement unit, and used the entropy method to measure the development level of new quality productivity according to the three indicators of labor force, labor object and labor data. Furthermore, the direct impact of new quality productivity on carbon emissions was tested empirically by using the fixed effect model of individual and time factors, and the robustness test was conducted. The mechanism of influence of new quality productivity to the carbon emissions was tested empirically with the level of industrial structure upgrading and green technology innovation as the intermediary variable, and the level of market integration and the target of economic growth as the moderating variable. The results show that a) the development of new quality productivity has a significant inhibitory effect on carbon emissions in the nine provinces of the Yellow River Basin. b) New quality productivity reduces carbon emissions by improving the level of green technology innovation and industrial structure upgrading. c) Excessive economic growth target will increase carbon emissions and weaken the carbon reduction effect of new quality productivity, while the improvement of market integration level will reduce carbon emissions and enhance the carbon reduction effect of new quality productivity. Suggestions: Further improve the institutional mechanisms for the development of new quality productivity, continue to strengthen support for enterprises' green innovation and further optimize the industrial structure, so as to enhance the carbon reduction and emission reduction effect of new quality productivity.

In order to explore the development level and regional differences of new-quality-productivity in the nine provinces (regions) of the Yellow River Basin and provide a reference for the high-quality-development of new-quality-productivity in the Yellow River Basin, this paper built an evaluation index system of new-quality-productivity development level from the three dimensions of new workers, new labor objects and new labor materials. Based on the panel data from 2013 to 2022, the entropy value method was used to measure the development level of new-quality-productivity in the nine provinces (regions) of the Yellow River Basin, and the nuclear density estimation, σ convergence test and β convergence test, spatial correlation analysis and diagnosis of main obstacle factors were carried out. The results show that a) from 2013 to 2022, the development level of new-quality-productivity in the nine provinces (regions) of the Yellow River Basin shows an increasing trend year by year, among which Qinghai and Gansu have relatively low development level of new-quality-productivity, while Shandong and Shaanxi have relatively high development level of new-quality-productivity. b) There are obvious differences in the development level of new-quality-productivity in the upper, middle and lower reaches of the Yellow River, among which the lower reaches of the Yellow River is always much higher than that in the upper and middle reaches, and the upper reaches of the Yellow River is always lower than that in the middle and lower reaches, but the difference among provinces (regions) is decreasing, the phenomenon of multi-polarization is weakening, and there is a “catch-up effect” and the development of new-quality-productivity in each province (region) will be affected by neighboring provinces (regions). c) From the three dimensions of the development of new-quality-productivity, the new labor object dimension is the “weak side” that needs to be strengthened in the development of new-quality-productivity in the Yellow River Basin. From the perspective of the evaluation indicators of new-quality-productivity, forest coverage rate, R&D personnel full-time equivalent, the number of authorized domestic invention patents, the added value of tertiary industry, traffic network density, the revenue proportion of software and information technology service industry, industrial structure, and environmental protection efforts are the main factors restricting the development of new-quality-productivity in the nine provinces (regions) of the Yellow River Basin. At the end of the paper, some suggestions are put forward, such as attaching importance to personnel training, strengthening environmental protection, encouraging scientific and technological innovation and accelerating industrial upgrading.

As a result of the heavy rainfall, flooding remains in the later stages of the rainfall and may continue to cause harm and impact. In order to accurately predict the depth and duration of urban flooding and waterlogging, the RF-LSTM model was proposed to address the difficulty of simulating floods in the later stages of the heavy rainfall. Based on the SWMM model-simulated flood data in Zhengzhou City, China, the flood depths at three representative flooded points were simulated by using the proposed model, and the flooding process caused by rainfall under different recurrence periods was predicted. The results show that compared to the single LSTM model, the simulation accuracy of the RF-LSTM model has been improved, verifying the applicability of the model in flood simulation. The growth rates of flood duration and the maximum flood depth at flooded points are the highest under the 1-2 a return period, therefore the existing drainage system should be renovated or redesigned.

In order to study the impact of the operation of cascade reservoirs in the upper reaches of the Yellow River on the hydrological regime of the downstream section, the Longyangxia Reservoir to Liujiaxia Reservoir section was taken as the research area, the Mann-Kendall mutation test was used to examine the years of abrupt changes in the average annual flow of the inflow and outflow hydrological stations (Tangnaihai, Guide, Xunhua, and Xiaochuan hydrological stations) from 1952 to 2021, the hydrological change index method-hydrological change range method (IHA-RVA method) was used to quantitatively evaluate the hydrological change degree of the monthly average flow of the inflow and outflow hydrological stations, Pearson correlation analysis method was used to evaluate the correlation between annual runoff and annual sediment discharge at the inflow and outflow hydrological stations. The results show that the flow of hydrological stations entering and leaving the reservoir exhibits periodic changes and overall increases, while the annual average flow of the upper reaches of the Yellow River undergoes a sudden change after the operation of the cascade reservoirs. After the operation of the reservoir, the monthly average flow of hydrological stations located upstream of the reservoir shows moderate to low changes, while the monthly average flow of hydrological stations located downstream of the reservoir shows moderate to high changes. The monthly average flow change is related to the “flood storage and dry discharge” operation mode of the reservoir. The annual sediment discharge of the inflow and outflow hydrological stations shows a decreasing trend, with the Tangnaihai Hydrological Station in the upstream showing the smallest decrease in sediment discharge, and the Xiaochuan Hydrological Station in the downstream showing the largest decrease in sediment discharge. The annual runoff is significantly positively correlated with the annual sediment discharge.

Utilizing panel data from 2010 to 2020 pertaining to energy consumption and socio-economic dynamics within the energy-abundant region of the Yellow River basin, this research employed the Logarithmic Mean Divisia Index (LMDI) model in conjunction with the Tapio decoupling index to examine the decoupling relationship between economic growth and carbon emissions. Additionally, the study assessed the respective contributions of energy structure, energy consumption intensity, economic output, and population size to the variability in carbon emissions and the decoupling index. The findings indicate that: Over the course of the decade, carbon emissions in the energy-rich regions of the Yellow River Basin have experienced a marked upswing, with a fluctuating growth rate that has decreased by 8.83% compared to the initial period. Over the long term, the escalation of economic output levels emerges as the predominant factor contributing to the augmentation of regional carbon emissions. The predominance of coal in the energy mix constitutes the primary driver behind substantial carbon emission levels, although its impact on the incremental increase in carbon emissions is moderated by the entrenched nature of the energy structure, which is resistant to short-term transformation. The energy intensity effect reflects the combined impact of energy efficiency and energy consumption demand, and it is a significant factor in promoting carbon emission increases. Conversely, a contraction in population size exerts a mild inhibitory on the escalation of carbon emissions. The study region undergoes a triphasic transformation in its decoupling status, evolving from an undesirable condition predominantly marked by negative decoupling to a more desirable state predominantly characterized by positive decoupling, culminating in a regression to a less favorable condition of negative decoupling by the terminal period. Ascending energy intensity and economic output emerge as the predominant impediments to the realization of decoupling between regional carbon emissions. Of particular interest is the contrasting influence of population size reduction on carbon emissions and decoupling status, which demands further scholarly consideration. Population size is a critical determinant of a region's ability to achieve decoupling. In light of these findings, the study put forward several recommendations, including optimizing the energy structure, enhancing energy efficiency, fostering technological innovation, promoting sustainable industries, attracting talent, consolidating the population base, undertaking mining area rehabilitation efforts, and strengthening environmental regulations.

In order to solve the coordination problem between agricultural green development and ecological protection in the Yellow River Basin and identify the reasons behind the contradiction between agricultural production and ecological environment protection, the paper took the nine provinces (regions) in the Yellow River Basin as the research object to build an evaluation index system for agricultural green development and ecological protection was constructed. The entropy method was used to measure the agricultural green development index and ecological protection index of each province (region) from 2006 to 2020. The fusion coordination model was used to calculate the coupling coordination between agricultural green development and ecological protection, and the obstacle degree model and grey correlation degree model were used to diagnose and analyze the obstacles and driving factors of coupling coordination development. The results show that during the research period, the coupling coordination degree between agricultural green development and ecological protection in the Yellow River Basin shows an overall upward trend, with a spatial pattern of “upstream>downstream>midstream”. There is still a significant gap between each province (region) and high-quality coordinated development. The coordinated development of agricultural green development and ecological protection is mainly hindered by the dimensions of output efficiency and resources endowment. The internal driving factors that affect the degree of coupling and coordination between agricultural green development and ecological protection in the Yellow River Basin, in descending order of correlation, are the proportion of nature reserves area, the multiple cropping index of arable land, forest coverage, grain yield per unit area, per capita arable land area and fertilizer application intensity. Therefore, it is necessary to strengthen the overall coordination of agricultural industry development planning in the upper, middle, and lower reaches of the Yellow River Basin, accelerate the flow of factors such as technology, capital, and labor between regions, and formulate differentiated agricultural development and ecological civilization construction strategies.

General Secretary Xi Jinping proposed to adhere to the principle of “defining city, land, population and production by water”(referred to as “Four Waters and Four Determinations”), at the symposium on ecological protection and high-quality development in the Yellow River Basin in China. In order to provide theoretical guidance and reference for ecological protection and high-quality development in Gansu Province, the Yellow River Basin, and even the water-scarce areas in the northern China, as well as to implement the “Four Waters and Four Determinations” policy, taking the Yellow River Basin in Gansu Province as a representative of water-scarce areas in northern China, this paper analyzed the characteristics and main water issues of the region, as well as the new situation and strategic position it faced. The current situation of water resources management in the Yellow River Basin in Gansu Province was analyzed, and strategic countermeasures for innovative management of the “Four Waters and Four Determinations” policy in the Yellow River Basin of Gansu Province under the new situation were proposed, including carrying out top-level design, strengthening rigid constraints on water resources, promoting key technology research and development and engineering construction, establishing a sound management system and mechanism, and promoting pilot projects. The core of implementing the “Four Waters and Four Determinations” in water-scarce areas of northern China is to use water resources as a rigid constraint, optimize the development pattern of ecology, energy and food, make the scale of population, urban, irrigation, and industrial development coordinated with water resources conditions, enhance the compatibility of water with city, land, population and production development, and fundamentally promote the harmonious development of human and water resources.

Suspended sediment concentration (SSC) is a crucial water quality monitoring parameter. Taking the Wangtuan section of Qingshui River in Ningxia as the study area, an SSC inversion model suitable for waters with extremely high suspended sediment concentration was developed based on in-situ hyperspectral data and SSC measurements from August 26 to November 5, 2022. Four empirical models were selected for comparison, including single-band model, band difference model, band ratio model and binary linear model. The results indicate that for waters with extremely high suspended sediment concentrations, the single-band model performs poorly, with a coefficient of determination (R²) of less than 0.25. The band difference, band ratio and binary linear models are able to reduce the impact of noise and improve the model's R². Overall, the band difference model performs the best, with an R² greater than 0.40 for the model based on the reflectance difference between the 650-720 nm and 560-700 nm bands. Among which, the R687-R685 model achieves the highest R² value of 0.76.

The Yellow River runoff has unsteady and non-linear characteristics. In order to provide reference for ensuring water security in Henan Province, the non-flood season discharge of Sanmenxia Hydrology Station of the Yellow River was studied. The paper built non-flood season runoff prediction models by combining variational mode decomposition (VMD) with long short term memory (LSTM) and support vector regression (SVR). The sparrow search algorithm (SSA) was used to adjust the model parameters to improve the prediction accuracy. The runoff data was decomposed into multiple eigenmode functions (IMF) by the VMD algorithm, Euclidean distance between components was calculated based on K-Means clustering method and the reciprocal of Euclidean distance was used as the weight of each component. Finally, the results of each component were put into LSTM/SVR for model prediction, and the runoff results were obtained by weighted reconstruction of the predicted values of components. Comparing with before and after weighted VMD-SSA-LSTM and VMD-SSA-SVR model, the results show that the proposed K-Means weighted VMD-SSA-LSTM model predicts the average daily runoff of Sanmenxia Hydrology Station from January 2003 to May 2023 (non-flood season month), with the mean absolute error being 82.54 m³/s, the root-mean-square error being 106.64 m³/s and the fitted coefficient being 0.92, the trend of runoff can be predicted more effectively.

The fundamental solution to the management of the Yellow River lies in sediment control. In order to examine the practical predicament of the legal rules for sediment prevention and control in the Yellow River Basin and put forward suggestions for optimizing the path, this paper conducted a normative analysis of national legislations such as the “Yellow River Protection Law of the People's Republic of China” and the “Law of the People's Republic of China on Prevention and Control of Desertification” as well as the local legislations promulgated by provinces and autonomous regions along the Yellow River which was related to the protection of the Yellow River. It was pointed out that there were issues such as the dispersion of legal rules for sediment prevention and control affecting the realization of legislative quality and efficiency, the principle of “not conflicting” with national legislation restricting the development of local legislative content, and the differences in local rules hindering the realization of fairness in river basins. Based on the existing issues, the optimization paths are proposed: Optimizing the legal rule system for sediment prevention and control in the Yellow River Basin, promoting the effective supply of legislation, advancing regional collaborative legislation, enhancing the scientific nature of legislation, adhering to the concept of harmony between humans and sediment, and strengthening the operability of legal rules

In order to deeply explore the characteristics and driving factors of runoff changes in the Shiyang River basin, and provide a scientific basis for basin management planning and ecological environment building, this study utilized the runoff data from 1956 to 2019 and applied mathematical statistics to analyze the runoff characteristics, in conjunction with meteorological data to assess the impact of climate change on runoff. The findings reveal that a) a decreasing trend in runoff volumes for the Gulang River, Huangyang River, Zamu River and Jinta River, while the runoff of Dajing River and Xiyang River remains relatively stable. b) The basin exhibits periodic changes over 2 to 10 years and 10 to 30 years. c) Apart from the Dongda River and Xida River, which lack significant abrupt change years, other rivers in the basin have notable abrupt changes in runoff between 1970 and 1990. d) The precipitation variation trends in the Shiyang River Basin are not significant, while the temperature has significantly increased. e) Based on the division of change points, the runoff reduction between the baseline and the change period ranges from 13.78% to 37.43%, with human activities identified as the key factor causing runoff reduction and changes.

The construction and management of flood retention areas are crucial for basin flood control safety, economic development and ecological construction. Based on an analysis of the current status and existing issues in the construction and management of flood retention areas in China, this study employed the PDCA cycle improvement strategy (Plan, Do, Check and Act) as its theoretical foundation. It focused on flood control, economic development and ecological construction to address issues such as lagging infrastructure development, inadequate compensation mechanisms and limited ecological construction in flood retention areas. Furthermore, considering the needs for coordinated development of flood retention areas, the study proposed improvement strategies for achieving coordinated flood control, economic and ecological development. Taking Dongdawei as a typical case, the current development status and challenges were analyzed. Based on the established evaluation index system for coordinated flood control, economic and ecological development levels in flood retention areas, the coordinated development level of Dongdawei after PDCA cycle improvements was assessed. Finally, comprehensive measures for ensuring the coordinated development of Dongdawei were proposed from the perspectives of flood control, economy and ecology.

The effects of UWB-Ⅱ flocculant and polycarboxylic acid superplasticizer on the fluidity and rheological properties of the slurry in underwater non-dispersible concrete were studied. The relationship between the fluidity and yield stress of the slurry was analyzed. The results show that a small amount of flocculant can increase the fluidity of slurry and reduce the yield stress and viscosity of slurry. The yield stress and viscosity of slurry are significantly increased with large dosage of flocculant. The addition of water reducing agent can slightly increase the fluidity of the slurry and reduce the yield stress and viscosity of the slurry, but the influence to the yield stress and viscosity of the slurry is weakened when the addition of water reducing agent is larger. When the dosage of flocculant is small, the slurry shows shear thickening, and when the dosage of flocculant is large, the slurry shows shear thinning. The addition of water reducing agent has no significant effect on the slurry shear thinning. There is a linear negative correlation between fluidity and yield stress.

Most of the provinces (autonomous regions) along the Yellow River Basin face challenges such as fragile eco-environment, underdeveloped economies and imbalanced industrial structures, making carbon peaking particularly difficult. In order to explore effective and feasible pathways for carbon peaking and provide references for formulating carbon emission policies in the Yellow River Basin, this study, based on the 14th Five-Year Plan for economic and social development and the long-term goals for 2035 of the nine provinces (autonomous regions), established the three development scenarios of a low-carbon development mode prioritizing green growth and balancing economic progress with ecological protection, a baseline development mode continuing current economic trends, and a high-growth development mode focusing on rapid economic expansion without energy-saving or emission-reduction targets. Using panel data from 2000-2021 on per capita GDP, energy intensity, urbanization rate, population size and industrial structure, a Quantile Regression Neural Network (QRNN) model was applied for empirical analysis and the Gaussian kernel function was adopted for kernel density estimation and the probability prediction of carbon emissions from 2022 to 2035. The results show that a) under all three scenarios, Henan, Inner Mongolia and Qinghai have achieved early carbon peaking (in 2011, 2020 and 2013 respectively), while the other six provinces (autonomous regions) are unlikely to achieve carbon peaking on schedule (among which Shanxi is expected to reach carbon peaking by 2035). b) Qinghai and Shandong are suitable for the benchmark development mode, Inner Mongolia, Shanxi, Sichuan and Shaanxi are suitable for the low-carbon development mode and Henan, Gansu and Ningxia are suitable for the high-growth development mode. It is suggested to formulate differentiated development policies, establish a regional carbon trading market and a linkage mechanism for pollution control in the Yellow River Basin, and promote overall carbon reduction and emission reduction in the Yellow River Basin.

In order to explore the possibility and impact of digital inclusive finance's intervention in agricultural green development in the Yellow River Basin, based on panel data from nine provinces (regions) in the Yellow River Basin from 2013 to 2021, the entropy method was employed to measure the level of agricultural green development. Fixed-effect and mediation-effect models were utilized to investigate the effect and mechanism of digital inclusive finance on agricultural green development. The results indicate that the comprehensive score of agricultural green development level exhibits a pattern of higher scores in Sichuan, Shandong and Henan. Digital inclusive finance and its three sub-dimensions significantly promote agricultural green development. Agricultural technology plays a bridging role between digital inclusive finance and agricultural green development. The development of digital inclusive finance in the Yellow River Basin is conducive to promoting the level of agricultural green development. Therefore, it is necessary to further strengthen the promotion of digital inclusive finance in the Yellow River Basin, fully leverage its role in enhancing agricultural technology, inject new vitality into agricultural green development, and promote ecological protection and high-quality development in the Yellow River Basin

Under the combined influences of global climate change, evolving underlying surface conditions, and anthropogenic activities, the hydrological-sediment regimes of the Yellow River Basin have undergone notable modifications in recent decades. These alterations have consequently driven adaptive transformations in fluvial landscapes, including waterfall systems. As a natural waterfall formed along the mainstem of the Yellow River within the Jin-Shaan Grand Canyon, Hukou Waterfall serves as a critical study target. Leveraging long-term continuous in-situ monitoring data, field investigations, and historical archives, this research systematically investigated the primary landscape characteristics of Hukou Waterfall-encompassing morphology, scale, and coloration, while elucidating its interactive relationships with reach-scale hydrological and sediment dynamics. Furthermore, an analysis of the waterfall's historical evolution from 1956 to 2023 reveals two key findings: a progressive reduction in overall scale since 1956, and a significant increase in the occurrence frequency of clear-water flow events.

Facing the national strategic requirements of improving the ecological environment quality and high-quality development in the Yellow River Basin, in order to promote the conservation and intensive utilization of water resources, this paper constructed 15 evaluation indexes including water resources system, socio-economic system and ecological environment system. The entropy weight method was used to evaluate the water resources conservation and intensive utilization level of 50 cities in the upper and middle reaches of the Yellow River Basin from 2018 to 2021, and identified the main factors affecting the water resources conservation and intensive utilization level of cities in the study area by using obstacle model. The results show that the overall level of conservation and intensive utilization of water resources in the study area is on the rise, from 0.505 in 2018 to 0.553 in 2021. The utilization rate of reclaimed water, the proportion of agricultural water use and the sewage treatment rate are the main obstacle factors affecting the improvement of the level of conservation and intensive utilization of water resources in the study area. Based on this analysis, the countermeasures for the conservation and intensive utilization of water resources were put forward from four aspects of water saving, social and economic development, ecological environment protection and unconventional water resources utilization.

Using remote sensing technology to dynamically monitor the utilization type of the Yellow River embankment-line is helpful to understand the construction process of ecological corridor along the Yellow River. This paper took the middle reaches of the Yellow River as the research object, extracted embankment-line utilization information at intervals of 5 years based on Landsat-5 TM and Landsat-8 OLI images from 1993 to 2023, analyzed the spatial-temporal variation characteristics of embankment-line utilization after the implementation of the national strategy of ecological protection and high-quality development in the Yellow River Basin and preliminarily discussed the effectiveness of ecological protection of the Yellow River corridor. The results show that from 1993 to 2023, the proportion of living embankment-line in the middle reaches of the Yellow River is increased from 2.12% to 16.96%, and the proportion of ecological embankment-line shows a fluctuating upward trend, reaching 39.68% in 2023. The embankment-line utilization of three sections in the middle reaches of the Yellow River is quite different, among which, the ecological embankment-line is mainly used in the Jin-Shaan Valley section, the agricultural embankment-line is mainly used in the Fen-Wei Plain section, and the Sanmenxia-Taohuayu section has changed from an agricultural embankment-line to an ecological embankment-line. From 2018 to 2023, the increase of ecological embankment-line and living embankment-line and the decrease of agricultural embankment-line are the most significant, and the ecological embankment-line of each section shows positive changes.

In order to clarify the groundwater quality evolution characteristics and the sources of groundwater chemical components in the saline irrigation area in western Jilin, the groundwater quality monitoring data from 2012-2014 and 2019-2020 were selected, and mathematical statistics, graphical method, entropy-weighted Bayesian, factor analysis, and Absolute Factor Score-Multiple Linear Regression (APCS-MLR) model were used to carry out the research on groundwater chemical characteristics, water quality evaluation and hydrochemical components traceability analysis in western Jilin irrigation area. The results show that:Fe, F, Mn and tri-nitrogen compounds in the irrigation area and its surrounding areas are seriously exceeded. The water chemistry type is mainly weak alkaline water of the HCO^-₃-Na⁺-Ca²⁺ type, affected by the dissolution and filtration of rocks and evaporation-crystallization, and the long-term irrigation and drainage salt-washing improves salinization of the irrigation area and its surrounding areas. During the research period, the salinization of the irrigation area and its surrounding areas diving Ⅳ,Ⅴ water proportion increased by a total of 5.3 percentage points, Ⅳ,Ⅴ water proportion in the pressurized water decreased by a total of 4.0 percentage points. Dissolved filtration-secondary enrichment effect on groundwater quality is the most significant, so that the concentration of soluble ions in the water, TDS, total hardness and other components of the water increased. Saline and alkaline development of paddy field irrigation area leads to increased regional agricultural activities on the impact of the chemical components of groundwater.

The flood resistance ability of rock dam during the construction is insufficient, and the choice of flood control scheme directly affects the safety risk and cost risk of the project. However, there is relatively little research on the collaborative control of safety risk and cost risk of flood control scheme during the construction of earth-rock dam. At the same time, the evaluation index in multi-objective cooperative control involves many professional fields, and a single expert has different grasp of each evaluation index, so it is difficult to assign an accurate value. Therefore, a number of experts are used to assign values to evaluation indicators in the form of interval numbers, and an expert group opinion negotiation model is built by minimizing the distance of indicator values assigned among experts, and the value of interval numbers assigned by many experts is converted into a point that integrates all expert opinions, so as to establish a safety risk and cost risk evaluation model of flood control scheme during the construction period of earth-rock dam. Taking Qianping Reservoir as an example, a comprehensive evaluation of 7 flood schemes was carried out to guide the construction of Qianping Reservoir, and the collaborative control of safety risk and cost risk was realized.

In the formation and evolution of the Yellow River, long underestimated but extremely important records are the form and location of the river channel, as well as the interdependence between riparian geological bodies. The study shows that the Yellow River channel generally presents three extension styles of long line extension, short bend and zigzag swing. Regional tectonic evolution, faulting tectonism and other internal dynamic geological processes are the main controlling factors for the formation and evolution of the Yellow River channel. The Qinghai-Tibet Plateau, the margin of the Ordos block and the North China Plain are three unique tectono-geomorphic units formed by regional tectonic evolution, and the tectonic factors in the basin have respectively created three different geometric patterns of river channel combinations, namely, inverted Z-shaped, Ω-shaped and wide V-shaped. During the formation and evolution of the three types of river channel, their own unique issues in geology, engineering, development and protection are derived, according to which the development and management suggestions are put forward.

In order to provide theoretical reference and scientific basis for the high-quality development of digital agriculture in the Yellow River Basin, an evaluation index system for the development level of digital agriculture was constructed. Based on the panel data of nine provinces (regions) in the Yellow River Basin from 2015 to 2022, the entropy weight method was used to measure the development level of digital agriculture in the provinces (regions) in the Yellow River Basin. Theil index and Moran index were used to analyze the regional differences and spatial autocorrelation of digital agriculture development in the Yellow River Basin, and the key driving factors of digital agriculture development in the Yellow River basin were diagnosed by geographic detectors. The results show that: a)During the study period, the development level of digital agriculture shows a steady upward trend, but the regional gap is obvious. The development level of digital agriculture in the lower reaches of the Yellow River is much higher than that in the upper and middle reaches of the Yellow River, the lowest in the upper reaches, and the gap between provinces (regions) is large and the gap is increasing. b) The development level of digital agriculture in the Yellow River Basin shows obvious L-L and H-H agglomerations and mainly L-L agglomeration, the spatial agglomeration pattern is relatively stable during the research period. c)The level of scientific and technological innovation, rural infrastructure and the living standard of rural residents are the key driving factors for the development of digital agriculture in the Yellow River Basin, and the influence of each driving factor is significantly greater than that of a single factor. Therefore, the development of digital agriculture should give play to the synergistic effect of all driving factors, especially the synergistic effect of rural infrastructure and other factors. Suggestions: a)Strengthen regional cooperation to ensure the balanced development of digital agriculture in the Yellow River Basin. b)All regions in the basin should consolidate their advantages, make up for weaknesses, and explore new models of personalized development based on resource endowment and digital agriculture development foundation. c)Increase investment in digital agricultural infrastructure and digital agricultural science and technology innovation.

In order to provide a reference for building the ecological compensation mechanism in the Yellow River Basin from the perspective of taxation, especially the horizontal ecological compensation tax mechanism, this paper analyzed the limitations of the existing ecological compensation schemes such as vertical ecological compensation from higher governments to lower governments, intra-provincial (regional) horizontal ecological compensation and inter-provincial (regional) horizontal ecological compensation in the Yellow River Basin, and put forward the idea of “fee to tax” for horizontal ecological compensation in the Yellow River Basin. From the perspective of tax regulation, the advantages of tax compensation in external governance, system design, vertical and horizontal complementarity and rebuilding of central-local relationship of ecological compensation were discussed. In terms of mechanism design, the corresponding analysis was made between water resources tax, environmental protection tax and ecological compensation tax and the key areas of ecological compensation, such as water conservation, cross-province (region) boundary water pollution, soil and water conservation and ecological compensation integrated management. Integrating the design of tax system into the ecological compensation mechanism could give full play to the regulating role of tax revenue, so that the horizontal ecological compensation mechanism can play a key role in the ecological function and economic and social development of the upper, middle and lower reaches of the Yellow River Basin.

Taking 25 central cities in the Yellow River Basin as samples, this paper built an evaluation model of urban flood resilience in the Yellow River Basin based on PSR theoretical framework, calculated the level of flood resilience in the central cities in the Yellow River Basin, and analyzed the spatial-temporal evolution of the three-dimensional index of urban flood system by using Jenks’ natural discontinuity method. The results show that: a) During 2012-2020, the flood resilience of the central cities in the Yellow River Basin maintains an overall growth trend. b) From the perspective of three-dimensional degree of urban flood system, the pressure stimulation index of each urban system shows a fluctuating upward trend, the fluctuation of state sensitivity index is obvious, and the adaptability index of response dimension shows an upward trend year by year. c) The level of urban flood resilience is unevenly distributed in space, and the cities with high flood resilience are sporadically distributed. d) The spatial correlation degree of urban flood resilience mainly presents the three types of spatial correlation of H-H cluster, L-L cluster and H-L cluster.

In order to explore accurate accounting methods for carbon sequestration in soil and water conservation measures and to provide technical support for carbon trading in soil and water conservation projects, this study focused on Ningxia as the research area. By comprehensively utilizing literature, remote sensing technology, artificial intelligence algorithms, and statistical analysis methods, a retrieval method for ecosystem carbon sequestration rates and carbon storage of soil and water conservation measures based on multimodal data and artificial intelligence algorithms was built. The 2022 carbon sequestration status of soil and water conservation measures in Ningxia was quantitatively assessed. The results show that a) among the six artificial intelligence machine learning algorithms, such as Random Forest (RF), Artificial Neural Network (ANN), Support Vector Machine (SVM), Lightweight Gradient Boosting (LGB), Extreme Gradient Boosting (XGB) and Extreme Random Tree Regression (EXT), the Extreme Random Tree Regression algorithm has the highest accuracy in inverting vegetation carbon density and soil organic carbon density in Ningxia. b)The spatial distribution of ecosystem carbon sequestration rates in Ningxia exhibits a pattern of higher values in the south and lower values in the north, with a regional average of 24.53 g/(m²·a). The carbon sequestration rates for soil and water conservation forests, enclosure management, economic forests, artificial grasslands, and terraced fields are 26.65, 27.25, 27.28, 18.80, and 22.68 g/(m²·a), respectively. c) The total carbon sequestration of soil and water conservation measures in Ningxia in 2022 ranges from 2.269 5 to 2.332 6 million tons per year, including an increased carbon sequestration of 2.080 3 million tons per year, soil carbon retention of 0.630 4 million tons per year, and emission reductions of 0.189 2 to 0.252 3 million tons per year. Of the increased carbon sequestration, 80.8% is distributed in vegetative measures, 79.5% of soil carbon retention is distributed in terraced fields and 79.5% of emission reductions are also distributed in terraced fields.

The banks of the Dongzhuang Reservoir area of the Jinghe River are crisscrossed with gullies and have a deep loess cover. After the reservoir area is filled with water, the fluctuation of water level will increase the probability of deformation and instability of new reservoir banks and the revival of ancient landslides. Based on the geological conditions of Dongzhuang Reservoir area, three typical water-related landslides with high risk (Hejia, Jiaojiahe and Fengjia) were selected for the analysis of the causes of landslides and the distribution characteristics of landslides. The coupling mechanism between landslide deformation and water level fluctuation after water storage were analyzed by establishing numerical models. The results show that there are three higher-risk water-related landslides and they are typical loess-bedrock landslides within the 30 loess landslides in the reservoir area. The stability of loess landslides along the bank of the reservoir is affected by the fluctuation of reservoir water level. The gradual decline of reservoir water level and the long-term maintenance of high water level will lead to the reduction of the safety coefficient of the landslides. The faster the rate of decline of reservoir water level, the faster the safety coefficient of the landslides decreases to the minimum value. The possibility of overall large-scale sliding of loess landslides in the reservoir area is low. Conversely, the risk of instability of the leading edge slides is relatively high when the water level drops.

In order to explore the synergistic relationship and evolutionary patterns between ecological resilience and high-quality economic development in the Yellow River Basin, we first conducted a theoretical analysis of their co-evolution. An evaluation index system for ecological resilience was built based on three dimensions of resistance, adaptability and recovery. Similarly, an evaluation index system for high-quality economic development was established based on four dimensions of economic scale, economic efficiency, economic structure and economic sustainability. Using the period from 2012 to 2022 as the study timeframe and the nine provinces (regions) of the Yellow River Basin as the calculation units, the entropy-weight TOPSIS method was employed to measure the annual ecological resilience and high-quality economic development capacity of each province (region). The Haken model was then used to calculate the annual synergy level between ecological resilience and high-quality economic development for each province (region). The results indicate that a) overall ecological resilience in the Yellow River Basin is higher than the capacity for high-quality economic development throughout the study period, showing a steady upward trend. The capacity for high-quality economic development is increased steadily from 2012 to 2019, with slight fluctuations from 2020 to 2022. b) The ecological resilience-high quality economic development composite system of the Yellow River Basin is still at a low-level orderly stage. In the process of their co-evolution, the capacity for high-quality economic development acts as the order parameter, guiding the path and direction of synergistic development and exerting a synergistic enhancement effect on ecological resilience. However, ecological resilience has a slightly inhibitory effect on high-quality economic development. c) The level of synergy between ecological resilience and high-quality economic development in the Yellow River Basin shows a steady upward trend during the study period, with a spatial pattern of higher levels in the east and lower levels in the west. The differences in synergy levels among the provinces (regions) are significant before 2018, and are narrowed after 2018.

Under the influence of climate change and human activities, the runoff of most rivers in Shanxi Province has been severely attenuated. Four typical watersheds in Shanxi province, including Fenhe, Qinhe, Zhanghe and Hutuo rivers, were taken as the research objects. The runoff evolution characteristics were analyzed. The hydrological processes were simulated by using the VIC model, based on which the contributions of climate change and human activities to runoff attenuation were analyzed. The results show that the annual runoff of typical watersheds shows a significant downward trend during 1956-2018, and all of which has an abrupt change around 1980. Compared with the baseline period (1960-1980), the average annual runoff (1981-2000) of Fenhe, Qinhe, Zhanghe and Hutuo rivers is decreased by 57.9%, 49.1%, 57.3% and 37.6%, and the contributions of human activities are 59.9%, 54.3%, 52.3% and 49.0% respectively. During 2001-2018, the attenuation is increased further, and the contribution of human activities increases to 74.8%, 73.1%, 72.4% and 57.7% respectively. Human activities such as surface and underground water extraction, coal mining, soil and water conservation measures and so on are the main driving factors of runoff attenuation.

In order to study the characteristics of river regime change during Diaokou River flow and the influence of human activities to the flow path evolution after the flow stopped, based on the measured data analysis, the paper compared and analyzed the water and sediment conditions, the horizontal and vertical geometry of the Diaokou River and the changes of erosion and deposition in two different stages of the Diaokou River during the river running from 1964 to 1976 and after the river stopped running from 1976 to now. The results show that during Diaokou River flow, the evolution of the flow path is influenced by the factors of water and sediment conditions, channel morphology and tidal current dynamics, and the flow path evolution goes through three stages of the initial stage channel wandering and swinging, the middle stage channel being single and straight, and the final stage channel branching out. After the stop of the flow of the Diaokou River, it is affected by human activities, resulting in significant changes in the terrain of the river, the main channel shrank and the river beaches crisscrossed. In the future, the Diaokou River control should focus on prominent issues such as channel deposition and shrinkage, estuarine and coastal erosion, and human activities. Engineering measures such as dredging channel and optimizing ecological water supplement should be taken, and gradually restore ponds to rivers, reclaimed land to wetland and farmland to beach in an orderly manner.

The Henan section of the Yangtze-to-Huaihe River Diversion Project supplies water from the Xifei River in Anhui Province to Henan Province, of which, the Qingshui River conveyance length is 47.46 km, and the conveyance channel has leakage and groundwater recharge problems. In this study, 15 groundwater level measuring points were set up around the Qingshui River to monitor the variation law of groundwater level after the water diversion experiment of the project in early December 2022. The results show that the rise of groundwater level at the measuring points near the river is earlier than that at the measuring points far away from the river, and the rise of water level is higher than that at the measuring points far away from the river. The change rate of groundwater level at different measuring points is generally a normal distribution of rising first and then falling at the initial stage after water diversion. The maximum change rate of water level at the measuring points close to the river channel is significantly higher than that at the measuring points far from the river channel. Different stratum conditions have a great influence to the groundwater recharge, which is manifested as that when there is a permeable layer with a large permeability coefficient or a thick permeable layer in the stratum, there is a large risk of leakage.