Branching channels are common in nature. After the construction of the upstream reservoir hub， the downstream clear water scouring causes the riverbed armoring of the branching channel to become normal. Therefore， it is of great significance to study the laws related to the riverbed armoring of the branching channel under the action of clear water. Through the flume test， it is found that in the dynamic process of the damage and formation of the armoring layer in the branching river bed caused by clear water scouring， the bed-load transport rate presents a fluctuating change of first increasing and then decreasing. And with the increase of flow， the peak value of the transport rate increases， the occurrence time is advanced， and the formation time of the armoring layer is shortened. The armoring degree of the main branch is higher than that of the branch， and the increase of discharge intensifies the damage of armoring layer， resulting in the overall increase of sediment diameter and the reduction of particle size distribution. In addition， the erosion and deposition of riverbed topography are significant. The main branch erodes violently and the branch deposits， and there is a dynamic balance between the flow and the riverbed topography.

Aiming at the freezing and thawing damage observed in dispersive soil canal slopes with high groundwater levels in seasonal frozen regions， we systematically investigated the frost-heave and thawing deformation characteristics of dispersive soils under varying initial conditions of temperature， moisture， and stress. The results indicated that： ① During the freezing process， as the temperature decreased， the freezing front of the dispersive soil advanced downward， and moisture within the soil migrated toward the freezing front， leading to ice formation. Ice layers and lenses were primarily distributed within the 1/2 to 2/3 depth range of the maximum frozen depth. ② The pore water pressure within the soil exhibited distinct periodic fluctuations in response to temperature changes， accompanied by a significant hysteresis effect. ③ Under identical conditions， as the dry density increased， the frost heave rate increased， the thaw settlement rate decreased， and the cumulative freeze-thaw deformation was reduced. ④ External water supply significantly influenced the frost heave process. Under conditions with external water supply， the frost heave rate of dispersive soil was 3 to 4 times higher than that without external water supply. ⑤ After three freeze-thaw cycles， greater overburden pressure resulted in a lower frost heave rate and a higher thaw settlement rate， indicating that overburden pressure effectively suppressed frost heave deformation. Based on the research findings， it is recommended that the anti-frost design of dispersive soil channel slopes in seasonal frozen regions should prioritize the impact of external water supply. Comprehensive measures， including thermal insulation， soil replacement， drainage， dry density control， and optimization of protective structure thickness， should be adopted to enhance frost resistance.

The uneven distribution of hydrological monitoring networks has resulted in a lack of long-term available streamflow monitoring data in most watersheds worldwide. However， traditional hydrological models and single machine learning models have poor simulation accuracy and generalization capability when simulating runoff in data-scarce watersheds. This study proposes a SWAT-LSTM-Transformer （SLT） coupled modeling framework that integrates physical mechanisms with data-driven approaches， implementing cross-basin knowledge transfer through transfer learning and innovatively introducing a rainfall-based peak flow identification correction method to enhance daily runoff simulation performance in data-scarce watersheds. Using the Hanjiang River Basin （a data-rich basin） as the source domain， a multi-feature input set was constructed， which includes seven hydrological variables simulated by SWAT （actual evapotranspiration， infiltration， surface runoff， etc.） and five meteorological factors （rainfall， temperature， etc.）. The SLT model demonstrated excellent simulation performance in both training and testing periods， with Nash-Sutcliffe efficiency （NSE） coefficients reaching 0.96 and 0.95， respectively. To address the streamflow data scarcity in the target domain of the Wusha River Basin（a data-scarce basin）， a cross-basin transfer learning strategy was designed： based on hydrological similarity analysis， the parameters of the pre-trained SLT model from the Hanjiang River Basin were transferred to the Wusha River Basin's SLT model， incorporating rainfall-based peak flow identification correction for runoff simulation at the Wanli station. Results show that the SLT model performed well in streamflow simulation at the Wanli station， achieving NSE values of 0.86 and 0.73 for the training and testing periods， respectively. Soil infiltration， rainfall， surface runoff， and soil moisture content significantly influenced the SLT model’s simulation performance. The established SWAT-LSTM-Transformer coupled model provides a viable approach for runoff simulation in data-scarce watersheds.

The tidal level in tidal river sections is influenced by multiple factors， including river hydrodynamics， astronomical tides， and meteorological conditions， with complex physical mechanisms that make precise forecasting challenging. This study develops a tidal level forecasting model on integration of mechanism-based and data-driven approaches. The Non-Stationary Harmonic Analysis Model （NS_TIDE） analyzes the seasonal and periodic characteristics of tidal level changes， accounting for the underlying mechanisms. This model provides a baseline for tidal level forecasting， ensuring the rationality of the predicted tidal level trends. The data-driven model， DRSN-LSTM， is constructed using Deep Residual Shrinkage Networks （DRSN） and Long Short-Term Memory Networks （LSTM）. It captures the impacts of multiple influencing factors on tidal levels and generates amplitude values for tidal changes. An Adaptive Genetic Algorithm （AGA） is employed to couple and optimize the forecasting results of the NS_TIDE and DRSN-LSTM models. The proposed model was applied to the entrance of the Qinhuai New River in the Yangtze River basin. By comparing the forecasting performance of NS_TIDE， DRSN-LSTM， and the coupled model under different forecast periods， the results demonstrate that the coupled model not only adheres to the physical laws governing tidal level changes but also simulates the effects of multiple influencing factors on tidal amplitude. For a 24-hour forecast period， the Root Mean Square Error （RMSE） for hourly forecasts in non-flood and flood seasons were 0.15 m and 0.18 m， respectively. During typhoon events， the average accuracy rate for forecasts with errors within ±0.30 m exceeded 80%. The coupled model exhibits high accuracy and practicality， ensuring the scientific validity and precision of hydraulic engineering operations in tidal rivers.

To achieve efficient resource utilization of construction waste residue （CWR） and address the issue of effluent pH reduction during the nitrogen removal process in a pyrite-enhanced bioretention system， a bioretention system was constructed using a composite medium composed of CWR and pyrite. This study investigated the impacts of varying dosing of CWR and different compositing approaches for the mixture medium on pollutant removal efficiency by bioretention system. Moreover， an optimal strategy for composite media was determined by analyzing microbial community composition and evaluating by-products control effects. The results demonstrated that the addition of 40% （V/V） CWR into the traditional medium resulted in an enhancement of 8.70% and 9.69% in the removal rates of NH₄ ⁺-N and TP， respectively. Nevertheless， due to alkaline leaching stress， there was a decrease of 5.27% in COD removal rate and emergence of NO₂ ^--N accumulation phenomenon. The integration of media significantly mitigated the alkaline stress effect caused by CWR， leveraged the strong adsorption capacity of CWR for nitrogen and phosphorus， and enhanced denitrification through the use of pyrite as an electron donor for autotrophic denitrification. Consequently， this strategy not only increased the α-diversity of the microbial community but also elevated the relative abundance of nitrifying genera （e.g.， Nitrospira） and denitrifying genera （e.g.， Denitratisoma and Bacilli）， while simultaneously inhibiting the growth of Thiobacillus and Thauera. As a result， the system's pollution removal efficiency was significantly improved， effectively addressing the issue of NO₂ ^--N accumulation in the effluent and achieving better control over effluent pH、TFe and SO₄ ^2- byproducts. Particularly， incorporating 40% （V/V） CWR in the planting layer along with 20% （V/V） in the submerged layer of bioretention system achieved superior decontamination performance with respective removal rates for COD、TP、NH₄ ⁺-N、NO₃ ^--N and TN being 84.49%、96.94%、91.83%、87.11% and 82.13% respectively. Additionally， all concentration levels for by-products remained below permissible limits.

Aerodynamic resistance represents the mass transport capacity of atmospheric turbulence in water-heat exchange， and its accuracy is important for modelling and estimation of land surface water-heat exchange. However， due to the absence of data of atmospheric stability， the existing studies usually estimate aerodynamic resistance based on the neutral stratification hypothesis， which would result in considerable uncertainties. Therefore， based on data at 187 global stations and the Monin-Obukhov similarity theory， Penman-Monteith equation， Thom model and nonlinear regression methods， this study constructed an aerodynamic resistance estimation model， which considers the effects of atmospheric stability and vegetation characteristics， and investigated the ecohydrological implications of the aerodynamic resistance estimation model based on comparing the estimated potential evapotranspiration using different aerodynamic resistance estimations. Results showed that： ① the mean equivalent aerodynamic resistance at the 187 flux stations was 44.6±24.6 s/m， while those estimated using the traditional method was 125.1±22.7 s/m， which considerably overestimated aerodynamic resistance； ② the land surface factors including canopy height（h_c ）， Leaf Area Index（LAI）， Normalized Difference Vegetation Index（NDVI） and Enhanced Vegetation Index（EVI） could express most of the variabilities in the aerodynamic resistance coefficient （R ²=0.81）， based on which the estimated mean aerodynamic resistance at the 187 stations was 57.8±51.9 s/m， which is significantly improved compared with the traditional method； ③ the potential evapotranspiration （PET） based on traditional aerodynamic resistance methods considerably underestimated PET （y=0.55 x）， while those based on the aerodynamic resistance coefficient model were very close to the truth （y=1.15 x）， especially in land surfaces with high canopy heights， such as deciduous broad-leaved forests， evergreen broad-leaved forests， and mixed forests，where the traditional method overestimated PET dramatically. These findings would be valuable for evaluating the interactions among land surface and atmosphere and for estimating water-heat exchange.

The Sixth Coupled Model Comparison Program （CMIP6） data is often employed to evaluate potential global-scale changes in climate variables. However， it is less efficacious in projecting changes at the regional level. The Ili River Basin in Xinjiang Uygur Autonomous Region of China （IRBC）， characterized by significant elevation variation and complex terrain， gives rise to considerable discrepancies in data analyses based on limited number of meteorological stations. Consequently， reliable meteorological data are essential for climatic and hydrological research. This study develops CMIP6 data into a new multi-model ensemble dataset by four approaches： reliability ensemble average （REA）， convolutional neural network （CNN）， random forest （RF）， and Bayesian model average （BMA）. Additionally， we employed performance indicators such as the Taylor Diagram， Taylor Skill Score （TSS）， and Kling-Gupta Efficiency （KGE） to identify the method with the best simulation effect on precipitation and temperature in the study area. The results demonstrate that the BMA dataset exhibits the most effective simulation of precipitation patterns across a range of extreme precipitation indices. In calibration period（1961-1999）， the annual total precipitation when daily wet day amount 95th percentile （R95PTOT） is the highest. In the validation period（2000-2014）， BMA's rank sum ratio （RSR） is 1.1， ranking first， indicating that its comprehensive simulation effect is the best. The KGE results of annual maximum consecutive 1-day （Rx1day） and 5 day precipitation （Rx5day）， and R95PTOT are 0.032， 0.39 and 0.52， respectively， which are all higher than the values obtained from other datasets. In the average temperature simulation， the RF dataset performed the best. The standardization deviation （SD）， the center root mean square error （CRMSE）， the correlation coefficient （r） and TSS in the calibration period are 1.005， 0.088， 0.996 and 0.49， respectively. These values represent the most favorable outcomes compared to other datasets. Similarly， the RF also outperformed others during the validation period， with a RSR value of 1.18. The findings of this study assess the efficacy of various approaches in simulating meteorological data within the study area. This can provide a usable method for the analysis of meteorological data in future scenarios and provide a scientific foundation for the management of meteorological disasters and water resources in the IRBC.

Combined supporting structures consisting of steel set and shotcrete are widely used in underground tunnels when the geological conditions are poor. However， there exist many difficulties in conducting nonlinear finite element analyses for the steel set due to its small size and dense arrangement. Therefore， according to the mechanical properties of the steel set， a four-node isoparametric element model of the steel set structure was proposed， and its mechanical action was simulated by stiffness superposition. Based on the Mises yield criterion and the secondary plastic flow model， an elastoplastic constitutive model was established to simulate the yielding and hardening behavior of steel set. The elastic damage constitutive model was used to simulate the damage softening behavior of concrete， and finally， a nonlinear numerical simulation method for the combined supporting structure of steel set and concrete was formed， which is verified to be reasonable by a planar circular tunnel example. This method was used to investigate the force characteristics of the combined supporting structure， and the results show that： when the surrounding rock pressure is small， the concrete is in an elastic state so it has a high bearing capacity and is the main bearing structure； when the surrounding rock pressure is large， the concrete undergoes compression damage， and the excess stress is transferred to the steel set， resulting in a significant increase in the stress of the steel set， and the steel set evolves into the main bearing structure； reducing the spacing between steel sets can to some extent reduce the steel set’s stress， slow down the development of concrete damage， and enhance the supporting effect of the combined supporting structure.

Global climate change has led to significant changes in hydrological cycle processes， resulting in an increased risk of hydrological droughts. Therefore， the study of hydrological drought changes under changing environments is of great significance for early warning of flood and drought and water resources management.Typical basins in north and south China （Xiangjiang river basin and Weihe river basin） are selected as the study areas.The period from 1982 to 2015 is selected as the base period （the historical period） and the period from 2030 to 2060 is selected as the future period. Five Global Climate Models （GCMs） provided by CMIP6 under the three scenarios of SSP126， SSP245 and SSP585 are selected to output the climate data for the future period.The Extreme Gradient Boost （XGBoost） is utilized to downscale the precipitation and temperature from GCMs to drive hydrological models to obtain streamflow in the future period， and then compare and analyze the evolution of hydrological drought characteristics in Xiangjiang river basin and Weihe river basin in different periods.The results indicate that， after downscaling by XGboost， the RMSE of simulated precipitation of Xiangjiang river basin and Weihe river basin are reduced by 57.6% and 51%， respectively， and the correlation coefficient with the measured values are improved by 20% and 32%， respectively. The RMSE of simulated temperature are reduced by 50.9% and 51%， and the correlation coefficients with the measured values are improved by 4.3% and 6.25%， respectively.The increase in precipitation in Xiangjiang river basin in the future period will increase the streamflow in this basin， thus alleviating hydrological drought， and the severity， duration， intensity and peak intensity of hydrological drought are reduced by 6.3%， 4.8%， 10.6%， and 6.5%， on average， compared with those in the historical period.In contrast to Xiangjiang basin， the increase in temperature and potential evapotranspiration decreases the streamflow in Weihe river basin.Therefore， Weihe river basin will face a greater risk of drought in the future period. Among the selected scenarios， the drought is the most severe under the SSP585 scenario. Compared with the historical period， the severity and duration of drought will be increased by 72.7% and 30.8%.

In deep buried water diversion tunnels， there are limited measures for preventing and controlling rock burst risks of TBM construction. Once an extremely strong rock burst occurs， the TBM machinery will be buried. Therefore， it is of great significance to study rock burst risk prevention and control measures suitable for TBM excavation. This paper proposes a method of using drilling and blasting pilot tunnels for stress release in the construction of deep buried water diversion tunnels. The stress adjustment process induced by drilling and blasting pilot tunnel excavation and full section excavation methods （single drilling and blasting or TBM method） was compared. The evolution law of strain energy near the TBM excavation face induced by pilot tunnel excavation was analyzed. The results show that the excavation of pilot tunnel reduces the degree of strain energy accumulation near the TBM excavation face， and the peak accumulation position of strain energy is far away from the tunnel surface， which will make the TBM excavation face in the stress release area and reduce the risk of rock burst. Finally， the strain energy release effect of drilling and blasting pilot tunnel excavation is verified based on case study.

The high energy efficiency of hydraulic machinery has always been the direction pursued by many scholars. Centrifugal pump is a kind of widely used hydraulic machinery， and its efficiency is generally between 70% and 80%. The method of optimizing centrifugal pump and improving its efficiency is worth discussing. In this paper， a vertical single-stage single-suction volute centrifugal pump is used to calculate and analyze the simulated fluid. Based on RNG turbulence model， the fluid simulation calculation of centrifugal pump under seven different flow inlet conditions of 0.5Q_d ~1.3Q_d was carried out， and the hydraulic performance of centrifugal pump under large and small flow conditions was obtained. The main performance was low efficiency and high head under low flow conditions. The opposite was true for large large flow conditions， with high efficiency and low head. After that， the impeller of centrifugal pump was optimized by Bezier spline curve， which mainly shows the change of bending degree of edge profile of blade inlet. Five schemes including the initial model were established. The simulation numerical calculation of different schemes was carried out under rated working conditions， and the changes of efficiency and head with the bending of blade inlet edge profile were analyzed. The difference of blade pressure， velocity vector and outlet pipe flow pattern under different schemes was compared. Finally， the optimal scheme was obtained， with the efficiency slightly increased to 91.2% and the head became closer to the design head.

Steel fiber reinforced concrete has been widely used in engineering practice due to its superior mechanical properties. However， unlike other fibers， steel fibers are susceptible to corrosion in corrosive environments. This paper systematically reviews the research progress and key findings on the corrosion of steel fiber concrete at home and abroad， including the corrosion mechanism， as well as the effects of corrosion on the mechanical and durability properties of concrete. Previous studies have shown that the corrosion resistance of steel fibers is influenced by several main factors， such as the water-cement ratio， fiber type， concrete cracks， and the erosion environment. Besides， steel fibers corrode only within approximately 5 mm of the surface layer in uncracked concrete. The strength of the steel fibers gradually decreases as corrosion advances， while the corrosion products play dominant roles in the filling and compression of pores at different stages. These processes affect the bonding performance between the steel fibers and the cement matrix， thereby altering the mechanical properties of the concrete. Consequently， the mechanical properties of the concrete are closely related to the corrosion degree of steel fibers. Most existing studies have not considered the impact of the corrosion degree on the strength of steel fiber concrete， and the quantitative relationship between the corrosion degree of steel fibers and the degradation of concrete mechanical property has not been established. Finally， this paper discusses the challenges in steel fiber corrosion research and suggests future research trend.

Developing a realistic and feasible water allocation solution is the key to resolving water competition conflicts of the trans-administrative rivers under water scarcity. The demand ratio method has been widely used in water management practice due to its simple calculation principle， transparent water distribution ratio， and easily operational solution. However， this method only considers regional water demand as the sole influencing factor for water allocation， without paying attention to the influence of other characteristic factors， and may result in a certain degree of one-sidedness in the allocation results. In response to the limitations of the demand ratio allocation method in resolving water allocation conflicts of the trans-administrative rivers， this study proposed a water allocation index system considering principles such as water contribution， social equity， respect for current situation， water use efficiency， and ecological environment sustainability. And an asymmetric demand proportion model for inter-administrative river water allocation was proposed by combining the information entropy-CRITIC method and bankruptcy game theory. Subsequently， taking the Hanjiang River Basin of Hubei Province as the practical case， it conducted study on trans-administrative river water allocation under two supply and demand scenarios using the basic data including distributable water volume， water demand， average annual runoff， water user population size， current water consumption， GDP， ecological environment flow， and sewage discharge as model inputs. The results showed that compared with the demand ratio allocation method， because the proposed model comprehensively considered the differences in water contribution， water use population， water demand， water use efficiency， and ecological environment among agents， the water allocation satisfactions of Shiyan and Xiangyang cities with higher water demand and larger weight coefficients both increased by 2.39% in dry year， while that of Suizhou and Qianjiang cities with lower water demand and smaller weight coefficients decreased by 47.25% and 33.54%， respectively； In the extremely dry year， the water allocation satisfaction obtained by Shiyan and Xiangyang cities raised by 32.09% and 23.10% respectively， whereas Suizhou and Qianjiang cities decreased by 46.71% and 40.94% respectively. The proposed model can highlight the differences in various influencing factors of the agents in water allocation， and ensure that the principle of individual rationality is not undermined. It has high application value in solving water allocation conflicts of the trans-administrative rivers.

Accurate water quantity estimation is the foundation for the rational development and utilization of water resources in a watershed. It is mainly based on the main stream runoff data and uses the fitting line method for hydrological frequency analysis. To ensure the accuracy and rationality of the calculation of the design value of available water supply， it is generally necessary to consider different distribution curves and fitting line rules. At the same time， to consider the differences in water demand in different regions， the regional composition of available water supply cannot be ignored. This article establishes a watershed available water supply calculation model based on genetic algorithm and Copula function. The model selects three different distribution lines， namely Gamma， P-III， and log normal， with two parameters. Based on the minimum sum of squares of relative deviations criterion and the minimum root mean square error criterion， the genetic algorithm is used to optimize and solve the optimal distribution line of water supply for each tributary in the watershed. Based on this， a joint distribution function of available water supply for downstream design sections of the watershed is constructed using GH Copula function， which can reflect the regional composition of water supply while calculating available water supply. The model is applied to the Liuxi River Basin， to obtain the optimal distribution lines of each tributary under different scenarios， and to calculate the range of available water supply for the downstream control section of the Liuxi River Basin under different assurance rates. In the optimization and fitting results of water volume in various tributaries of the watershed， the optimization and fitting based on the minimum sum of squared deviations criterion has a good fitting effect on the low water points of the sample， while the optimization and fitting based on the minimum root mean square error criterion has a good fitting effect on the overall sample data. Based on this result， using GH Copula function to construct a joint distribution function for the available water supply of the watershed design section to solve the available water supply of the watershed can better reflect its regional composition and has higher accuracy than traditional available water supply estimation methods.

The Simulation of daily water and nitrogen output processes during the snowmelt runoff generation period in seasonal freeze-thaw zones remains challenging due to influences from processes such as snowmelt and soil freeze-thaw. In this study， we took the Heidingzi River basin in Changchun City， Jilin Province， a typical seasonal freeze-thaw zone， as an example. Calibration and validation of the Soil and Water Assessment Tool （SWAT） model were conducted using daily monitoring data of water and nitrogen at the basin outlet during the freeze-thaw period from 2014 to 2016. The applicability of the SWAT model in simulating daily runoff and daily nitrogen loads during the thawing period was explored. The results indicated that within the SWAT model， the parameters CN₂， CNFROZ， SNOCOVMX （for daily runoff） and CN₂， SDNCO， CNFROZ （for daily nitrate nitrogen output） were the three most influential parameters. The SWAT model performed well in simulating daily runoff， with Nash-Sutcliffe Efficiency （NSE）， coefficient of determination （R2） and relative error （Re） values of 0.75、0.78 and -12.76% during the calibration period， and 0.54、0.51 and 5.65% during the validation period， respectively. The primary reasons for the decline in accuracy were that the SWAT model did not consider the lag effect of snowpack on runoff generation and the snowmelt-refreezing process. Additionally， parameters adjusted for accurate simulation of the snowmelt runoff process during the soil thawing period often led to overestimation of runoff and underestimation of baseflow during non-freeze-thaw periods. Due to biases in runoff simulation and inadequate representation of the impact of freeze-thaw processes on nitrogen transformation within the model， the SWAT model exhibited relatively low accuracy in simulating daily nitrate nitrogen loads， with NSE， R2 and Re values of -0.19、0.44 and 2.7% during the calibration period， and 0.60、0.26 and -13.79% during the validation period， respectively. This study validated the applicability of the SWAT model in seasonal freeze-thaw zones and revealed its limitations， providing a scientific basis for model optimization and application.

In this paper， the study collected and calculated the water level difference between upstream and downstream of the annual peak of more than 40 typical ship locks in China， and obtained the uncertainty parameters and coefficients of variation of hydrostatic pressure. Based on the statistical parameters of resistance under the current code， the modified-JC method was used to calibrate and calculate the reliability index for different components of all levels of the mitre gate， and a method for determining the five partial factors in the ultimate limit state design formula was proposed. The research methodology and theoretical framework can be used as a reference for the research on the structural reliability of similar hydraulic steel gates， provide methodological guidance for the revision of specifications， and help to promote the updating and improvement of specifications.

Precipitation is one of the most important driving factors in hydrological processes， and its data source and accuracy are key factors affecting the accuracy of flood forecasting. Affected by many factors such as the imperfect water and rain condition monitoring system and the small range of the basin， the accuracy of the measurement of precipitation data in the small and medium -sized basin is high， but the distribution is uneven， which will affect the simulation results of hydrological models. In order to improve the accuracy of flood forecasting in the watershed， this study combines the measurement data with satellite product precipitation data by constructing a CNN-LSTM neural network model， and combines the HEC-HMS model to carry out the flood simulation Taking the catchment area above the Jinpen Reservoir in the Heihe River Basin in Shaanxi as an example， the application effect and applicability of satellite-ground fusion precipitation in the flood simulation are discussed. The results show that ① The HEC-HMS model with the site precipitation data as the input has good applicability in the research area， and can achieve Class B accuracy in both the rate period and verification period. ② The correlation coefficients between the two types of IMERG satellite products and measured precipitation are low， which are generally higher than the actual value， and the error is large. After CNN-LSTM data fusion， it is close to the measured precipitation data， and the fusion effect of the IMERG-Early product is better. ③ The HEC-HMS model after fusion of satellite products has a simulation pass rate of 80% for the 10 floods， with an average definitive coefficient of 0.856 9， and the average absolute value of the absolute value of the flood peak is 0.8h， reaching Class A accuracy. ④ The certainty coefficient of the flood simulation results of satellite-ground fusion precipitation increases， and the absolute value of the average flood peak time difference is reduced； the simulation effect of the flood peak flow decreases and is significantly smaller. The results show that integrating the actual measurement precipitation data and appropriate satellite precipitation product data in small and medium -sized basin can improve the accuracy of flood forecast models to a certain extent.

In natural river channels， aquatic vegetation typically grows in the areas near the riverbanks， which in turn affects the stability of the riverbank and the discharge capacity of the river channel. During the growth of vegetation， the inundation degree （ratio of water depth to vegetation height， H/hv） will change with the change of vegetation height or water level， which will affect the flow characteristics.By constructing a three-dimensional numerical model of an open channel with submerged vegetation groups distributed along the river bank， the Large Eddy Simulation （LES） method was used to study the average flow field and turbulent structure around the vegetation group under four submergence levels （4.0、3.0、2.0 and 1.5）. The results indicate that， when submerged vegetation is distributed on one side of the open channel， the maximum cross-sectional velocity deviates from the channel center， appearing on the non-vegetation area， and gradually approaches the water surface as the submergence ratio decreases. The presence of submerged vegetation generates a mixing layer in the vertical direction， intensifying flow turbulence. High turbulent kinetic energy regions are distributed along the interface between the vegetation and non-vegetation area as well as at the vertical interface between the submerged vegetation and the upper water layer. As the submergence ratio decreases， the size of the horizontal shear layer vortices increases. When the submergence level is 1.5， the horizontal shear layer vortex can extend into the non-vegetated area. At the same time， the intensity of the secondary flow in the cross-section strengthens， and the turbulence within the entire flow field becomes more intense.

Intelligent grouting technology plays a critical role in hydraulic engineering and foundation reinforcement. Currently， grouting pressure and unit grouting rate are primarily adjusted manually， leading to low grouting precision and frequent overpressure incidents. This study designs an intelligent grouting pressure control system， integrating a pressure regulation platform， intelligent control unit， and upper-level master control center. The system is capable of controlling pressure and processing real-time data， ensuring the stability and safety of the grouting process. The system's hardware includes key components such as a grouting pump， diverter valve， inflow meter， pressure gauge， outflow meter， and electric control valve. By integrating a PLC with the electric control valve， real-time adjustments to the return pressure are made， ensuring stable and precise pressure control. A data acquisition and pressure stability control logic program for the grouting process are developed， and an integral sliding mode controller is applied for pressure regulation. The controller's performance under dynamic and disturbance conditions is verified， demonstrating its ability to respond quickly to pressure changes and adapt to different grouting requirements. This enhances the automation and intelligence of the grouting operation. This provides a solid foundation for the widespread application of intelligent grouting technology and offers significant potential for future use. This work presents a comprehensive design of an intelligent grouting system， explores the effects of various pressure control algorithms， and confirms the system's performance in real-world applications. The research results show that the intelligent grouting system operates stably and has precise pressure control， which provides a solid foundation for the widespread application of intelligent grouting technology and has broad application prospects.

Revealing the coupling coordination relationship between water resources utilization and high-quality economic development in the Yellow River Basin is very important for improving the macroeconomic regulation of natural resources and economy society， as well as promoting regional sustainable development. Taking cities along the Yellow River in Henan as the research object， an index system of high-quality economic development and water resources utilization was established in this study. Based on the panel data of Henan Province from 2012 to 2022， the comprehensive empowerment-TOPSIS method， which combines entropy weight method and coefficient of variation method， is used to measure the water resources utilization and high-quality economic development level；Combined with the coupling coordination degree model and the relative development degree model， the coupling coordination development trend and interaction mechanism of the two are analyzed. The results show that： ① During the study period， the water resources utilization efficiency of the cities along the Yellow River in Henan fluctuated and increased. The water resources utilization efficiency of Zhengzhou city was the highest， and the water resources utilization effect of Xinxiang city was the worst； ② The overall economic quality development index of cities along the Yellow River in Henan has been continuously improved， with Zhengzhou having the highest economic quality development index and Puyang having the lowest economic quality development level； ③ The cities along the Yellow River in Henan Province as a whole showed the characteristics of high quality economic development synchronized with water resource utilization， but there were obvious differences among cities； ④ The coupling coordination degree between water resources use efficiency and high-quality economic development in cities along the Yellow River in Henan Province is on the rise， but the level is still low. In terms of time series， it has undergone the evolution process of forced coordination - primary coordination， and the spatial distribution pattern is south of the Yellow River > north of the Yellow River， and the coupling coordination evolution process of each city is different. It is necessary to combine the characteristics of cities， pay attention to energy conservation and environmental protection， improve water-saving measures in agriculture and industry， and strengthen scientific and technological innovation capabilities， so as to improve the coupling and coordination of water resources utilization and high-quality economic development.

Water and soil resources are the basic elements of “Production-Living-Ecological Space”. The particularity of water and soil resources in Inner Mongolia Autonomous Region makes the optimization of “Production-Living-Ecological Space” face major challenges. Based on the perspective of “Production-Living-Ecological Space” and PSR model， an evaluation index system of water and soil resources carrying capacity in Inner Mongolia Autonomous Region was constructed. The entropy weight-TOPSIS evaluation model was used to study the spatial-temporal evolution and influencing factors of water and soil resources carrying capacity in Inner Mongolia Autonomous Region from 2013 to 2022. The coupling coordination degree model was used to analyze the coupling coordination degree of “Production-Living-Ecological Space” for the water and soil resources carrying capacity. The results show that： ① The carrying capacity of water and soil resources in each league and city of Inner Mongolia Autonomous Region showed a fluctuating upward trend， and it was mainly at three levels： lower carrying capacity， general carrying capacity and higher carrying capacity， and there is no low carrying capacity level and high carrying capacity level. ② During the study period， the carrying capacity of water and soil resources in each city and league can be divided into two stages： In the first stage （2013-2017）， the carrying capacity of water and soil resources in each city and league showed a slow and fluctuating upward trend， which was mainly at a lower carrying capacity and general carrying capacity level， and the evaluation value of carrying capacity was mainly concentrated in 0.3~0.6； In the second stage （2018-2022）， the carrying capacity of water and soil resources in each city and league showed a steady and upward trend， which was mainly in the general carrying capacity and higher carrying capacity level， and the evaluation value of carrying capacity was mainly concentrated in 0.4~0.7， which has been improved to a certain extent compared with the first stage. ③ The coupling coordination degree of “Production-Living-Ecological Space” for the water and soil resources carrying capacity in Inner Mongolia Autonomous Region generally shows an upward trend. The change trend of the coupling coordination degree of “Production-Living-Ecological Space” was basically consistent with the spatial-temporal evolution trend of water and soil resources carrying capacity in each city and league， which is the result of a steady improvement in the coordination between production， living and ecological space. The research results can provide reference for the sustainable planning， utilization and management of water and soil resources as well as the optimization of “Production-Living-Ecological Space” pattern in Inner Mongolia Autonomous Region.

Based on the upper reservoir face rockfill dam of a pumped storage power station， the analysis methods and safety control standards of the ultimate seismic capacity of the concrete-face rockfill dam （CFRD） are expounded from the aspects of permanent deformation of the dam body， seismic stability of the dam slope， tensile fracture resistance of dam body and seismic safety of face slab. The seismic wave overload method is used to calculate the three-dimensional seismic response of the dam under different peak accelerations， and the ultimate seismic capacity of the CFRD is quantitatively analyzed based on the indexes such as the seismic subsidence rate at the top of the dam， the cumulative duration when the minimum safety factor of the slope is less than 1.0， the cumulative slip， the deformation gradient of the dam after the earthquake and the stress of the face slab. Through in-depth and comprehensive analysis， the following conclusions can be drawn： the dam has strong seismic resistance， and its ultimate seismic resistance is between 0.55~0.60 g. The calculation and analysis results provide reference for scientific evaluation of seismic safety of CFRD and reasonable formulation of seismic reinforcement measures.

After the impoundment of the Three Gorges Reservoir， the braided river reaches downstream of the dam have undergone significant long-term scouring and silting adjustments under the condition of unsaturated sediment-laden flow. These changes have resulted in increased complexity in the diversion ratios of the main branch and tributary channels. It is extremely important to use different methods to assess the direction of scouring and silting adjustments in braided channels based on measured data， which provides support for effective flood control planning and the strategic layout of economic development. This paper takes the Tiebanzhou bifurcation section of the Middle Yangtze River in Wuhan as an example， using a combination of multiple methods including flow area change analysis， measured diversion ratio change analysis and river model experiment to assess the direction of scouring and silting adjustments after the operation of the Three Gorges Reservoir. Results show： ① All three methods yield consistent qualitative judgments regarding the scouring and silting adjustments in Tiebanzhou straight braided channel， specifically， the minor branch of the channel has generally undergone scouring development， with an increase in the flow area proportion and diversion ratio of the minor branch， while the diversion ratio of the main branch has decreased. ② The primary reasons contributing to the scouring development of the minor branch in Tiebanzhou straight braided channel are the sediment unsaturation in the minor branch exceeding that of the main branch and the leveling of the runoff process. ③ All three methods are effective in qualitatively assessing the direction of scour and silt in Tiebanzhou straight braided channel. Additionally， the river model experiment can offer valuable quantitative insights， particularly regarding changes in the diversion ratio at the same flow rate. Since the impoundment of the Three Gorges Reservoir， the diversion ratio in the minor branch has increased by 7.4% to 13.4% under different flow regimes， ranging from flood to low-flow conditions.

To better understand the evolution of heatwaves characteristics at global scale， this study introduced a temperature threshold based on the Excess Heat Factor （EHF） index， and analyzed the characteristics of the heatwave occurrence， frequency， duration and average cumulative intensity. The increases in four heatwave characteristics in 20 IPCC regions were compared. In addition， differences in heatwaves based on four global temperature datasets， ERA5， MERRA2， JRA55 and NCEP/NCAR， were evaluated. The results show that during 2002-2021， the number， frequency and duration of extreme heatwave events are larger in Europe， northern and southern Africa， southern North America， eastern South America and eastern Australia， while the higher cumulative intensity are concentrated in the mid-latitude regions. The heatwave trend has increased significantly since the 21st century， among which the growth trend of extreme heatwave days is greater than the cumulative intensity. Western Asia， Southern Europe and the Mediterranean region have not only experienced more frequent heatwaves， but also greater cumulative intensity. The four reanalysis datasets show differences in the number， frequency and duration of heatwaves， but have a high consistency in the average cumulative intensity. These findings are helpful to better understand the evolution of global extreme heatwaves， providing scientific basis for mitigating the adverse effects of extreme events and enhancing regional adaptation to climate change.

To solve the problem that the acoustic signal used to detect the running state of the water supply pipeline is easily disturbed by noise， which leads to the low accuracy of leakage detection and leak location， a noise reduction algorithm for vibration acoustic signal was proposed， which combined variable mode decomposition （VMD） and Hilbert transform. Firstly， the leakage signal was decomposed into several intrinsic mode functions （IMF） by VMD， the number of decomposition layers was determined， and the IMF component was Hilbert transformed to obtain the marginal spectrum， and the noise was preliminarily screened through the characteristics of the marginal spectrum and the cross-correlation coefficient； Secondly， filter and cross-correlation coefficient were used to screen the secondary noise； Finally， the time delay of the denoised signal was estimated， and the leakage point position was calculated according to the positioning principle. To verify the performance of the algorithm， the cross-correlation algorithm， VMD correlation coefficient algorithm and the proposed algorithm were analyzed through experiments. The results show that compared with the other two algorithms， the proposed algorithm can effectively remove the noise in the leakage signal and reduce the positioning error.

Compared with a single reservoir， successive breach disasters have a greater impact and more complex causative factors in cascade reservoirs. However， the numerical simulation of the successive breach process of the core wall dam in cascade reservoirs still faces significant difficulties. This article proposes a numerical simulation method for the cascading reservoir breach process： DLBreach is used to simulate the dam breach flood process， and a one-dimensional high-precision numerical simulation method of natural river hydrodynamics is used to simulate the dam breach flood evolution process. A numerical simulation program for successive breach process in cascade reservoirs is developed based on C# language. In terms of model connection， text interactive data is used to connect the dam breach model and flood routing model. Case studies have shown that the DLBreach model has a relative error of only 1.8% between the simulated flood peak of the Sheyuegou Reservoir dam breach and the measured value， with a peak time difference of only 1.2 minutes， indicating high simulation accuracy. In terms of dam breach flood evolution， the relative error between the method proposed in this paper and HEC-RAS （FVM） simulation of peak flow is only 1%. The process of flood evolution is similar. This indicates that the method is suitable for simulating the flood evolution of natural river channel breaches. The method described in this article has high calculation accuracy and efficiency， achieving rapid and high-precision numerical simulation of the successive breach of the core wall dam in cascade reservoirs. This method creates favorable conditions for rapid forecasting， early warning， and emergency response of sudden flood events and their consequences.

The carbon sequestration and oxygen release function of wetlands plays an important role in regional atmospheric regulation and is one of the important ecosystem service functions of wetlands. To quantify the carbon sequestration and oxygen release capacity of the Yellow River Delta wetland ecosystem and analyze its driving mechanism， this paper used the CASA model to calculate the net primary productivity（NPP） of the Yellow River Delta Wetland from 2005 to 2020， and converted it into carbon sequestration and oxygen release through the photosynthesis equation， and used the geographical detector and contribution index to identify the main driving factors and contributions of the evolution of carbon sequestration and oxygen release function. The results showed that the multi-year average net primary productivity of the Yellow River Delta wetland from 2005 to 2020 was 321.5 g/m²， with a total of 907.9 Gg C/a， with an overall decreasing trend in NPP from 2005 to 2020； the multi-year average of carbon sequestration and oxygen release were 309.3 and 836.4 g/m²， respectively. The overall trend of carbon sequestration and oxygen release is decreasing. In terms of spatial distribution， the spatial distribution characteristics of oxygen sequestration were consistent with those of NPP， and the high value areas were mainly concentrated in forest land， followed by grassland and cropland； the results of the Geodetector indicated that the land use type and NDVI are the main controlling factors for the spatial distribution of carbon sequestration and oxygen release in the Yellow River Delta wetland； the analysis results of the contribution index show that forest， grassland， and cropland have positive contributions to carbon sequestration and oxygen release， while land use types such as aquaculture ponds， salt pans， and construction land have negative contributions to carbon sequestration and oxygen release， the contribution indices of culture ponds， salt pans and construction land showed an increasing trend from 2005 to 2020， indicating that the negative impacts of human activities such as the development of urbanization and reclamation culture on the carbon sequestration and oxygen release functions of the Yellow River Delta wetland have been gradually strengthened. The study results can provide the scientific basis for the stability and sustainable healthy development of the Yellow River Delta wetland ecosystem.

In order to investigate the mechanical mechanisms of compression failure in cohesive soil under varying initial moisture conditions and unveil the microscale mechanical effects of water on the macroscopic deformation properties， advanced particle flow software PFC^3d was employed in conjunction with indoor triaxial compression test results. The results show： the DEM simulation results established can effectively reflect the mechanical performance of soil under varying initial moisture content conditions； The peak strength， tangent modulus， cohesion and internal friction angle of the soil exhibit a decreasing trend with the moisture content increases； As the vertical strain increases， larger displacements occur at the specimen's ends， with smaller displacements in the central region. This leads to the formation of a shear zone in the central area， characterized by initial shear contraction followed by shear dilation of the soil. Upon applying confining pressure， the anisotropy of the particle contact normal is initially small. However， as the soil reaches its peak state， the contact normal of the particle system exhibits strong anisotropy； During the shear process， the development of microcracks in the specimen undergoes stages of zero development， rapid development， and slow development， with shear cracks dominating the process；In the model， shearing converts a significant portion of boundary energy into elastic strain energy and a smaller portion into damping energy. This study offers a novel approach to understand the compressive deformation and failure behavior of soil under varying initial moisture content.

In order to investigate the effect of air-entraining agent dosage on the capillary water absorption saturation of unsaturated hydraulic concrete， the capillary water absorption test of unsaturated hydraulic concrete with different air-entraining agent dosage （mass fractions of 0?， 2.50?， 3.75?， 5.00?， 6.25?， respectively） was carried out in a low-temperature environment， by using infiltration absorption and horizontal absorption methods. Then the effect of air-entraining agent dosage on concrete porosity， compressive strength， and capillary water absorption saturation was studied. And finally a prediction model for the capillary water absorption saturation of unsaturated hydraulic concrete coupled with different depths of water absorption and different air-entraining agent contents was established. The results show that： with the increase of air-entraining agent dosage， the porosity of hydraulic concrete increases linearly， the compressive strength decreases slightly with an upward convex curve， and the saturation degree decreases gradually. The saturation degree and water absorption depth were exponentially related. The saturation degree of concrete and air-entraining agent admixture of the infiltration absorption and horizontal absorption methods were linearly and quadratically related， respectively. Then a prediction model of capillary water absorption saturation of unsaturated air-entraining hydraulic concrete was established based on the separation of variables model. And the analysis shows that the new model can better predict the distribution law of capillary water absorption saturation of unsaturated hydraulic concrete under the joint action of different water absorption depths and different air-entraining agent mixing amounts.

One-dimensional consolidation tests， scanning electron microscope tests， and mercury intrusion porosimetry tests were conducted to explore the compression properties and microstructure of compacted clay under dry-wet and freeze-thaw environments with different initial moisture contents. A compression model considering the influence of environmental factors was proposed to describe the relationship between compacted clay void ratio and compression stress. The results indicate that the optimally compacted clay samples with optimal moisture content on the dry side exhibit an aggregate structure with a bimodal pore size distribution curve， while those on the wet side show a dispersed structure with a unimodal pore size distribution curve. Both dry-wet and freeze-thaw environmental effects can promote the transformation of small pores to medium and large pores within the two types of samples， leading to improved compressibility characterized by a reduction in initial consolidation stress and an increase in recompression index， with limited variation in compression index. The influence of dry-wet cycles on the pore system and compressibility of samples is greater than that of freeze-thaw cycles， with a significantly higher enhancement in compressibility observed in wet-side samples compared to dry-side samples under environmental effects. The proposed compression model considering environmental influences effectively describes the compression properties of compacted clay.

The coordinated development of urbanization development with water security and food security is an inevitable requirement for achieving high-quality development. Metropolitan areas are key drivers for optimizing resource allocation and promoting coordinated regional development. Taking Nanjing metropolitan area as an example， we deeply analyze the evolution pattern of water security， food security， and urban development from 1990 to 2020. We use the coupling coordination degree model to reveal the spatio-temporal characteristics of the coordinated development of water security- food security- urbanization development， and identify the relevant influencing factors through the gray correlation analysis method. The results show that： ① The water security level and urban development index showed a steady increase from 1990 to 2020， while the food security level first declined and then rebounded. Overall， both water security and food security performed well， and by 2020， all cities in the metropolitan area had reached a relatively safe level. Nanjing， as the central city of the metropolitan area， had an urban development index significantly higher than other cities. ② The coupling coordination degree of water security-food security-urbanization development continues to improve， gradually entering the stage of intermediate or good coordination from a state of dissonance in 1990. The development of water security in each city is particularly prominent and prioritized. Among them， Yangzhou has the highest level of coordinated development， while for cities like Xuancheng， Wuhu and Ma'anshan their water safety and food security are far better than the urban development index， and have great potential for development. ③ Expansion of built-up land area， urbanization rate， and increase in population density are the most important factors affecting the degree of coordination of the three couplings. In addition， factors such as green coverage of built-up areas， food prices， the proportion of tertiary industry and the use of fertilizer per unit area also play an important role. The study provides a reference for coordinating the relationship between water， food， and urban development， optimizing the allocation of regional resources， and promoting the high-quality development of the metropolitan area.

It is of great significance to study the influence of landscape pattern on the water quality of urban rivers at different spatial and temporal scales for the protection of ecological environment in river basins. Taking Yangtze River Basin water system within Wuhan， Hubei Province as the research object， based on the statistical results of water quality indexes （including pH， DO， COD_Mn， NH₃-N， TP and TN） of 7 local monitoring sections in 2021， and extracting their land use situation in circular buffer zones with 5 radii （200， 500， 1 000， 1 500 and 2 000 m） from GlobeLand30 dataset， the relationship between landscape pattern and surface water quality at different spatial and temporal scales was studied with redundancy analysis method. The results showed that： ① The interpretation rates of water quality indexes by land use composition were the largest in the 200 m buffer zone in both wet and dry seasons （84.1% and 97.2% respectively）， and the interpretation rates by landscape pattern indexes were the largest in the 200 m buffer zone in the wet season （90.9%） and 500 m buffer zone in the dry season （88.2%）. ② The main explanatory variables of land use composition and landscape pattern indexes affecting the water quality were different at different spatial and temporal scales. For land use composition， water area and grass land had the highest contribution rate under small spatial scale in the wet season， and construction land had the highest contribution rate under large spatial scale， while in the dry season， forest land was the main explanatory variable. When it comes to landscape pattern indexes， patch density （PD）， largest patch index （LPI） and Shannon’s diversity index （SHDI） contributed the most to explaining water quality indexes in most cases. ③ Under most situations， cultivated land， grassland and PD， landscape shape index （LSI） and SHDI in the study area were significantly positively correlated with COD_Mn and NH₃-N， while forest land， unused land and LPI were positively correlated with DO， and water area was negatively correlated with COD_Mn， NH₃-N and TP. However， there was a significant positive correlation between construction land and polluted water quality indexes only in the 200 m buffer zone. Therefore， it is vital to focus on the prevention and control of pollutant discharge within the 200 m buffer zone， strengthen the management of cultivated land， forest land and construction land， and optimize the spatial pattern of urban landscape for the pollution control of urban water system in Wuhan.

In order to explore the effect of freezing-microwave method for purifying sewage quality， this study designed an experiment of indoor freezing wastewater， combined with microwave rapid thawing， and the melted water was collected at five times intervals （i.e. T1~T5）. The results show that： ① The microwave thawing of 17 min can completely melt the sewage ice， and the efficiency is much higher than that of the natural thawing process （14.5 h）. ② The microwave treatment of the first 8 min （T1+T2） melts 40% of the total water and removes more than 59.18% of the physical and chemical index content and 64.57% ion content in the sewage. The chromaticity， turbidity and yellow flocculent precipitation of sewage were significantly reduced. ③ In the final aquatic products obtained by microwave thawing for 17 min， the concentration ratio of total alkalinity， HPO₃， PO₄ ^3-， COD_Mn， SiO₂ and H₂SiO₃ is between 0.20 and 0.41， and the maximum concentration ratio of TDS to total hardness is only 0.16. The concentration ratio of eight conventional ions in K⁺， Na⁺， Ca²⁺， Mg²⁺， Cl^-， SO₄ ^2-， HCO₃ ^- and NO₃ ^- wastewater is only between 0.05 and 0.20. The concentration of As is close to 0. ④ The results of principal component analysis （PCA） showed that the purification effect of TDS and total anions was the best when freezing-microwave method was used to purify sewage water， and the principal component comprehensive scores Y were 4.55 and 3.65， respectively. In general， combined with freeze-thaw process and microwave rapid thawing， sewage treatment can be realized quickly and efficiently.

A 23 m wide fault fragmentation zone is developed at the foundation of a medium-sized reservoir gravity dam in Southwest China， and the mechanical properties of the rock body in the fragmentation zone are weak， which will have an important impact on the stability of the dam foundation during the construction， impoundment and operation of the dam. Based on the engineering geological conditions and rock mechanical parameters， a micro-arch concrete plug replacement foundation scheme for dam foundation treatment is proposed， and three-dimensional finite element calculations and sensitivity analyses of rock mechanical parameters of the F1 fault at the dam foundation are carried out. It is concluded that in the case of soft bedrock body with wide fracture zone， the difference of deformation modulus and the weak bearing capacity of the fault zone lead to the uneven deformation phenomenon of the dam foundation. After the replacement of the concrete plugs by micro-arch， the load carrying capacity of the dam foundation and the stress deformation of the gravity dam during the impoundment process meet the requirements. As the concrete plugs can work well， the influence of the variation of fault fracture zone parameters on the stress and deformation of the dam and dam foundation is weakened. The study provides an important reference value for the foundation treatment of gravity dams across wide faults.

The combination of hydrological and meteorological forecasts can effectively improve the accuracy and forecast period of flood forecasting. The land-surface hydrological modeling module has become the focus of research by hydrometeorologists. As a new generation of distributed land-surface hydrological model， the WRF-Hydro model has broad application prospects in multi-scale flood forecasting. However， due to the complex parameterization scheme of each physical process and the large amount of calculation of the model， the current parameter sensitivity research of the WRF-Hydro model is insufficient， which also affects the simulation accuracy of the model. This study takes the Tunxi basin in the upper reaches of the Xin'anjiang River in the humid area as the research basin， constructs a set of single-objective and multi-objective functions， and combines Morris method for global sensitivity analysis to explore the parameter sensitivity of the WRF-Hydro model under different objective functions. The result shows that： soil parameters （DKSAT， SMCMAX， BEXP） mainly affect subsurface and surface runoff， and have a significant impact on runoff volume.In particular， DKSAT is the most sensitive and directly affects the movement speed of water in the soil. When increasing， the base flow rate increases significantly while the peak flow rate decreases significantly.； runoff parameters （SLOPE， REFKDT） mainly affect the distribution of surface runoff and baseflow， and have an important effect on the overall shape of the flood hydrograph； the channel routing parameter ManN affects the speed of runoff convergence to channel network and mainly controls the peak time； vegetation parameter MP has a certain influence on annual water volum； overland flow parameter OVROUGHRTFAC and groundwater parameter Zmax are the least sensitive.. There are certain differences in the parameter sensitivity order and optimal parameter values under different objective functions. The single objective function based on relative bias focuses on the simulation of the total annual runoff and the low flow part， while Nash-Sutcliffe and Kling-Gupta coefficients focus more on the simulation of floods and high flow parts. The multi-objective function comprehensively considers the influence of different objective functions， and the results are better than the single-objective function to a certain extent. This work can provide a reference for reasonably determining the WRF-Hydro model parameter optimization strategy.

Continuous strong human activities have changed the mutual feedback relationship between water resources， economic society and ecological environment， and affected regional sustainable development. In order to explore the coordinated development of water resources， economic society and ecological environment in the Yellow River Basin of Henan Province and identify the drivers of coordinated development， this study improved the traditional coupling coordination degree model based on synergetics and random forest model， and calculated the comprehensive development index and coupling coordination degree of water resources， economic society and ecological environment in the Yellow River Basin of Henan Province from 2011 to 2022. The spatial and temporal evolution characteristics are revealed by kernel density estimation， and the driving factors of the coordinated development are analyzed by geographic detector model. The results showed that during the study period， the comprehensive development index of each system showed a different degree of growth trend， but there was a certain degree of heterogeneity. The water resources， economic society and ecological environment system showed a spatial disequilibrium pattern of “high in the west， low in the east， high in the south and low in the north”， “the center leads the periphery， the edge develops slowly”， “the upstream is superior to the downstream， the southwest is superior to the northeast”. The coordinated development level of water resources， economic society and ecological environment showed a significant positive trend， and the spatial heterogeneity among cities was obvious， showing the evolution characteristics of “regional rise， high in the south and low in the north， high in the west and low in the east”. Natural endowment， economic foundation and human settlement environment are the main driving factors for coordinated development， and the relationship between each factor is becoming increasingly close， and the interaction type shows a trend of transformation to “nonlinear enhancement”. This study innovatively puts forward a new method of coordinated development evaluation， and verifies its scientific nature， which provides a powerful tool for in-depth analysis of the coordinated development of water resources， economic society and ecological environment in the Yellow River Basin of Henan Province， and has certain practical guiding significance for promoting regional sustainable development.

The external water pressure of lining is of great significance to the determination of lining thickness and drainage scheme of water-rich deep buried tunnel. The existing research often ignores the analysis of the influence of macroscopic geological conditions on the seepage field， which leads to the lack of reliability evaluation of the external water pressure estimation results and lining design schemes of deep buried tunnels. Based on the Qinling Water Conveyance Tunnel Project of Hanjiang-to-Weihe River Diversion Project， this paper generalizes the deep-buried tunnel in the water-rich area into three representative macro-geological environment models under the watershed， the mountainside area and the river， and studies the influence law and mechanism of geological conditions and engineering measures on the seepage field of surrounding rock and the external water pressure of lining. The results show that： ① The seepage direction of groundwater around the watershed tunnel is mainly vertical under the condition of the same height of groundwater at the top of the tunnel and impermeable lining. The seepage direction of groundwater around the tunnel under the river is mainly horizontal. The external water pressure reduction coefficient of the watershed tunnel， the tunnel near the mountain area and the tunnel under the river increases in turn. The reduction coefficient of external water pressure of tunnel under watershed increases with the increase of buried depth， which is 0.72，0.77 and 0.84 respectively. The reduction coefficients of the external water pressure of the mountain tunnel and the river tunnel are almost unchanged， which are 0.91， 0.91， 0.93 and 0.95， 0.96， 0.96， respectively. ② After the same drainage measures are taken， with the increase of buried depth， the reduction coefficients of external water pressure of watershed tunnel are 0.15，0.42，0.64 respectively， and the pressure reduction effect is the best. The external water pressure reduction coefficients of the tunnel near the mountain and the tunnel under the river are 0.48，0.67，0.77 and 0.63，0.80，0.83， respectively， and the pressure reduction effect gradually deteriorates. ③ When the buried depth of the tunnel is 1 200 m， the reduction coefficients of external water pressure of the watershed， mountainside and river tunnel are 0.43~0.73， 0.67~0.89 and 0.80~0.95 respectively with the increase of the permeability coefficient of the surrounding rock， which shows the regularity that the external water pressure increases with the increase of the buried depth of the tunnel. The research results are universal， and the rationality of water pressure resistance design of tunnel lining in water-rich area can be evaluated from the regularity of macroscopic hydrogeological conditions of tunnel and reduction coefficient of external water pressure.

In the practical processes at water purification plants， the water quality is complex and variable， and there are instances of missing water quality parameters due to malfunctioning detection instruments， thus bringing challenges to determining the dosage of coagulants. Traditional methods， such as beaker stirring tests or manual control of excessive dosage， can easily bring water quality risks such as excessive metal ions， posing health risks to users and reducing economic efficiency. To address these issues， a predictive model combining Genetic Algorithm optimized Fuzzy C-Means clustering （GA-FCM） and Adaptive Neuro-fuzzy Inference System （ANFIS） was developed. This model leverages the inference capability of fuzzy rules and the adaptive capability of neural networks to accurately predict coagulant dosage under unstable water quality conditions.Pearson correlation coefficient method was used to filter input water quality indicators， enhancing model efficiency and generalization capability. The genetic algorithm was employed to determine the optimal parameters for FCM clustering， improving clustering outcomes and generating more accurate fuzzy rules. A hybrid method combining backpropagation and ridge regression was used to adjust network parameters， addressing nonlinear components while optimizing the weights of the consequent network. A water purification plant in Northeast China was used as a case study. Experimental results indicated that compared to traditional linear regression and machine learning models， GA-FCM-ANFIS exhibited superior predictive performance under unstable water quality conditions. Furthermore， in the absence of certain parameters， GA-FCM-ANFIS achieved significantly higher predictive accuracy than other coupled models. The prediction evaluation metrics R ²， RMSE， MAE， and MAPE under sudden water quality changes were 0.93， 2.79， 2.33， and 3.71%， respectively； under missing parameters， the metrics were 0.89， 3.07， 2.57， and 4.06%， respectively. The proposed model significantly improves prediction accuracy and serves as a reliable method for determining coagulant dosage.

This paper proposes a Transformer-based local timestep two-dimensional hydrodynamic simulation method aimed at optimizing the speed and accuracy of flood simulations to meet the urgent needs of flood prevention and mitigation. By incorporating the self-attention mechanism and sequence prediction capabilities of the Transformer model， combined with local timestep techniques， this method dynamically adjusts the local timestep in the hydrodynamic system. Using the real flood process in the Mengwa flood storage area as an example， the simulation results demonstrate that， compared to remote sensing inundation imagery and traditional numerical methods， this approach shows higher consistency and reliability in the precise prediction of inundation extent and depth， maintaining a relative error within 4%. Compared to traditional global timestep methods， this method significantly reduces computational time while ensuring simulation stability and accuracy， achieving a 70.27% improvement in computational efficiency at a 150 m grid resolution.

Clarifying the specific strategies for enhancing the resilience of the “water-energy-grain-carbon” system in the context of high-quality development in the Yellow River Basin is of great value for achieving ecological protection and high-quality development strategies in the Yellow River Basin. By comprehensively utilizing social network models， interpretive structural models， entropy weight methods based on game theory， and obstacle degree models， this study explores the action path of influencing factors on the resilience of the “water-energy-grain-carbon” system in the Yellow River Basin. Based on the analysis of the spatial pattern of resilience in the “water-energy-grain-carbon” system in the Yellow River Basin in 2021， the key obstacles to system resilience are diagnosed， and corresponding resilience improvement strategies are proposed by combining the factor pathways and causal attributes of the influencing factors. The research has found that： ① The main obstacles to the resilience of the “water-energy-grain-carbon” system in the Yellow River Basin are the total power of agricultural machinery， the total capacity of built reservoirs， per capita water resources， recycled water production capacity， per capita energy production， and comprehensive groundwater production capacity. Except for per capita water resources， other factors exist as causal factors in the system. The five main obstacle factors belong to the bottom and middle layers in the explanatory structural model， which play a driving role in the overall resilience level of the “water-energy-grain-carbon” system； ② During the research period， the water resource subsystem had the highest degree of obstacles， and most of the obstacles that hindered the resilience development of the “water-energy-grain-carbon” system in the Yellow River Basin belonged to the water resource subsystem. The obstacle level of the water resource subsystem in the middle reaches was higher than that in the upstream and downstream areas， and the obstacle level of the energy and food subsystems in the upstream was greater than that in the middle and downstream areas. The difference in the degree of carbon subsystem barriers is relatively small， and the rate in the middle reaches is higher than the average level.