Understanding the trend of sediment load variation and future projections in the Ningxia-Inner Mongolia reach of the Yellow River is crucial for its management. This paper analyzed and summarized the characteristics of sediment load changes in the main stream and tributaries of this reach, and identified the causes for the sediment reduction. The characteristics of the sediment load variation in the Ningxia-Inner Mongolia reach (1960-2020) included: a decrease in sediment inflow, with a more pronounced reduction in the mainstem; altered sediment contribution ratio between mainstem and tributaries, showing increased proportional input from tributaries; distinct temporal inflection points in sediment changes for both mainstem and tributaries, with recent reduction phases being largely synchronous and; recent sediment load variations approximately follow a lognormal distribution. The main driving factors influencing these changes of sediment inflow included the detention of the main stream reservoir, water and soil conservation measures in the tributaries, and the variation of rainfall. Considering long-term rainfall stability with cyclical fluctuations and diminishing reservoir sediment retention capacity over time, this study based its analysis on actual sediment yield conditions during 2000-2020, by evaluating reduced sediment interception capacity and newly implemented conservation measures, it is projected that the annual sediment load at Xiaheyan Station on the mainstem, and annual sediment input from interval tributaries will both increase moderately compared to recent levels.

In order to scientifically evaluate the spatial-temporal characteristics of water-saving levels, identify key influencing factors, reveal the spatial equilibrium patterns in the Yellow River water-receiving area of Henan Province, provide a scientific basis for optimizing water resources allocation and formulate differentiated water-saving policies, a water-saving evaluation index system was built, encompassing five dimensions of comprehensive, agricultural, industrial, domestic, and ecological with 12 quantitative indicators. The TOPSIS method was employed to dynamically assess the water-saving levels of 14 prefecture-level cities in the Yellow River water-receiving areas of Henan Province from 2014 to 2023. Additionally, based on the DEMATEL method and spatial equilibrium analysis, the key influencing factors and their regional differentiation characteristics were systematically analyzed. The results indicate that a) from 2014 to 2023, the average water-saving level in the Yellow River water-receiving areas of Henan Province is classified as Level IV on a 5-level evaluation scale, indicating a relatively low level, with significant spatial heterogeneity in water-saving levels among prefecture-level cities. b) Using the DEMATEL method, five main influencing factors are identified and ranked by their degree of impact: the proportion of planned water users (C2) > water consumption per 10 000 yuan of GDP (C1) > effective utilization coefficient of farmland irrigation water (C5) > water consumption per 10 000 yuan of industrial added value (C7) > proportion of saved water (C3). c) The spatial equilibrium of water-saving in the study area generally remains relatively stable but exhibits a slight declining trend over time, reflecting potential risks of regional imbalance in water-saving development. Therefore, it is essential to strengthen water-saving policy guidance and optimize water resources allocation to ensure sustainable development.

While the cascade reservoir group is exerting comprehensive benefits, it has significantly altered the carbon and nitrogen cycle paths of rivers, forming a “source-sink duality” of greenhouse gases (GHGs). This paper systematically reviewed the progress and challenges of research on the GHGs source-sink effect of gradient reservoirs in sediment-laden rivers. In terms of monitoring technology, existing technologies such as flux chambers and eddy covariance complement each other, thereby enhancing GHGs flux observation capabilities, furthermore, acoustic surveys and sediment coring techniques have optimized the assessment of carbon burial. However, the precision of multi-source data monitoring and data fusion continues to constrain the accurate evaluation of source-sink effects. Concerning the spatial-temporal distribution patterns of these sources and sinks, GHGs fluxes exhibit distinct longitudinal gradients along the cascade reservoirs and vertical stratification within the water column; specifically, the drawdown zone emerges as a significant hotspot for enhanced emissions due to frequent wet-dry alternation; the cascade reservoirs trigger the accumulation of GHGs by extending hydraulic retention times, altering dissolved oxygen states, and transforming organic matter composition. Regarding the underlying mechanisms influencing these GHGs dynamics, sediment plays a pivotal role: density currents transport and deposit external organic carbon, serving as a crucial substrate, while sediment resuspension disturbances critically affect redox microenvironments at the sediment-water interface. Simultaneously, hydrodynamic conditions directly govern CO2 diffusion efficiency across the air-water interface, influence CH4 bubble transport pathways and dissolution within the water column, and regulate N2O production dynamics via impacts on nitrification and denitrification processes. Notably, in highly sediment-laden rivers like the Yellow River, suspended sediments uniquely promote the proliferation of methanogens directly within the water column, fostering a distinct emission pattern characterized by methanogenesis occurring in the water itself, rather than solely in the sediments. For optimization and regulation, GHGs models have evolved from empirical statistics to mechanism-machine learning fusion, but the existing multi-objective optimization models still lack quantification of water-sediment-GHGs coupling mechanisms. In view of the above issues, it is urgent to build a tracking observation system of GHGs source-sink effects in the middle reaches of the Yellow River in the group of terraced reservoirs, the spatial-temporal variability of GHGs sources and sinks and their key influencing factors, elucidate the biogeochemical process of water-sediment-GHGs interactions, and optimize the water-sediment regulation model of the cascade reservoirs.

In order to investigate the characteristics of microbial community and influencing factors in aquatic bodies during the rainy season in coastal cities, based on Illumina MiSeq sequencing, this paper studied the distribution characteristics of microbial community structure and its correlation with environmental factors in Xixiang River, Shenzhen, and analyzed the effects of environmental factors on microbial community structure. The results show that the nitrogen and phosphorus pollution of Xixiang River is serious, and the water quality of Xixiang River is poor Class V with the risk of eutrophication. There is no significant difference in microbial diversity among sampling sites. At the phylum level, Proteobacteria, Bacteroidetes and Actinobacteria are the dominant species, and Proteobacteria is the first dominant species with a relative abundance of 62.25%-77.28%. At the level of genera, the dominant genera at all sampling points are not completely consistent.  NH+4-N, TDS, NO-3-N, TN and TOC in river water are strongly correlated with the relative abundance of microorganisms, among which the microorganisms are  the most affected by NO-3-N, NH+4-N and TDS. The upstream is affected by the rehydration of reclaimed water from Gushu Sewage Plant, and the bacteria mainly removes organic matter, while the sewage and wastewater in the middle and downstream provide a good living environment for denitrifiers in the water body, resulting in lower nitrate concentration and increased NH+4-N concentration. In the rainy season, the Pearl River estuary is easily supported by the tidal tide of the Lingdingyang Sea area, which is suitable for the growth of Marivita.sp.

With the advancement of water-saving technologies, China's industrial water use efficiency has been continuously improved, and the total industrial water use has shown a downward trend. The LMDI model was applied to analyze the driving factors of changes in industrial water use, and the rebound effect was used to quantitatively analyze the actual offset degree of the effectiveness of technological water-saving measures. An empirical analysis of the long-series panel data of Henan Province and its 18 prefecture-level cities from 2014 to 2022 shows that the improvement of industrial water use efficiency has effectively reduced the industrial water use, with the role of this factor being significantly enhanced. Meanwhile, economic scale and industrial structure have also contributed to a significant reduction in industrial water use, though there are large differences in their driving directions across different years and prefecture-level cities. On the whole, industrial water use in Henan Province is in a state of partial rebound effect. Driven by technological progress, the rebound effect value has decreased year by year, and the decoupling phenomenon between industrial water use and industrial added value has become obvious since 2019. Additionally, industrial water use in all 18 provincial-level cities also experience partial rebound, but there are significant regional differences (the rebound effect is relatively low in Xuchang, Pingdingshan and Kaifeng, while it is higher in Luohe, Anyang and Jiyuan). In order to alleviate the pressure of water resources shortage, reduce water environmental pollution and improve the level of industrial water conservation, controlling the rebound effect of industrial water use is essential. In order to achieve the high-quality development of Henan’s industrial economy, suggestions are put forward, including continuing to promote the improvement of industrial water use efficiency, coordinately advancing the formulation of industrial policies and water-saving policies, and building a regionally differentiated collaborative governance system.

With the proposal of the major national strategy of ecological protection and high-quality development in the Yellow River Basin, the research on the Yellow River Basin has become increasingly abundant. This paper mainly reviewed the literature on the high-quality development of the Yellow River Basin from the perspectives of its connotation, level measurement and spatial pattern, constraining factors, multi-dimensional studies, development paths and future directions. The results show that a) the connotation of high-quality development in the Yellow River Basin has been continuously enriched, expanding from economic development to the areas such as regional coordination, rural revitalization and cultural-tourism integration. b) By building different evaluation index systems, the measurements of the high-quality development level of the Yellow River Basin indicate that its spatial pattern is closely related to the administrative hierarchy of cities. c) Constraints to high-quality development in the basin include water resources conflicts, difficulties in industrial structure adjustment and transformation, and insufficient support from scientific and technological innovation capabilities. d) Studies on the high-quality development of the Yellow River Basin have been carried out around dimensions such as industrial structure optimization, technological innovation, urban and city cluster development, and cultural-tourism integration. e) The development paths mainly focus on strengthening ecological environment and industrial layout, promoting economic structure transformation and upgrading, and accelerating institutional and mechanism innovation. f) Future research should focus on interdisciplinary studies, multi-dimensional coupling and coordination research, comprehensive integration of multi-source data methods, and refined policy research based on zoning, grading and classification.

The integrated control of small watersheds in the Yellow River Basin is an important part of implementing the national strategy of ecological protection and high-quality development in the Yellow River Basin. In view of the control issues caused by the stepped landform, the characteristics of the climate-vegetation transition zone and the vulnerability of the cascading ecology within the basin, the core contradictions of the comprehensive management of small watersheds were analyzed from three perspectives. In terms of the natural system dimension, it was reflected in the dual pressures of resources and the environment faced by the upstream, midstream and downstream respectively. In terms of the technical system dimension, it was reflected in the lag between the rigid constraints of the resources background and the adaptability of management technologies. In the dimension of the management system, it was reflected in the fragmentation of cross-departmental rights and responsibilities, weak cross-regional collaborative capabilities, and the imbalance between protection and development goals. Building upon this analysis, this study proposes pathways to address the systemic challenges in integrated small watershed management: establishing a resilience enhancement pathway centered on “soil and water conservation, resources efficiency improvement, ecological restoration and climate adaptation”; developing a dynamic intelligent zoning and digital twin decision support system; devising a cross-domain authority-responsibility integration mechanism and a trilateral compensation system for water quality, quantity and sediment; and creating an eco-industrial value-added chain with ecological credit conversion channels. These proposals provide scientific underpinnings for overcoming the systemic challenges in integrated small watershed management within the Yellow River Basin and exploring pathways to improve its quality and efficiency.

In order to reasonably predict the future water demand situation in Henan Province, considering population scale and economic size, this study built a water demand forecasting method based on social characteristics to project the changes in water demand from 2025 to 2035. The results indicate that a decreasing trend in the total water demand for Henan Province in the future, with the total water demands for 2025, 2030, and 2035 being 21.795 billion m³, 21.198 billion m³, and 20.369 billion m³, respectively, representing reductions of 8.11%, 10.63%, and 14.03% compared to 2020. The proportion of water demand across different sectors is ranked as agriculture>domestic>ecological>industrial, with the share of water demand in agriculture and industry showing a decreasing trend, while the share of water demand in domestic use and ecological needs is increasing. The future population change in Henan Province is relatively small, with urban population growth significantly impacting domestic water demand. There is a negative correlation between economic growth and changes in water demand in Henan Province. The increase in water resources utilization efficiency is a primary factor contributing to the reduction in agricultural and industrial water demand, and is also the reason behind the overall decreasing trend in water demand. The rising level of urbanization and improvements in economic and social living standards are important driving forces behind the changes in future water demand in Henan Province.

In order to curb the severe wind erosion in the Great Bend Region of the Yellow River and reduce aeolian sediment input, this study investigated the aerodynamic mechanisms of sand transport and clarified the underlying principles and scientific issues of sand arrestation. Turbulent velocity distribution formulas incorporating basal roughness and concentration distribution models typical of desert environments were applied to analyze the wind speed, sediment concentration, and sand flux during dust events. The validation against field observations and theoretical calculations reveals a clear inverse relationship between sediment flux and surface roughness, indicating that sand-control engineering effectively weakens both wind erosion intensity and sand production under strong winds. Further calculations using threshold velocity formulas that account for drag effects show that the entrainment threshold of sand particles is positively related to surface roughness. Natural desert surfaces with low roughness exhibit lower threshold velocities, intensifying wind erosion, whereas the installation of sand barriers increases surface roughness, which simultaneously raises the entrainment threshold and reduces near-surface wind velocity. Under this dual effect-enhanced threshold and diminished near-ground wind speed-the activity of aeolian sand is significantly suppressed. This demonstrates that the principle of sand-control engineering lies in increasing surface resistance to restrain sand mobility. In contrast, smooth-surfaced control structures hinder particle deposition atop dunes, thereby suppressing dune migration and expansion. Based on the principle of minimum energy dissipation in natural systems, we have proposed aligning sand-control layouts along the most stable dune ridge lines. Meanwhile, the overall configuration of control structures, optimized under the principle of minimum resistance, not only modifies near-surface wind fields but also exhibits multi-directional adaptability through its crest morphology.

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”.

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.

Reservoirs are significant emission sources of methane (CH4), and methanotrophs can mitigate their emissions by oxidizing CH4. In order to comprehend the community characteristics, gene abundance, and assembly processes of methanotrophs in the reservoir sediments of the Huangshui River Basin on the Qinghai-Tibet Plateau, surface sediments from eight reservoirs were collected respectively in May 2023 (dry season) and August 2023 (wet season). Based on real-time fluorescence quantitative PCR and sequencing technology of the functional gene pmoA of methanotrophs, the abundance, community composition, and the diversity of methanotrophs were analyzed, and the assembly processes of methanotrophs were analyzed using the neutral community model. The results show that at the phylum level, the methanotrophs in the Huangshui River Basin are mainly composed of Proteobacteria. At the genus level, they are mainly constituted by Methylocystis and Methylobacter. The α diversity is manifested as being higher in the wet season than in the dry season, while the β diversity is not significant. The abundance of the pmoA gene in the dry season is significantly higher than that in the wet season. The assembly processes of methanotrophs in reservoir sediments are dominated by stochastic processes, among which drift is the most powerful. Temperature, total nitrogen, and pH are the main factors influencing the methanotroph community, and sediment pH is the dominant environmental factor for the abundance of the pmoA gene.

Integrated hydro-wind-photovoltaic development in river basins represents a crucial initiative for implementing low-carbon and green development principles. However, intensified climate change currently leads to increased volatility in renewable energy outputs, heightened uncertainty regarding future power generation potential, and challenges in accurately predicting the eco-environmental benefits of integrated energy bases. These factors pose significant obstacles to the efficient utilization of basin clean energy resources and ecological conservation. Therefore, the Cihaxia integrated water-wind-photovoltaic base in the upper reaches of the Yellow River was taken as the research object. The quantile mapping method, CNN-LSTM-Attention deep learning prediction model and improved theoretical output calculation method of water-wind-photovoltaic were used to screen high-precision future climate model data applicable to the study area. The daily average output of water-wind-photovoltaic power and its multi-time scale complementarity during the planned operation period of the integrated base (2035-2065) were predicted, and the ecological and environmental benefits of the integrated base were estimated. The key findings are: a) From 2035 to 2065, the predicted average annual power generation is 10.13 billion kW·h for hydropower, 1.187 billion kW·h for wind power, and 43.785 billion kW·h for photovoltaic power. Under four SSP scenarios, the average daily inflow to the Cihaxia Hydropower Station is increased by 0.97, 1.74, 1.25, and 1.99 m3/s respectively. The average daily theoretical hydropower output is increased by an average of 2.23 MW, while wind and photovoltaic outputs experience slight average decreases of 0.29 MW and 0.80 MW respectively. b) The annual power generation correlation coefficients are -0.22 for hydro-wind, 0.18 for hydro-photovoltaic, -0.10 for wind-photovoltaic and -0.03 for hydro-wind-photovoltaic combined. The hydro-wind combination exhibits stronger inter-annual complementarity, with the strongest intra-annual complementarity occurring during winter. c) The annual power generation from the integrated base can potentially replace 55.102 billion kW·h of coal-fired power, reducing carbon emissions by 48 million tonnes per year. Furthermore, replacing coal power with wind and photovoltaic generation saves approximately 108 million m3 of water annually. Additionally, the base is projected to reduce the average annual potential evapotranspiration of the underlying surface by 284.56 mm and increase the average annual Net Primary Productivity (NPP) of the ecosystem by 97.04 gC/m2.

In order to effectively integrate raster-based remote sensing monitoring results of soil erosion with plot-based (land use patches) soil and water conservation management, and to enhance the application of dynamic soil erosion monitoring outcomes in conservation practices, this study proposed a method and standard for categorizing land use patches based on practical experience in remote sensing image interpretation. Using land use patches derived from dynamic soil erosion monitoring as the basic evaluation unit and raster-based monitoring results as the foundation, land use patches were classified into five types of non-urgent treatment, desirable treatment, preventive protection, industry management, and non-soil erosion. The categorization criteria were determined based on topographic slope, vegetation cover, proportion of soil erosion area, and whether the responsible entity for soil erosion prevention and control was clearly defined. In Yunyang County, where hydraulic erosion dominates, the application results align with local conditions and meet the requirements of soil and water conservation management.For regions with mixed wind and hydraulic erosion, areas dominated by other erosion types, or locations with special conservation management needs, the categorization methods and standards can be adjusted accordingly during land use patch classification.

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. 

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 application of Artificial Intelligence (AI) in water resources management aims to solve complex issues such as water scarcity, water environmental pollution, and water ecological degradation. Its core idea is to utilize the data processing, pattern recognition and predictive analysis capabilities of Artificial Intelligence to build an intelligent solution for water resources management. This paper mainly studied the current development status, key technologies and practical application effects of AI technology in the field of water resources, and explored its application potential in the three core fields of hydrological prediction and analysis, water quality monitoring and assessment, and water resources management and optimization. Based on comprehensive research, the main algorithms and typical applications of AI in water resources management were analyzed, such as the application of models like Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Transformer in hydrological prediction, the application of Convolutional Neural Network (CNN) in water quality monitoring and the application of algorithms like DDPG and DQN in reservoir regulation. The practical applications of AI technology in scenarios such as water level prediction, flood forecasting, inversion of water quality parameters and intelligent irrigation were discussed. The future development direction of AI application in the field of water resources management was prospected, emphasizing the need to enhance the integration of physical mechanisms and data-driven methods, improve model transparency, and provide technical support for building a smart water resources management system.

In order to explore the water-saving efficiency of floating balls on large water bodies in the arid regions of northwest China, this study was based on a water surface shading experiment conducted in Kunyu City of Hetian Prefecture. The experiment utilized two Φ20 standard evaporation pans, six 20 m² evaporation ponds, and one 3 000 m² evaporation pond as evaporation devices, with the covering material being HDPE black weighted floating balls with a diameter of 10 cm. The study mainly analyzed the differences in annual evaporation between the Φ20 standard evaporation pans and the 20 m² evaporation ponds and calculated the evaporation conversion coefficient between the two. Additionally, by analyzing the stability of the floating balls in the 3 000 m² evaporation pond under different wind speed conditions, the relationship between floating ball coverage area and water-saving rate was explored. The study primarily reveals that the main cause of the evaporation differences between the Φ20 standard evaporation pans and the 20 m² evaporation ponds lies in the variation in internal water temperature and the heat supply differences caused by the wall effects. The evaporation conversion coefficients are 0.587 during the non-freezing period and 0.282 during the freezing period. When the wind speed exceeds 4 m/s, the blank water area under the floating ball coverage shows a nonlinear positive correlation with wind speed, expressed by the equation y=0.070 68x1.913 69, the floating ball coverage rate and water-saving rate decrease as wind speed increases.

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.

In order to understand the current situation of extreme precipitation events in Henan Province, scientifically recognize and master the spatial-temporal evolution characteristics of extreme precipitation events, and provide basic information support for flood and drought disaster prevention and extreme precipitation event early warning, based on the precipitation data of 26 meteorological stations near Henan Province from 1973 to 2023, an extreme precipitation threshold standard was established to screen extreme precipitation events. Meanwhile, in combination with the recommendations of the World Meteorological Organization (WMO), indicators such as extreme precipitation and continuous wet period CWD were selected. The spatial-temporal distribution of extreme precipitation indicators was statistically analyzed by using M-K trend analysis, and the period was studied by using the wavelet function. The results show that in terms of spatial distribution, the extreme precipitation threshold and eight extreme precipitation indicators in Henan Province gradually increase from northwest to southeast, but the number of extreme precipitation days and the intensity of extreme precipitation do not have obvious spatial distribution characteristics. During the time series changes, among the 8 extreme precipitation indicators, except for the continuous wet period CWD, the number of heavy rain days R25, and the number of heavy rain days R50, the remaining 5 indicators all show a decreasing trend, but they show an increasing trend after 2000. The extreme precipitation in Henan Province has periodic scale characteristics of 26-31, 16-20, and 8-11 years during the study period.

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.

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.

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.

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.

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.

Yulin in Northern Shaanxi is rich in high-quality coal resources. However, large-scale coal mining has caused severe damage to regional water resources. Taking Yulin coal mine as the study area, this study built a Relative Risk Model (RRM) to quantify the stress effects of risk sources including industrial development, mining-induced collapse and groundwater drainage on four types of receptors of social water stress, underlying surface, vegetation ecology and water resources. By dividing 84 watershed risk units, the study used log-normalization of risk values and natural break classification to zone the study area into five risk levels, proposing differentiated protection strategies. The results show that the mining-induced collapse is the primary risk source (contributing 52% of the risk value). The underlying surface and vegetation ecology are sensitive receptors (accounting for 35% and 28% of the risk value respectively). Level I risk areas require prioritized surface restoration and comprehensive utilization of drained water, while Level V areas need to be given attention, and buffer zones should be delineated.

In September 2024, Yellow River Conservancy Commission carried out a joint sediment discharge operation on key reservoirs in the upper and middle reaches of the Yellow River, including Longyangxia, Liujiaxia and Wanjiashan. The operation lasted for 16 days and achieved good results in sediment discharge and silt reduction. The five reservoirs of Shapotou, Qingtongxia, Haibowan, Wanjiazhai and Longkou discharged a total of 152.61 million tons of sediment, and the total erosion in the reservoir area was 66.92 million tons, with a combined sediment discharge ratio of 178.1%. The front sections of the Qingtongxia and Haibowan reservoir dams had been severely scoured, providing favorable boundary conditions for sediment reduction in the future. The Wanjiazhai Reservoir had achieved an annual equilibrium between sediment erosion and deposition, thereby effectively slowing the reservoir’s sedimentation rate. The aforementioned analysis demonstrates that utilizing upstream reservoir water storage to implement joint sediment discharge is not only effective but also offers a novel approach for reducing reservoir sedimentation during flat low-water years.

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.

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.

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.

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%.

The Yellow River is characterized by its scarce water resources and abundant sediment, leading to an imbalance between water and sediment dynamics. With the advancement of hydrological monitoring and forecasting capabilities, there have been significant strides in water level and flow monitoring. However, sediment concentration monitoring technology has yet to see a breakthrough. In order to slove the issue of sediment monitoring, the Hydrology Bureau of the Yellow River Conservancy Commission developed the HHSW·NUG-1 photoelectric sediment meter. This instrument overcame the limitations of traditional optical sediment measurement methods, which were constrained by flow velocity and range requirements. It enabled year-round online continuous monitoring, providing stable and highly accurate data. This paper focused on the comparative testing and application of this instrument at the Xiaolangdi and Huayuankou hydrological stations on the Yellow River. The study found that during the comparative testing period, the Xiaolangdi Reservoir is undergoing regulation, resulting in significant water and sediment processes and favorable sediment conditions. The performance of the photoelectric sediment meter is relatively stable, with no abrupt changes in sediment data. The overall trend of the data from the photoelectric sediment meter is consistent with the unit sediment concentration. The photoelectric sediment meter is capable of real-time online monitoring of sediment concentration data, accurately capturing the rise and fall processes and trends of sediment concentration. This aids in the rational arrangement of sediment discharge measurements at the stations, allowing for more precise judgments on abnormal sediment conditions and peaks, and the rational scheduling of tests. This not only reduces labor intensity but also enhances the rationality and timeliness of the testing process.

In order to provide a scientific theoretical foundation for promoting the coordinated development of new quality productivity between the Yellow River Basin and Yangtze River Basin, and provide decision-making references for formulating more rational regional development policies, this study established an evaluation index system for regional new quality productivity development. Employing methods such as entropy method, Theil index, spatial correlation analysis and QAP analysis, a comparative empirical investigation was conducted on the development levels and influencing factors of new quality productivity in both basins from 2013 to 2022. The results show that a) the development level of new quality productive forces in the Yangtze River Basin is generally higher than that in the Yellow River Basin. The spatial distribution of the development of new productive forces in the two major river basins has a distinct “block segmentation” feature. The development levels of both show a pattern of increasing successively from the upper to the middle and lower reaches. The multi-polarization phenomenon in the Yellow River Basin is more obvious than that in the Yangtze River Basin. b) The intra-regional and inter-regional differences in the Yangtze River Basin has decreased significantly, with a turning point occurring in 2019 when inter-regional differences fall below intra-regional differences for the first time, signaling a shift toward intra-regional variance dominance. Conversely, the differences between eastern and western regions within the Yellow River Basin, along with intra-regional differences in western areas, display an expanding trend. c) The global spatial autocorrelation of new quality productivity development in both basins shows continuous growth during 2013-2022, reflecting intensified spatial agglomeration. The provincial-level spatial correlation intensity in the Yellow River Basin remains weaker than that in the Yangtze River Basin. d) The regional differences in future-oriented industries and green development emerge as the strongest drivers of new quality productivity differences in the Yangtze River Basin, while innovation-driven industrial development levels and production materials differences constitute the predominant influencing factors in the Yellow River Basin. Based on these findings, the study has proposed the recommendations including optimizing resources allocation to enhance regional equilibrium, implementing innovation-driven strategies with differentiated approaches for cultivating new quality productivity, refining targeted policy frameworks, and strengthening inter-regional collaborative development mechanisms.

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.