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.

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 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.

New quality productive forces serve as the endogenous driver for rural revitalization, while rural revitalization provides a broad practical arena for their development. In order to offer theoretical and practical insights into advancing new quality productive forces and facilitating rural revitalization in the Yellow River Basin, this study elucidated their coupling mechanism. Using panel data from nine provinces (autonomous regions) in the basin from 2012 to 2022, it measured the development levels of both dimensions via a projection pursuit model optimized by an accelerated genetic algorithm. An improved coupling coordination degree model quantified their synergistic relationship. Additionally, a coordinated influence model identified the key drivers affecting their coupling coordination. The results indicate that a) the new quality productivity and the development level of rural revitalization in all provinces (autonomous regions) have steadily improved, and the two show a “concave relationship”. b) The development indices of the three subsystems of new quality productive forces, namely laborers, objects of labor and means of labor, all show a continuous upward trend. c) The new quality productive forces have played a key role in promoting the transformation of the coupling coordination degree of most provinces (autonomous regions) in the Yellow River Basin from mild imbalance to primary coordination. d) The improvement of the new quality productive forces in the Yellow River Basin mainly relies on the contribution of the development index of the objects of labor. However, this contribution gradually weakens over time, while the coordinating influence of the laborers usually shows a blocking effect, and the influence of the means of labor is relatively small. Based on this, it is suggested that a higher level of coordinated development in the Yellow River Basin be achieved by stimulating the growth of the objects of labor, alleviating the constraints on workers and strengthening the promoting effect of labor materials on new quality productive forces.

Exploring the spatial-temporal characteristics and influencing factors of the new and old growth drivers conversion in the Yellow River Basin is crucial for fostering high-quality development in the basin. The evaluation index system was built according to the dimensions of new and old growth drivers, and the Entropy Weight-TOPSIS method and the GMM model were introduced to portray the spatial-temporal characteristics and the influencing factors of the new and old growth drivers conversion in the basin. The findings reveal several key insights: a) The process of transforming old and new growth drivers in the Yellow River Basin can be divided into three distinct stages of “fluctuating rise-slow decline-steady rise”, ultimately leading to a steady upward trajectory. This trend reflects the alternation and replacement of the driving forces behind economic growth in the basin. b) Significant disparities exist in the level of new and old growth drivers  conversion among the upper, middle, and lower reaches of the Yellow River Basin, resulting in a spatial distribution pattern characterized by higher levels in the east and lower levels in the west. c) Regarding influencing factors, labor force, infrastructure, informationization, technology research and development, and high-end human resources exert positive effects on the conversion of old and new growth drivers in the basin. Conversely, financial development negatively impacts this conversion process, while the influence of capital remains non-significant. Therefore, it is imperative for the Yellow River Basin to prioritize the cultivation of new growth drivers alongside existing resources. Tailored policies should be designed, formulated, and implemented to facilitate the conversion of old and new growth drivers according to local conditions. Additionally, efforts should be made to maximize the influence and linkage effects of the basin's central cities.

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.

Mastering the spatial-temporal characteristics and driving forces of historical and current runoff changes in water source areas can reveal the complex relationship between changing environments and runoff responses, thereby more accurately predicting the complex characteristics of runoff changes in a future period. Based on the runoff and precipitation data from six hydrological stations in the study area from 1961 to 1975 and 2006 to 2020, this article compared and analyzed the basic characteristics of runoff changes in each hydrological station during the two periods. The cumulative slope change rate method was introduced to reveal the main driving forces of runoff changes in different periods. Finally, the R/S analysis method was used to predict the future trend of runoff changes in each hydrological station. The research results indicate that a) the annual flow change trends of each hydrological station from 1961 to 1975 and from 2006 to 2020 are basically consistent. From 1961 to 1975, except for the Maerkang Hydrological Station, the average annual flow of other hydrological stations shows a non-significant downward trend. From 2006 to 2020, the average annual flow of each hydrological station shows a significant upward trend. b) Compared with 1961 to 1975, the average annual flow in the Yalong River Basin increases by 8.30% from 2006 to 2020, the proportion of dry season flow increases by 7.16%, the coefficient of non-uniformity decreases by 1.33%, and the coefficient of variation shows no significant change. The average annual flow in the Dadu River Basin decreases by 1.50%, the proportion of dry season flow increases by 1.85%, the coefficient of non-uniformity increases by 2.78%, and the coefficient of variation increases by 61.54%. c) The runoff supply between the Daofu to Yajiang and Maerkang to Dajin sections is relatively weak. The runoff changes in the Yalong River Basin show a more positive trend compared to the Dadu River Basin. d) From 1961 to 1975, human activities contribute 91.94%, 60.44%, 60.22%, and 87.71% to the runoff changes at Ganzi Station, Zumuzu Station, Maerkang Station, and Dajin Station, respectively. The precipitation contributes 56.20% and 64.19% to the runoff changes at Daofu Station and Yajiang Station, respectively. From 2006 to 2020, human activities contributes 58.13%, 72.52%, 67.46%, 55.75%, and 66.36% to the runoff changes at Ganzi Station, Daofu Station, Zumuzu Station, Maerkang Station, and Dajin Station, respectively. The precipitation contributes 50.87% to the runoff changes at Yajiang Station. e) The runoff of the six hydrological stations may continue to show an upward trend in the future.

Given the significant implications of the dynamic hydrological characteristics of the Bosten Lake Basin for regional water resources management, ecological preservation, and socio-economic activities, this study undertook an in-depth investigation into the fluctuations in precipitation, water surface evaporation, and drought index within the basin spanning from 1955 to 2020. Through the comprehensive application of diverse statistical methodologies, including trend analysis, cluster analysis, mutation detection, and wavelet analysis, this research unveiled the evolutionary patterns and potential trends in precipitation, evaporation, and drought index within the study area. The findings reveal that the Bosten Lake Basin falls into an extremely arid zone, where precipitation demonstrates significant interannual variability alongside a non-significant upward trend. Such variation patterns persist across multiple temporal scales, with the most prominent periodic oscillations observed at 10-20 year cycles. The abrupt change of evaporation mainly occurs around 2000, showing a periodic variation trend across multiple time scales, with the main variation cycle being approximately 40 years. While the drought index exhibits no statistically significant overall variation during the study period, it displays distinct periodic characteristics at decadal (10 year) and tridecadal (30 year) scales. Ultimately, the research outcomes not only elucidate the intricate change characteristics and potential trends of precipitation, evaporation, and drought index in the Bosten Lake Basin, but also furnish a robust scientific foundation and decision-making support for water resources management, ecological preservation, and drought relief and mitigation strategies within the basin.

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 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.

Based on its high temporal and spatial resolution surface observation advantage, time-series Sentinel data can monitor floods and their impacts on embankments and surrounding areas in real time, monitor water changes in real time, and achieve rapid response and accurate assessment of floods, which is of great significance in flood regime monitoring and other aspects. This study combined Sentinel-1 radar image data and Sentinel-2 optical image data, taking into account the characteristics of surface features in the flood-inundated areas of the middle and lower reaches of the Yellow River, and proposed a flood regime monitoring method based on long-term Sentinel satellite data with the help of the GEE platform. First, the water extraction index (SDWI) and the normalized difference water index (NDWI) of Sentinel-1 dual-polarization data were combined with the Otsu method (OTSU) to obtain the extraction results. Taking July 2022 as an example, regional water information was extracted based on Sentinel-1 SAR and Sentinel-2 images and the accuracy was evaluated. The water extraction results were 95.3% and 95.1% respectively, and the Kappa coefficients were 0.91 and 0.90 respectively. Subsequently, the Sentinel-2 image extraction results were used to supplement and correct the Sentinel-1 extraction results, and the long-term monthly dynamic changes of the water body in the middle and lower reaches of the Yellow River from 2016 to 2022 were monitored. The time variation analysis of the water body extraction results in different periods was used to summarize the spatial-temporal changes of the water body in the study area. Finally, the inundation range of the study area was divided based on Google images and the actual situation in the region.

The underground aquifer structure has the characteristics of complex space and variable parameters, which leads to the uncertainty of the groundwater model built by numerical simulation to reveal the groundwater movement. In order to analyze the influence of the uncertainty of the groundwater structure model on the output results, two models of different structures were established. Based on the commonly used Bayesian theory in groundwater movement simulation and parameter optimization, the standard difference evolutionary adaptive (DREAM) algorithm was used for sampling, and parameter samples of the two different structure models were obtained. By establishing alternative models, the simulation calculation efficiency was improved, and the collected samples and corresponding calculation results were statistically analyzed. Finally, the uncertainty of the model structure was analyzed. The results indicate that the uncertainty of the model structure can cause uncertainty in the input parameters, and the uncertainty of the parameters will increase with the increase of the uncertainty of the model structure. The closer the model structure is to the actual situation of the underground aquifer, the closer the parameters are to their true values; During the simulation process, there are phenomena where different parameters result in the same simulation results, and different model structures and parameters result in the same simulation results. Overall, the uncertainty of the output results caused by the model structure cannot be compensated for by the uncertainty of the parameters. However, the degree of uncertainty caused by the model structure is limited by the sensitivity of the input parameters, and the closer the groundwater model structure is to the real groundwater aquifer system, the more accurate the simulation results of the model.

In order to quantitatively analyze the decoupling relationship between water resources utilization and economic development in the Yellow River Basin in Shandong Province, based on the relevant statistical data of the Yellow River Basin in Shandong Province from 2012 to 2022, the water footprint theory, Tapio decoupling model and LMDI decomposition model were used to analyze the water resources utilization situation, the decoupling relationship between water resources utilization and economic development and their decoupling factors in the Yellow River Basin in Shandong Province. The results show that the total water footprint of the Yellow River Basin in Shandong Province shows a fluctuating upward trend, with agricultural water footprint accounting for the largest proportion and ecological water footprint growing fastest, and the average per capita water footprint over many years is close to the internationally recognized water shortage line. Water resources mainly come from internal supply, and the issue of water safety is prominent, and the economic benefits of water footprint continue to grow, with an average annual growth rate of 5.06%; There is a weak decoupling relationship between water resources utilization and economic development as a whole, between agricultural water use and economic development as a whole, and between industrial water use and economic development as a whole. The decoupling rate of Jinan is 100%, Jining, Tai 'an and Heze is 90%, Zibo and Dezhou is 80%, and Dongying, Liaocheng and Binzhou are relatively weak. Water use efficiency effect is the main driving factor to promote decoupling, and economic scale effect is always the main factor to inhibit decoupling; The water use efficiency of most prefecture-level cities has a good decoupling relationship. Except Dongying's economic scale decoupling decomposition index in 2016 is negative, other prefecture-level cities are positive.

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.

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.

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.

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.

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.

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.

Aiming at the issues of strong dependence on experience and dispersed multi-source knowledge in the support design of hydraulic tunnels, a hybrid natural language processing (NLP) method integrating rules, statistics, and artificial intelligence was proposed to built a knowledge graph for hydraulic tunnel support design and intelligently generate support schemes. Structured entities and classification relationships were extracted from standards through rule matching, and unstructured knowledge was mined from academic literature and related documents by using a TF-IDF model and a Bidirectional Long Short-Term Memory Network-Conditional Random Field (BiLSTM-CRF) model. In total, 1 220 entities, 3 types of classification relationships, and 8 types of non-classification relationships were extracted. Based on ontology, the knowledge graph supported knowledge retrieval, semantic reasoning, and dynamic querying. Taking the access tunnel of a pumped-storage power station as an example for technical application, the results show that the hydraulic tunnel support scheme generated by the method proposed in this paper maintains a high degree of consistency with the original design scheme in terms of overall design framework and key technical indicators, and further improves and optimizes the support details design by adding design values for the arrangement of anchor rods and steel mesh diameter parameters.

In order to improve the fault diagnosis accuracy of pumping station units, this study utilized a rotor test bench to simulate operational states of pumping station units and obtained vibration signals under both normal and abnormal conditions. Mel-Frequency Cepstral Coefficients (MFCC) were employed to extract time-frequency domain features from the vibration signals. These features were then input into a DenseNet model optimized by a modified cuckoo search algorithm (DMCS) for fault identification. In order to validate the applicability of the proposed method in real-world environments, the diagnostic model's accuracy, noise resistance, and performance under small-sample conditions were tested after hyperparameter optimization. The results demonstrat that the MFCC-DenseNet model, optimized by the DMCS algorithm, achieves a 100.00% recognition rate for all state features. Compared to other diagnostic methods, the proposed method also performs better in noise resistance and few sample testing, it achieves a 93.50% recognition rate at a Signal-to-Noise Ratio (SNR) of 4 dB and required only 80 samples to reach 100.00% recognition accuracy. This method effectively addresses the problemof scarce real-world fault data in practical applications.

Focusing on alkali excitation technology, this study investigated the effects of different dosages of alkali excitants on the permeability properties of modified Yellow River silt, and the relationship between the fine structure and macroscopic properties of Yellow River silt-based alkali excitation materials through NMR experiments. Firstly, different proportions of calcium hydroxide, sodium hydroxide and Yellow River silt were added to the homemade molds according to the determined proportion design, and the specimens of Yellow River silt-based alkaline-excited materials were formed by pressing with uniaxial apparatus, and they were maintained at different ages. The permeability coefficients of the cured specimens were determined by using a homemade permeability apparatus, and a nuclear magnetic resonance imaging analyzer was used to analyze the fine structure of the Yellow River silt-based alkali excited materials. The study finds that the relationship between calcium hydroxide dosage and permeability coefficient satisfies the third degree polynomial relationship, and its R2 reaches more than 0.95, and a mathematical model involving the permeability coefficient, age and calcium hydroxide dosage is established, which has an R2 as high as 0.97. The pore size of the Yellow River silt-based alkaline-excited material is transformed from small pores to micropores with the increase of calcium hydroxide dosage. And the fractal dimension of the pore structure of small pores is negatively correlated with the permeability coefficient.