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

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

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

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

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

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

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

A risk population estimation model based on Sentinel-2A remote sensing images was proposed to address the lack of downstream population distribution data in the risk assessment of life loss for small reservoirs. Taking the DYJ reservoir as an example, supervised classification was used to quickly extract the building information of rural residents from remote sensing images, and combined with the evolution results of dam break flood, a risk population estimation model was built considering the flooded state of the buildings. Four supervised classification methods, including Maximum Likelihood Classification (MLC), Support Vector Machine (SVM), Mahalanobis Distance Method (MDM), and Minimum Distance Classification (MDC), were compared. The results show that the MDC has an overall classification accuracy of only 65.7%, while the other three methods achieve over 90% accuracy. Among them, the MLC provides the highest recognition accuracy for remote sensing images, with an overall classification accuracy of 97.55% and a Kappa coefficient of 0.93, in extracting residential building elements in the study area. With the construction information extracted by MLC and the dam break risk population estimation model, the risk population downstream of the DYJ reservoir is estimated to be 1 470 people. This model can rapidly estimate the risk population downstream of small reservoirs, addressing the shortcomings in accuracy and efficiency of population density methods and cumulative estimation methods for residential areas.

In order to investigate the influence of land use change to the basin flood process, the Fenhe River Basin was chosen as the study area. The SWAT model and the extreme land use scenario analysis method were employed to analyze the effects of land use type changes on the flood process in different periods and scenarios. The results show that a) the mean value of Nash-Sutcliffe Efficiency(E_NS) is greater than 0.70 and the mean value of determination coefficient (R²) is greater than 0.65 during the calibrated and validated period, indicating that the SWAT model has good applicability in the Fenhe River Basin. b) Between 2000 and 2020, there is a reduction in the area of cultivated land, grassland, water bodies and unused land, while the area of forested land and built-up land is increased. c) Under the land use in 2000, 2010 and 2020, each peak flow and the total flood volume show a slight upward trend. d) Under the arable land scenario, there is an increasing trend in each peak flow and its total flood volume; while under both the woodland and grassland scenarios, there is a decreasing trend. In terms of magnitude of impact, land use type change has a smaller impact on larger flood processes and a larger impact on small and medium flood processes. Therefore, it is necessary to increase the area of forest and grass and vegetation coverage, promote water-appropriate planting, and avoid high-water-consuming vegetation in areas with high incidence of flood disasters and serious soil erosion, so as to improve the ability of flood control, flood resistance, disaster prevention and mitigation in Fenhe River Basin, and promote ecological restoration and high-quality development in Fenhe River Basin.

For the simulation of one-dimensional open channel hydrodynamics on complex terrain with supercritical flow, shockwave or transient mixed super-subcritical flow, a complex open channel hydrodynamic model was developed based on the Saint-Venant equations in Godunov format by using the finite volume method. First of all, the HLL approximate Riemann solution was applied to calculate the interface fluxes, meantime the spatial-temporal accuracy was improved to the second order by MUSCL scheme and Runge-Kutta method, while the flux results were replaced by the flux form in the continuity equations to ensure flux conservation. Besides, the water surface gradient was taken as the source term in equation then the bottom slope flux method was introduced to solve it. Last but not least, the frictional source term was treated by an explicit-implicit method that requires no iterations. The model was validated by four typical examples and the comparison results show that the model can simulate complex processes such as dam break and transient mixed super-subcritical flow very well, having good conservation and adaptability.

In order to analyze the coupling relationship among energy, water and carbon in the Ω-shaped bend of the Yellow River urban agglomeration and to promote the green and low-carbon development of the region, this paper built an evaluation index system for the energy-water-carbon system of the urban agglomeration. This paper built energy-water-carbon evaluation index system of urban agglomeration of Ω-shaped bend of the Yellow River, used the entropy method and coupling coordination degree model to calculate the level of coupling coordination of energy, water and carbon in the urban agglomeration from 2005 to 2020, and built a random forest model to identify the main influencing factors. The results show that the coupling coordination degree of the energy-water-carbon system in the urban agglomeration of Ω-shaped bend of the Yellow River presents a fluctuating upward trend, but it has not reached a good coordination level in 2020. Environmental regulation, total factor productivity and proportion of built-up area are the main factors influencing the changes in this level. Based on these findings, suggestions are proposed to develop specialized environmental regulation policies, lead the energy revolution through technology, and promote the integration of environmental protection with economic development.

In order to enhance the efficiency of urban drought emergency management, based on the urban drought emergency plan, the urban drought emergency water supply process and its Petri net simulation model were established. Taking the drought in Ejin Horo Banner of Inner Mongolia in June 2022 as an example, the urban drought emergency water supply process strategies of 9 single strategy scenarios and 4 mixed strategy scenarios were derived by combining the water consumption processes of various water users. According to the simulation results, the effects of various strategies were obtained. The results show that a) when the storage capacity of the water supply reservoir is increased from 5.24 million m³ to 6.14 million m³ by using the urban emergency reserve water source, the normal water supply of the city can be increased from 7 days to 8 days, and the water usage satisfaction rate increases from 58.62% to 68.69%. b) The external water resources transfer capacity is increased from 0.15 million m³/d to 0.25 million m³/d, the duration of normal water supply in the city can be increased from 8 days to 9 days, and the water usage satisfaction rate is increased from 73.72% to 83.79%. c) When the proportion of domestic, agricultural, industrial and ecological water supply is 90%, 70%, 50% and 0% of the normal water supply, the normal water supply can be increased from 7 days to 10 days, and the water satisfaction rate can be increased from 58.62% to 89.57%. d) By successively applying water supply restriction, using urban emergency backup water source and using external water transfer strategies, the water usage satisfaction rate can reach 100%.

In order to select an appropriate interpolation method to reveal the spatial variation characteristics of groundwater depth in the arid oasis, 53 groundwater monitoring well sample points were selected to be taken as the study area, and three interpolation methods, including spline function method, inverse distance weight method and kriging method, were used to interpolate the groundwater depth of the monitoring wells, and the cross-validation method was selected to verify the interpolation effect, and the factors affecting the spatial distribution of groundwater depth in the Keriya River were qualitatively analyzed. The results show that from 2019 to 2021, the groundwater depth of the tail oasis gradually increases from southwest to northeast with time, and the groundwater depth of the desert section is smaller in the south and north and larger in the middle, and the groundwater depth in the Yutian oasis is smaller than that in the tail oasis and the desert section. In 2019, 2020 and 2021, the average groundwater depth of the desert section is 4.64 m, 4.08 m, 2.78 m; 4.80 m, 4.22 m, 2.88 m; 4.86 m, 4.10 m, 2.87 m. The kriging method is the optimal method for spatial interpolation of groundwater depth in arid areas, and the oasis vegetation cover, transpiration and human activities are important factors affecting the groundwater depth of the Kriya River.

In order to calculate the maximum population scale and economic scale that the urban water resources in Qingdao City can support, and to formulate the urban development model for urbanization and sustainable utilization of water resources, the entropy weight method was used to measure the water resources carrying capacity and urbanization level of Qingdao City from 2015 to 2022. A system dynamics model was built from both water resources and social economy aspects, and the water supply and demand situations of four development models (natural development, rapid development, water conservation priority, and comprehensive development) from 2023 to 2030 were simulated. The results show that the water resources carrying capacity of the urban area of Qingdao City shows a fluctuating upward trend from 2015 to 2022, and the urbanization level is steadily increased. The comprehensive development is the optimal mode of the urbanization development in Qingdao City, which can ensure that there is still a surplus water resources after meeting the needs of residents' life and economic development.

In order to reasonably delineate the stages of water and sediment series in the Yellow River, the Mann-Kendall and Bayesian Model Averaging(BMA) were employed to analyze the trends and detect change points in the hydro-sediment sequences from six cross-sections of the Yellow River mainstream, namely Tangnaihai, Lanzhou, Toudaoguai, Tongguan, Huayuankou and Lijin from 1956 to 2022. The results indicate that the flow-sediment conditions in the Yellow River source region show no significant trend, while the other sections exhibit a decreasing trend. The abrupt points of runoff sequence are 1969, 1986 and 2018, which are closely related to the operation of water storage in key water control project and have regional influence. Most of the abrupt change points of sediment sequence in hydrological sections occur in the 1960s, and then show a significant downward trend, mainly due to the influence of soil and water conservation in the basin. It is recommended to divide the runoff series into four stages of before 1969, 1969-1985, 1986-2017 and from 2018 to the present, and the trend evaluation should be the main stage for sediment sequence analysis.

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

In order to investigate the spatial distribution characteristics and health risks of heavy metals in groundwater from abandoned mines, this study selected the abandoned mine in Houshan Town, Xuyong County, Luzhou City as the research area. Seven heavy metals (Fe, Cd, Cu, Pb, Zn, Mn, and Cr) in groundwater were measured and analyzed. The pollution characteristics, spatial distribution patterns, and health risks of heavy metals were systematically evaluated by using pollution index assessment, fuzzy comprehensive evaluation, and health risk assessment models. Monte Carlo simulation was employed for uncertainty analysis of health risk assessment. Results indicated that the mean concentrations of Fe, Pb, Mn, and Cd in groundwater exceeded Class Ⅲ water quality standards. The aggregate non-carcinogenic risk values from five heavy metals (Fe, Cu, Pb, Zn, and Mn) through drinking water exposure were 0.617 for adults and 0.145 for children, both below the threshold 1, with adults exhibiting higher susceptibility than children. Carcinogenic risks were identified for Cd and Cr through dual exposure pathways of ingestion and dermal contact. Monte Carlo simulations predicted carcinogenic risk ranges of 1.78×10^-4 to 6.33×10^-4 for adults and 2.29×10^-4 to 4.40×10^-4 for children, with mean values of 3.96×10^-4 and 3.33×10^-4 respectively. These findings demonstrate potential carcinogenic risks for adults and significant carcinogenic hazards for children from Cd and Cr exposure in the studied groundwater system.

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

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

In order to solve the issue of uneven subsidence of the channel, serious subsidence and slide of the concrete lining plate in the collapsible loess area, the reasons for subsidence of the No.10 main canal in Guhai extention irrigation in Ningxia were analyzed, and the foundation soil of the channel was ramped, and the bearing capacity of the foundation soil was increased. The channel subsidence is treated by arc bottom trapezoidal concrete section, composite geomembrae and benzene plate. The results show that the density of the channel reaches more than 1.78 g/cm³, the pore ratio of the base soil is greatly reduced, and the density is increased. The cast-in place arc bottom trapezoid section has good structural loading condition and uniform adjustment of frost heave force and uneven subsidence. The analysis of the effect after the reconstruction and treatment of the channel shows that the water content of the foundation soil, the frost heaving amount and the settlement amount of the concrete slab has been effectively controlled. Through the comprehensive treatment of collapsible channels, the theoretical design and methods for the treatment of collapsible channels and the collapse of concrete slabs are improved.

In order to mitigate the adverse effects of turbine sediment abrasion and enhance the operational efficiency of hydroelectric plants, an intelligent monitoring and early warning system for water and sediment in the diversion channel of hydroelectric power stations was designed and developed, the image-based method was employed in conjunction with the Residual Neural Network model (ResNet50_v2) to facilitate the synchronous online intelligent monitoring of water and sediment, the Long Short Term Memory (LSTM) model was employed to forecast the sediment concentration for the next 5 h. Determined the optimal sediment concentration warning threshold and appropriate warning mechanism through profit and loss balance analysis to minimize power generation losses. Taking the Talade Sayi Hydropower Station in the Kashgar River Basin as an example, the system was applied in practice. The application results show that the system monitors the flow rate and the measured values of ADCP flow measurement equipment, with E_MA≤2.97 m³/s、E_MR≤2.17%. The system monitors the sediment concentration and the measured values of manual drying method and optical sand analyzer, with E_MA≤0.20 kg/m³、E_MR≤16.91%. The LSTM model has an E_NS>0.7 for predicting sediment concentration during a 5 hours forecast period, indicating high overall monitoring and prediction accuracy of the model. The threshold for sediment concentration warning in hydropower stations is 3.59 kg/m³. Through precise measurement and scientific warning, it is possible to avoid sediment wear accidents in power generation equipment, save maintenance costs, and improve overall efficiency.

Vibration trend prediction of water pumping units is an important initiative to ensure the normal operation of the units, while the complexity and nonlinearity of the vibration signals make the prediction difficult. Therefore, a vibration trend prediction model for water pump units based on STOA-VMD and improved Time Convolution Network (TCN) was proposed. Firstly, the Variable Modal Decomposition (VMD) parameters were optimized by using the Seagull Optimization Algorithm (STOA) to achieve the optimal adaptive decomposition of the vibration signal, and then each decomposed mode was predicted by using the improved TCN, and finally the final prediction result was obtained by superimposing all the results. Taking the pumping unit of a domestic rainwater pumping station as an example, the model validation was carried out based on the horizontal oscillation data of the water-guide bearing. The results show that the predicted values of the above combined model are basically consistent with the trend of the monitored values, and it has good predictive ability. Compared with the STOA-VMD-TCN, VMD-EnTCN, VMD-TCN, and TCN models, the proposed model has the smallest E_MA、E_RMS、E_MAP, and the highest prediction accuracy.

Based on the theoretical of eigenvalue buckling analysis method and considering the material utilization efficiency of chord member structures, this study employed numerical simulation method to conduct stability calculations for gate arms without chord member, with single chord member, and with double chord members. The influence of chord member positioning, quantity, and cross-sectional properties on the structural stability of steel gate arms was analyzed. An optimized chord-layout scheme was proposed, and on this basis, finite element analysis was conducted on the overall stability of the steel gate support arm. The results indicate that for single chord member gate arms, the optimal ratio of the distance between the chord and the hinged support to the total arm length (l/m) ranges from 0.60 to 0.75, achieving the highest load-bearing capacity per unit mass. Arranging double chord members away from the hinge end can improve the unit mass bearing capacity of the support arm, but the spacing between chord members should not be too large. Dimensional analysis of the chord member structure reveals that when the width-to-height ratio of the chord is 1.4, the overall stability of the gate arm is favorable. The thickness ratio of the flange to the web (t₃/t₄) has minimal effect on the load-bearing capacity per unit mass, with the primary design consideration being to ensure local stability of the gate arm. Adding chord members improves gate stiffness and enhances the stress state, primarily by reducing the maximum equivalent stress in the steel gate arm. Compared to gate arms without chord member, single chord member arms reduce the maximum equivalent stress by 8.44%, while double chord member arms achieve a reduction of 12.99%.

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

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