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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.}

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.

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.

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.

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.

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.

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.

To achieve the safe and stable operation of reservoirs and the efficient utilization of water resources in the basin， the key lies in clarifying the operation rules and dispatching strategies of reservoirs. To this end， aiming at the problems that traditional neural networks have when simulating reservoir dispatching operation strategies， such as vanishing gradients， getting stuck in local optimal solutions， and difficulty in determining hyperparameters， an improved deep neural network model （TSD） combining the Stochastic Gradient Descent with Momentum （SGDM） and the Tree-structured Parzen Estimator （TPE） is proposed. It has enhanced the accuracy and applicability of the deep neural network model by improving the training method of network parameters and automatically optimizing hyperparameters. Meanwhile， considering the numerous factors affecting reservoir dispatching decisions， the F-test method （FR） and the Mutual Information method （MIR） have been adopted respectively to achieve the optimization of input factors. Further， six simulation methods for reservoir dispatching strategies were constructed based on the Decision Tree model （DT）， Support Vector Machine model （SVM）， and improved deep neural network model： FR-DT， MIR-DT， FR-SVM， MIR-SVM， FR-TSD and MIR-TSD. And case studies were carried out with four reservoirs， namely Ahai， Jin’anqiao， Ertan and Pubugou. The research results show that compared with other methods， the FR-TSD and MIR-TSD methods have larger deterministic coefficients and smaller root mean square errors and mean absolute errors when simulating the dispatching strategies on various reservoirs. This indicates that the simulation effects of the FR-TSD and MIR-TSD methods are better and the accuracy is higher， and they can simulate the dispatching operation strategies of reservoirs more accurately， thus providing decision support for the actual operation of reservoir dispatching. Furthermore， an analysis of the simulation results of different reservoirs under the same method reveals that the simulation effect of the model is influenced by the regulating capacity of the reservoir and the allowable range of water level variation. Reservoirs with smaller regulating capacity and allowable range of water level variation have poorer simulation effects， while those with larger ones have better effects.

Based on in-depth research， this study systematically reviews the development history， current status， and existing problems of rural water supply and standardization. It thoroughly analyzes the demand for standardized development in rural water supply and proposes several considerations and recommendations to accelerate progress. The standardization of rural water supply should adhere to a problem-oriented and demand-driven approach， emphasize technological innovation， strengthen deep integration of industry， academia， research， and application， foster and develop new quality productive forces， and leverage the guiding role of standards to unleash innovation potential. Following the principle of balancing development and safety， a full-lifecycle technical standard system should be established， covering planning and design， construction， operation and maintenance， water quality safety， and management services. This system will consist of "2+N+M" standard system. In terms of engineering planning， it is essential to effectively align with strategic plans such as the National Water Network， urban-rural integration， rural revitalization， and rural construction to optimize the overall layout of rural water supply. For engineering construction， adherence to standards must be prioritized to ensure standardized construction of rural water supply projects， establishing and proving rural water supply system that achieves overall optimal performance. Regarding operation and management， upgrading standards is crucial to transition rural water supply toward a modernized management model characterized by specialization， equalization， and degitization， thereby promoting high-quality development in rural water supply.

To address the the complexity of wind resource simulation for mountainous wind farms， this study takes a complex mountainous wind farm as an example. Based on existing anemometer tower data near the wind farm， and considering the relative relationship between the terrain shape and the prevailing wind direction， the computational fluid dynamics （CFD） software Windsim 12.0 was employed to establish two digital terrain models with different boundary ranges of the wind farm. Numerical simulations of the flow fields in the wind farm area were simulated， and the power generation results from the two models were compared with the actual power output of the wind farm. The results indicate that， to accurately assess wind resources in complex mountainous wind farm areas， it is essential to avoid insufficient development of numerical terrain flow field simulations and the adverse effects of boundary conditions on internal flow fields during modeling. This study highlights the critical role of digital terrain model construction in wind resource assessment for complex mountainous wind farms， providing a reference for wind resource evaluation and rational utilization in such terrains， as well as technical support and empirical insights for wind energy development in similar environments.

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.

The conventional reservoir operation diagram， constrained by static regulation frameworks and linear assumptions， demonstrates limited capacity in characterizing dynamic coupling mechanisms and nonlinear constraints within cascade reservoir systems. To address this， based on the theory of system dynamics， this study built a simulation model for early flood-season storage scheduling in mega reservoirs. Taking six cascade reservoirs （Ludila， Guanyinyan， Wudongde， Baihetan， Xiluodu， and Xiangjiaba） in the middle and lower reaches of the Jinsha River as the case study， the dynamic coupling path among water level， reservoir capacity and flow rate was analyzed through system dynamics feedback loops and stock-flow architecture. The study coupled optimization scheduling techniques using LOOKUP functions and IF-THEN-ELSE conditional statements， which characterized nonlinear relationships including water-level-reservoir capacity curves and hydropower unit output constraints， achieving multi-objective dynamic simulation of coordinated reservoir impoundment operations. The Research results indicated that the system dynamics model could accurately depict the dynamic and nonlinear characteristics of the impoundment operations， and its simulation results were highly consistent with those of optimal operation schemes. Under various hydrological scenarios （wet， normal， dry， and extremely dry years）， the Nash-Sutcliffe Efficiency （NSE） values for the reservoir operation water levels exceed 0.99， and the NSE values for the reservoir discharge processes surpass 0.97. The mean absolute error （MAE） values for reservoir operation water levels have not exceeded 0.11 m， while the root mean square error （RMSE） values have not surpassed 0.28 m. For reservoir discharge simulations， the MAE values are below 54 m3/s， and the RMSE values are less than 171 m3/s. Compared with the conventional operation scheme， the system dynamics simulation scheme can increase the multi-year average hydropower output by 2.495 billion kWh/a （an improvement rate of 3.21%）， reduce the spilled water volume by 1.435 billion m3/a （an improvement rate of 15.61%）， and decrease the average computation time for the joint operation of mega reservoirs from 6 hours to 5 seconds. The results not only thoroughly demonstrate the accuracy and reliability of the simulation model， but also provide scientific and technical support for the joint operation of mega reservoirs.

The calculation of TBM tunnel segment lining structure is an important link in lining design. This paper combines an engineering example in South China to establish the lining structure calculation model using the modified usage method， beam-spring method， and three-dimensional finite element method（3D FEM）， and compares the internal forces and deformations of the lining structure calculated by each method. At the same time， the paper studies the influence of the staggered assembly angle on the lining structure forces. The results show that the maximum axial force and shear force of the structure calculated by each method are close to each other. The order of the maximum bending moment and deformation of the whole structure is as follows： modified conventional method > beam-spring method > three-dimensional finite element method. According to the results， the modified conventional method yields results with high safety reserve， simple calculation， making it suitable for preliminary design of engineering. The three-dimensional finite element method is suitable for accurate calculation and preliminary design check of segments， and can show the mechanical characteristics of the detailed structure of segments. The calculation result of beam-spring method is between other two methods， which is relatively economical and can reflect the stiffness contribution of the joint of segment more accurately than the modified conventional method， and the model is more user-friendly than the three-dimensional finite element calculation model which is suitable for engineering design. At the same time， the beam-spring method has a more obvious staggered assembly effect than the 3D FEM in calculating the maximum bending moment.

The Baihetan Hydropower Station is China's second largest hydropower facility. The left bank features complex geological conditions and extensive underground caverns， which have exhibited seepage in the powerhouse area after reservoir impoundment. This seepage significantly influences the deformation and stability of the surrounding rock. This study investigates the stability of the surrounding rock of the underground caverns on the left bank during the reservoir filling process， employing a combination of onsite monitoring data and numerical simulations to analyze the mechanism of how rising reservoir water levels affect the deformation of the surrounding rock. Monitoring data were used to analyze characteristics of the seepage field， such as the underground water free surface， seepage pressure， and leakage quantity， thereby revealing patterns in the deformation and stress trends of the powerhouse surrounding rock. Based on the theory of steady-state seepage， the Finite Element Method was used to simulate the left bank seepage field at reservoir levels of 640、775 and 816 m. Furthermore， the Finite Difference numerical simulation software FLAC3D was utilized to study the impact of groundwater seepage on the deformation of the surrounding rock. The comparison between numerical simulations and monitoring results shows a consistent deformation pattern. The findings indicate that during the reservoir impoundment， the deformation of the surrounding rock of the Baihetan left bank powerhouse is positively correlated with the reservoir water level， with rock deformation increasing as the water level rises. The maximum displacement of the upstream rock bench reached 8.27 mm. The rise in reservoir water level led to changes in the seepage field within the powerhouse area， particularly in regions with developed geological structures. These changes in the seepage field during the impoundment period are the primary cause of deformation in the underground powerhouse surrounding rock. Overall， the stability of the surrounding rock of the left bank underground powerhouse during the impoundment period is satisfactory. Stability can be further enhanced by either extending the length of the C₂ seepage-cutoff tunnel or increasing the drain-hole in the exposed area of fault zone C₂ to mitigate the impact of C₂ seepage on the stability of the surrounding rock.

The wind-photovoltaic-hydro complementary energy is an effective strategy to enhance the consumption of renewable energy. In the context of short-term operational scheduling， the multi-energy complementary dispatch of cascade reservoir systems necessitates the coordination of power generation and load balancing across various reservoirs and diverse renewable energy sources. Furthermore， the scheduling process must consider the time delay associated with water flow through the cascade reservoirs， resulting in a lag effect on power discharge during the scheduling period. This scenario presents a multi-objective optimization challenge， requiring a balance between the benefits of power generation both within and outside the scheduling period， as well as the benefits of peak-shaving during the scheduling period. This study develops a short-term multi-objective optimization model for the wind-photovoltaic-hydro complementary energy in cascade reservoir systems. The model generates a Pareto-optimal set of solutions， encompassing power generation benefits， peak-shaving benefits， and potential power outside the scheduling period. Additionally， it investigates the conflicting and synergistic relationships among these multiple objectives and quantitatively assesses the comprehensive benefits of complementary dispatch through comparative analysis. Using the cascade hydropower station group in the Yuanshui River Basin as a case study， model simulations for typical dry and wet seasons yield the following key findings： ① There exists a conflict between long-term and short-term scheduling benefits. As the energy storage capacity and lagged power within the cascade reservoirs increase， the power generation benefits within the scheduling period diminish. ② A trade-off exists between power generation and peak-shaving objectives， with this trade-off becoming less significant as the potential power decreases. ③ Hydro power compensation for wind and photovoltaic generation effectively enhances the total system output， with additional generation during the dry and wet periods amounting to 8.08 million and 5.2 million kWh， respectively. In peak-shaving mode， the maximum residual load is reduced by 880，000 and 60，000 kW during the dry and wet seasons， respectively. The multi-objective optimization scheduling model for wind-photovoltaic-hydro complementary energy in cascade reservoirs provides valuable insights for advancing the integration and consumption of renewable energy.

The bidirectional operation of inlet/outlets of pumped storage power stations must meet the requirements of smooth flow and minimal head loss. So， hydraulic optimization of inlet/outlets is crucial for the safety and efficiency of stations. Some low-head stations adopt layouts with open-air powerhouses， where inlet/outlets are closely linked to the draft tubes. Due to the influence of the elbow section of the draft tube， the problem of uneven flow is obvious， so a new shape needs to be proposed. Taking a certain station as an example， CFD simulations were conducted to carry out research and found that the original inclined side inlet/outlet scheme was connected to draft tubes. Due to the centrifugal forces， the main flow within the diffusion section of the original oblique lateral inlet/outlet deviated， resulting in inadequate flow evaluation parameters. Starting from the principle of advanced flow allocation， a solution involving additional baffles was proposed to improve the flow pattern. To further optimize the flow pattern， an innovative shape combining the advantages of lateral and vertical shapes was proposed， with its sensitivity analyzed. The special shape parameters that ensured uniform flow were given. This shape has reference value for the design of the inlet/outlet of pumped storage power stations with open-air powerhouses.

Studying the future precipitation and aridity characteristics of the Weihe River Basin under the background of climate change provides a theoretical basis for policy formulation and decision-making in water resources management and flood-drought disaster prevention in the basin. Based on the measured precipitation， average temperature， sunshine duration， average relative humidity and average wind speed from 18 meteorological stations in the Weihe River Basin， the potential evapotranspiration of these stations were calculated by the Penman-Monteith method， the four scenarios of SSP1-1.9、SSP2-4.5、SSP3-7.0 and SSP5-8.5 from the CanESM5 model in CMIP6 were selected， and the SDSM was used to predict the precipitation， potential evapotranspiration and aridity index in the Weihe River Basin from 2031 to 2090. The results show that SDSM can simulate potential evapotranspiration and precipitation in the Weihe River Basin well， with better simulation effects on potential evapotranspiration compared to precipitation. Climate change has a significant impact on precipitation and aridity index in the Weihe River Basin， with varying degrees of influence under different climate scenarios and time periods. Temporally， the future precipitation in the Wei River Basin will increase， with the interdecadal trend rates of precipitation under four scenarios are 2.34、13.3、32.5 and 25.1 mm/10 a respectively； In particular， the precipitation in the SSP3-7.0 scenario from 2071 to 2090 will increase by 35.2% relative to the baseline period； Except for the SSP1-1.9 scenario， potential evapotranspiration of the other scenarios shows an increasing trend； The aridity index decreases by an average of 0.145. Spatially， precipitation shows an increasing trend from northwest to southeast in the basin， with significant increases in precipitation above the Beiluohe Zhuangtou station as the forcing scenarios enhance； Potential evapotranspiration increases from west to east， and higher forcing scenarios result in greater increases in the same region； The aridity index decreases from northwest to southeast， and the climate of the basin becomes humid overall. In the future， the Weihe River Basin should enhance its ability to prevent and control flood and drought disasters by strengthening risk monitoring， allocating water resources scientifically and establishing a water and drought disaster early warning mechanism， so as to effectively respond to risks and challenges brought by climate change.

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.

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 order to explore the changes of water environment pollutant concentrations in the urban section of Qingjiang River in Changyang County， a water environment simulation study under three hydrological conditions （wet year， normal water year and dry year） was carried out based on the MIKE21 hydrodynamic water quality coupling model， and the single factor pollution index was used to evaluate the NH₃-N and TN indicators， and three pollutant discharge improvement measures were proposed for the non-standard scenarios. The results show that the water quality of the Qingjiang River urban section is characterized by a better pollutant content in wet years than in normal water years， while the water quality in dry years is the worst， and the NH₃-N and TN concentrations exceed the standard， which cannot be reduced by the self-purification capacity of the river section. However， by reducing the concentration of sewage at the outfall， the reduction of TN can reach up to 15%， and the reduction of NH₃-N can reach up to 20%. The results of this study are helpful to better understand the impact mechanism of sewage discharge on the water quality of Qingjiang River in Changyang County， and provide a reference for the prevention and improvement of pollution in the urban section of Qingjiang River.

In order to reveal the co-evolution mechanism of water-energy-food-ecology （WEFE） system security and economic resilience in the Beijing-Tianjin-Hebei urban agglomeration， this study used the panel data of 13 prefecture-level cities in the Beijing-Tianjin-Hebei region from 2007 to 2022 to construct a three-dimensional evaluation framework of pressure-state-response， and systematically analyzed the characteristics and influencing factors of regional coupling spatial network from 2007 to 2022 by comprehensively using the coupling coordination degree model， modified gravity model， social network analysis and secondary assignment procedure. By quantifying the nonlinear correlation between resource constraints and economic resilience， this paper aims to break the limitations of traditional single-factor research and propose a differentiated networked governance path， so as to provide theoretical support and decision-making basis for urban agglomerations to break through the path dependence of "resource consumption for growth" and realize sustainable development of ecological priority. The results show that from 2007 to 2022， the average coupling coordination degree of the WEFE system security and economic resilience in Beijing-Tianjin-Hebei increased from 0.38 to 0.48， but regional differences expanded significantly， and the spatial pattern evolved from a “core-periphery” fragmented structure to a “multipolar network” form. While the number and density of network associations are increasing， the correlation and stability still need to be optimized： Beijing and Tianjin form technology capital spillover through the “siphon-radiation” effect， and intermediary cities such as Shijiazhuang and Baoding play the role of “structural holes” to promote peripheral integration； Geographical proximity significantly strengthens network association， while population quality， government efficiency， technological innovation， openness level and climate risk differences have inhibiting effects on network formation. Based on this， this study proposes to promote the multi-directional circulation of elements by constructing a dynamic monitoring and three-level governance structure， implementing a core node feedback mechanism and reward fund to promote network collaboration， and establishing a cross-domain collaboration， talent sharing and climate adaptation mechanism， so as to realize the differentiated networked governance of the coupling of WEFE system security and economic resilience in Beijing-Tianjin-Hebei.

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.

Vibration monitoring of hydropower units plays a crucial role in evaluating unit health status and providing early warnings of deterioration. Accurate prediction of the trend of vibration deflection of unit components can detect the abnormal operation of the unit in advance， and effectively enhance the safety and stability of the unit operation. However， vibration oscillation signals of hydropower units monitored on-site contain noise， and the current methods for predicting the vibration oscillation of hydropower units mostly predict the single position of the hydropower units， leading to incomplete evaluation of the operational stability of the hydropower units， and the interaction among the vibration oscillation of multiple measurement points is not fully considered. To address these challenges， this paper proposes using Cross Graph Neural Networks （CrossGNN） to predict the vibration oscillation signal of multiple positions of hydropower units. CrossGNN is a graph neural network model with linear complexity. The multi-component vibration signals of hydropower units can be interoperable across scales and variables， thus implicitly revealing the spatio-temporal relationship of vibration signals at multiple positions of hydropower units. In order to effectively deal with the noise in time dimension， the adaptive multi-scale identifier （AMSI） is used to construct a multi-scale time series with noise reduction effect. Then a cross-scale neural network is proposed to accurately extract scales with clear trend and weak noise. At the same time， cross-variable GNN is constructed based on the homogeneity and heterogeneity among different variables. By focusing synchronously on edges with higher significance scores and restricting edges with lower scores， the time and space complexity of CorssGNN can be linearly related to the length L of the input sequence， thus effectively improving the prediction accuracy and generality. Finally， taking a hydropower station unit in China as an example， the effectiveness of the proposed method is verified by predicting the vibration oscillation signal of six positions of the unit， which provides a new idea for the vibration prediction of the hydropower station.

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 increasing nitrogen input load in the Pearl River Delta urban agglomeration has led to a rising trend in total nitrogen （TN） levels in the Pearl River Estuary. To reveal the spatiotemporal variations of different nitrogen forms and identify the sources of nitrate nitrogen （NO??-N） ， the dominant inorganic nitrogen species， surface water sampling was conducted during both flood and ebb tides in the wet and dry seasons of 2023 across the complex river network of the estuary. Based on the analysis of the spatiotemporal distribution patterns of various nitrogen forms， nitrate sources were quantitatively apportioned using nitrate isotopes （δ1?N-NO?? and δ1?O-NO??） and the SIAR model. Results indicated that nitrate was the predominant form of inorganic nitrogen， with a mean concentration of 1.85 mg/L. Except for a few sampling points affected by upstream cross-border inflows， ammonia nitrogen （NH??-N） and nitrite nitrogen （NO??-N） concentrations were generally low at most monitoring sites， typically below 0.50 mg/L and 0.10 mg/L， respectively. Although higher nitrogen concentrations were observed at some locations during the dry season， their contribution to the annual total load was substantially lower than that during the wet season. The isotopic compositions ranged from +3.08‰ to +10.03‰ for δ1?N-NO?? and from +0.51‰ to +5.12‰ for δ1?O-NO??. Quantitative source apportionment revealed that the primary contributors to nitrate pollution were agricultural sources （44.7%）， followed by domestic sewage （36.4%） and industrial wastewater （18.9%）. No significant differences in contribution proportions were observed between flood and ebb tides； during flood tide， the contributions from agricultural， domestic， and industrial sources were 45.6%， 36.2%， and 18.2%， respectively， while during ebb tide， they were 43.4%， 36.5%， and 20.1%. The significant spatial heterogeneity in nitrogen concentrations and fluxes， along with the identified source characteristics， provides a scientific basis for developing targeted total nitrogen pollution control strategies in the Pearl River Estuary.