Water flow is an important piece of information in hydrological assessments， aiding in understanding variations in river flow and predicting its trends. Traditional contact-based methods for measuring water flow are greatly affected by environmental conditions during emergencies， with difficulties in installation and low measurement efficiency. To address this issue， this study explores a method for calculating video-based flow measurements using a non-contact spatiotemporal imaging approach. The study selects the Pukou section of the Chuhe River in Nanjing City as the experimental site for water flow detection. The detection method in this paper uses video flow measurement to measure the velocity of water flow. The collected data is processed visually and displayed on the interface of terminal equipment， and the collected data can be transmitted to a specified address in the format of the hydrological protocol. Experimental results indicate that using drones equipped with video flow measurement devices can rapidly and effectively complete water flow detection. The data can be displayed in a visual format on terminal equipment， facilitating viewing by relevant personnel. This form of detection is fast， safe， and environmentally adaptive， with the potential for practical applications. Further research into this detection method will promote the smart and integrated development of hydrological assessments.

The inland river basin in Hexi， Gansu Province， is extremely short of water resources. There are certain differences in the changes of mountain runoff between the central and western and eastern water systems in the basin. Studying the changes in mountain runoff and the contribution rates of different factors is of great significance for ensuring the sustainable development and utilization of regional water resources. Based on the data of mountain runoff and precipitation and temperature in the main runoff producing areas from 1956 to 2021， various trends and mutation tests， cumulative slope change rate methods， and combined with the characteristics of runoff supply， the changes in mountain runoff and their responses to changes in precipitation and temperature in the three major water systems were analyzed. The results show that： ① the average annual mountain runoff of the Shiyang River system was 1.36 billion m³， showing a non-significant decreasing trend over the years and a non-significant increasing trend in precipitation， The significant increase in temperature leads to an increase in evaporation， resulting in a decrease in runoff； ② The average annual runoff from the Heihe River system has increased from 3.062 billion m³ before the mutation point in 2006 to 3.56 billion m³ after the mutation point. The contribution rate of precipitation to runoff changes is 16.7%， and the temperature has significantly increased， enhancing the impact on runoff changes； ③ The average annual runoff from the Shule River system has increased from 1.422 billion m³ before the mutation point in 1998 to 17.93 m³ after the mutation point. The impact of precipitation and temperature on runoff changes is similar， with contribution rates of 30.4% and 30.2%， respectively. There are certain differences in runoff supply characteristics and climate conditions among the three major inland river systems in Hexi， resulting in inconsistent responses of runoff to different driving factors.

Hydrological similarity is an index to measure the similarity degree of two basins， which is often used to identify and select similar basins. Traditional research usually only discriminates whether there is similarity between basins， but pays little attention to the spatial and temporal characteristics of hydrological similarity of basins. In order to explore the spatio-temporal variation characteristics of hydrological similarity in the Fenhe River Basin， this paper set the calculation time scale based on the different meteorological elements of the year， month and day， set the sub-watershed scale according to the different river grades of the first， second and third levels nested in the Fenhe River basin， and carried out principal component analysis on 5 meteorological elements and 17 underlying surface indicators in the study area. Finally， the hydrological similarity evaluation system of Fenhe River Basin was established with the average annual precipitation， average annual temperature， topographic humidity index， topsoil PH， average elevation and surface roughness as the characteristic indexes， and the coefficient of variation method was used to determine the hydrological similarity weight coefficient of the basin， and the temporal and spatial characteristics of the hydrological similarity of the main and tributary basins of Fenhe River were quantitatively studied. The results show that： ① the hydrological similarity between the first-level Fen River basin and the Fen River basin is greater than 0.750 on the scale of year， month and day. Under the three time scales， the hydrological similarity between the main stream of Fanwang River and Fenhe River basin is the highest， which is 0.908， 0.927， 0.910 in order. At the annual scale， the hydrological similarity between the main stream of Dachuan River and Fenhe River basin is the lowest， which is 0.773. On the monthly scale， the hydrological similarity between Changyuan River and Fenhe River basin is the lowest， 0.818. On the daily scale， the hydrological similarity between ZhongMafang River and Fenhe River basin is the lowest， which is 0.791. ② At different sub-watershed scales， the hydrological similarity gradually decreases with the decrease of the river series of Fen River's nested tributaries. The hydrological similarity of the first to third tributaries of Lanhe River， Changyuan River， Wenyu River and Fanwang River with respect to Fenhe River basin is 0.845， 0.814， 0.736， 0.800， 0.891， 0.794， 0.811， 0.772， 0.722， 0.908， 0.738， 0.725. ③ Hydrological similarity is positively correlated with the characteristic indexes. The coefficient of determination of terrain moisture index， topsoil PH and hydrological similarity regression equation are 0.573 3 and 0.894 6， respectively， showing a significant and high correlation， while the other characteristic indexes are weakly correlated with hydrological similarity. The research results are of great significance for hydrological forecasting and parameter transplantation in areas without data in Fenhe River Basin.

Flood forecasting is crucial for flood prevention and mitigation in both watersheds and urban areas. In watersheds， the development of flood forecasting methods is relatively mature， while their application in urban areas is still in the research and exploration stage. In practice， high-precision hydrological and hydrodynamic modeling during large floods is constrained to varying degrees by power， timeliness， and transmission conditions， whereas the unit hydrograph method is simple， efficient， has fewer constraints， and plays an important role. To address the current situation， this study introduces an improved synthetic unit hydrograph method to evaluate its practical effectiveness in watershed and urban flood forecasting. Firstly， based on the Snyder's synthetic unit hydrograph method， the flooding process in Muyangxi watershed in Fujian Province was calculated and compared with the results of the Xin'anjiang model and the measured data； secondly， based on the Snyder's synthetic unit hydrograph method， the urban synthetic unit hydrograph was established by taking into account the impermeability of the sub-surface and the slope， which was then applied to the calculation of the flooding process line in the urban area of Zhengzhou， and the differences of the simulation results between this method and the mainstream SWMM model were compared. The differences between this method and the mainstream SWMM model simulation results are compared. The results show that the synthetic unit hydrograph method is close to the measured and hydrological model results in the selected watersheds， and the forecast pass rate is 91.7%， with no peak-present time difference； compared with the SWMM model results， the relative error of the peak flow of the most floods is within 10%， and the coefficient of certainty of the floods in 72.7% is above 0.9. The example application shows that compared with the hydrological and hydrodynamic modeling methods， the partial rise and fall process of the flood calculated by the synthetic unit hydrograph method is better than the model results， which are more in line with the actual process， and its calculation is concise. The synthetic unit hydrograph method requires fewer parameters， and has strong implementation and popularity. The research further verifies the superiority of the synthetic unit hydrograph method in flood forecasting and provides an effective method for flood process calculation.

The prediction of sediment concentrations is of significant importance for watershed sediment control， water-sediment regulation， as well as water quality and environmental management. The upper reaches of the Yangtze River， vast area in size and abundant in tributaries with complex water and sediment sources， pose a great challenge to accurately predict the process of suspended sediment concentration （SSC） entering the Three Gorges Reservoir. In this study， we propose a deep learning model named RF-LSTM， which combines Random Forest （RF） algorithm and Long Short-Term Memory （LSTM） neural network for daily SSC prediction at Cuntan station. This model addresses the varying impacts of rainfall in the upper reaches of the Yangtze River， as well as the inflow of water and sediment from its main stream and tributaries， on the daily SSC observed at the station. Firstly， the RF algorithm is employed to identify water and sediment factors that exhibit a strong correlation with the SSC at Cuntan. These factors are then utilized as input variables for the LSTM neural network to discern the mapping relationship between the optimized set of factors and the SSC at Cuntan. Finally， the model is applied in the region spanning from Xiangjiaba to Cuntan of the upper Yangtze River to predict the daily SSC during flood season at Cuntan station under different forecast periods. Results show that， compared to the LSTM model， the RF-LSTM model can better account for the lagged effects of the predictor factors on the SSC， and effectively capture the features that are strongly correlated with the SSC at Cuntan station. Under all the four different forecast horizons considered， the RF-LSTM exhibits superior performance in terms of both prediction accuracy and overall capability. Specially， when considering no-forecast and 1-d forecast horizons， both models exhibit high prediction accuracy， with Nash-Sutcliffe efficiency coefficients exceeding 0.82 during the validation period. Notably， the RF-LSTM model achieves a Nash-Sutcliffe efficiency coefficient of 0.91 in the no-forecast horizon， outperforming the LSTM model by reducing mean absolute errors and root mean square errors by 8% and 13%， respectively. Furthermore， under both of these forecast horizons， the RF-LSTM model more precisely captures SSC peaks and their occurrence timings. However， as the forecast horizon increases to 2 days and 3 days， the accuracy of both models decrease significantly. Nevertheless， the RF-LSTM model continues to outperform the LSTM model in terms of computational accuracy， demonstrating its robustness and reliability across different forecast horizons. These findings highlight the potential of the RF-LSTM model as a valuable tool for SSC prediction in the upper reaches of the Yangtze River， offering a valuable reference for future studies in this domain.

Hydrological model is an important tool for flood simulation， and most of the models contain a certain number of parameters. Therefore， parameter calibration is one of the keys to improve the precision of hydrological model runoff simulation and ensure the accuracy of model results. As the optimization standard of parameter calibration process， there is currently no detailed classification system to provide a clear selection basis for the selection of objective function. In order to explore the effects of different types of objective functions on the calibration results of hydrological model parameters and the precision of runoff simulation， this paper comprehensively considered various types of objectives， such as Nash efficiency coefficient， Kling-Gupta coefficient， flood relative error， etc.， and constructed an objective function classification system that includes high flow target， low flow target， flood volume target， flood process target and weighted target. According to the requirements of the current hydrological forecast information standard， some criteria were provided for the selection of objective function. Further， the Xinanjiang model was established， and the optimization algorithms of SCE-UA and NSGA-II were introduced. A variety of objective function selection schemes were set up for different algorithms， and the influence of different objective function schemes and optimization algorithms on the precision of runoff simulation was analyzed by taking Muma River in Hanjiang River basin as an example. The results show that using a single objective function can improve the simulation accuracy of hydrological elements embodied by the objective function； Selecting the appropriate objective function is the key to improve the precision of runoff simulation. Under the requirements of existing norms， selecting flood process target and high flow target is the best choice to ensure the accuracy of hydrological model. Compared with Nash efficiency coefficient， Kling Gupta coefficient has better performance in flood volume simulation accuracy and is a better choice for flood process target. The simulation results of weighted single target method and multi-target method are different in the high-flow part.

The Songhua River Basin is an important grain production base and ecological region in China， and studying its water supply and water quantity changes is of great significance for achieving scientific water allocation and ecological environment protection in the basin. This study employed the CSR RL06 Mascon data products derived from the GRACE and GRACE-FO gravity satellites from 2003 to 2020. For the missing data between GRACE and GRACE-FO， published reconstructed data were used to fill the gaps. The accuracy of the data in the study area was validated through comparison with GLDAS simulated water storage data. Based on this， the spatial and temporal variation characteristics of terrestrial water storage in the basin were analyzed using a combination of Theil-Sen and Mann-Kendall trend tests. Additionally， the Pearson correlation coefficient and geographical detector methods were utilized to delve into the influence of various factors， including precipitation （Pre）， evapotranspiration （ET）， population density （POP）， normalized difference vegetation index （NDVI）， ecological zones （Ez）， and digital elevation model （DEM）， on terrestrial water storage. Furthermore， aiming to address the issue of errors introduced by resampling when performing correlation analysis on remote sensing data of different resolutions， the traditional raster data resampling method was optimized. The research findings indicate the following： ① The GRACE data products exhibit good accuracy in the study area， and the linear trend range of their changes exhibits a high correlation with GLDAS data. ② The optimized resampling method is more suitable for spatial studies similar to Pearson correlation analysis， and it significantly improves the accuracy of most data compared to directly using raw data. ③ The water storage in the Songhua River Basin has shown an increasing trend during the study period， with a noticeable increase in the extreme value ratio. By the end of the study period， the spatial distribution of water storage in the region tended to stabilize， exhibiting a basic pattern of more water in the northeast and less in the southwest. ④ The primary individual factors causing changes in water storage in the basin are precipitation and evapotranspiration， and the combined effects of most factors manifest as nonlinear enhancement.

Canopy interception is an important part of forest rainfall redistribution and is of great significance to the study of water balance and nutrient cycle in forest ecosystems. In recent years， many studies use different methods to explain this process and determine the suitable models for different forest vegetation， but there are few studies on canopy interception of wild peony shrubs with complex structures. This study collected meteorological and rainfall data through field observation， analyzed the composition characteristics of rainfall over the Melastoma candidum shrubs， simulated and verified canopy interception using a modified Gash model， and tested the sensitivity of the model. The results showed that the modified Gash model could well simulate the rainfall interception process over the shrubs. The measured throughfall and stemflow were 632.6 mm and 118.2 mm， resulting in 141.4 mm canopy interception， accounting for 70.9%， 13.2% and 15.8% of the total rainfall， respectively. Strong linear relationships were established between total rainfall and throughfall and stemflow， which indicated that they increased with the increase of total rainfall， and the quadratic function was used to fit the total rainfall and canopy interception（R ²=0.71）. Meanwhile， a logarithmic relationship was observed between total rainfall and the ratios of its three components and the simulation of throughfall was 3.6% higher than the measured values， while stem flow and canopy interception was 10.6% and 7.3% lower than the measured values， respectively. From the various components of the model simulation， the evaporation of intercepted rainfall accounted for 44.4% of the total interception， which was the main compartment of interception. At the same time， sensitivity analysis showed that the changes of canopy density c and trunk water holding capacity S_t had significant influence on the simulation of canopy interception by Gash modified model compared to other parameters.

From 2011 to 2023， a total of 20 ecological operation experiments of artificial flood peak were conducted in the Lower Jinsha River-Three Gorges cascade reservoirs， focusing on the fish spawning， and a lot of experience was accumulated while achieving good experiments results. In order to systematically figure out the effectiveness and experience of the ecological operation experiments of artificial flood peak over the years， this paper takes the Lower Jinsha River-Three Gorges cascade reservoirs as an example. First， the principles， key points， monitoring and evaluation methods of the ecological operation experiments of artificial flood peak were introduced. Second， the development of operation experiments over the years was reviewed. Finally， the operation experience was summarized and the future optimal direction was proposed. The results showed that the ecological operation experiments of artificial flood peak in the Lower Jinsha River-Three Gorges cascade reservoirs effectively promoted the spawning of fishes spawning drifting eggs in the Yangtze River. The effect of promoting the natural spawning of the representative fishes spawning drifting eggs——the four major Chinese carps under the dam is the most significant in the Three Gorges Reservoir. By 2023， the total spawning scale of the four major Chinese carps in the middle reaches of the Yangtze River reached 38.25 billion. Under the joint promotion of multi-year ecological operation practice and 10-year fishing ban plan， the fish resources of the four major Chinese carps is close to the level of the 1980s. However， under the influence of climate change， fish spawning and developmental characteristics change， spawning ground change and other factors， the ecological operation experiments of artificial flood peak need to carry out targeted optimization and adjustment in the aspects of operation process optimization， operation effect evaluation， and operation effect improvement. The results can provide a reference for the ecological operation of artificial flood peak for fish spawning in similar basins under changing environment.

Net cage aquaculture has a significant impact on the regional water environment， and studying the changes in water quality parameters in net cage aquaculture areas is of great practical significance for understanding the impact of regional aquaculture on the water environment. This article uses GF-1WFV data to construct an inversion model for the total suspended solids concentration in the net cage aquaculture area， which has grown exponentially in the Manwan Reservoir area in recent years. The results indicate that the model has high accuracy， with an average relative error of 9.65% between the inverted values and the measured values， and a root mean square error of 0.33mg/L. Based on the constructed inversion model and satellite imagery， the total suspended solids concentration in the Manwan net cage aquaculture area was inverted， and the variation patterns of total suspended solids concentration in the reservoir area and different net box positions were analyzed. Research has found that the variation pattern of suspended solids concentration in the Manwan reservoir area and different positions of net cages is basically consistent. The total suspended solids concentration in net cages has not shown any abnormalities due to the phenomenon of local “delineation” in aquaculture， but is lower than the overall suspended solids concentration in the reservoir area. This is mainly because the variation of total suspended solids concentration is mainly affected by precipitation， surface runoff， water flow velocity， etc. Net cage aquaculture can reduce its impact on the total suspended solids concentration in local “delineation” areas. This study has certain reference significance for understanding the changes in total suspended solids concentration in the Manwan reservoir area and net cage aquaculture area. In the future， a multi-source remote sensing data remote sensing estimation model for water quality parameters will be developed for understanding the changing patterns in water environment in the Manwan net cage aquaculture area.

The coastline of the Yellow River Delta has undergone significant alterations due to fluctuations in fluvial water and sediment conditions. To analyze changes in the coastline of the Yellow River Delta from 1976 to 2020， this study considered the effects of various factors， such as tide levels， water calculation indices， and high and low tide stages on coastline extraction. Coastlines were extracted utilizing tools like ArcGIS and ENVI， and the Digital Shoreline Analysis System was used to quantify the coastline characteristics. The study found that selecting remote sensing images with good imaging quality and similar tide levels during the ebb phase， along with the use of the Modified Normalized Difference Water Index for calculation， resulted in higher accuracy in coastline extraction. Based on the extracted coastline data， it was found that the coastline of the Yellow River Delta has undergone spatio-temporal variations. The Shenxiangou-Diaokouhe lobe coastline has been eroding since 1976， while the coastline from Dongying port to Gudong oilfield has remained stable since the 1990s due to an artificial seawall for protection. The changes in the coastline near the estuary were found to be related to the amount of fluvial sediment. When there was enough sediment， the coastline tended to accumulate or deposit， while it eroded and retreated when there wasn't enough sediment. Other factors， such as deltaic channel avulsions and oceanic dynamics， also had an impact on the coastline of the Yellow River Delta. The findings of this study can serve as valuable guidance for future comprehensive management planning of the Yellow River Delta.

The Jialing River， a key watershed in the upper Yangtze River， faces challenges in maintaining stable water quality due to its extensive area and issues such as agricultural and cross-border pollution. This study examines the water quality variations in the Jialing River's main course and its two major tributaries， Fujiang and Qujiang， using 2021 monitoring data for five water quality indicators： dissolved oxygen， permanganate index， ammonia nitrogen， total phosphorus， and total nitrogen， across 48 river sections. Methods including Fuzzy Comprehensive Evaluation， Nemerow Index， and Nearest Neighbor Analysis were applied. The findings reveal that： ① The Fuzzy Evaluation method effectively demonstrates the impact of each indicator on various water quality standards. ② In the study area， 38 sections are rated below Grade III for total nitrogen， and one section is rated Grade IV for permanganate index， indicating significant pollution of total nitrogen and exceedances of permanganate standards. Agricultural activities are identified as a major contributor to the exceedances of these two indicators. The remaining three indicators meet the water quality control standards for the Jialing River. ③ Spatially， the sections with Class III water quality are the least in the main stream， indicating relatively optimal water quality， while the Fujiang exhibits the poorest water quality. Class V sections are mainly distributed in the middle and lower reaches， with better water quality in the upper reaches of the watershed. ④ Seasonally， the water quality of river sections categorized as Class III deteriorated during the dry season， with an increase of three sections compared to the wet season. The water quality during the dry season exhibited greater instability. Specifically， the Fujiang demonstrated relatively stable water quality throughout the year， whereas Qujiang exhibits a decreasing trend in the number of Class V sections from July to December， indicating an improvement in water quality during the year. Conversely， the main stream shows an increase in the number of Class V sections from July to December， suggesting a declining trend in water quality during this period. These results offer valuable insights for pollution control and aquatic ecosystem restoration in the Jialing River basin.

A modified DRASTIC model， named DRASTLZ， has been proposed to better assess the sensitivity of groundwater systems to pollution by replacing the vadose zone media type （I） and hydraulic conductivity of the aquifer （C） with land use type （L） and groundwater quality （Z） indicators. First， a scoring system for the DRASTLZ model was established， assigning different weights to seven influencing factors. Using the ArcGIS platform， collected data were processed and statistically analyzed. Evaluation score maps were constructed for seven assessment indicators： groundwater depth （D）， net recharge of groundwater （R）， aquifer media （A）， soil media （S）， surface slope （T）， land use type （L）， and groundwater quality （Z）. These maps were then overlaid， and the composite vulnerability index of Juxian County was calculated according to the assigned weights. The natural breaks classification method was employed to divide the area into five vulnerability zones： low vulnerability， relatively low vulnerability， moderate vulnerability， relatively high vulnerability， and high vulnerability. The groundwater vulnerability assessment for Juxian County was thereby completed. The calculated results indicate that the overall vulnerability of groundwater in Juxian County is relatively high， with the highest proportion （approximately 38%） falling in the high vulnerability zone， followed by moderate vulnerability （36%） and high vulnerability （15%） zones. The proportions of relatively low and low vulnerability zones are smaller， accounting for 10% and 1%， respectively. There is a positive correlation between groundwater vulnerability assessment results and the exceedance of water quality sampling points， suggesting the applicability of the developed DRASTLZ model in Juxian County closely reflects actual conditions. The successful application of the DRASTLZ model provides valuable experience and guidance for future groundwater vulnerability assessment studies in similar regions.

Studying the complex flow field structure and its impact on leaf movement characteristics in shallow embankments and deep pools is of great significance for the construction of ecological waterways. To study the flow field structure and leaf movement characteristics of different forms of shallow embankments and deep pools， combined with the shallow embankments and deep pools habitat construction plan of the Chaotianmen to Fuling River section in the upper reaches of the Yangtze River， a water tank experiment was designed by adjusting the length of the shallow embankments （L） to change the river width narrowing ratio （N）， the distance between the shallow embankments （S）， and the degree of submergence of the shallow embankments （Z）. The flow field structure and leaf trajectory characteristics were compared and analyzed. The research results indicate that： ① The characteristics of the reflux zone and the flow velocity gradient are key factors affecting the movement of leaves， and most leaves move in areas with larger flow velocity gradients. ② When the shallow embankments are not submerged， the range and average flow velocity of the reflux zone in the upstream deep pools are larger than those in the downstream deep pools. A length to width ratio of 3∶1 in the reflux zone is most conducive to the leaves entering the deep pools. ③ As the narrowing rate of the river increases， the flow velocity gradient in the watershed near the head of the shallow embankments increases， and the probability of leaves entering the deep pools gradually increases. ④ When the shallow embankments are submerged， it is difficult for the deep pools area to form a backflow zone， and the water drop process that occurs at the top of the shallow embankments makes it difficult for the soaked leaves to remain in the deep pools. ⑤ The probability of leaves entering the deep pool is an important indicator for evaluating the shallow embankments deep pools habitat. N=0.33 and S=3 L are proposed as the optimal solutions for the shallow embankments deep pools habitat. The height of the shallow embankment （D） can be appropriately increased， which is conducive to the enrichment of organic floating substances such as leaves. The research results can provide scientific reference for subsequent research on the habitat construction plan of shallow embankments deep pools fish.

In order to explore the drag reduction characteristics of different jet parameters in the bulb through pump， the bionic design was carried out for the shark gills， and the model of the bulb through the pump with a jet port at the front end of the bulb body was established， and the influence mechanism of the placement position， jet velocity and number of jet ports on the flow field of the bulb through the pump was studied by CFX. The results show that the near-wall main stream collides with the jet， and the axial momentum transmitted by the main stream to the jet weakens the axial velocity of the near-wall main stream. The radial momentum of the jet to the main stream increases the radial velocity of the near-wall mainstream， and lifts the near-wall high-velocity zone away from the bulb body， so that the near-wall medium and low velocity bands are widened， the high-velocity zone is contracted， and the wall shear stress is reduced. The calculation predicts that the drag reduction effect is up to 23.069%， the head is increased by 0.083 m， and the efficiency is increased by 1.729%， which can provide guidance for the optimal design and efficient operation of the bulb through-flow pump.

In an effort to suppress cavitation in low-specific speed centrifugal pump， a method of changing the axial angle of slotted blade was proposed， and three oblique slotted blade schemes were designed. By using numerical simulation methods to compare the experimental results of centrifugal pumps， analyze the effect of blade oblique slotting on the suppression of cavitation in centrifugal pump. The simulation results show that the oblique slotted blade with an axial angle of 5° has the most significant cavitation suppression result on low-specific speed centrifugal pump， and the fracture head is increased by 0.281 m. The oblique slotted blade suppress the development of cavitation in the flow field of the centrifugal pump impeller， and the maximum reduction in cavitation volume is 67.25% during the severe cavitation stage； The oblique slotted blade optimize the flow field structure of the impeller， reduces the low-pressure area at the impeller inlet， and reduces the turbulent kinetic energy in the impeller channel.

Considering the real stress and deformation state of impeller during the operation of centrifugal pump， the fluid-structure coupling numerical simulation of impeller of centrifugal pump model was carried out based on the software platform of Ansys Workbench and the computational fluid dynamics analysis software CFX. The strength of impeller of centrifugal pump under the combined action of centrifugal force and CFD pressure load was calculated. The position of the maximum stress on the impeller under the action of cyclic alternating stress during rotation is determined. Finally， nCode Designlife software was used to predict the fatigue life of the impeller. The results show that the maximum stress is located at the interface between the blade outlet edge and the cover plate， and the cyclic cyclic stress is the main cause of the fatigue damage of the impeller. The impeller meets the design of infinite life fatigue strength， and the impeller has no risk of fatigue failure.

In order to investigate the influence of cutwater on the hydraulic performance of the pump as a turbine （PAT） and improve the performance of the pump operated in reverse as a turbine， a single-stage single-suction centrifugal pump with a specific speed of 69 was selected as the research object. Nine schemes， including the original model， with variations in cutwater placement angle and cutwater radius， were designed. Using the SST k-ω model， numerical simulations of the entire flow passage were conducted for each scheme. Entropy production diagnostic analysis was introduced to analyze the variations in head， efficiency， and internal flow field of the PAT under different schemes. The research results show that within a certain range， increasing the cutwater placement angle leads to a significant reduction in head of the hydraulic PAT in the larger flow rate range. In this PAT， when the cutwater radius is 1.5 mm， the entropy production loss inside the impeller and volute is reduced， resulting in an increase in PAT efficiency.

To solve the complex problems of low scheduling efficiency， poor peak shaving capacity， and low power generation stability faced by cascaded small hydropower stations near remote rural areas， an improved honey badger algorithm （IHBA） is proposed. While considering the above problems and ensuring traditional hydraulic constraints， special power generation constraints such as peak summer and self-supplied area power supply are considered， and multi-objective optimization scheduling is carried out in this research. Firstly， initialization is achieved through Fuch chaotic mapping to ensure a uniform distribution of initial solutions. Secondly， in the update stage， the Golden Sine， Harris Eagle Siege， and T-distribution perturbation strategies are introduced to enhance optimization ability and improve the quality of search solutions. Then， combining non-dominated sorting and the ideal point method to solve multi-objective problems. Finally， IHBA will be applied in the scheduling of cascaded small hydropower stations in a rural area of Hunan Province compared with the actual scheme for verification. The results show that considering the three indicators of annual power generation， guaranteed output， and power generation guarantee rate， the proposed method can effectively improve the comprehensive efficiency of power generation， and compared to actual scheduling， and it can improve the power supply capacity of the self-supply area and the ability to meet the summer peak during peak hours， while increasing the efficient power generation of upper-level reservoir type power stations by raising the water head， and reducing the inefficient power generation of lower-level runoff type power stations.

In response to the lack of fault diagnosis methods for bulb tubular hydroelectric units， this study utilizes a rotor fault simulation platform to simulate typical faults within these units as the basis. This research combines the Subtraction-Average-Based Optimizer （SABO） with Chaotic Mapping， to enhance Variational Mode Decomposition （VMD） for decomposing raw data. The components obtained are then analyzed using multiscale sample entropy， with the results fed into a BP neural network optimized by a multi-strategy improved Butterfly Optimization Algorithm （BOA） for fault diagnosis and classification identification. The results demonstrate a diagnostic accuracy of 98.75%， significantly superior to non-optimized models. This research provides a valuable addition to the existing fault diagnosis methods for bulb tubular hydroelectric units.

To improve the dynamic performance of the hydroelectric unit regulation system （HURS）， a method for optimizing the parameters of the HURS is proposed， which integrates Q-learning and gradient search JAYA algorithm （QJAYA）. The equivalent circuit theory is introduced to derive the equivalent model of the pressure pipeline circuit. A hydroelectric turbine neural network model， reflecting the nonlinear characteristics of turbine flow and torque adequately， is established using BP neural networks. Subsequently， combining with the governor and generator models， a refined nonlinear model of the HURS as a whole is constructed. The QJAYA algorithm is utilized to optimize the PID control parameters of the HURS， and through simulation experiments， it is verified that the proposed method can effectively improve the dynamic performance of the HURS.

Vibration trend prediction of hydropower units is of great significance to ensure the safe and stable operation of hydropower units. To address the limitations of existing models for predicting the vibration trend of hydropower units. In this paper， we propose a combined trend prediction model based on adaptive multivariate variational mode decomposition （WOA-MVMD） and bidirectional short-duration memory neural network （BiLSTM）. The model adopts multivariate variational modal decomposition （MVMD） to decompose multi-channel data synchronously， retains the coupling between the original data channels， adopts whale optimization algorithm （WOA） to optimize the selection of MVMD decomposition parameters， avoids the shortcomings caused by manual parameter selection， and realizes the optimal adaptive decomposition of vibration sequences. A series of IMF sub-sequences obtained from modal decomposition are normalized. Then the BiLSTM trend prediction network is established for each subsequence signal， and the final prediction result is obtained by superposition and reconstruction of the subsequence prediction results. Based on the actual operation data of a power station in China， the proposed model is proved and tested， and the high prediction accuracy of the proposed model has been verified.

Rotating machinery is an important component of mechanical equipment， and misaligned rotor systems are a key factor leading to equipment failures. If there is a misalignment fault during operation， it may have various adverse effects on the stable operation of mechanical equipment， such as causing dynamic and static friction between the rotor and stator， bearing friction damage， shaft bending deformation， oil film oscillation， vibration， etc.， all of which may seriously interfere with the stable operation of mechanical equipment. Studying the mechanism and vibration characteristics of misalignment faults in rotor systems is particularly crucial for accurately judging and mastering the operating conditions of the rotor system. This article focuses on the parallel misalignment fault of the rotor system of a hydroelectric generator set and the collision friction coupling fault between the rotor system of the generator set. Based on nonlinear rotor dynamics theory and the motion mechanism of parallel misalignment faults， a nonlinear dynamic model of the rotor system of a hydroelectric generator set is constructed， which considers the influence of parallel misalignment and collision friction coupling faults. The model explores the nonlinear dynamic performance of the generator rotor system under multiple parameter changes such as unit speed， eccentricity， and parallel misalignment.

Pumped storage power stations have flexible functions such as peak shaving， frequency regulation， phase modulation， and emergency backup， which can suppress the fluctuation of new energy output， promote new energy consumption， and improve the safe and stable operation level of the power grid. However， under the current two part tariff system， the rotating reserve value of pumped storage power stations in the power grid has not been fully reflected. This article takes the complementarity of wind power， photovoltaic， and pumped storage power stations as the background， constructs a day-ahead scheduling model for pumped storage power stations considering the requirement of rotating reserve. The goal is to maximize the operational revenue of the pumped storage power station and minimize the peak valley difference in the output of other power plants in the power grid. By using the weight method， the multi-objective problem is transformed into a single objective optimization problem to solve. Furthermore， the impacts of the current two part tariff and peak valley electricity price on the scheduling strategy and the operational profit of pumped storage power stations are analyzed and compared. The calculation results show that considering the requirement of rotational reserve can significantly improve the operating profit of pumped storage power stations， and the scheduling objectives have a significant impact on the operation mode of the power station. The model and method in this paper can be used to make the day ahead scheduling of pumped storage power stations.

Based on one-dimensional water hammer theory and combined with an engineering example， the selection of the flow characteristics of the end control valve of gravity flow system with wide-range flow variation is numerically studied from three aspects： the influence of flow characteristics of control valve on its steady-state opening-degree， the determination of the most unfavorable flow conditions of valve-closing water hammer， and the influence of flow characteristics of contrive valve on valve-closing water hammer. And the flow characteristics of linear type， parabola type and equal percentage type are compared. The results show that： ① The equal percentage flow characteristic is more conducive to the stable operation of the control valve under the low flow condition. Under this condition， the steady-state opening-degree of the equal percentage type control valve is larger， which can avoid cavitation and vibration caused by too small opening. ② The most unfavorable flow condition of the valve-closing water hammer should consider the minimum initial flow condition， under which the water hammer pressure of the input point of the control valve is largest because of the largest initial pressure and the shortest closing time. ③ The equal percentage flow characteristic is more conducive to reducing the control valve-closing water hammer pressure. Under the same initial flow rate and valve closing rate， the control valve with equal percentage type flow characteristics has a larger initial opening-degree， a longer actual closing time， and a smaller change gradient of flow coefficient in the small opening-degree range， so the extreme value of the valve-closing water hammer pressure is smaller， which is more conducive to pipeline safety.

The numerical simulation of model I stress intensity factor for SENB specimens with different aspect ratios was carried out by using finite element software ABAQUS. The research explores the effect rules of fulcrum friction on the dimensionless stress intensity factor Y _I and the dimensionless T stress T* of SENB specimens. The results show that the values of Y _I and T* increase gradually with the increase of the aspect ratio of the specimen， and the increase of the friction coefficient leads to the decrease of Y _I. When the sample with small length-to-width ratio is subjected to fulcrum friction， T* will decrease and the fracture trajectory will be more stable. Through the compacted clay mode I fracture test， the experimental results with and without the fulcrum friction effect are compared， and the accuracy of the numerical simulation is verified.

Urban drainage culverts， suffering from years of disrepair and constrained by the conditions above them， are often repaired using in situ methods. The selection of the timing for diversion is a key issue concerning the safety of in situ culvert repair construction. This paper considers risk factors such as construction technology and duration， diversion methods， and construction periods， and establishes a risk measurement model for the diversion process. By analyzing the uncertainty of diversion risk factors and comparing the construction periods with the risk change process， a risk analysis model for diversion during in situ culvert repair construction is established， providing a reference for the timing of urban culvert repairs.

Traditional water pipe settlement meters mainly measure water levels through pressure sensors to calculate the settlement within the dam. However， it has the problem of poor measurement stability. To address these shortcomings， a water level measurement method for water pipe settlement meters based on deep learning is proposed. This technology includes a specially designed water gauge and corresponding algorithms. The method involves segmenting the water gauge from top to bottom using a camera and selecting the image containing the water level line. A QR code is used to correct the angle of the image and separate the water gauge， simultaneously， and centimeter-level water level coordinates are obtained. Based on the UNet model， an image matting model is used to accurately segment the water level. Finally， a YOLOv5 model is employed to identify millimeter-level coordinates on the gauge. Experimental results demonstrate that this technology has strong environmental adaptability. The measurement error is less than 0.3 mm compared to manual readings， meeting the requirements of practical engineering applications.

The shape of the connecting section of the shaft spillway directly affects the flow pattern of the tunnel， the vibration characteristics of the shaft and the energy dissipation effect. At present， the research on the shape of connecting section is mostly single factor， and few multi-factor studies. In engineering design practice， the optimization of shaft shape mostly refers to similar engineering experience， and there is no more systematic optimization method. In this paper， the numerical orthogonal test is used to analyze the sensitivity of the length-width ratio， the contraction ratio of the exit pressure slope and the compression slope ratio of the connecting section. The results show that the length-width ratio has the most significant effect on the outlet turbulent kinetic energy， followed by the compression slope ratio and the lowest contraction ratio. The research results can provide some reference for the optimization of the joint shape of the shaft spillway tunnel in engineering design.

The shape design of arch dams requires consideration of multiple complex factors， such as the shape of the valley at the dam site， engineering geological conditions， regional seismic intensity， hub layout， and flood discharge methods. Therefore， the shape design of arch dams is a typical complex optimization problem. In this paper， a general parametric design method of arch dam shape is proposed， which can describe all kinds of arch dams such as parabola and hyperbola. By fixing the position of the arch end and adjusting the position， shape， and thickness of the arch crown beam to drive the shape change of the arch dam， automatic modeling and finite element stress deformation calculation of the arch dam are achieved. Taking the minimum volume of the arch dam as the optimization objective， intelligent optimization of the arch dam shape is carried out under constraints such as geometry， stress， and stability. Using this method to optimize the shape of a high arch dam， the optimization efficiency is high and the optimization effect is obvious. The stress of the optimized arch dam body and the equivalent stress of the foundation surface meet the requirements of the specifications， and the flexibility coefficient and stress level also meet the indicators recommended by experience.

For the disaster prevention and control problems of down-gradient slopes， a pre-reinforcement structure of yielding anchor pile with a flexible material bedding layer between the soil body of the slope and the anchor cables as well as the anti-slip piles is used. The finite element numerical model is constructed to analyze the effects of the modulus of elasticity （E ₁） and thickness （D） of the let-shear layer and the modulus of elasticity （E ₂） and thickness （d） of the let-shear layer on the load-bearing capacity of the yielding anchor pile. The results show that the horizontal displacement， internal force and axial force of anchor cable of yielding anchor piles are significantly reduced compared with those of ordinary anchor piles， and the smaller E ₁ and E ₂ or the larger D and d are， the horizontal displacement， internal force and axial force of anchor cable are reduced， and the peaks of shear force and bending moment of the pile body are in the middle and lower parts of the pile body. The sensitivities of the factors affecting the load-bearing capacity of yielding anchor piles are D， E ₁， d， E ₂ in order.

Based on Terzaghi-Rendulic's axisymmetric consolidation theory， a radial consolidation coefficient calculation method is proposed， and a calculation formula is provided， followed by experimental verification. Firstly， the calculation formula of the radial consolidation coefficient was derived based on the relationship between radial consolidation degree and time factor. Then， using the GDS consolidation test system， radial drainage consolidation tests under different consolidation pressures were conducted， and displacement-time curves were obtained. Finally， the calculation method proposed in this paper was used to calculate the radial consolidation coefficient under various consolidation pressures， and the theoretical solutions were compared with experimental data. The results indicate that the computational method proposed in this paper is feasible and can accurately predict the time-dependent displacement of samples undergoing radial drainage consolidation.

This study investigates the intricate interactions between strip spacings， water-fertilizer treatments， and the ensuing impact on the physiological attributes and productivity of maize and soybean intercropping systems. Implementing a 2∶4 maize-soybean planting configuration within the Ningxia Yellow River irrigation zone， the research scrutinizes the effects of strip spacing （A）， irrigation allocation （W）， and fertilization intensity （F） on the physiological dynamics， net assimilation rate， leaf area index， and yield metrics of both crops and their integrated systems. It aims to provide comprehensive technical insights for the widespread application of strip intercropping strategies in maize and soybean agroecosystems. Findings reveal nuanced influences， notably the dominant effects of A during critical growth stages of maize （contributing rates of 75.6% to 83.7% during jointing and 52.4% to 81.3% during grain filling） and W primarily impacting the tasseling stage （contributing rates of 91.4% to 92.5%）. Moreover， A significantly shapes soybean physiological indices during flowering （contributing rates of 97.9% to 99.3%）， while W predominantly impacts pod setting （contributing rate of 70%）. Treatment T6（A2W3F1）， characterized by heightened irrigation and reduced fertilizer application， augments maize net assimilation rate （NAR） and leaf area index （LAI） but exhibits an inverse relationship with soybean LAI. The tripartite factors significantly influence both system yield and economic benefits， ranking in order of W>A>F. Notably， all levels of A and W significantly affect maize yield and system productivity， particularly A2>A3>A1 and W3>W2>W1， while the F level shows negligible impact on soybean yield. Contribution analyses underscore A2>A3>A1， W3>W2>W1， and F1>F3>F2 in terms of system economic benefits. Specifically， A2 presents a 25.2% higher benefit compared to A1， W3 demonstrates a 32.3% higher benefit than W1， and F1 exhibits an 11.2% higher benefit over F2.

Waterlogging is an important natural disaster that affects agricultural production， and the planning of farmland drainage facilities is crucial for disaster reduction. This research proposes an engineering layout method of integrated gate station external discharge control technology for the current situation of drainage engineering in agricultural waterlogging in China. This technology integrates strong discharge pumps on self-discharge gates， forming an integrated engineering layout mode. In addition， an optimization control equation and solution method for drainage were established to minimize energy consumption and find the optimal flow distribution combination and startup combination strategy. Through practical application， this technology can effectively reduce the cost of drainage and provide a new solution for the construction of agricultural drainage projects in China.