Rivers carry water resources and are channels for material and energy transfer. The management of river-related construction projects is an important part of ensuring the flood control， drainage， and stable river conditions of rivers. The water resistance ratio is an important control indicator for river-related construction project management， and the study of its calculation method is of great significance for controlling the impact of river-related construction projects. The traditional water resistance ratio， also known as the structural water resistance ratio， refers to the proportion of the cross section area of the river occupied by a river-related construction project at a certain design flood level. The article reveals the inadequacy of the current structural water resistance ratio in reflecting the degree of obstruction of water flow dynamics propagation in river related construction projects. The structural water resistance ratio weakens the flood control impact of river-related construction projects near the main channel of the river， and over-reflects the flood control impact of river-related construction projects near the shallow shoals of the river. On the basis of the structural water resistance ratio， combined with the hydrological properties such as water depth and flow velocity of the river， the article proposes a hydraulic water resistance ratio. The hydraulic resistance ratio refers to the proportion of the flow of the cross section occupied by the river-related construction project to the total flow of the entire river section at a certain design flood level. Compared with the structural water resistance ratio， the hydraulic water resistance ratio more effectively reflects the degree of obstruction of water flow dynamics propagation in river related construction projects， and the calculation method is simple， which can compensate for the shortcomings of the structural water resistance ratio. This article suggests incorporating the hydraulic water resistance ratio into the control indicators of river related construction projects， effectively controlling the degree of impact of river related construction projects on river flood discharge.

The low spatial resolution of the time-varying gravity field model data provided by GRACE and its successor satellite GRACE Follow-On limits its application in high-resolution long-term drought monitoring. In order to solve this problem， the XGBoost machine learning method was used to carry out downscale reconstruction of the changes in terrestrial water storage in mainland China from 2002 to 2022， and the GRACE TWSA with a resolution of 0.1 ° was generated for nine major basins in China. The modeling effects of different basins were compared. Then， the GRACE-DSI drought index based on GRACE data was compared with the traditional drought index scPDSI and SPEI， and the spatial distribution characteristics of different grades of drought in nine major basins in China were analyzed. Finally， the drought events in nine major basins in China and the spatial distribution of drought in 2022 were monitored.The results show that except for the inland river， the performance of the other eight watershed downscaling reconstruction models is better， and the consistency between GRACE TWSA and NOAH TWSA is further improved after downscaling reconstruction. The correlation between GRACE-DSI after downscaling reconstruction and scPDSI and SPEI drought index was also significantly enhanced. The frequency of drought in the middle and lower reaches of the Yellow River Basin， the Haihe River Basin and the Pearl River Basin is high and mainly light drought. Similarly， the frequency of drought in the southern part of the Songliao River Basin is also high， but it is mainly characterized by moderate drought and light drought. In addition， the proportion of light drought and moderate drought in the nine major basins is close， and the proportion of heavy drought and extreme drought is different. The proportion of heavy drought in the Huaihe River Basin and the Songliao River Basin is the highest， which is 14 % and 13.4 % respectively. The proportion of extreme drought in the Yangtze River Basin is the highest， which is 16.5 %， while the proportion of extreme drought in the Haihe River Basin is the lowest， which is only 6.1 %. From 2002 to 2022， most of the severe drought events occurred in the northern basins， and 3 of the top 6 drought events occurred in the Songliao River Basin； compared with scPDSI and SPEI， the spatial variation of drought monitored by GRACE-DSI is more consistent with the actual situation. However， since GRACE data represent all water changes， glacier melt water may lead to underestimation of GRACE-DSI.

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.

This study takes Luoma Lake as the research area， utilizing Sentinel-2 satellite imagery， in-situ water quality data， and spectral data to construct remote sensing inversion models for water transparency and suspended sediment concentrations. The models were developed using both statistical methods and machine learning techniques. The performance of both models in water quality inversion was comprehensively compared， and the optimal model was selected for an in-depth analysis of the spatial distribution characteristics of water quality in Luoma Lake. The results indicate that： ① The correlation analysis between Sentinel-2 equivalent remote sensing reflectance and water quality parameters show that the correlation of band combinations is significantly improved compared to single bands. The transparency has the highest correlation with B3/B4 （0.85）， and the suspended matter concentration has the highest correlation with B5/B4 （0.68）； ② Compared with the statistical regression-based inversion model， both water transparency and suspended sediment concentration achieve higher inversion accuracy using machine learning models. The optimal inversion model for transparency （testing set： R2=0.85， RMSE=7.25， MAE=5.25） and suspended sediment concentration （testing set： R2=0.87， RMSE=3.36， MAE=2.49） are both GA-XGBoost models； ③ The inversion results for Luoma Lake indicated that suspended sediment concentrations are higher， and transparency is lower in the northeastern nearshore areas， possibly due to ongoing human activities such as fish farming； ④ A long-term analysis of inversion results from 2018 to 2022 revealed significant seasonal characteristics in the water quality of Luoma Lake. Suspended sediment concentrations were higher， and transparency was lower during the spring and autumn seasons， while suspended sediment concentrations decreased， and transparency increased in winter. During the 2018-2020 period， both suspended sediment concentrations and transparency showed small fluctuations within a certain range， with only a few significant fluctuations driven by seasonal or weather factors. In 2021 and 2022， the removal of embankments and fishing nets in the northern part of Luoma Lake caused sediment disturbance， leading to increased suspended sediment concentrations and decreased transparency.

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.

Efficient and accurate detection and analysis of concrete dam defects images is necessary to ensure the safe operation of the dam. Aiming at the problems of multi-category and uniqueness of surface defect images of concrete dams and the lack of high-quality samples for on-site inspection and inspection of existing dams， this paper first simulates typical defects such as cracks and leakage through self-made concrete slabs to construct a multi-category defect data set of concrete dams， and then uses Yolov8 + U-Net “two-step method” to establish a multi-category surface defect detection and analysis model of concrete dams. Finally， the surface defect images of on-site inspection and inspection of a concrete gravity dam is taken as the test object， and the established detection and analysis model is used for intelligent detection. The results show that the “two-step method” model based on Yolov8 + U-Net algorithm can realize the efficient and accurate detection of seepage and crack defects in concrete dams. The recognition and positioning accuracy rate of the model is 0.84， the recall rate is 0.98， the segmentation accuracy rate is 0.91， and the recall rate is 0.71.

In order to investigate the relationship between the changing law of phreatic evaporation of summer maize in sandy ginger black soil and yellow tidal soil of Huaibei Plain and the meteorological factors and burial depth， the meteorological observation and evapotranspiration meter data of Wudaogou Experimental Station from 2011 to 2022 were selected， and the correlation analysis between phreatic evaporation and meteorological factors during the growth period of summer maize was carried out， and multiple linear regression was performed by the stepping method， and the independent variables of the model were analyzed by the pass-through analysis to reveal the main influencing elements of maize phreatic evaporation， and a regression model was established. We also proposed a nonlinear fitting function between phreatic evaporation coefficient and 0.2-5.0 m burial depth. The results show that： ①in the sandy ginger black soil， the phreatic evaporation coefficient was significantly correlated with the water vapor pressure difference at the burial depths of 0.2 m and 0.4 m； with water vapor pressure difference and absolute humidity at the burial depths of 0.6 m；with water vapor pressure difference， sunshine hours， and relative humidity at the burial depths of 1 m. In the yellow tidal soil， the phreatic evaporation coefficient was significantly correlated with the water vapor pressure at the burial depths of 0.2 m， 0.4 m and 1.0 m； with water vapor pressure difference， absolute humidity， and average temperature at the burial depths of 0.4 m. ②The regression models of maize evapotranspiration and meteorological factors were constructed under different soil qualities and burial depths， and the models met the accuracy requirements （R ²>0.810 for the model of sandy ginger and black soil， and R ²>0.800 for the model of yellow tidal soil）. ③The nonlinear fitting of the phreatic evaporation coefficient to the burial depth showed a logarithmic function relationship （R ²>0.75） for sand-ginger black soil maize； an inverse function relationship （R ²>0.800） for yellow tidal soil maize at the early and late stages， and an exponential function relationship （R ²>0.950） for the developmental stage and the middle stage. ④The maximum burial depth Z_{m of summer maize in sandy ginger-black soil was in the range of 2.7~3.1 m； Zm in yellow tidal soil was in the range of 3.5~4.6 m. The calculation model meets the accuracy requirements and can be used for the calculation of phreatic evaporation of maize during the growing period.}

In view of the application requirements of natural pozzolan in 17.1 million m³ RCC at 1 yr. design age in Basha Dam in Pakistan， the real long-term activity of natural pozzolan was researched by using strength activity index （SAI）， X-ray diffraction （XRD）method and selective dissolution method， and the feasibility of improving the activity of natural pozzolan was explored by using low temperature calcination and particle grading optimization. The results show that the SAI of natural pozzolan tends to decrease continuously with the increase of age， and the main mineral components are mainly inert crystals， whose reaction degree is only comparable to that of quartz powder. Although calcination can activate chlorite and kaolinite in pozzolan， it is difficult to effectively increase the long-term SAI because of its low content. Through the optimization of gradation， the compressive strength ratio of cementitious materials with 50% high pozzolan content can be increased by 6%， and the filling effect can be fully exerted.

The meteorological drought-waterlogging abrupt alternation regulation displays a significant dependency on the spatiotemporal scales of data sources. The response of the regulation on the data resources is very important. This paper evaluated the drought-waterlogging abrupt alternation’s spatiotemporal distribution during the flood season， driving factors and its response to data sources based on the 59 weather stations， 302 rainfall stations， and 130 meteorological-climatical monitoring indexes， using drought-waterlogging abrupt alternation index （DFAI）， time series analysis， geostatistical and machine learning methods. The results show that the main types and intensity of drought-waterlogging abrupt alternation in the flood season are opposite under the two data sources. The drought-to-waterlogging incidents increased by 2.5 times as the main type for the meteorological data， followed by the intensity of abrupt alternation decreasing more than 10%. In comparison， the waterlogging-to-drought incidents increased by 2.6 times as the main type for the precipitation data， in addition to the intensity of abrupt alternation increasing more than 69%. Besides， the drought-to-waterlogging incidents presented a significantly spatial distribution difference under the two types of data resources. The drought-to-waterlogging and waterlogging-to-drought incidents on annual scale and typical annual scale were observed in the eastern and southern part of the study area for the meteorological data， respectively. In comparison， these two types of incidents on the annual scale and the typical annual scale were detected to appear in the northern and southern part of the study area for the precipitation data， respectively. The DFAI’s temporal changes’ driving factors were significantly different for the two types of the data sources. Based on the random forest and K-nearest neighbor algorithms， the Tibet Plateau Index and El Nino and Southern Oscillation indices were detected as the main driving factors under the weather station data source， indicated by the absolute values of correlation coefficient and partial correlation coefficient ranging from 0.32 to 0.35 and 0.33 to 0.36. Their contribution rates were greater than 45% on the temporal changes of the DFAI. Under the rainfall station data source， the Asian Meridional Circulation index was regarded as the main driving factor， indicated by the absolute values of correlation coefficient （0.32） and partial correlation coefficient （0.38）. Its contribution rate was estimated to be 79% on the DFAI’s temporal changes.

Based on a high head and large discharge shaft spillway tunnel project， a new Dragon head shaft spillway tunnel is proposed. Numerical simulation is used to compare and analyze the original design of the platen-type shaft spillway and the optimized new-type dragon head shaft spillway. The latter has a smooth flow connection and a better flow pattern. The hydraulic characteristics of the new Dragon head shaft spillway are studied by numerical simulation and model test. The results show that the water cushion in the stilling well is deeper and the floor impact pressure and pulsation pressure are smaller， which improves the turbulent strength and energy dissipation rate and reduces the risk of cavitation and cavitation erosion. The water flow in the connecting section of the dragon head is stable， and the phenomenon of water rushing to the top is avoided. The results of hydraulic model test and numerical simulation on the water surface line， flow rate and pressure in the spillway tunnel of the new Longhead shaft are in good agreement. The optimized new Dragon head shaft spillway can effectively improve the energy dissipation of shaft and provide a new energy dissipation scheme for the project.

In the increasingly complex and harsh geological environment of engineering， the quality requirements for grouting reinforcement are becoming higher and higher. A single grouting method and material can no longer meet the actual needs of engineering construction. This article proposes the concept of composite grouting for sandy tunnels through material composite and process composite， in order to meet the strict requirements for anti-seepage and reinforcement in high head and large flow loose gravel formations. That is， for low-permeability and dense sand layers， high-pressure fracturing method is used to generate a slurry vein skeleton， followed by infiltration grouting in locally weak and loose sand areas， ultimately forming a dense and solid composite structural system. This article analyzes the mechanical mechanism of slurry splitting and diffusion in composite grouting technology， derives the basic relationship between splitting width， slurry pressure， and ultimate diffusion distance. Then， based on the basic theories of elasticity and structural mechanics， the stability of the slurry vein skeleton and surrounding rock composite structure is analyzed， and the reinforcement effect of composite grouting is scientifically evaluated. Finally， the section tunnel of Chongqing Metro Line 10 is selected for on-site testing of the actual reinforcement effect of composite grouting.

River-crossing bridges can alter the flow structure of river channels， and excessive flow-blocking effects may compromise both flood control safety and the structural safety of the bridges themselves. The blockage ratio， a key parameter quantifying the water resistance of the bridge， deserves thorough investigation. This study evaluates the effects of bridge types， bridge span arrangements， and skewed piers on blockage ratios through data analysis and generalized calculations. Results show that arch bridges and suspension bridges exhibit relatively smaller blockage ratios， followed by cable-stayed bridges， while continuous girder bridges demonstrate comparatively higher blockage ratios. Under identical pier diameters， larger span lengths between piers correlate with reduced blockage ratio. Notably， an increase in the oblique angle between piers and water flow significantly amplifies the blockage ratio， suggesting optimal control of oblique angles within 5° or 10°. The 1D and 2D mathematical model are employed to calculate the backwater height under the design flood condition in Wuhan river-reach of the middle Yangtze River. Results show that when the blockage ratios range between 2% and 20%， 1D modeling indicates a backwater height of 0.02~0.22 m at the cross-section upstream of bridge， 2D modeling indicates local backwater height of 0.12~0.30 m in front of piers and an average backwater height of 0.01~0.14 m at the same cross-section. The discrepancy in computational results between the two models stems from differences in modeling principles and simplification approaches. Based on comprehensive backwater calculations and relevant technical standards， it is recommended to maintain the blockage ratio of river-crossing bridges within 5%， and the blockage ratio requirements for river sections in mountainous canyon reaches without critical flood-protection objects may be appropriately relaxed upon technical confirmation of minimal impact on flood control safety. Research proposes the following measures to reduce the blockage ratio： selecting bridge types with lower blockage ratio， maximizing span lengths， adopting streamlined or circular pier shapes， aligning pier axis parallel to the flow direction， and so on. These recommendations provide a scientific foundation for bridge engineering design， flood impact assessments， and regulatory management of river-related projects.

Water-gas-sand three-phase flow is the most complicated flow in intake system for hydraulic machinery， where the key difficulty is that the vortex takes both gas and sand into the system， which induces large erosive damage on pumps， resulting in unsafe and unstable operation of hydraulic machinery. This study focuses on the characteristics of three-phase vortex flow in sump with sand by experimental test to figure out the effects of water-gas vortex flow on the sand movement in the bottom， and further to analyze the critical submerged height. The results obtained show the physical process that the bed material load is possible to enter the system following FAGV， i.e.， during the formation to dissipation of the floor-attached gas vortices （FAGV）， the particle movement in the bottom is enhanced to spirally enter the pipe. Compared with the same situation in clean water， the frequency of vortex occurrence is higher and the duration is longer if the FAGV occurs， and the critical submerged height is also different， so it is necessary to make new design standards of sump with sediment flow.

Based on the precipitation， runoff and sediment transport data of three typical hydrological stations （Lanzhou， Longmen and Lijin） in the upper， middle and lower reaches of the Yellow River Basin from 2002 to 2022， the characteristics of water-sediment change and its driving factors were analyzed by the Mann-Kendall trend test， Pettitt mutation test， water-sediment relationship curve and double accumulation curve， and the contribution rates of climate change and human activities to the changes of runoff and sediment discharge were calculated. The results show that the runoff of Lanzhou （flood season and non-flood season） and Lijin （non-flood season） has a significant increasing trend and the change rates are 483， 247 and 337 million m³/a， respectively； the sediment transport of Longmen has a significant decreasing trend and the change rate is -1.280 1 million t/a in the non-flood season. The abrupt change points of precipitation， runoff and sediment transport at each hydrological station are different to some extent. For example， the abrupt change points of sediment transport at Lanzhou， Longmen and Lijin during the flood season are 2008， 2009 and 2018， respectively. The water-sediment relationship fitting of Lanzhou （non-flood season） and Lijin （flood season and non-flood season） is relatively good， Longmen （flood season） and Lijin （non-flood season） have the largest sediment transport capacity under the action of runoff erosion， and Lanzhou （non-flood season） and Lijin （flood season） have the strongest erosion capacity. In the non-flood season， the contribution rates of human activities to Longmen （runoff） and Lijin （sediment transport） are relatively large， at 94.69% and 94.50%， respectively， and the contribution rates of precipitation to Lanzhou and Longmen are relatively large， at 99.54% and 99.03%， respectively. The research results can provide a scientific basis for the rational control of water and sediment and the high-quality sustainable development of ecological environment in the upper， middle and lower reaches of the Yellow River basin.

Heilongjiang Province is the main distribution area of high-latitude permafrost in China. Under the trend of climate warming， the degradation of permafrost is serious， and the hydrological， ecological and environmental problems caused by it have become the focus of attention of related scientific research. Based on the air temperature and surface temperature data from 34 meteorological stations in Heilongjiang Province from 1971 to 2019， the temporal and spatial variations of mean annual air temperature， mean annual surface temperature， freeze-thaw index， the characteristics of permafrost distribution and its influencing factors were investigated by using the freeze-thaw index and surface freezing number models， combined with the trend fitting and the localized thin-disk smooth spline function interpolation method. The results show that the range of multi-year mean air and surface temperature changes in Heilongjiang Province is -8.64~5.60 ℃ and -6.52~7.58 ℃， respectively， with a banded spatial distribution with latitude and altitude， and the interannual warming rates of mean annual air and surface temperatures tend to be consistent with each other， which are 0.34 and 0.33 °C/10 a， respectively. From 1971 to 2019， the air freezing index and surface freezing index decreased at the rate of -5.07¹ and -5.04 ℃·d/a， respectively， and the air thawing index and surface thawing index increased at the rate of 7.63 and 11.89 ℃·d/a. The spatial distribution of the air/surface freeze-thaw index all showed latitudinal trends， but in the northern mountainous areas the effect of elevation was greater than latitude. Permafrost is mainly distributed in the Greater and Lesser Khingan Mountains in the north， and sporadically distributed in the central mountainous areas. The southern boundary of permafrost shifted northward by about 2° from 1970 to 2010s， and the total area of permafrost shrunk from 11.1×10⁴ km² in the 1970s to 6.53×10⁴ km² in the 2010s， and the distribution of permafrost is most highly correlated with the air temperature， the surface temperature and air freezing index， and its spatial distribution is strongly correlated with latitude and altitude. The results of the study are of great significance for analyzing the trend of high-latitude multi-year permafrost degradation in Heilongjiang Province and the entire Northeast China， and can also provide references for the development of natural cold resources， ecological protection and engineering construction in permafrost areas.

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.

In this paper， a bidirectional fluid-structure coupling method based on the Large Eddy Simulation （LES） and the fourth-order Runge-Kutta method is used to numerically simulate the one degree-of-freedom （1DOF） VIV of a circular cylinder under the Reynolds number range of 2×10³~1.4×10⁴. The simulation results including vibration amplitude ratio， frequency ratio， and wake vortex structure are all in good agreement with the experiment results， and the characteristics of three response branches （the initial branch， upper branch， and lower branch） in the 1DOF VIV of a circular cylinder are accurately reproduced. On this basis， further research on the interaction between cylinder vibration and vortex evolution is conducted to explore the response mechanism of the three response branches in 1DOF VIV. The results show that in the initial branch， there is mainly the effect of vortex evolution on cylinder vibration， while the cylinder vibration has little effect on the vortex evolution. In the upper branch， there exists a fierce interaction between cylinder vibration and vortex evolution. After entering the lower branch， the interaction becomes weaker， but still has a certain intensity.

Well-type pumping station is a new type of pumping station layout， in which the pumps are arranged along the circumference of the top slab of the outer working wells. Compared with traditional pumping stations， the fluent conditions of the pump are more complex. Based on the SST k-ω turbulence model， numerical simulation was carried out， and combined with physical models， the flow pattern around the inlet of the pump with and without different vortex elimination measures. Furthermore， we selected appropriate vortex elimination measures was analyzed. The results show that under the condition of no vortex elimination measure， periodic top vortices will be generated near the inlet， and the asymmetry of water flow flanked the inlet is an important reason for the flow deviation. The four vortex elimination measures adopted can improve the flow state of varying degrees， among which the measure of setting a horizontal cover plate has the best improvement effect. The flow state near the bell mouth is uniform and the water inlet conditions are good.

As global climate change intensifies， the hazards of different types of droughts have further increased. The causes of droughts are complex， involving a blend of natural and human factors， which makes it challenging to fully assess drought conditions with a single index. To more accurately monitor and evaluate droughts， this study uses the Copula function combined with precipitation data and GRACE satellite-derived terrestrial water storage to develop a comprehensive drought index （saCMDI） that comprehensively considers natural factors and human activity elements. Applied to mainland China from 2002 to 2021， saCMDI demonstrates strong correlations with commonly used indices such as SPEI3， WSDI， and scPDSI. It effectively detects droughts caused by both precipitation deficits and terrestrial water storage shortfalls， capturing the onset and end of drought events， and the identified drought events are highly consistent with historical records in China， indicating that the index has a high reliability for evaluating large-scale droughts. The results reveal significant spatial variability in drought characteristics across mainland China. Southern， northeastern， and some western regions experience longer drought durations （2.5~3.5 months） compared to central and eastern regions （1.0~2.5 months）. Drought frequencies are notably higher in arid and semi-arid areas （13%~18%） than in humid and semi-humid regions （7%~13%）. Drought intensity generally increases from northwest to southeast， with the southern， northeastern， and certain western regions exhibiting higher drought intensities due to the cumulative effects of prolonged drought periods. Reduced precipitation and soil moisture are the main contributors to droughts in most of mainland China， although groundwater extraction and surface water supply issues also play significant roles in specific river basins. This study provides essential insights for improving drought risk management and guiding water resource planning across different regions of China.

The maximum height of the upstream earth-rock cofferdam of a hydropower station is 62 m， and the height of the slope formed by the cofferdam and foundation pit is 135 m. The earth-rock cofferdam is located on deep overburden layer with a maximum thickness of 71 m. The overburden layer has the characteristics of “low bearing capacity， small permeability coefficient， low shear strength and high compressibility”. In order to ensure the safety and stability of the cofferdam and slope， vibro-replacement stone column is used in design to reinforce the deep overburden layer of the cofferdam foundation. The depth of the designed stone column of a hydropower station far exceeds the existing technology level. It is the deepest stone column applied ever in engineering practice in China on a large scale. In order to solve the problem of ultra-deep vibro-replacement stone column construction and verify the effect of stone column reinforcement and drainage， the ultra-deep vibro-replacement stone column construction equipment and technology are determined through on-site productive tests， and the physical and mechanics parameters such as shear strength， bearing capacity and compression modulus of stone column body and soil between column， permeability coefficient of stone column， etc. are obtained. A set of control methods which can be applied to large-scale construction， quality inspection of vibro-replacement stone column in cofferdam foundation are summarized. This research results can be used as a reference for the design， construction and acceptance of foundation treatment of hydropower engineering projects.

Soil salinization is one of the key factors affecting the sustainable development of agriculture in the Hetao Irrigation District. Accurate prediction of soil salinization and sodification trend is an important means to formulate scientific prevention and control measures. Traditional studies usually use the total amount of soil salinity in the root zone as an indicator to evaluate the evolution trend of salinization， while rarely paying attention to changes in ion composition. Due to the different physical and chemical behaviors and migration capacities of different salt ions， soil salts not only changes in total amount， but also change in composition of salt ions under the influence of external forces such as irrigation leaching， evaporation， freezing and thawing. To conduct in-depth research on the distribution and transport patterns of salt ions in different land use types， this paper selects a typical area in the Yichang Irrigation Area of Inner Mongolia's Hetao Irrigation District as the research area. From 2017 to 2019， observations were conducted on the distribution processes of various ions， analyzing the dynamic processes of water， salt， and ions， as well as the characteristics of ion differentiation.The soil moisture content increases with depth due to water infiltration and water-holding capacity， while variability showes an inverse trend， decreasing with soil depth. The electrical conductivity （EC） profile of abandoned cultivated land decreases with depth， with surface accumulation being the main feature of overall salt distribution. The distribution of salt ions in soils of different land types is primarily characterized by highly differentiated Na⁺， Cl^-， and SO₄ ^2- ions. The HCO₃ ^- content is also significant but is relatively uniformly distributed in the soil profile. The contents of Ca²⁺ and Mg²⁺ are noticeably lower， especially in wasteland where both their composition and proportion are minimal. The mobility differentiation of various salt ions is evident. The migration degree and rate of cations are in the order of Na⁺ > Mg²⁺ > Ca²⁺， which correlates with ion migration rates through soil layers. Among anions， Cl^- shows the strongest differentiation， while HCO^3- exhibits weaker differentiation.

Accurate discrimination of surrounding rock state after excavation is of great significance in guiding the excavation construction and improving the support scheme. Aiming at the problem that the plastic zone index in the traditional finite difference simulation method cannot accurately reflect the influence range of surrounding rock excavation， this paper proposes a kind of surrounding rock state discrimination index based on local elastic strain energy release， and elucidates the feasibility of this index based on FLAC^3D finite difference numerical simulation. At the same time， through the comparison of elastic strain energy release and plastic zone distribution， the excavation stability evaluation of Gongyi Pumped Storage Power Station′s underground cavern group was carried out. The results show that the range of elastic strain energy release is obviously lower than the depth of plastic zone， which can better reflect the loss of bearing capacity of surrounding rock， and the discrimination method of surrounding rock state based on elastic strain energy release has good applicability in the evaluation of stability of top arch excavation support of Gongyi Pumped Storage Power Station.

Green roof is an important infrastructure for the low impact development （LID） and sponge city construction. How to establish a simple and practical hydrologic model， taking the runoff coefficient as an important index， for green roof to evaluate the rainfall-runoff reduction effect is an important question. Based on the measured data of rainfall runoff of green roofs at different times， the calculation expression of runoff coefficient is developed on the basis of the calculation formula of rainfall runoff depth of SCS model. Also， the potential maximum retention is calculated when the measured initial loss is selected reasonably using event analysis method. The results showed that the initial loss and the potential maximum retention at that time are basically linearly related， with an average ratio coefficient of about 0.28. The potential maximum retention will be reduced due to the rainwater retention during the rainfall period， and then gradually recovered during the drought period， and the overall trend is that the initial recovery rate is fast， then gradually decreases， and finally approaches 0. Based on this， A calculation expression to describe the variation process of the potential maximum retention including the rainfall and drought periods is proposed. Based on the runoff depth and runoff coefficient formulas of the SCS model， combined with the calculation expression of the potential maximum retention variation process， the continuous variation processes of the runoff depth and runoff coefficient for green roof are simulated and then the model effect is evaluated using the certainty coefficient R ² and the Nash Sutcliffe efficiency coefficient NSE. The results showed that the calculated values of runoff depth and runoff coefficient are in good agreement with the measured values. The R ² values are 0.93， and 0.85， the NSE values are 0.94， and 0.85 respectively， which has a good simulation effect.

In light of the current challenges in managing flash flood disasters in small and medium-sized basins， it is imperative that improvements to hydrological models take into account the vegetation cover of the underlying surface. further clarify the runoff generation and routing characteristics of the watershed， thereby enhancing the accuracy of forecasting and early warning systems. This study builds upon the traditional TOPMODEL， selecting the Gaotian River Basin and Pajiang River Basin in Qingyuan City， Guangdong Province as the research areas. It selects 15 flood events from the Gaotian River Basin （1975-2013） and 15 flood events from the Pajiang River Basin （1971-2002） for simulation. The coefficient of determination is employed as the objective function， and the SCE-UA optimization algorithm is utilized for parameter calibration and validation. This analysis explores the feasibility of incorporating the curve number （CN value） and generalized unit hydrograph theory to enhance the model's runoff generation and routing module. The results indicate that the average coefficients of determination for the calibration and validation periods improved from 0.74 and 0.75 to 0.82 and 0.80 for the Gaotian and Pajiang River Basins， respectively， demonstrating enhanced simulation accuracy compared to the traditional TOPMODEL. According to the "Hydrological Information Forecasting Specification GB/T 22482-2008，" the model achieved pass rates of 80% and 100% for the two study areas， indicating its capability to accurately capture peak flow rates and their occurrence times， along with a high reliability in simulating total runoff for the selected flood events. Moreover， the generalized unit hydrograph， as a model not yet widely utilized， requires further validation in additional practical applications. The multi-event flood simulation results presented in this study not only contribute to the validation of the model but also provide important data support and theoretical foundations for investigating the relationship between generalized unit hydrograph parameters and the characteristics of watershed underlying surfaces， thus promoting its widespread application in the field of hydrological analysis.

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.

There are a lot of crisscrossing waterways in the plain area， with slow and unpredictable water flow. There are numerous gate stations in the plain basin， resulting in extremely complex water and engineering conditions. Once a flood occurs， it will lead to a large-scale flood disaster， posing a significant threat to the safety of people's lives and property. In order to accurately simulate the runoff generation and convergence process of flood in the plain areas， this paper combines the advantages of the SCS model and MIKEFLOOD model to construct a hydrological and hydrodynamic model， and fully considers the different types of underlying surface runoff processes and complex gate station scheduling regulations， which can effectively improve simulation accuracy. The Tongshun River Basin located in the hinterland of the Jianghan Plain in Hubei Province was selected as the research area. The model was calibrated and validated by measured data. The impact of different rainfall conditions on the region was analyze based on the hydrological and hydrodynamic model. The results showed that ① The model was calibrated and validated by using the measured water levels in 2003， 2010， and 2016. The simulated correlation coefficients were all above 0.8， with an error of less than 2%； This result indicates that the simulation effect of the model is good and can be used for simulating the runoff of the Tongshun River Basin. ②The Tongshun River Basin was divided into 11 sub-drainage areas. According to the calculation results of the SCS model， the Pai hu drainage area was the highest water production area； The current drainage capacity of 7 drainage areas， such as Xingfu and Tongbei， is less than that of the 3-day rainstorm with a 10-year return period. ③ When the 5 to 20-year return period flood occurs， the water level of the river gradually decreases when the drainage time of the watershed reaches 10 to 12 days. When the 30-year return period flood occurs， the water level in the basin first increases and then tends to stabilize although the drainage time of the watershed reaches 10 to 12 days. This result indicates that the current drainage capacity within the Tongshun river basin cannot meet the requirements of a 30-year return period flood. This study can provide reference for the development of drainage measures in complex plain river network areas.

Soil moisture （θ） plays an important role in water cycle and climate change. However， due to the strong spatial and temporal heterogeneity of θ， it is still a challenge to effectively monitor and estimate soil moisture. In order to optimize the layout of soil moisture monitoring sites and predict soil moisture， this paper took the Shale Hills in Huntington， central Pennsylvania， USA as the study area. Based on the daily scale data of 33 sites in the study area for 3 years （from May 20， 2011 to May 19， 2014）， a time stability analysis was carried out. Then the sites of each soil layer are optimized by combining the analysis results with the division of landform units in the study area. Finally， the optimized sites were taken as the input values of the model， and linear （stepwise multiple linear regression-SMLR） and non-linear （back propagation neural network-BPNN） models were used to construct soil water relationship models between other sites （27 sites） and the optimized sites （6 sites）， so as to predict θ at sites other than the optimized sites. The results show that it is feasible to select sites based on time stability analysis， and the method of time stability analysis combined with the division of landform units can select 6 sites in each soil layer as the input values of the model. The nonlinear model is much more suitable for soil water prediction in the study area， and has good prediction effect for the whole study area， every landform unit and every site. In the validation datasets of different soil layers， 32， 29 and 30 sites in each soil layer have R2 values above 0.7. The RMSE values were all lower than the accuracy of the soil moisture content probe. The ratio of the average RMSE to the measured soil water is less than 6% in whole small watershed， and no more than 8% in each landform unit， and in more than 90% of the sites， the ratio does not exceed 10%. The research results provide a theoretical basis for optimizing soil moisture monitoring and solving the data loss at some sites.

The ecological footprint of agricultural water use is of great significance for understanding the ecological status of water environment and measuring the ecological occupation of water resources by agricultural development. The dynamic evolution patterns and driving factors of China's agricultural water ecological footprint are analyzed using water ecological footprint models， visualization maps， Kernel density estimation， Moran index， and geographic detectors. The results show that： ①From 2005 to 2022， the total ecological footprint of agricultural water use in China increased from 19 million square meters to 21 million square meters， with a regional ranking of Northeast>Central>West>East. The ecological footprint of agricultural water use per 10000 yuan of GDP decreased from 2.13 to 0.49， with a regional ranking of West>Northeast>Central>East. ②The ecological footprint of agricultural water use per 10000 yuan of GDP shows a spatial change feature of decreasing “from north to south” and “from northwest to southeast”. High value areas are distributed in Xinjiang， Xizang and Ningxia， while low value areas are distributed in Sichuan and Chongqing in the southwest and Henan， Shandong and Hebei in North China； ③The Kernel density estimation shows a dynamic evolution pattern of “increasing peak height、 decreasing peak number、 curve moving to the left、shortening right tail、decreasing width”； ④ During the investigation period， the spatial Moran index was significantly positive and mainly distributed in the first、second、and third quadrants； ⑤The results of the geographic detector reveal that， the average explanatory power of driving factors is ranked as follows： fiscal support for agriculture （0.25）>economic development level （0.23）>proportion of primary industry （0.20）>water resource endowment （0.19）>agricultural water conservancy infrastructure （0.19）>proportion of animal husbandry （0.15）>agricultural disaster rate （0.11）>degree of agricultural mechanization （0.07）. The explanatory power of agricultural water conservancy infrastructure， fiscal support for agriculture， proportion of animal husbandry， and agricultural disaster rate shows a fluctuating upward trend. The research conclusion is that the ecological footprint of agricultural water use per 10，000 yuan of GDP in China shows a trend of decreasing convergence and agglomeration； In terms of space， it mainly presents a positively correlated agglomeration pattern， with "low-low agglomeration" areas accounting for 45.16%， which is the most important agglomeration mode； The financial support for agriculture and the infrastructure of agricultural water conservancy are the core factors that continue to promote spatial differentiation.

Laos is one of the important member countries of the “Belt and Road” construction， and the Nangong1 Hydropower Station is a key project of China-Laos clean energy strategic cooperation and development. In order to solve the problems of short construction period， shortage of personnel during the epidemic， the need for construction in high temperature seasons， and the difficulty in controlling the quality of spillway excavation materials used as dam materials for Nangong1 Hydropower Station， the construction process and crack prevention technology of the panel concrete were optimized through measures such as material selection， mix ratio experiments， and optimization of construction technology， ensuring the quality of concrete panels and the safety of dam operation. The main research results are as follows： during the construction process， the dam material effectively solves the problem of quality control in the construction of panel concrete during the high temperature season by controlling the compression of the side wall structure， concrete panels， and concrete pouring process， ensuring that the various performance indicators of the concrete panels of Nangong 1 hydropower station reach or even exceed the design standards and similar types of panels； We conducted relevant tests such as concrete shrinkage and cement hydration heat comparison， combined with the performance of concrete mixtures， concrete mechanics and other related test results， and selected the optimal concrete mix proportion that meets the design requirements to enhance the ability of panel concrete to adapt to deformation and reduce the occurrence of cracks in the panel. After testing， it was found that the panel of the Nangong 1 hydropower station′s rockfill dam is tightly combined with the squeezed side wall， and no cracks were found on the concrete panel. The quality is excellent， providing a guarantee for the stable and safe operation of the dam.

Groundwater is an important water supply source in Jinan City. In order to achieve sustainable development and utilization of groundwater resources， it is necessary to carry out groundwater storage changes analysis and groundwater resources assessment in Jinan. This paper is based on the GRACE gravity satellite and GLDAS global land surface assimilation system data， and uses singular spectrum analysis method to reconstruct terrestrial water storage change （ΔTWS） data. A multiscale geographical weighted regression （MGWR） model was constructed， using evapotranspiration （ET）， precipitation （PRE）， land surface temperature （LST）， and vegetation index （NDVI） as regression variables to downscale groundwater storage change （ΔGWS） data in Jinan， and the spatiotemporal change analysis of ΔGWS and groundwater resource evaluation were conducted. From April 2002 to December 2023， ΔTWS and ΔGWS showed a downward trend in Jinan. During the year， ΔGWS was the smallest in June and the largest in December. The lag effect of ΔGWS on precipitation changes is obvious. The MGWR model enhanced the resolution of ΔGWS data in Jinan from 0.25° to 1km. The trend changes and spatial distribution of ΔGWS exhibited a high degree of consistency before and after downscaling， indicating that the MGWR model is effectively applicable for downscaling ΔGWS data.The BEAST algorithm is used to deconstruct ΔGWS time series in Jinan. ΔGWS is mainly controlled by the trend term， and there are two mutation points with a probability greater than 0.5. There are obvious differences in the spatial distribution of ΔGWS in Jinan. Laiwu District and Gangcheng District have relatively large groundwater storages， while Pingyin County and Changqing District have lower groundwater storage. The ΔGWS center of gravity is mainly located in Licheng District. The water amount in the rising section of ΔGWS is used to characterize the amount of groundwater resources in Jinan. From 2003 to 2019， the average amount of groundwater resources is 2.290 billion^{m3， and the amount of groundwater resources in extraordinary dry years， dry years， and normal flow years are 1.657、2.722 and 2.955 billionm3 respectively in Jinan. The research results provide scientific reference for the rational development and utilization of groundwater resource in Jinan.}

Large deformation or landslide of dam slope seriously threatens the long-term operation safety of the reservoir area. The mainstream traditional slope deformation prediction models fails to fully considered the temporal and spatial characteristics of deformation. This article introduces four representative deep learning methods， namely Transformer， Spatio-Temporal Graph Convolutional Neural Network （STGCN）， Temporal Convolutional Network （TCN）， and Graph Convolutional Neural Network （GCN）， and proposes a spatiotemporal prediction method for slope inclinometer deformation based on deep learning models. The deformation monitoring data of a certain hydropower slope inclinometer hole are used， and the monitoring data are systematically analyzed. The prediction results indicate that all four models， GCN， TCN， STGCN， and Transformer， are suitable for slope spatiotemporal prediction. Among them， the TCN model shows higher prediction accuracy and reliability compared to the other three spatiotemporal prediction models， with evaluation indicators MAE、MSE、RMSE、MAPE and R ² of 1.007、2.208 2、1.486、102.40% and 0.988 4， respectively. In addition， the prediction results of the four models on different dates have an error distribution of 0-4mm compared to the actual measurement， which verifies the accuracy and effectiveness of the four models in predicting the deformation of slope inclinometers in time and space. The research results provide new ideas for short-term spatiotemporal prediction of slope deformation in the reservoir area.

Pumping station technology upgrading is an important part of building a national water network， realizing the goal of “dual carbon”， and integrating water resources， ecology and energy security. Overseas pumping stations have made significant progress in hydraulic design， material application， informatization and energy synergy， which is manifested in the enhancement of adaptability to extreme working conditions， improvement of the level of intelligent operation and maintenance， improvement of the ecological mode of operation and the development of green energy supply system. However， under complex conditions such as high sand content and strong corrosion， there are still problems such as insufficient design accuracy， imperfect failure prediction， unclear ecological response mechanism and limited multi-energy synergy optimization. In this paper， the latest foreign research results and engineering practices are sorted out， and key technologies such as inverse problem and machine learning fusion design， digital twin technology， fish-friendly flow channel and ecological protection measures， and wind-solar storage and complementary evaluation are summarized. It also proposes technical paths for the national water network and the follow-up project of South-to-North Water Diversion， which will provide reference for the modernization of water conservancy infrastructure and the construction of intelligent water conservancy during the 15th Five-Year Plan period.

The purpose of this study was to investigate the effects of different brackish water irrigation modes on salinity distribution， physiological and ecological characteristics of rice， and yield in saline-alkali soils. According to the utilization of brackish water， four irrigation modes were set up： freshwater irrigation （control group）， re-irrigation， freshwater-brackish water shallow wet alternate irrigation and freshwater-brackish water alternating irrigation. The results showed that： ① Freshwater-brackish water shallow wet alternating irrigation and freshwater-brackish water alternating irrigation could reduce the maximum photochemical quantum yield （F_v /F_m ）， actual quantum yield （Ф _PSⅡ） and photochemical quenching （q_p ） of rice leaves， while these two treatments could also reduce the net photosynthetic rate （P_n ）， transpiration rate （Trmmol） and stomatal conductance （Cond） of rice leaves， while the decrease of rice photosynthetic rate was caused by non-stomatal factors. ② Compared with freshwater irrigation， freshwater-brackish water shallow and wet alternate irrigation and freshwater-brackish water alternating irrigation significantly increased the salinity of the upper layer of soil， and the reirrigation of retreat water could mainly reduce the soil salinity by 0~30 cm. All irrigation modes carried out different degrees of soil salt washing， and the desalting rate of 0~50 cm soil layer was more than 40%， in which the desalting effect was the most significant with the re-irrigation mode， reaching 58.3%. ③ Different brackish water irrigation modes inhibited the growth of rice， and the yield of rice gradually decreased with the increase of irrigation water salinity concentration， and the yield was in the order of re-irrigation> freshwater irrigation> freshwater-brackish water shallow and wet alternate irrigation >freshwater-brackish water alternating irrigation. During the growth period of rice， the water consumption of freshwater-brackish water shallow and wet alternate irrigation was the least， and the crop water use efficiency was the largest. In this study， the implementation of freshwater-brackish water shallow-wet alternating irrigation strategy in saline-alkali soil can not only effectively improve rice yield， but also significantly improve the water use efficiency of crops. This provides a practical and sustainable agricultural irrigation solution for saline-alkali areas with limited freshwater resources， and has important practical significance and promotion value.

Piping is a typical form of seepage failure in earth-rock dams， and its evolution process is accompanied by internal physical field changes within the earth-rock dam structure. Investigating the relationship between the variations in the internal physical field of earth-rock dams and the evolution of piping is of significant importance for identifying the state of piping progression. In view of this， a multi-field information fusion analysis framework for piping evolution is first constructed based on the multiple physical field information obtained during the operation of earth-rock dams. Building on this foundation， the seepage pressure， temperature， electrical potential， and flow velocity fields during the piping evolution process in earth-rock dams are integrated. By applying normalization and dimensionality reduction techniques， a matrix decomposition fusion method and principal component analysis （PCA） are employed to perform fusion analysis of the multi-field fitting functions. Subsequently， a quantitative characterization function with established correlations is constructed to analyze the logical symbiotic relationships among seepage pressure， temperature， electrical potential， and flow velocity fields. Finally， by analyzing the characteristics of different stages in the evolution of piping， the normalized timeline of piping evolution in earth-rock dams is divided into three stages： （0， 0.481）， （0.481， 0.663）， and （0.663， 1）. These stages correspond to the initial phase， expansion phase， and critical phase of piping evolution， respectively. The proposed method for multi-field information fusion and state identification in the piping evolution process of earth-rock dams offers a valuable reference for seepage safety monitoring and early warning in such structures.

Accurate and timely soil moisture inversion is a crucial foundation for implementing precision irrigation management in farmlands， significantly enhancing irrigation water resource utilization efficiency. This study developed enhanced Thermal Optical Trapezoid Model （TOTRAM） and Optical Trapezoid Model （OPTRAM） by incorporating nonlinear dry/wet boundaries and phenological characteristics， using multi-source remote sensing data from Landsat-8/9 and Sentinel-2A/B. The OPTRAM model further accounts for the influence of phenological stages.The accuracy of the enhanced models in soil moisture inversion for arid farmland was then evaluated using measured soil moisture data.The findings of the study demonstrated that the original TOTRAM model exhibited superior performance in comparison to the basic OPTRAM model， with root mean square errors （RMSE） of 0.183 cm3/cm3 and 0.141 cm3/cm3， respectively. The implementation of non-linear dry/wet boundaries resulted in a substantial enhancement in the performance of both models， achieving comparable reductions in RMSE to 0.145 cm3/cm3 （TOTRAM） and 0.126 cm3/cm3 （OPTRAM）. The phenology-integrated OPTRAM model demonstrated optimal accuracy， with a root mean square error （RMSE） of 0.096 cm3/cm3. In summary， the enhanced OPTRAM model exhibited superior precision in the retrieval of soil moisture in arid agricultural soil compared to TOTRAM， while concurrently maintaining the higher spatiotemporal resolution advantages afforded by optical satellite data. This advancement provides critical technical support for precision irrigation management systems.

Meandering rivers exist widely in nature， and understanding their complex evolution process and mechanisms is important. Many studies have been conducted to investigate the movement of water and sediment， as well as the evolution of riverbeds in meandering rivers， using river model tests. This paper reviews the research results of existing meandering river models and systematically summarizes the development process， characteristics， and application scope of idealized river models and natural river models. The main results are as follows： the idealized river models make a high degree of generalization of natural rivers. It can be categorized into three types of meandering river models based on different design approaches： arc and straight line combination， sine-derived curve， and Kinoshita-derived curve. These idealized river models are more applicable in fundamental theoretical studies of river sediment dynamics. The natural river model is based on an actual river and is designed according to a certain similarity principle. It mainly includes the scale model and the natural evolution model. The scale model is a physical model of the prototype river scaled according to a certain geometric scale that ensures the similarity of water movement and sediment movement. The scale model is suitable for the inversion and simulation of water and sediment transport， channel siltation and degradation， and riverbed evolution of the prototype river channel. The natural evolution model is a model river similar to the prototype in riverbed morphology， which is shaped by controlling the flow conditions and river boundary conditions such as riverbed composition and riverbed gradient. The natural evolution model is more applicable in studies related to the evolution of river types. Both types of natural river models bear similarities to the prototype river and can provide a direct reference for practical engineering applications. In summary， idealized river model and natural river model have their own advantages and disadvantages in basic and applied research， and different model types can be selected according to the research needs.

Accurate groundwater level prediction is of great significance for groundwater resources management in irrigation areas. However， due to the difficulty of processing unstructured well position data in irrigation areas， traditional deep learning methods do not consider the spatial positional relationship of each monitoring well and the own attributes of each well in irrigation areas， resulting in a serious lack of physical interpretability of deep learning models. This study fully considers the spatial positional relationship of each monitoring well and the static attributes of well points to construct a graph structure with sufficient physical meaning. A GWN model based on graph neural networks is proposed. Taking the Yichang irrigation area in the Hetao irrigation area as an example， combined with the EEMD algorithm to preprocess the groundwater level data， the model groundwater level prediction results are compared with the two baseline models LSTM and GRU to verify the rationality of the model. The results show that the GWN model with EEMD algorithm is better than the baseline model， and the statistical indicators such as MAE， RMSE， and NSE are better than the baseline model. At the same time， compared with the single well prediction of the baseline model， the GWN model can predict the water levels of all monitoring wells at the same time， and the prediction efficiency is significantly improved. In addition， the graph structure containing physical meaning is adaptive and iteratively updated to reproduce the groundwater network with physical background in the irrigation area. The relationship and reasons between the wells can be intuitively interpreted from the adjacency matrix combined with the static attribute distribution map. In short， the model has good groundwater level prediction effect and interpretability， which can provide a reference for the groundwater level management of the Yichang irrigation area in the Hetao irrigation area of Inner Mongolia.

The change of temperature stress in high altitude area has a significant influence on the overall bearing capacity of concrete double-curvature arch dam. In order to analyze the overall bearing capacity of the concrete double-curvature arch dam of ZY hydropower station under temperature effects， and ensure the safety design， construction and operation of the project， a three-dimensional nonlinear finite element analysis method of TFINE program was employed to establish a numerical model of the integrated arch dam-foundation system. Firstly， under normal water level conditions， the displacement， stress and yield state of arch dam under temperature decrease and increase scenarios are analyzed， and unfavorable conditions are obtained. Then， under this working condition， the bearing capacity of arch dam is analyzed by overload method， such as arch dam displacement， unbalanced force， complementary energy norm and yield zone volume. The results show that under the action of temperature stress， the safety of the arch dam meets the requirements under the normal water level condition， and the temperature drop condition is a more unfavorable condition. When the overload ratio is 1.2~1.5， the upstream dam heel cracks； when the overload ratio is 4.0~5.0， the dam body is in nonlinear deformation； when the overload ratio is 7.5~8.5， the dam body loses its bearing capacity.

As a new type of ecological agricultural model， crayfish-rice co-culture has gradually occupied an important position in China's agricultural development. Understanding the variation characteristics of the rice growth environment is of great significance for increasing the grain yield in crayfish-rice fields and ensuring the achievement of double harvests from one water source in crayfish-rice co-culture system. Based on this， this paper reviews the current development status， industrial advantages， and still existing theoretical and technical problems in actual production of crayfish-rice co-culture system in China. Combining with existing literature and research foundations， this article summarizes the research progress on the characteristics of the crayfish-rice symbiotic system and the variation characteristics of the soil environment， field water layer control methods， and biological - ecological environment brought about by the changes in co-cultivation management methods. It also summarizes the impacts of the above characteristic changes on rice growth. Finally， it outlines future research directions from three aspects， including the coupling mechanism of the crayfish-rice co-culture system， the collaborative regulation technology for water conservation， emission reduction， and carbon reduction， and model development， aiming to provide a scientific basis for stabilizing grain production and increasing income in paddy fields under integrated rice-fishery farming and for the efficient utilization of agricultural resources.

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.