This paper systematically elaborated on the transformation of Yellow River research from the traditional “Three Yellow Rivers” paradigm (Prototype Yellow River, Model Yellow River, Digital Yellow River) to the new paradigm of “Authentic Yellow River”. Over the past 20 years, the construction of the “Three Yellow Rivers” elevated the scientific research and technological development of the Yellow River to a higher level, playing a crucial role in the governance and protection of the Yellow River. With the breakthrough of artificial intelligence technology, this paper proposed the concept of “Authentic Yellow River”, which took the real Yellow River as the foundation, combined artificial intelligence technology to build dynamic scenarios, achieved instant question-and-answer and precise analysis, and broke through the bottleneck of traditional research paradigms. Through the case of the Beijing-Hangzhou Grand Canal crossing the Yellow River project, it demonstrates the application logic of “Authentic Yellow River” in the governance and protection of the Yellow River, pointing out that the “Authentic Yellow River” provides methodological innovation for Yellow River research through the integration of “artificial intelligence + scenario”.

The source region of the Yellow River (SRYR) is an important water conservation and runoff production area in the Yellow River Basin. In the context of climate change, evaluating the water source conservation and runoff evolution trends in the SRYR is of great practical significance for basin management. This research collected DEM, land use, soil, meteorological, and measured runoff data from the SRYR, and built a high-precision ecological hydrological model (soil and water assessment tool, SWAT) and statistical downscaling model (SDSM) to calculate and analyze the temporal, spatial, and ecosystem scale changes in water conservation capacity and the evolution trend of runoff in the SRYR. The results show that the average water conservation capacity of the SRYR from 1970 to 2024 is 126.4 mm, with a distribution pattern of less in the east and more in the west, and less in the south and north, with significant spatial differences. The contribution rate of grassland to the water conservation of the SRYR is the highest, at 78.2%. The rainfall runoff method shows that the precipitation in the SRYR has increased and decreased by 15%, and the runoff has increased and decreased by 26.82% and 21.15% compared to the baseline level. The simulation results of the ecological hydrological model show that comparing to the current year (2010-2023), the recent (2025-2050) and long-term (2051-2100) changes in runoff in the source area are -2.22% to 6.51% and -0.23% to 10.23% respectively. 

In 2024, the Yellow River Basin faced a severe and complex situation of drought resistance and flood control. The Yellow River Conservancy Commission (YRCC) implemented scientific scheduling, carried out emergency drought-relief regulation of the key reservoir on the main stream of the Yellow River with Xiaolangdi Reservoir at its core, and conducted three flood-season water-sediment regulation processes. This achieved multiple objectives include drought relief, flood control and deposition reduction. Based on the inflow water-sediment data and reservoir operation process, this study analyzed the sediment discharge of the Xiaolangdi Reservoir and the reservoir area’s siltation-erosion changes in 2024. The results are as follows: The annual sediment inflow and outflow volumes are 309.8 million tons and 205.2 million tons respectively, with a sediment discharge ratio of 66.2%. During the three flood seasons, a total of 199.7 million tons of sediment is discharged through water and sediment regulation, accounting for 97.3% of the total sediment discharge for the year. In 2024, the reservoir area is silted up by 116.5 million m³, of which, the main stream and tributaries account for 78.6% and 21.4% of the siltation respectively, with most siltation occurring between elevations of 220 m and 235 m. After the 2024 flood season, the sandbar at the mouth of the Zhenshui River (located 16.39 km from the dam) reaches a height of 5.63 m, resulting in approximately 40.7 million m³ of reservoir capacity in the Zhenshui River being un-utilizable due to the sandbar blockage. It is recommended that in future reservoir operations, measures should be taken to reduce the height of the sandbar at the mouth of the Zhenshui River or slow down its rate of rise, in order to enhance the comprehensive benefits of the reservoir. The scheduling practice in 2024 shows that in order to ensure the water supply for drought resistance downstream, no water and sediment regulation dispatching was carried out before the flood season. However, during the flood season, through scientific optimization, Xiaolangdi Reservoir can still achieve good sediment discharge results.

Water scarcity constitutes a critical constraint on the sustainable development of the Yellow River Basin. To provide a reference for formulating water resources security strategies in the Yellow River basin, this study systematically analyzes the fundamental characteristics, administrative situation and the historical utilization of water resources in the basin, and projects future supply-demand trends. The results indicate that: 1) The Yellow River Basin suffers from a suboptimal natural endowment of water resources, primarily characterized by severe overall shortage, uneven spatiotemporal distribution, high inter-annual and intra-annual variability, prolonged periods of consecutive dry years, and a significant declining trend in natural runoff. 2) With the continuous improvement of water resource management systems, the total water use within the Yellow River water supply zone remained generally stable from 1989 to 2023, yet notable structural changes occurred, evidenced by a substantial decrease in the proportion of agricultural water use. 3) Water use in the basin is constrained by both resource availability and management policies. Although water use efficiency has reached a relatively advanced level domestically, a significant supply-demand gap persists. The intensity of water resources utilization has exceeded the basin's carrying capacity, leading to prominent issues such as insufficient environmental flow in the mainstream and tributaries, river channel sedimentation and shrinkage, and severe groundwater over-exploitation. 4) To support national strategic goals such as ecological conservation and high-quality development within the Yellow River Basin, long-term stability and security, as well as food and energy security, water demand in the basin is projected to continue growing. It is thus imperative to accelerate the construction of inter-basin water transfer projects to secure water security for the basin through external water sources.

In actual application on the Yellow River, the change law of sediment scouring and silting is greatly significant for the sediment and flood control, but the law in short time scale has not received enough attention. In this paper, a roll prediction model for short-term scour and silt was established at Bayangaole and other stations on the Yellow River. Sense the error from the model was obviously smaller than that of the directly borrowed section, it was verified that the sediment content, velocity and water depth were correlated with the short-term changes of the section area, and the model parameters were continuous across the years. Further study and analysis of variables had provided theoretical support for optimizing in production. In addition, this paper deeply discussed the factors that affect the quality of the model, and put forward the technical direction for improving the model.

In order to promote the intensive construction of digital twin water conservancy professional models and enhance the reusability and scheme construction efficiency of the models, it explored the construction ideas and practice-applications of the digital twin water conservancy professional model platform. Based on the cloud-native model, it designed the platform architecture, proposed a component-based abstraction model for water conservancy professional models to achieve unified integration and management of water conservancy professional models, and proposed a cloud-based workflow simulation engine to achieve flexible orchestration and parallel computing of models. The ideas were applied to the construction of the Ministry of Water Resources digital twin model platform. The Ministry of Water Resources digital twin model platform was used to conduct the simulation of the typical flood No.2 in the Beijiang River in 2024 and the review practice of the catastrophic flood happened in July 2023 in the Haihe River Basin. The application results verify that the model platform construction ideas proposed in this paper can achieve standardized centralized management of digital twin water conservancy professional models, simplify the model construction process and enhance the reusability of the models.

The upper reaches of the Yellow River contribute 58% of the water volume and 12% of the sediment to the entire basin. Due to climate change and human activities, there have been significant changes in the upstream water and sediment characteristics. Based on hydrological, meteorological and other observation data, and using methods such as hydrological statistics, double cumulative value correlation curves, and Kendall rank correlation, this article analyzes the evolution law of water and sediment in the upper reaches of the Yellow River and its influencing factors. The results show that, during the period of 1956-2022, due to the increase in precipitation and temperature, the natural runoff of the main stream above Tangnaihai and the Huangshui River Basin increased by 0.005-0.011 billion m3 per year, while the hydrological stations in the Lanzhou to Toudaoguai section of the main stream and the Daxia River and Tao River basins were affected by the decrease in precipitation and changes in underlying surfaces, resulting in a decrease of 0.003-0.047 billion m3per year in natural runoff. The sediment discharge of the main and tributary control stations has shown a decreasing trend over the years. The main stream above Tangnaihai has decreased by 20 000 tons per year, the hydrological station between Lanzhou and Toudaoguai has decreased by 1.58-2.15 million tons per year, and each tributary has decreased by 50 000-470 000 tons per year. The distribution of runoff and sediment in various rivers is uneven throughout the year. The runoff is mainly concentrated from May to October, accounting for 67.8% to 81.4% of the annual total. Sediments are mainly concentrated from June to September, accounting for 63.2% to 91.4% of the annual total. The impact of reservoir and hydropower stations on water and sediment changes is significant. Taking the Longyangxia and Liujiaxia hydropower station as an example, the joint operation of the two reservoirs after 1986 resulted in a 13.6% reduction in annual runoff and a 75.3% reduction in annual sediment discharge at Lanzhou station.

The pollution load of the Jialu River constitutes approximately one-ninth of the total load in the Huai River Basin. To achieve sustainable development in the Jialu River Basin, it is necessary to conduct water quality assessment. This article was based on monthly monitoring data from 9 monitoring sections in the Jialu River Basin from 2011 to 2022. It combined single factor evaluation method and comprehensive pollution index method to evaluate water quality, and used principal component analysis to identify the key indicators influencing water quality in the basin. The results indicated that: Temporally, the pollution level of the basin water body showed an overall decreasing trend. After 2017, the water quality was consistently rated as lightly polluted. Spatially, the pollution severity of river segments decreased in the following order: Zhengzhou Segment > Kaifeng Segment > Zhoukou Segment. The variation in water quality exhibited distinct spatial characteristics. The primary pollution source in the Zhengzhou Segment was industrial wastewater, whereas pollution in the Kaifeng Segment was mainly influenced by the chemical products manufacturing and food processing industries. In the Zhoukou Segment, the pollution originated primarily from urban domestic sewage.

Water scarcity is the core bottleneck restricting socio-economic high-quality development and ecological protection in the Yellow River Basin. To address the water resource challenges in the basin and support decision-making for ecological protection and high-quality development, this study systematically analyzes the multi-dimensional contradictions among water, food, energy, and ecology within the basin, revealing that the current water supply and demand are in a state of “tight balance”, and the gap is expected to continue widening in the future. However, existing measures-such as water conservation, engineering storage and regulation, and regional water transfer-are constrained by the total available water resources and limited coverage, making it difficult to fundamentally alleviate the structural water shortage. Therefore, guided by the water governance principle of “prioritizing water conservation, balancing spatial distribution, adopting systematic approaches and leveraging the roles of both government and market”, water safety guarantee a four-pronged integrated approach of “water saving, water diversion, water allocation and water management” is proposed: a) Deepening water conservation across all sectors to promote a transformative shift from “efficiency enhancement” to “an efficiency-to-effectiveness revolution”. b) Advancing major strategic projects, particularly accelerating the assessment and construction of the western route of the South-to-North Water Diversion Project. c) Incorporating water resources carrying capacity as a binding constraint into territorial spatial planning, industrial layout and urban development frameworks to achieve broader spatial equilibrium. d) Leveraging the synergistic roles of government and market in water governance to optimize water allocation and ensure sustainable utilization.

Based on the recent boundary conditions of the Xiaolangdi Reservoir area, the operation methods and sediment discharge indicators of the Xiaolangdi Reservoir for the recent pre-flood water and sediment regulation had been optimized from the perspectives of  mitigating reservoir siltation, reducing safety risks in downstream river channels, lowering the sandbar at the entrance of the Zhenshui tributary, and increasing the reservoir’s sediment discharge capacity. The water level for sediment discharge operation should be lower than the sedimentation surface of newly deposited sediments in the main stream channel and the elevation of the internal sedimentation surface of the Zhenshui tributary. About 12 hours before the water level of the Xiaolangdi Reservoir was dropped to the sediment discharge water level, the Sanmenxia Reservoir should first release a small flood process with a discharge of approximately 1 400 m³/s to scour and gradually restore the flow capacity of the river channel. After that, the outflow discharge of the Sanmenxia Reservoir should be increased in real time to around 3 000 m³/s. During the sediment discharge period, the Xiaolangdi Reservoir maintained balanced inflow and outflow operation. Through optimization, during the 2025 pre-flood water and sediment regulation, the maximum outflow sediment concentration of the Xiaolangdi Reservoir is reduced to 250 kg/m³; the outflow sediment volume is 168.3 million tons, and the erosion volume in the reservoir area is 107.0 million tons. Both the outflow sediment volume and the erosion volume rank first among all previous water and sediment regulation before the flood season.

The upper reaches of the Yellow River (UPYR) serve as the primary source area for the basin’s runoff. It is essential to quantify the impacts of climate change and anthropogenic activities on the variation patterns of runoff in this region to enhance effective water resource management and support informed decision-making within the Yellow River Basin. In this study, we developed the SWAT hydrological model for the upper reaches of the Yellow River, calibrating and validating it from the base period of 1964 to 1980. We systematically evaluated the effects of climate change and human activities （including water usage, reservoir regulation and land use） on runoff changes from 1981 to 2020. The findings indicate that: a) The basin is currently undergoing a significant increase in both precipitation and temperature, with precipitation levels rising at a rate of 8.11 mm per decade and a corresponding warming rate of 0.35 ℃ per decade. It is important to note that there is spatial heterogeneity in the intensity of the impacts of climate change. In the source area, the contribution rate of climate factors at the Jimai Station is 94%. In contrast, at the Toudaoguai Station, the contribution rate decreases to 21%. b) The influence of human activities on runoff attenuation exhibits spatial gradient characteristics, with variations ranging from 60% to 80% between Lanzhou and Toudaoguai section. Water abstraction and consumption are identified as the principal contributing factors, accounting for approximately 40% to 45% of this phenomenon. The establishment and operation of the reservoir have resulted in a temporal redistribution of runoff, leading to a decrease of 18.11%±6.27% during the flood season and an increase of 12.33%±4.2% during the non-flood season. c) Between 1964 and 2020, the annual runoff in the upstream region of the Yellow River experienced a decline of 148 million cubic meters per decade. An analysis of the factors contributing to runoff reveals that precipitation recharge is the primary determinant, accounting for approximately 80%±11.33%. This is followed by contributions from snow and ice melt, thawing of frozen soil and groundwater recharge. The findings of this study elucidate the nonlinear superposition effects of climate change and anthropogenic activities in the upper reaches of the Yellow River, thereby providing theoretical support for understanding the variations in upstream runoff in the context of climate change.

Facing the trend of frequent extreme weather and the increasing flood disasters, it is particularly important to ensure the accuracy of design flood calculations in the context of flood prevention and control in small watersheds. Seeking design flood calculation methods applicable to small watersheds can effectively improve the level of flood safety. Combining the characteristics of small watershed rainstorm floods in Lanzhou area, the rational formula method, the empirical formula method of small watershed flood peak flow in Gansu Province, the   regional rainstorm empirical formula method and the empirical formula method of flood peak flow were adopted to calculate the once-in-a-century design flood of typical channels, and the selection methods of various parameters were analyzed to evaluate their rationality. The results show that there is a significant correlation pattern between typical gully flood modulus, with the larger the watershed area, the smaller the flood modulus. The flood peak modulus value of the empirical formula method of flood peak flow in small watersheds in Gansu Province is close to the average value, and the result of its flood volume calculation is relatively more reasonable. The rational formula method calculates more realistic results, but requires more parameters. Compared to the two, the former expression is simple and easy to compute. In this method, the relationship of CV=2F^-0.08 and CS=3CV is selected to determine the modal ratio coefficient, and the design flood results obtained have the highest accuracy and the smallest error, which is in line with the characteristics of the Lanzhou area, and can provide a reference for the selection of the calculation method of flood in a small watershed.

The Kubuqi Desert, located within the inner rim of the Yellow River’s Great Bend, straddles the central part of the top-ten Kongduis gully. It is a key national area for soil and water loss control in the Yellow River Basin and a priority zone for the Three-North Shelterbelt Program. It serves as a major source of sediment entering into the Yellow River from the Ordos Plateau. In order to reduce the amount of wind-blown sand entering the river, targeted sand control strategies and key sediment containment technologies must be developed. Building on our previous study of “Principle and Scientific Inquiry into Aeolian Sand Arresting in the Yellow River’s Great Bend Region”, this paper proposed a sand management approach based on “increasing integral resistance along the most stable sand ridge line through engineering measures while reducing drag on the surface of sand-control structures”, guided by the implementation principles of “adapting to local conditions, coordinated layout, using local materials and repurposing waste”. Focusing on challenges such as the technical difficulty of sand control, unpredictable wind directions, high cost of containment projects and poor stability of sand barriers, we identified three key technical problems to be addressed. By resolving issues including the difficulty in controlling bedload transport, high costs of wind-sand containment works, and low efficiency and high expense of emergency erosion control, we developed a series of innovative sand containment technologies such as “Salix + iron sheet composite barriers”, “triangular steep slope sand sliding control”, “FRP prefabricated component composite barriers”, “group-pile netting barriers” and “hose sand barriers”, along with auxiliary techniques like “group-pile netting”. Diverse containment structures were deployed along the planned project alignment, forming a large-scale “Great Wall of Wind-Sand Resistance” and preventing particle deposition on dune crest. By leveraging the wind-flow interference effects of these structures, we optimized deposition volume and distribution patterns on leeward slopes, effectively curbing the expansion and migration of mobile dunes. In addition, we successfully developed the “Salix-bundle emergency windbreak and erosion mitigation technique”, which offered advantages such as low cost, rapid response and ease of operation.

To investigate future trends in hydrometeorological elements in the Yellow River Basin, assess its future water resources status, and provide targeted scientific references for subsequent decision-making and development planning, this study adopted a calibrated and validated WEB-DHM-SG hydrological model driven by the ISIMIP3b meteorological dataset under three different shared socioeconomic pathways （SSP126, SSP370 and SSP585）. Using the historical period 1985-2015 as a baseline, the spatial and temporal evolution trends of hydro-meteorological elements in the basin were projected for the near- （2025-2040）, mid- （2041-2070） and long-term （2071-2100） future. The results indicate that: Temperature, precipitation and runoff in the Yellow River Basin generally increase to varying degrees, though the rates and magnitudes of increase differ. Under global warming, all provinces （regions） in the basin （except Shandong） exhibit warming trends, with Sichuan Province showing the most pronounced rise （3.87-7.57 ℃）. In contrast, Shandong Province experiences a cooling trend （-0.94 to -4.14 ℃）. Both precipitation and runoff fluctuate upward interannually, but the variation in runoff is significantly smaller than that in precipitation. The projected precipitation increases across provinces （regions） ranged from 10.85% to 34.15% in the mid-term and from 18.88% to 54.21% in the long-term. Runoff is projected to continuously decrease in Gansu, Qinghai and Sichuan provinces, with reductions ranging from 5.19% to 59.44%; Meanwhile, the other six provinces （regions） show steady increases in runoff, ranging from 49.02% to 158.11%.

Faced with the problem of insufficient accuracy in traditional water quality parameters prediction methods when dealing with complex nonlinear water quality parameters change, a CNN-Transformer-based parallel prediction model for water quality parameters in the Yellow River was proposed, based on the periodic and nonlinear characteristics of water quality parameters change. This model predicted dissolved oxygen, permanganate index, ammonia nitrogen, and total phosphorus at the Qilipu monitoring section of the Yellow River from 2020 to 2025. The model inputed monitoring data in parallel into the CNN (Convolutional Neural Network) module and the Transformer module, respectively extracting local detail features and global dynamic features, and used a fully connected layer to map the fused features to the prediction results. Comparing the prediction performance of the CNN-Transformer model with RNN (Recurrent Neural Network), CNN, LSTM (Long Short-Term Memory), and Transformer models, the results show that, compared with the other four models, the CNN-Transformer model reduces MSE by 3.93%~10.96%, RMSE by 5.82%~9.33%, MAE by 12.44%~14.48%, and improves R² by 6.56%~26.65%, demonstrating the most outstanding performance.

It is aimed to provide references for the integrated and coordinated advancement of carbon ecological security and high-quality economic development in resource-based cities of the Yellow River Basin. Based on panel data from 37 resource-based cities from 2012 to 2021, the TOPSIS model and the Kernel Density Estimation model were employed to evaluate the carbon ecological security level and analyze its spatio-temporal distribution pattern. The σ and β convergence models were further used to reveal its evolution characteristics. The results show that: a) Carbon ecological security level is increasing in resource-based cities year by year, evolving from a phase of moderate increase to one of rapid growth, and an obvious “catch-up” effect is in resource-based cities of the middle and downstream. b) The differences in carbon security levels are gradually narrowing among resource-based cities in the upstream and downstream, but the differences in the middle reaches are not obvious. c) Carbon ecological security in resource-based cities of the Yellow River Basin shows σ and β convergence trend, which has the characteristic of “downstream resource-based cities being higher than upstream and middle reaches” in terms of convergence reduction and convergence degree. It is suggested that resources-based cities in the Yellow River Basin should break administrative boundary constraints from a holistic perspective, enhance regional correlation, develop differentiated paths, plan collaborative promotion, strengthen catch-up effects, improve convergence levels, so as to achieve the balance of carbon ecological security across the entire basin.

The flow field information of axial flow pumps serves as the basis for operational stability analysis and structural optimization design. Due to the limitations of measurement technology, it is challenging to obtain complete flow field information during operation. Therefore, an improved Physics-Informed Neural Network (PINN) model was proposed for reconstructing the flow field under sparse data conditions. Firstly, the flow field problem was described by analyzing physical constraints, boundary conditions, and flow field constraints. Then, a 3D Convolutional Neural Network (3D CNN) was introduced to solve the flow field problem. Lastly, the Finite Volume Method (FVM) was used for numerical simulation to obtain steady-state velocity and pressure distribution information. After meshing preprocessing, 1% of the flow field data was sampled for model training. To validate the proposed method, a simplified axial flow pump pipeline was used as a test case. The results indicate that the reconstructed flow field using the improved PINN model closely matches the FVM-simulated flow field, with pressure being largely consistent and velocity trends being similar, exhibiting only minor deviations in the flow field regions near the impeller and guide vanes. This demonstrates that the proposed method can accurately predict the three-dimensional flow field under sparse data and complex boundary conditions.

The establishment of traditional hydrological models relies on the simulation and generalized assumptions of real hydrological phenomena, which inherently suffer from parameter uncertainties and difficulties in dynamically characterizing underlying surface changes. Leveraging deep learning techniques based on big data, this study conducted an in-depth investigation into the theory and methodology of deep learning modeling for runoff and sediment prediction, utilizing the vast, diverse, long-term sequential, and dynamically correlated spatiotemporal attributes of Yellow River water and sediment data. Selecting the main sediment producting tributaries of the Yellow River, the Kuye River and Wuding River, collected multi-source data on hydrology, vegetation, and other factors, performed feature extraction, identified the time of abrupt changes in water and sediment  elements using the Mann-Kendall test, quantified driving forces through multiple regression linear analysis, and constructed runoff and sediment intelligent prediction models for typical basins in the main sediment-producing regions of the Yellow River based on Deep Belief Network (DBN), Long Short Term Memory (LSTM), and Extreme Gradient Boosting  (XGBoost) models. The results show that the annual runoff and sediment discharge of the two watersheds show a decreasing trend after the abrupt change year. The contribution value of non rainfall factors to annual sediment discharge is negative, and they play a role in reducing sediment. The LSTM model and DBN model can basically reflect the process of flood fluctuations, and the performance of LSTM in simulating peak values is slightly better than that of DBN model. The average relative percentage errors of the XGBoost model on the test datasets of Baijiachuan Station and Wenjiachuan Station are 44.0% and 13.4%, respectively.

Land-use change leads to variations in terrestrial ecosystem carbon storage. Simulating land-use patterns and carbon storage under different scenarios in the Yellow River Basin (Henan section) is of great significance for promoting the high-quality development strategy of the Yellow River Basin and advancing the dual-carbon goals. Based on the FLUS and InVEST models, land-use patterns and carbon storage in the Yellow River Basin (Henan section) in 2030 were simulated under the natural development scenario and the high-quality development scenario. Furthermore, the standard deviation ellipse was employed to investigate the spatiotemporal evolution of carbon storage and the migration trajectory of its center of gravity.The results indicate that the dominant land-use types in the Yellow River Basin (Henan section) are cultivated land, forest land. The carbon storage 1980, 1990, 2000, 2010 and 2020 were 1.255 billion tons, 1.254 billion tons, 1.253 billion tons, 1.214 billion tons, and 1.193 billion tons respectively. By 2030, carbon storage under the natural development scenario and the high-quality development scenario is projected to be 1.180 and 1.184 billion tons, respectively. Over the past 40 years and under both 2030 scenarios, the center of gravity of carbon storage has generally migrated from the northeast toward the southwest, while remaining consistently located within Luoyang city.

To study the water hammer during pump trip in long-distance pressurized water transmission projects, the characteristic line method was used to numerically simulate actual pressurized water transmission projects. This study analyzed and studied the impact of the absence of water hammer protection measures, the installation of check valve protection measures, and control strategies on water hammer. Based on this, a water hammer protection scheme combining air valve and check valve was proposed, and sensitivity analysis was conducted on the parameters of the air valve. The results indicate that when without water hammer protection measures, pump trip in accidents will result in continuous reversal of the pump and severe negative pressure along the water pipeline; When using two-stage closing check valve protection measures, optimizing the valve closure strategy can improve the maximum pressure of the pipeline and the reversal of the water pump, but the improvement effect on the negative pressure inside the pipeline is not significant; The joint installation of fast forward and slow exhaust air valves can effectively improve the serious negative pressure problem. The diameter of the air valve has a significant impact on the water hammer protection effect, and there is an optimal solution.

To investigate the spatiotemporal variation patterns of extreme precipitation in the Haihe River Basin, daily precipitation data from 37 meteorological stations during 1956-2022 were used to select 6 extreme precipitation indicators. Mann-Kendall non-parameter test, inverse distance weighted interpolation and Morlet wavelet analysis were employed to examine the spatiotemporal variation patterns of extreme precipitation in the Haihe River Basin. The results showed  that in the past 67 years, the extreme precipitation indexes in Haihe River Basin showed a decreasing trend, but enter the 21st century, all indexes showed an increasing trend of different degrees, especially in 2021. The extreme precipitation frequency and extreme precipitation intensity index decreased to northwest and southeast in the north central and northeast plain areas, and the extreme precipitation indexes in mountainous and hilly areas are generally higher than that in plain areas. The number of heavy rain days, the maximum precipitation of 5 days and the extremely extreme precipitation showed more or less mutations in 1964, and the maximum precipitation of 1 day and the maximum continuous precipitation days showed more or less mutations in 1968 and 1978. The periodicity of different extreme precipitation index series is different. The first main cycle is within 41-51 years. Under the scale of the first main cycle, the average change period of the number of heavy rain days, extreme precipitation and maximum continuous precipitation days is 31 years, and the average change period of the 1-day maximum precipitation, the 5-day maximum precipitation and extremely extreme precipitation is 20-36 years.

In order to promote the coordinated development of green finance and low-carbon economy in the Yellow River Basin, promote ecological civilization construction in the Yellow River Basin, this paper uses panel data from 35 cities in the Yellow River Basin from 2013 to 2022, measures their coupling coordination degree model, and combines spatial autocorrelation model and spatial Durbin model to explore their spatial agglomeration characteristics and influencing factors. The findings indicate that: a) The coupling coordination level between green finance and the low-carbon economy in the Yellow River Basin has shown a consistent upward trend, with values in the middle and lower reaches substantially exceeding those in the upper reach. b) The global Moran's index was significantly positive during the study period, showing an overall fluctuating downward trend; In local spatial agglomeration, H-H agglomeration is mainly distributed in the middle and downstream areas, while L-L agglomeration is mainly distributed in the upstream areas. c) The degree of government support, green technology innovation, economic development level, and degree of openness to the outside world have a significant positive and direct effect on the coupling and coordinated development of the two.Based on this, it is suggested that the Yellow River Basin should promote regional balanced development, strengthen support for upstream areas, optimize industrial structure, reduce dependence on high polluting industries, strengthen government support, and drive technological innovation, in order to achieve coordinated development of ecological benefits and economic growth.

The operation of the Xiaolangdi Reservoir alters the flow and sediment conditions in the Lower Yellow River （LYR）. Coupled with the construction of river defense projects, this leads to significant changes in the planform morphology of the wandering reach in the lower reaches. Based on long-sequence Landsat satellite remote sensing images and measured runoff and sediment data from 1986 to 2023, this study calculated and analyzed the changing trends in the wandering degree, sinuosity and braiding intensity of the wandering reach after the reservoir’s operation, as well as the spatio-temporal patterns of the upward shift and downward retrogression of the river regime at river training works. Furthermore, the physical mechanisms underlying these evolution laws of the river regime were analyzed. The results indicate that: At the reach scale, the wandering degree shows a significant downward trend under the combined effects of long-term low-flow processes and strong artificial constraints, while sinuosity shows an upward trend and braiding intensity tends to stabilize. The primary causes for the decline in wandering degree are the reduced rate of flood peak rise, the enhanced longitudinal stability of the channel, and the construction of river defense projects. On the other hand, after the operation of the Xiaolangdi Reservoir, approximately 74% of the river training works exhibit a general trend of downward retrogression in space. Temporally, the annual mean distance of the upward shift and downward retrogression at these works correlates with the river scour efficiency and the difference in beach-bed elevation in the reach. Specifically, higher river scour efficiency and smaller beach-bed elevation differences tend to result in an easier occurrence of the upward shift of the river regime. 

The aim of this study is to reveal the evolutionary patterns of extreme precipitation in the Yellow River Water Receiving Area of Henan Province, to scientifically understand the risks of flood and drought disasters at the regional scale, and to provide a scientific basis for water resources allocation and for disaster prevention and mitigation in the water receiving area. Based on daily precipitation data from 20 meteorological stations during 1973-2022, eight extreme precipitation indices were calculated using the RClimDex model, and analyzed via the Mann-Kendall trend test, Morlet wavelet analysis, and Range of Variability Approach (RVA). This study systematically analyzed the spatio-temporal evolution characteristics, periodic variation patterns, and the degree of variability of extreme precipitation indices in the region. The results show that: Seven precipitation indices, including annual precipitation, increase from northwest to southeast, while the consecutive dry days index shows an opposite distribution, indicating a higher drought risk in the northwestern region. All indices exhibit no significant linear trends and are mainly characterized by strong interannual fluctuations, with extreme value indices fluctuating drastically and the suddenness of extreme precipitation becoming highly significant after the abrupt change in 2010. A long-period evolution characteristic of 15-17 years exists during the study period. The region is currently in a relatively wet season, suggesting relatively high precipitation and a frequent trend of extreme events in the near future. The variation degrees of extreme value indices are significantly higher than those of total amount indices. Among them, the maximum 1-day precipitation is the only index reaching a moderate degree of variation, indicating that regional climate risks mainly stem from the enhanced suddenness of single-day extreme heavy precipitation.

The Ten Tributaries are ten adjacent first-order tributaries of the Upper Yellow River. Spatial differentiation of ecological and environmental elements in this region is highly pronounced. Conducting spatial zoning for ecological restoration is an essential foundational step toward improving the systematic approach and overall effectiveness of ecological restoration efforts in the Ten Tributaries. Drawing upon multiple field investigations and analyses, combined with a comprehensive review and analysis of existing literature, this paper identified the prominent challenges in the current ecological governance of the Ten Tributaries and proposed the main scientific issues and key technologies that urgently need to be studied for the spatial zoning of ecological restoration in the Ten Tributaries. The investigation reveals that: Although the ecological environment of the Ten Tributaries has improved to some extent after years of management, there are still problems. These include unsystematic governance, a singular approach to restoration measures, a lack of application of new technologies, and the absence of a systematic spatial zoning framework for ecological restoration. The critical scientific questions that urgently require resolution include the spatiotemporal distribution patterns and mechanisms of wind-water composite erosion; the spatial heterogeneity characteristics of ecological functions; the multi-phase composite flood and sediment transport processes and the spatial distribution characteristics of high-sediment flood sources; the identification of spatial suitability for ecological restoration through forestry and grassland vegetation; and the spatial zoning methods for ecological restoration of the Ten Tributaries based on multi-objective synergy. Consequently, this study proceeds from the prominent characteristic of marked spatial variability in the ecological elements of the Ten Tributaries. Guided by the technical principle of multi-scale and multi-dimensional coupling between landscape patterns and ecological processes, this approach aims to identify priority areas for ecological protection and restoration in the Ten Tributaries. By implementing measures based on ecological suitability, the goal is to advance a systematic, holistic and comprehensive spatial ecological restoration of the Ten Tributaries. Such efforts are of great significance for establishing a robust ecological security barrier in the Yellow River Basin.

To provide a decision-making basis and reference for the green and low-carbon development of the Yellow River Basin and the implementation of the “dual carbon” strategy, this study adopted the super-efficiency SBM model to measure the carbon emission efficiency of 50 cities in the Yellow River Basin from 2013 to 2021. The Malmquist index model was used to conduct a static and dynamic comprehensive evaluation of carbon emission efficiency. The spatial autocorrelation of urban carbon emission efficiency was analyzed by calculating the Moran’s I and plotting the Moran scatter plot, and a spatial Durbin model was constructed to explore the influencing factors of urban carbon emission efficiency. The results show that: a) The urban carbon emission efficiency in the Yellow River Basin is generally low. Although it showed an overall upward trend during the study period, the long-formed development model relying on high-carbon energy is difficult to change completely in the short term, which restricts the substantial improvement of carbon emission efficiency. b) There are significant differences in carbon emission efficiency among cities in the Yellow River Basin. Approximately a quarter of the cities are in an effective state of carbon emission, while most cities are in an ineffective state, showing spatial characteristics of high-high agglomeration and low-low agglomeration. c) Economic development and technological innovation have a significant role in promoting and driving the improvement of urban carbon emission efficiency in the Yellow River Basin, foreign trade and government intervention have a certain promoting effect, urbanization and industrial structure have a certain negative impact on the improvement of urban carbon emission efficiency. Suggestions: Develop and utilize new energy sources, optimize the industrial structure, strengthen scientific and technological innovation and the transformation and application of its achievements, implement targeted policies in light of local conditions, and build new green and low-carbon cities.

To explore the coupling and coordination status and mutual response relationship between digital economy and green development in the Yellow River Basin, and to provide references for ecological protection and green high-quality development in the basin, based on the analysis of the coupling mechanism between digital economy and green development, this paper uses panel data of 64 prefecture-level cities (prefectures) in the Yellow River Basin from 2013 to 2022. The entropy weight method is adopted to measure the development level of digital economy, the Super-efficiency-SBM model is used to measure the efficiency of green development, and the coupling coordination degree model is employed to measure the coupling and coordination status between digital economy and green development. The PVAR model is used to empirically analyze the mutual response relationship between digital economy and green development. The research shows that: a)The development level of digital economy in the Yellow River Basin has steadily increased, but it is still at a relatively low level at the end of the study period. Spatially, it shows the highest level in the downstream region, followed by the middle reaches, and the lowest in the upper reaches, with a circular structure centered on relatively high provincial capital cities. b)The efficiency of green development in the Yellow River Basin has also steadily increased during the study period, but the imbalance in green development among prefecture-level cities is prominent. c) The coupling and coordination level between digital economy and green development in the Yellow River Basin has been increasing year by year, rising from a barely coordinated level at the beginning of the study period to a primary coordinated level at the end. Spatially, the downstream region has the highest level, followed by the upper reaches. d)Both digital economy and green development have strong self-dependency, and a two-way high-quality interaction relationship has not yet been formed between them. The promoting effect of digital economy on green development is relatively strong, but the promoting effect of green development on digital economy is relatively weak. Suggestions: Accelerate the construction of new digital infrastructure in the Yellow River Basin to further improve the development level of digital economy; formulate plans and strengthen cross-regional cooperation to quickly narrow the regional gap in green development; promote the further improvement of the coupling and coordination level between digital economy and green development through reasonable industrial layout and technological innovation.

In order to build green and efficient agriculture and realize the sustainable utilization of agricultural water resources, based on the construction of the index system of green efficiency and influencing factors of agricultural water resources in Henan Province, the spatial and temporal evolution characteristics were analyzed by using SBM model. Using the Tobit model, the influencing factors were discussed. The results showed that: a) The green efficiency of agricultural water resources in Henan Province showed a fluctuating increasing trend as a whole, with the largest increase from 2019 to 2020 and the largest decrease from 2014 to 2015. There are significant differences in the green efficiency of agricultural water resources among cities in Henan Province. The green efficiency of agricultural water resources in 9 cities such as Pingdingshan, 4 cities such as Hebi and 5 cities such as Sanmenxia is low, medium and high respectively. b) The scale efficiency and pure technical efficiency of agricultural water resources in Henan Province are stable. The average scale efficiency of each city for years is less than 1, among which Xinxiang is the highest and Hebi is the lowest. The average pure technical efficiency of 9 cities for years such as Nanyang is greater than 1, and that of 9 cities such as Pingdingshan is less than 1. c) The green efficiency of agricultural water resources in central Henan shows a fluctuation trend from high (2013) to low (2017) to high (2022), and the green efficiency of agricultural water resources in eastern, western, northern and southern Henan remains at a high level. The center of gravity of the green efficiency of agricultural water resources in Henan Province is distributed in Zhengzhou, and the overall trend is to migrate from southwest to the northeast. d) Economic development level, agricultural economy, urbanization development level, water-saving facilities, resource endowment and other influencing factors are conducive to the improvement of green efficiency of agricultural water resources in Henan Province, while such as the structure of crop planting and water supply structure are not conducive to improvement.

To accelerate the cultivation of new quality productive forces and provide reference for implementing the major national strategies of ecological protection and high-quality development in the Yellow River Basin, based on the connotation of new quality productive forces, this paper constructed an “technology-factor-industry” analytical framework to explore the inherent logic of how new quality productive forces empower ecological protection and high-quality development in the Yellow River Basin. Specifically, revolutionary technological breakthroughs provided new driving forces, innovative allocation of production factors strengthened data empowerment, and in-depth transformation and upgrading of industries provided carrier support. It pointed out that empowering ecological protection and high-quality development in the Yellow River Basin with new quality productive forces still faced challenges such as insufficient innovation drive, the need to improve the level of factor integration and allocation, and lagging industrial transformation and upgrading. Given the reality of the Yellow River Basin, this paper proposes an enhancement path for empowering ecological protection and high-quality development in the Yellow River Basin with new quality productive forces: improving the science and technology innovation system, achieving high-level self-reliance and self-strengthening in science and technology, deepening factor market allocation, promoting the flow of data factors, accelerating the transformation and upgrading of industrial structure, and enhancing the competitive advantage of the modern industrial system.

Based on the development of method, theory and the legislation in the process of Yellow River management, this paper proposed the philosophical concept of “Method, Theory, Legislation and Daoism” in Yellow River management, analyzed the basic principles and rules of dialectical materialism reflected in it, and demonstrated its philosophical scientificity, rationality and the dialectical relationship between them. Through reviewing the ancient river management ideas, analyzing the People’s Yellow River management at different stages, and comprehending the profound essence of the new era’s water management ideas in Yellow River management, we aimed to explore the concepts of “Method, Theory, Legislation and Daoism” in it, exploring its dialectical development in the practice of Yellow River control in various historical periods. Analyzing that the Yellow River control is a comprehensive process of the method progress, the ideological development, and the legislation improvement, which is a historical practice of the coordinated development of “Method, Theory, Legislation and Daoism”. The protection and management of the Yellow River should innovate the method of river management, study the theory of water management, clarify the legislation of watershed harnessing and follow the Daoism of harmonious coexistence between humans and water.

Rapid closure of breached dikes is crucial for minimizing disaster losses. To address the difficulties in coordinating multiple objectives for material dispatch during emergency breach closure, as well as the problem of differentiated material demands caused by its multi-stage nature, a multi-objective collaborative model for breach closure material dispatch was developed. This model incorporated time satisfaction, psychological risk perception, and vehicle transportation costs. To solve the model efficiently, introducing Simulated Binary Crossover (SBX), polynomial mutation, and dynamic neighborhood search to improve the base NSGA-Ⅱ algorithm. A case study of the Tuanzhou Township Levee Breach closure in Dongting Lake was conducted for validation. Results show that: The enhanced NSGA-Ⅱ algorithm effectively generates a better-distributed Pareto solution set. The proposed model can dynamically adapt to the needs of each closure stage. The selected optimal solution achieves a balance among time, psychological risk, and cost, providing a scientific basis for emergency response dispatch decision-making.

This study prepared glass-ceramics using Yellow River sediment as the primary raw material. By integrating performance tests such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), fourier transform infrared spectroscopy (FTIR) and hardness testing, the effects of different nucleation/crystallization regimes on the microscopic structure and macroscopic properties of glass-ceramics were investigated. The results demonstrate that: The main crystalline phase precipitated in the glass-ceramics made from Yellow River sediment is ferrite silicate. Crystallization begins inside the particles and gradually extends to the exterior. The primary influencing factors for the flexural strength, Vickers hardness, bulk density, acid resistance, alkali resistance and thermal properties of the glass-ceramics are crystallization time, nucleation time, crystallization time, nucleation temperature, crystallization temperature and nucleation time, respectively. The optimal nucleation and crystallization regime is nucleation temperature 750 ℃ (60 min) and crystallization temperature 910 ℃ (180 min). The glass-ceramics made from Yellow River sediment have a flexural strength of 79.07 MPa, Young’s modulus of 51.59 GPa, Vickers hardness of 6.37 GPa and fracture toughness of 1.39 MPa·m^1/2. These properties meet the performance requirements specified in the industry standard “Glass-Ceramics for Architectural Decoration”. Under nucleation temperature 720 ℃ (60 min) and crystallization temperature 880 ℃ (240 min), the dielectric constant and dielectric loss of the microcrystalline glass made from Yellow River sediment are 7.43 and 0.88, respectively. These values meet the performance requirements specified in the national standard “Structural Ceramic Materials for Electronic Components”.

As a crucial engineering measure safeguarding the lives and property of hundreds of millions of people, the modernized operation and management of the Lower Yellow River levees are pivotal for ensuring the safety and stability of the Yellow River and supporting the high-quality development of the river basin. Confronted with challenges such as frequent  extreme climate events, the prominent perched river characteristics, and the efficacy bottlenecks of traditional management models, there is an urgent need to transform the management paradigm towards intelligence, resilience, and collaboration. This paper systematically analyzed the bottleneck issues in the current management of Yellow River levees, including information sensing, risk prediction, emergency coordination, engineering resilience, and institutional mechanisms. It  proposed a modern management framework centered on comprehensive intelligent perception-digital twin empowerment-resilient engineering foundations-intelligent collaborative governance. Key measures were elaborated, including constructing an integrated “space-air-ground-river-engineering” monitoring network, building a high-fidelity digital twin levee decision-making hub, integrating ecological and engineering resilience enhancement technologies, and establishing a flattened inter-departmental emergency command system. A phased implementation path is also presented. The research aims to provide a systemic solution for building a safer, smarter, and more resilient “digital twin levee”, contributing to the long-term safety and stability of the Yellow River.

To provide decision-making references for ecological protection and high-quality development of the Yellow River Basin from an agricultural perspective, a carbon emission accounting list for agriculture in the Henan section of the Yellow River Basin was constructed based on carbon sources from crop planting and livestock breeding. The agricultural carbon emissions from 2012 to 2021 were calculated, and the spatio-temporal evolution characteristics of agricultural carbon emissions were analyzed using the statistical comprehensive analysis method and the natural break point method. The results show that: a) From 2012 to 2021, the total agricultural carbon emissions in the Henan section of the Yellow River Basin showed an overall downward trend. The period from 2012 to 2015 was a stage of “minor fluctuations and relative stability”, and the period from 2016 to 2021 was a stage of “obvious changes and fluctuating decline”. b) In the agricultural carbon emissions of the Henan section of the Yellow River Basin, the carbon emissions from agricultural materials accounted for a relatively large proportion, with an average annual proportion of 54.15%. Among them, fertilizers were the main source of carbon emissions from agricultural materials, with an average annual proportion of 50.17%. In the spatial dimension, Jiyuan, Hebi, Jiaozuo, and Sanmenxia had less cultivated land area and lower agricultural carbon emissions, Zhengzhou, Luoyang, and Puyang had significant achievements in agricultural carbon reduction, Kaifeng, Xinxiang, and Anyang still had relatively large agricultural carbon emissions.Based on this, the implementation path of agricultural carbon reduction was proposed, including compiling a carbon source list, establishing unified standards, conducting surveys and monitoring, strengthening surface source control, innovating circular utilization, and implementing unified management in Henan Section of the Yellow River Basin.

In order to clarify the changes in the water use structure in Henan Province and identify the evolution characteristics of future water demand processes, this study conducted an in-depth analysis of total water consumption and structural changes based on Henan’s water use statistics from 2003 to 2023. It explored the relationship between key socioeconomic indicators and water use processes to elucidate the patterns of changes in water consumption in Henan. Linear trend analysis and per capita social water demand quota methods were employed to forecast the future scale of water demand. The results reveal that a) from 2003 to 2023, the total water resources in Henan Province exhibits a non-significant declining trend, while total water consumption shows a fluctuating upward trend. The proportion of water used in agriculture and industry has generally shown a decreasing trend, while the proportion of water used in daily life and ecology has shown an increasing trend. b) The linear trend method predicts a total water demand of 21.475 billion m³ for Henan in 2025 and 19.962 billion m³ in 2035. c) Based on the per capita social water demand quota method, it is predicted that the total water demand in Henan Province will be 22.029 billion m³ in 2025 and 20.421 billion m³ in 2035. The close agreement between these two forecasting methods enhances the reliability of the predictions, providing valuable data references for future water resources management in Henan Province.

In order to accurately assess the water resources carrying capacity in Zhangye City and enhance its water resources management and development, a comprehensive evaluation system comprising 20 indicators was established based on the “water resources-social-economy-ecology” composite system. The period from 2014 to 2023 was analyzed using a combination of quadratic game combined weights and the GRA-TOPSIS model to track the changes in Zhangye City’s water resources carrying capacity. The primary obstacles to the water resources carrying capacity were identified through the obstacle degree model. The results showed that: a) From 2014 to 2023, Zhangye City’s overall water resources carrying capacity remained at Level Ⅲ (close to critical capacity), showing an increasing trend from 2014 to 2017 and a fluctuating decline from 2018 to 2023; b) From 2014 to 2017, the economic and ecological subsystems were the main obstacles indicators to enhancing water resources carrying capacity, while the water resources and ecological subsystems emerged as the main obstacles from 2018 to 2023; c) From the perspective of the entire study period, key obstacle indicators were water development utilization rate, per capita water resources, population density, average irrigation water volume per hectare of farmland, ecological environment water usage rate and sewage treatment rate. It is suggested to develop water-saving technologies, optimize water resource allocation, scientifically manage residential domestic water, agricultural irrigation water and ecological water, so as to further improve the water resources carrying capacity.

New quality productive forces are the core driving force for the construction of a modern industrial system. This study aimed to provide references for the deep transformation and upgrading of industries and for the construction of a modern industrial system in the Yellow River Basin. By integrating the goals of ecological protection and high-quality development in the Yellow River Basin, this paper analyzed how new quality productive forces enable the deep transformation and upgrading of traditional industries towards high-end, intelligent and green development. It also examined the internal logic of how disruptive and frontier technological innovations empower emerging and future industries. Based on the current development status of the Yellow River Basin, this paper identified issues in the empowerment process of new quality productive forces, such as weak technological innovation foundations, insufficient supply of high-quality labor, high pressure for green transformation, insufficient vitality of data elements, and imperfect new forms of production relationships. Therefore, this paper proposes practical pathways to strengthen the empowerment of new quality productive forces in the Yellow River Basin’s modern industrial system, including strengthening the cultivation of high-quality labor, reinforcing technological support, facilitating the flow of data elements, accelerating green and low-carbon transformation, and deepening institutional and mechanism reforms.

In order to address the challenges of safe operation of reservoirs in the context of frequent extreme weather events, based on the framework of modern reservoir operation management matrix system, taking Meizhou Reservoir in Guangdong Province as an example, this paper explored the systematic building and practice of flood control “four pre” (forecasting, early warning, rehearsal, and contingency plan) measures in the matrix. This paper integrated CNFF distributed hydrological model, progressive risk warning model, Godunov format flood dynamics model, digital twin scenario rehearsal technology, and intelligent contingency plan generation technology, and built a full chain management process with “four pre” as the technical center. The application results show that the “four pre” measures significantly extend the forecast period of reservoir floods, improve the accuracy of risk warning, the authenticity of scenario simulation, and the scientificity of dispatch plans. The reservoir simulation and contingency plans are presented in a visual form, helping decision-makers quickly understand flood scenarios and formulate optimal dispatch strategies.