Irrigation is one of the types of land management that has the greatest impact on regional climate， and its impact has been increasing in recent decades. A large number of papers have demonstrated the cooling effect of irrigation， particularly in arid and semi-arid regions. However， the cooling effect in humid regions has been found to be not significant， and the investigation of the cooling effect pertaining to extreme high temperatures has received comparatively less attention.In this study， a sliding window search algorithm is used to investigate the impact of augmenting the proportion of irrigated areas on the occurrence of extreme high temperatures in the Yangtze River Basin based on a global gridded temperature dataset and a historical irrigation distribution dataset. To isolate the climatic effects of various factors in the observed data， the multiple linear regression techniques are employed. Furthermore， a control test is set up by using the WRF model of the coupled irrigation module to perform numerical simulations for verification.The results show that irrigation in the Yangtze River Basin has a cooling effect on extreme high temperatures， and the intensity of the cooling effect depends on the proportion of irrigated area， which becomes more obvious with the increase in irrigated area， but when the proportion of irrigated area exceeds the threshold （0.25~0.30）， the cooling effect gradually diminishes. Numerical simulation experiments verified the results of the analysis based on observed data， but the model would overestimate the cooling effect of irrigation to some extent. Meanwhile， it was found that irrigation could increase soil moisture and latent heat flux and decrease sensible heat flux and soil heat flux， and the cooling effect would be weakened as the proportion of irrigated area increased， the surface moisture increased and the albedo decreased. The results of this research can provide a theoretical basis for the scientific management of agricultural irrigation in the Yangtze River Basin， which is of great scientific significance.

Under the goal of “double carbon”， China urgently needs to carry out the transformation of energy structure and increase the proportion of renewable energy in the power system. Regulating hydropower stations and pumped storage power stations have good storage capacity， and can be used as regulating power sources to operate in conjunction with wind and solar power sources， from the front-end slowing down the impact of unstable wind and solar output on the power system， and promoting new energy centralized online consumption. Therefore， making full use of the regulating performance of cascade hydropower stations and pumped storage power stations， and formulating a reasonable integrated scheduling strategy are conducive to the realization of bundled transmission and synergistic consumption of water， wind， and solar storage on the power generation side， which will help realize the goal of “double carbon”. Based on the consideration of the grid-side load demand and the utilization rate of hydropower water resources in the short-term scheduling of the cascade hydro-wind-solar hybrid power generation system， a short-term complementary scheduling model is constructed with the goal of minimizing the difference between the sources and loads， and maximizing the incremental amount of cascade hydropower storage and with the constraints on the safe operation conditions of the conventional hydropower plant， the photovoltaic power plant and the pumped-storage power plant， and the model is solved by using the inner and outer nested algorithms of the PSO-DP coupling. The hydro-wind-photovoltaic-storage complementary power generation system composed of conventional cascade hydropower stations， pumped storage power stations and surrounding wind power and photovoltaic stations in a basin in Southwest China is selected as the research object for simulation. The results show that： ①pumped storage power stations tend to choose water discharge for power generation when the head of the cascade power station is low， and choose to pump water or keep the current water level unchanged when the head of the cascade power station is high； ② the model constructed in this paper effectively improves the matching degree between the total system output curve and the grid load curve， realizes a reasonable distribution of load and water between cascade hydropower stations， reduces the benefit loss of cascade hydropower stations to a certain extent， improves the utilization rate of hydraulic energy， increases the cascade hydropower storage increment， and is conducive to the coordinated operation of the source and grid and the stable operation of cascade power stations.

The artificial division of administrative regions makes the same river flow through different administrative regions， and water conflicts appear when water resources are insufficient to meet the demands claimed by stakeholders along the trans-regional rivers. Transregional water resources allocation has become an important means to solve trans-regional water conflicts. The Rubinstein bargaining model has been successfully applied in solving water conflicts due to its ability to reflect the bargaining power of various stakeholders. However， the above-mentioned Rubinstein bargaining model treats the discount factors of various stakeholders with a single fixed value， ignoring the impact of dynamic changes in the discount factor. This paper proposes a multi-agent Rubinstein bargaining water resources allocation model based on the consideration of the dynamic discount factor. First， the dynamic discount factor is determined based on bargaining rounds， deviation degree of water demand and adjustment coefficient， the quotation strategy considering dynamic discount factor is constructed， and the negotiation cost is determined by considering the factors of time cost and water loss. Then， a multi-agent Rubinstein bargaining water resources allocation conceptual model is established， and the influence of three factors on the dynamic discount factor is discussed， a comparative study of Rubinstein bargaining model based on dynamic and fixed value discount factor is carried out. Finally， six administrative regions in Tai’an section of Dawen River Basin are selected as examples to show the effect of the model. The results show that the water resources allocation scheme obtained by the proposed multi-agent Rubinstein bargaining water resources allocation based on dynamic discount factor can advance the negotiation round， lower the negotiation cost， and better balance the economic and social development level among various stakeholders.The proposed model provides a new method for obtaining a reasonable water allocation scheme that is acceptable to all stakeholders， and expands the theory of transregional water resource allocation.

Climate change and land use change will affect the spatial and temporal distribution of blue and green water resources. Accordingly， quantifying the changes caused by them is of great significance for water resources management. The Hekouzhen-Longmen Region， located in the middle of the Yellow River has experienced rapid economic development and the implementation of large-scale ecological restoration project（the “Grain for Green Project”）. The land use pattern of this area has undergone considerable variation， which has affected the spatial and temporal distribution of blue and green water resources. Based on remote sensing data， this study analyzed the land use change characteristics of this region in the past 40 years. By combining the VIC model with four scenarios， the temporal and spatial effects of climate and land use change on blue and green water in the basin are quantitatively analyzed. The response of productive green water flow and non-productive green water flow to climate and land use change is further analyzed in order to explore the production potential of green water resources. The results are presented as follows： ①The annual maximum temperature and the annual minimum temperature in the Hekouzhen-Longmen Region changed from decreasing to increasing in 1997. The trend of annual precipitation changed from decreasing to increasing in 2006. The dominant land use types in the Hekouzhen-Longmen Region were grassland and cropland. The cropland decreased by 3 407 km² from 1980 to 2020， while the areas of woodland， grassland and shrubland showed an increasing trend， which was closely related to the implementation of the “Grain for Green Project”. ② Climate change and land use change contributed 90.89% and 9.11% to blue water flow， 103.13% and -3.13% to green water flow， and 89.07% and 10.93% to green water storage， respectively. Climate change played a leading role in the change of blue and green water. Under the four scenarios， the blue and green water showed a gradual increasing trend from northwest to southeast. ③ After vegetation restoration， the proportion of vegetation transpiration as a productive green water flow among the total green water flow increased from 71.63% to 72.93%. In the four scenarios， the spatial distribution of evaporation from canopy storage and vegetation transpiration showed an increasing trend from northwest to southeast， while bare soil evaporation showed an opposite spatial distribution pattern. Under the impact of climate change， canopy storage evaporation and vegetation transpiration showed an increasing trend， while land use change had a greater effect on bare soil evaporation.

The optimal regulation of multi-energy complementary systems helps to take advantages of different power sources. The growing installed capacity of wind and photovoltaic power has brought about the problems of clean energy consumption and grid peak shaving. A bi-level optimal scheduling model of wind， photovoltaic（PV）， hydropower， thermal power and energy storage is proposed to solve the problems. Firstly， considering that there are many variables and constraints involved in the optimal scheduling of multi-energy complementary， the model is processed hierarchically based on the output characteristics and complementary relationship of multiple energy sources， to reduce the complexity of model solving. Then， according to the demand of source-load coordination， clean energy consumption and power generation economy， the model is divided into the upper-level model of Wind-PV-Hydro-Storage joint optimal scheduling and the lower-level model of thermal power unit optimal scheduling. The optimization objectives of upper-level model are the minimum net load variance and the maximum clean energy generation， and the optimization objective of lower-level model is the minimum operation cost of thermal power units. The net load curve achieved by the upper-level model is used as the constraint of the lower-level model. Finally， taking the IEEE30-bus system as an example， the CPLEX solver of MATLAB platform is used to calculate three pre-defined scheduling scenarios. The results show that the anti-peak regulation of wind power and photovoltaic output will expand the peak-valley difference and variance of net load， increase the pressure of peak shavingand reserve of thermal power， and increase the power generation cost and unit loss. The participation of hydropower in multi-energy complementary systems has a significant improvement on the net load fluctuation of the power grid， which can effectively reduce the peaking pressure of the power system. Energy storage can reduce the conflict between smoothing net load fluctuation and improving clean energy generation to a certain extent. The optimal scheduling model proposed can effectively reduce the fluctuation of source and load， promote the consumption of clean energy and reduce the operation cost of the system， which contribute to the low-carbon and safe operation goals of the grid.

In order to explore the theoretical technology and method system for the formulation of ecological water replenishment schemes for seasonal rivers， this paper proposes an ecological water replenishment mutual feedback method combining ecological flow calculation and hydrodynamic model.Based on the diagnosis of hydrological sequence variation， this method lays a foundation for the formulation of ecological water replenishment scheme by calculating the ecological flow process in the river channel.Then， according to the actual process of ecological water replenishment， a hydrodynamic model of river ecological water replenishment is established and solved， which provides a model support for the study of ecological water replenishment evolution. Finally， the hydrodynamic model is used to analyze the water replenishment evolution of different water replenishment schemes， so as to obtain the best water replenishment scheme under the given target. By taking a seasonal river DY River in the north as an example， this paper carries out an application analysis. The results show that： ① The variation point of TG reservoir inflow runoff sequence is 1980. On this basis， the runoff sequence can be divided into two parts： natural stage and human disturbance stage. ② The ecological water replenishment scheme obtained by the ecological water replenishment mutual feedback method can not only meet the ecological flow demand in the river channel， but also fully consider the characteristics of the annual variation of the river runoff process， which is of important scientific significance for understanding the ecological flow restoration process of seasonal rivers in China； ③ The ecological water replenishment mutual feedback method is applied to the ecological water replenishment project of DY River， and the effect is good. According to the requirements of the ecological water replenishment target， the ecological water replenishment scheme that meets the water supply of the whole line in DY River is obtained， that is， when the ecological water replenishment of DY River is in spring， the optimal ecological water replenishment flow from March to May is 49.82， 27.17 and 8.67 m³/s. This method can be used for the subsequent DY River to formulate corresponding ecological water replenishment schemes for other water replenishment targets， and can also provide new methods and new ideas for the formulation of ecological water replenishment schemes for seasonal rivers in other basins.

Understanding the characteristics of extreme climate change is an important part of groundwater resources management. To investigate the impact of extreme climate on groundwater resources， this paper takes the Dagu River groundwater resources area as an example and based on the meteorological data for over 40 years， 14 extreme climate indices are selected to analyze the trend， mutation and periodicity of meteorological changes in the study area by using methods such as linear trend method， Mann-Kendall mutation test and wavelet analysis. And based on extreme climate index and hydrological frequency analysis， the representative extreme climate years of the research area are determined， and the groundwater balance under extreme climate year is estimated by using water balance analysis method. Meanwhile， the influence of extreme climate index on groundwater depth is evaluated by correlation coefficient and periodicity analysis. The results are listed as follows： ① From 1979 to 2021， the extreme climate indexes representing high temperature and precipitation show an increasing trend， while the extreme climate indexes representing low temperature show a decreasing trend. The representative years of extreme wet years are 2007 and 2020， and the representative years of extreme dry years are 1981 and 1986. ② The extreme climate indexes mutate in the 1990s and the early 21st century， and then the trend of high temperature becomes more significant. ③The mean period corresponding to the first main period of the extreme temperature index have three main variation ranges： 20~24， 12~14 and 5~6 a. The average cycles of most extreme rainfall indices are 11~16 a. ④ Extreme precipitation index inhibits the increase in groundwater level depth. Extreme precipitation （R95p） and simple daily precipitation intensity index （SDII） are the main precipitation indexes affecting the groundwater level depth in Dagu River water source area. The period corresponding to the first main cycle of the groundwater level depth is 13~15 a， which is basically consistent with the cycle characteristics of the extreme precipitation index. This means that the groundwater level depth is significantly affected by the extreme precipitation index. ⑤ In the extreme wet year （2007）， the total groundwater recharge and discharge are about 319.4 mm and 204.8 mm， respectively， with an equilibrium difference of about 114.6 mm. In the extreme dry year （1981）， the total groundwater recharge and discharge are about 104.2 mm and 141.1 mm， respectively， with an equilibrium difference of about -36.9 mm.

It is one of the necessary conditions to obtain the measured discharge for hydrological frequency analysis and water resources management. It plays a pivotal role in gaining insights into the variations in discharge， forecasting flood risks， and optimizing the allocation of water resources. The installation of the conventional devices is often complex and low-efficient while the non-contact devices （e.g.， video discharge measurement） is easily set and can cut costs. However， for non-contact devices， the error analysis of the discharge measurement results is insufficient， resulting in risks associated with applications in hydrological analysis and water resources management. In order to analyze the error of video discharge measurement， based on the video image method to calculate the cross-section water level and the space-time image velocimetry （STIV） method to calculate the cross-section flow velocity， this study assumes the error distribution of a single measurement， and deduces the water level and flow velocity measurement errors， flow measurement errors and their primary sources. Also， the error average bandwidth （EAB） is defined to quantitatively evaluate the size of the error. Taking the discharge measurement in Yangzigou watershed of Luanchuan County as a case study， the results indicate that the range of the discharge measurement error is small during the stage of the rapid rises in water level or flow velocity. The error average bandwidth （EAB） is 4.98%， 10.83% and 16.08% if there are only the water level error， only the velocity error， and the total errors of the water level and velocity， respectively. The contribution of velocity measurement error for discharge measurement is greater than that of water level measurement error. The video discharge measurement that considers the effects of the error distributions of water level and velocity is beneficial for improving the accuracy of discharge measurement and providing reliable data for its application in hydrological frequency analysis and water resource management， particularly when the need arises for monitoring and responding to dynamically changing hydrological conditions. Additionally， a more profound understanding of measurement errors serves to guide improvements in video-based flow measurement techniques， with the ultimate goal of minimizing errors and enhancing the method’s reliability in practical applications.

. Poyang Lake receives incoming water from the basin， and its flood formation and development are influenced by both incoming water from Poyang Lake basin and Yangtze River flood. This makes the area extremely vulnerable to severe flooding at a certain time of the year. Based on the flood data of Hankou and Hukou from 1959 to 2009， this paper analyzes the flood occurrence of Yangtze River and Poyang Lake and the frequency of Yangtze River flood inpouring into Poyang Lake. By constructing a two-dimensional hydrodynamic model of Poyang Lake and Yangtze River mainstream， this paper reviews and analyzes typical flood processes such as the intensification scenario of Yangtze River and Poyang Lake overburden， the equilibrium scenario of Yangtze River and Poyang Lake overburden， and the extreme scenario of Yangtze River flood flowing backwards into Poyang Lake overburden. The simulation results are verified and errors are analyzed with the measured water level process， and the extreme flood encounter process in 1998 is simulated and analyzed with this model. The results show that the flood of Poyang Lake generally occurs earlier than the flood of Yangtze River， and the two floods mainly occur in June to July. The backflow of Yangtze River flood into Poyang Lake generally occurs in the main flood season of Yangtze River. Through statistical analysis of the number of days and water volumn of backflow， it shows that the intensity of Yangtze River and Poyang Lake overburden fluctuates in interdecadal scale. The model has high accuracy and good effect in simulating and predicting the typical water level process of the flood encounter of Yangtze River and Poyang Lake and the extreme flood in 1998， indicating that the model can well deal with the highly dynamic changes of Poyang Lake flood and Yangtze River flood， and can provide theoretical support for the economic construction and flood control in Poyang Lake Region.

Conducting a comprehensive research into the pollution loads originating from non-point sources within the Yangtze River Basin carries profound implications for practical environmental management. The traditional approach， which relies on an aggregated export coefficient model， presents limitations in capturing the intricate spatial variations of pollutants. Moreover， it fails to account for the intricate dynamics of pollutant migration losses that occur during the transit from pollution sources to the receiving water bodies. Consequently， the outcomes generated by traditional model predominantly reflect pollutant generation rather than the genuine quantities that find their way into the river system. In order to reduce errors in simulation results caused by regional variations in natural geographic conditions， this study considers comprehensively an array of factors that exert pivotal influences on the process of pollutant transport during migration. These factors include rainfall patterns， local topography， vegetation cover， and the spatial separation between pollution sources and water bodies. By integrating these factors into the framework， this research introduces a novel modification to the traditional Johnes export coefficient model. This modification entails the incorporation of spatially adjusted river load ratio， culminating in the formulation of an advanced and spatially refined export coefficient model. Applying the refined export coefficient model to the Yangtze River Basin， the paper proceeds to simulate the concentrations of total phosphorus and chemical oxygen demand along nine selected monitoring sections. In comparison to the conventional aggregated export coefficient model， the advanced model demonstrates heightened accuracy consistently in predicting pollutant distribution within the river system. This remarkable improvement underscores the potential of the refined model to offer a more realistic representation of pollution dynamics across the Yangtze River Basin. Consequently， these findings provide noteworthy implications and theoretical foundation for the broader context of non-point source pollution management.

In response to the current problems in water quality prediction models， such as the complexity of the data itself， noise interference in signal processing， and insufficient decomposition depth， which make it difficult for a single decomposition to fully capture the nonlinear features of the signal， this paper proposes a water quality prediction model based on secondary decomposition. This innovative method firstly uses the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise （CEEMDAN） to decompose the raw data. Then， Variational Mode Decomposition （VMD） is adopted to perform a secondary decomposition of the Intrinsic Mode Function （IMF） with the highest entropy value. Finally， the processed time series are put into the TCN-light GBM multi-feature prediction model. At the same time， the Sparrow Search Algorithm （SSA） is used to optimize the prediction model. By taking the water quality of Yufu River in Shandong Province as an example， the Root Mean Square Error （RMSE） of this model is 0.105 3， the Mean Absolute Error （MAE） is 0.081 5， and the coefficient of determination （R ²） is 0.947 1.The predictive metrics of the model are compared with those from popular contemporary deep learning and neural network algorithms， such as the Gated Recurrent Unit （GRU）， Long Short-Term Memory （LSTM）， Light Gradient Boosting Machine （Light GBM）， and Temporal Convolutional Networks （TCN）， among others. The results show that， in terms of R ²， the model achieved improvements of 53.04%， 70.41%， 66.07%， and 65.20% respectively. In terms of RMSE， the model represented reductions of 62.76%， 65.50%， 64.93%， and 64.80% respectively. And in terms of MAE， the model witnessed decreases of 62.76%， 66.24%， 63.80%， and 65.24% respectively. Therefore， it is evident that the model based on CEEMDAN-VMD-TCN-light GBM exhibits superior predictive performance， which can reduce the fluctuation of water quality sequences more effectively and improve the ability to capture nonlinear features of signals.

The plain river network area has a flat terrain and slow flow velocity， resulting in a limited ability to resist pollution. Therefore， enhancing the connectivity of the water system is crucial for improving the quality of the water environment. This article focuses on the Yuejin polders which has poor water system connectivity in Shengze Town as the subject of research. By conducting water diversion experiments and constructing a hydrodynamic model of the river network in the polders area， the study explores the scheduling and operation rules of water conservancy work， methods of connecting the river network， and the corresponding changes in the water environment. The study utilizes water age as a time scale parameter to measure the connectivity of the water system. It establishes a river network model for hydrodynamics， water quality， and water age in the Yuejin polders. The simulation evaluates the connectivity and water quality improvement in the polders area under five water diversion schemes. Additionally， an evaluation system of pressure， state and response is constructed to quantitatively analyze changes in water system connectivity and the level of water environmental improvement resulting from water diversion. The results reveal that from the perspective of the length of water exchange， the exchange time of water bodies in the main river channels of the research area is within 5 days. The greater the connectivity of these water bodies， the shorter the water age becomes. From the perspective of changes in water quality indicators， during the water diversion experiment， the most noticeable change in the water environment inside the polders is the level of ammonia nitrogen. It shows a strong response to water diversion， and simulation results indicate that water age generally aligns with the concentration of ammonia nitrogen. Enhanced connectivity of water bodies leads to a shorter water age， which aids in reducing ammonia nitrogen levels. From the perspective of water diversion scheme， the uni-source water diversion and uni-region drainage scheme has limited effectiveness in improving the connectivity of the water system within polders， especially in areas with weak water flow in the river network. This scheme also increases variations in water flow within the polders， resulting in spatial differences in connectivity and water quality in the river network. Consequently， local stagnant water areas or dead water areas may be formed. Therefore， the combination of multiple sources of water diversion and multi-regional drainage scheme can enhance the connectivity of the water system and improve water environmental quality.

The coastal areas of China are rich in coastal resources. However， due to heavy rainfall in the coastal areas and loose soil on the coaster slope， the slope is prone to produce rainfall runoff erosion， which leads to serious soil erosion and drenching difficulties on the slope of coastal engineering. Rainfall experiments are simulated indoors to study the characteristics of the generated slope runoffs when rainfall intensities are changing with different water and soil conservation measures. Results show that： ① The amount of time for the initial runoffs to be generated on slopes with various measures is negatively correlated with rainfall intensity. When the rainfall intensity is 50 mm/h， the effectiveness of the measures to delay generating runoffs on the slope surface is in the order of leaching pit > leaching ditch > salt-tolerant grasses cover. When the rainfall intensities are 100 and 150 mm/h， the effectiveness to delay generating runoffs on the slope surface is in the order of leaching ditch > leaching pit > salt-tolerant grasses cover. ② The process of producing the runoffs on slopes with different measures is synchronous. Before the slope collapse， the intensity of the runoffs increases with the development of rills and tends to stabilize when the rills become mature. When the slope collapses， the intensity of runoffs increases sharply in a short period of time before decreasing. When the experimental results are compared， it is evident that the stability of the coastal slopes can be improved by covering with salt-tolerant grasses.

Clarifying the pollution status and quantitatively identifying the pollution sources are an important foundation for effective control of surface water pollution. This paper proposes a data preprocessing method by comprehensively uses mathematical statistics， GIS spatial analysis， and principal component analysis-absolute principal component score-multiple linear regression （PCA-APCS-MLR） model and other methods. Using this data preprocessing method， a quantitative analysis of pollution sources and their contribution rates was conducted on 23 key water quality indicators at 49 sampling points in the surface water system of Yan'an City from 2018 to 2020. The results indicate： ① The main sources of surface water pollution are nutrient pollution （54.02%） and heavy metal pollution （17.97%）. ② The average contribution rate of nutrient pollution to various water quality indicators （52.70%） is greater than that of heavy metal pollution （47.30%）. ③ Nutrient pollution has a greater impact on the northeastern part of Yan'an City， and heavy metal pollution has a greater impact on the upper reaches of Yan River and Xiuyan River. Compared with the traditional data preprocessing method， the analysis results of the data preprocessing method proposed in this paper are more regionally representative which can provide a data support for the treatment of surface water pollution in Yan′an City and a scientific reference for the designation of surface water quality protection policies.

This paper focuses on the analysis of the non-standard horseshoe-shaped section of the Chuxiong-Kunming segment of the Water Diversion Project in Central Yunan. It utilizes a geometric segmentation approach to deduce the hydraulic elements for this unique section， providing expressions for these elements at varying water depths. Additionally， it employs a three-part trial algorithm to calculate the normal water depth for the section， and this trial calculation process was facilitated by using C# programming. Recognizing the complexity of normal water depth calculations for such a section， a direct calculation formula for normal water depth is derived by using a fitting optimization principle. The results of the calculations reveal that within the applicable range of the formula， the maximum relative error in computing the normal water depth of the section is only 0.496%. Furthermore， over 89.3% of the calculated points within the entire calculation interval exhibit a relative error of less than 0.24%. These findings signify a relatively high level of precision in the calculations， demonstrating their suitability for meeting the requirements of actual projects.

In 2018， a large-scale landslide occurred in the upstream of the Jinsha River due to heavy rainfall， forming a barrier lake. After the breach of the barrier lake， large amounts of silt and sediment were transported downstream with the floodwaters， resulting in significant changes in the morphology and flow characteristics of the downstream river channel. The tailwater section of a certain planned power station was affected by this event， with a sediment deposition of 6 to 10 meters. In order to ensure the normal construction of the power station as scheduled， a physical model test was conducted to explore the restoration plan for the tailwater section of the river， covering a distance of 3 kilometers upstream and downstream. An analysis of the channel evolution showed significant unidirectional erosion of the engineered section of the river in the first year after the breach of the lake. By the pre-flood season of 2022， the overall trend of the river channel was characterized by upstream erosion and downstream deposition， particularly evident in the significant growth and development of gravel bars downstream of bends. The topography of the engineered section of the river in 2027 was predicted by using model tests， which showed that the riverbed would still be 1 to 6 meters higher than the pre-burst level of the barrier lake. Therefore， dredging measures would be necessary to lower the tailwater level of the planned power station to the design level. In order to effectively reduce the dredging area and volume， a detailed analysis of the water and sediment characteristics and evolution trend of the newly formed gravel bar segment downstream of the bends was conducted. A remediation plan was proposed， which involved an initial local dredging downstream， followed by adjusting the riverbed through natural evolution before conducting an overall dredging. The test confirmed that this plan could reduce the length of dredging and save approximately 68 800 cubic meters of dredging volume compared to a direct dredging approach. Sedimentation tests are carried out for the new plan， as the upstream power stations have been gradually built and put into use， their detention effect has significantly reduced the sediment inflow to the research river section. Under the water and sediment effects of five typical years， the overall bed of the river section remains relatively stable， and only a certain degree of sedimentation appears on the left side downstream of the tail water outlet. It is recommended that the local dredging as needed be regularly carried out to ensure the safe operation of the power station.

Urban surface pollution is the second largest non-point water pollution following the agricultural surface pollution and an important cause of the deterioration of urban water ecosystems. With the rapid urbanization in recent years， the increasing area of urban surface has led to an increase in flood flow and surface runoff， thus bringing more pollutants from the city into the urban pipe network and causing a more serious pollution to urban water bodies. In this paper， the pollution level of rainfall runoff， the change characteristics of runoff water quality and the initial scouring effect under different underlay conditions are investigated by using the monitoring data of four typical urban underlying surfaces， namely， asphalt roofs， brick pavements， linoleum roofs and green spaces. The results show that： ① the quality concentration of total nitrogen in rainfall runoff from the four types of underlying surfaces is inferior to Class V water； the degree of total phosphorus pollution of the four types of underlay is relatively light， and the frequency of rainfall runoff total phosphorus quality concentration of asphalt roofing， brick pavements， linoleum roofing and green spaces that is better than Class IV water is 80%， 16%， 88.46% and 5.56%， respectively. The distribution ranges of rainfall runoff mass concentrations of total suspended solids for asphalt roofing， brick pavements， linoleum roofing and green spaces are 7~798， 15~569， 10~871 and 44~378 mg/L， respectively. ② The runoff pollution levels of total nitrogen and total phosphorus are ranked as follows： brick pavements > green spaces > asphalt roofing > linoleum roofing； and the runoff pollution levels of total suspended solids were ranked as follows： green spaces > brick pavements > linoleum roofing > asphalt roofing. ③ The trends of the different pollution indicators varied greatly among the underlying surfaces under the medium rainfall scenario， while the concentration of the pollution indicators is higher in the underlying surfaces that are greatly affected by anthropogenic activities under the light rainfall scenario. ④ The initial flushing intensity of pollutants on each underlay is ranked as follows： total suspended solids （TSS） > total phosphorus （TP） > total nitrogen （TN）； and the initial flushing intensity of each underlay is ranked as follows： asphalt roofing > linoleum roofing > brick pavements >green spaces. ⑤ Total suspended solids and total phosphorus in rainfall runoff from asphalt and linoleum roofs has good homology， while total phosphorus in rainfall runoff from brick pavements has good homology with both total nitrogen and total suspended solids. In summary， the average field rainfall runoff concentrations of total nitrogen and total suspended solids in the various underlying surfaces far exceed the water quality standard for surface water Class V， which would pollute urban water bodies， and corresponding measures can be taken to reduce the pollutant concentrations according to the characteristics of different underlying surfaces.

In In order to reveal the turbulence characteristics of open channel with rough bed of non-uniform bulk particles， this paper uses the rough bed surface made of cubic particles with d ₁=1.0 cm and d ₂=1.5 cm to carry out the turbulence test of open channel in PIV flume to investigate the distribution of turbulence intensity， higher-order moments of velocity， Reynolds stress and turbulence kinetic energy. The results show that： ①In the middle of the intergranular zone， the turbulence intensity changes significantly due to the bypassing effect of neighboring profiled particles. ②The distribution properties of the longitudinal skewness coefficient S_u′ and the vertical skewness coefficient S_v′ of the velocity high-order moments reveal that sweeping events predominate near the bed， while ejections dominate in the region above the top of the particles. ③The mean Reynolds stress R _mean increases and then decreases along the intergranular region， and decreases and then increases in the granular region. ④The turbulent kinetic energy is distributed in bands， and the suppression at the bottom of the riverbed and at the water surface causes the overall turbulent kinetic energy to increase from the bed surface and to decrease after reaching a maximum near the top of the particles.

Soil salinization and sodification is one of the key factors affecting the sustainable agricultural development in cold arid irrigated districts. Traditionally， the total soil salt contents were used as the indicator to evaluate the evolution trend of salinization and sodification， but little attention is paid to the change of ion composition. For a further study of the distribution and migration patterns of salt ions among various water in agricultural irrigation and drainage systems， this paper analyzes the distribution and change characteristics of salt and ions in different water in irrigation areas systematically based on the observation data of various water during the irrigation and drainage process. Research has shown that the composition of salt ions in waters in the irrigated districts is different obviously/ Irrigation water is dominated by Ca²⁺ and HCO₃ ^–， while groundwater and drainage are mainly Na⁺， Cl^– and SO₄ ^2–. The quality of irrigation water is relatively good， and it is generally HCO₃ ^–－Ca²⁺ type water. Groundwater shows weak alkalinity， and is generally of Cl^–·SO₄ ^2–－Na⁺ and Cl^–·SO₄ ^2–－Na⁺·Mg²⁺ type water. Drainage is mainly influenced by factors such as regional groundwater and irrigation recession， with Cl^–·SO₄ ^2–－Na⁺ and Cl^–·SO₄ ^2–－Na⁺·Mg²⁺ type.

The prediction of reservoir collapse in loess area is still dominated by empirical graphical methods such as Kachugin method， and the accuracy of the prediction results of such methods depends on the accurate description of the profile morphology of the bank slope. In order to improve the accuracy of the prediction of the collapse width of reservoirs in the loess area， this paper selects typical reservoirs in the Loess Plateau Area of Weibei for on-site investigation， compares and analyzes the bank slope morphology of the original river channel and the bank slope morphology after water storage， and establishes an underwater bank slope morphology prediction model on this basis. The results show that after the loess bank slope collapses steadily in Weibei Loess Plateau Area， the above-water bank slope is upright， with a height of more than 30m， and the underwater bank slope is curved， and the collapsed material may be exposed to the water surface due to the combined influence of water depth and bank slope height. On this basis， the underwater bank slope morphology prediction model is established based on the logarithmic spiral equation， and compared with the linear bank slope used in the classical graphical method。 The error analysis results show that the stacked volume error is 4.50%~39.70%， the average value is 12.64%， while the prediction error of the linear bank slope is 25.75%~124.69%， and the average value is 75.69%. That is， the logarithmic spiral equation can better measure the shape of underwater bank slope and the amount of underwater accumulation. The relevant research results are of practical significance for the improvement of the prediction method of reservoir collapse in the Weibei Loess Plateau Area and the high-quality development of the Yellow River Basin.

For single-pipe water delivery in long-distance pressure gravity flow diversion projects， the time required for drainage and water filling is the basis for making precise decision for emergency water supply dispatching plan during the overhaul. The time of overhaul for drainage and water filling of long-distance water diversion project is affected by the water level of the upstream reservoirs， flow characteristics of sluices or valves， roughness of pipe and wave speed of pressurized flow. Based on the digital twin of long-distance water diversion project， the time of overhaul for drainage and water filling can be determined promptly and accurately. By taking a long-distance water diversion project as an example， virtual and real data interaction can be done with real-time monitoring data such as pressure and water level of reservoir provided by the monitoring system and then the parameters of digital model can be determined to make approximation of physical entity by digital models and to build a digital twin of the physical entity. Based on one-dimensional hydrodynamic model， numerical simulation on drainage and water filling process is done. Water level and flow are taken as variables in Saint-Venant equations for drainage process， and water depth and discharge are taken as variables in Saint-Venant equations for water filling process. The programme language is Java in the interface of the simulation software and the programme language is Python in numeical simulation.

In order to explore the suitable supply irrigation strategy for winter wheat on the saline soil farm of arid and semi-arid regimes， this paper carries out the field experiment with different irrigation times and soil salinity treatments. The AquaCrop model is calibrated and validated by using the winter wheat growth and production data. The supply irrigation strategy for winter wheat on the saline soil farm under typical hydrological years is optimized through scenario simulation. The results show that： ① the AquaCrop model accurately simulates the effect of supply irrigation on the canopy cover， cumulative evapotranspiration， dry biomass and grain yield of winter wheat on saline soil farm， with Pe in -28.54% to 20.78%， R ² in 0.90 to 0.98， RMSE in 5.28% to 12.19%， 14.99 to 26.81 mm， 0.57 to 1.04 t/hm²， 0.45 to 0.55 t/hm²，and NRMSE in 6.49% to 20.10%. ② With the decrease in irrigation frequency and the increase in soil salinity， the accuracy of the model decreases. Meanwhile， due to the consistent crop coefficient in the whole growth period， AquaCrop cannot accurately predict the early senescence of winter wheat under water and salt stress， and the model is prone to overestimate the growth and production of winter wheat under deficient irrigation and saline soil conditions. ③ The recommended supply irrigation strategy for winter wheat in slight saline soil is three irrigations of 60 mm each at the jointing， flowering， and grain-filling stage for the dry year， two irrigations of 60 mm each at the jointing and flowering stage for the normal year， and one irrigation of 60 mm at the jointing stage for the wet year. The recommended supply irrigation strategy in moderate and severe saline soil needed irrigated once with 60 mm on this basis. These supply irrigation strategies could decrease irrigation water and achieve 6.53~8.37 t/hm² winter wheat grain yield， which is over 80% of the potential grain yield.

Wheat drip irrigation technology is the main project of high-standard farmland construction in North China， and it is also an important technical means to deal with the shortage of water resources in the region and ensure national food security. Based on the latest research progresses of drip irrigation technology on wheat at home and abroad and the research results of our group for many years， this paper elaborates the influences of drip irrigation factors such as drip flow， dripping element spacing， drip belt laying distance on soil water distribution， the ways of drip irrigation scheduling on wheat， and the effects of drip irrigation on wheat water consumption characteristics， dry matter accumulations， yield compositions and so on. At the same time， the development trends of wheat drip irrigation in the future are put forward： smart irrigation decision-making and water-fertilizer integration technology that integrates multiple factors such as meteorology， soil and crops， It is hoped these contents would provide theoretical and technical support for accelerating the application and popularization of drip irrigation technology in the main wheat-producing areas in China..

With the comprehensive advancement of the rural revitalization strategy， the reservoir migration work has entered a new stage with common prosperity as the essential requirement and high-quality development as the primary mission. It is of great significance to propose a way to evaluate the resettlement effect that meets the new needs. Based on Amartya Sen’s capability approach， this paper establishes a comprehensive reservoir migrant welfare evaluation index system， analyzes the welfare changes of migrants before and after relocation through fuzzy evaluation method， and discusses the resettlement effect and assistance direction. By taking the migration in Pingqiao District of Chushandian Reservoir as a research case study， this analysis shows that although some welfare indicators of migrants are damaged during the relocation process， their overall welfare is improved after the resettlement is completed. The welfare inequality analysis shows that the welfare gap within the immigrants widens after relocation. This paper recommends highlighting the key points when formulating resettlement and follow-up support planning for immigrants， and adapt to local conditions and times.

In order to study a wire breakage identification technique for prestressed steel cylinder concrete pipe （PCCP）， this paper designs a simulated test environment by using a DN 4000mm PCCP and conducts a 1∶1 sample wire breakage monitoring test under almost actual working conditions. The test combines the collected wire break signal and the previously collected noise signal in the operating pipeline with each other， and the time-frequency spectrograms transformed by both continuous wavelet transform （CWT） and synchrosqueezed wavelet transform （SWT） are used as the wire break signal dataset. The YOLOX-based target detection algorithm is used to determine the occurrence of wire breakage events by extracting the features of the time-frequency spectrograms of the wire breakage signals in the dataset. The accuracy rate， recall rate， F1 score， and false detection rate of the model are 100%， 100%， 1 and 0% for both datasets trained. In the subsequent pruning calculation stage， the pruning rate of the SWT group is higher than that of the CWT group， while ensuring the same detection accuracy， and the final model size is only 1.36 MByte. It can be seen that the time-frequency spectrogram obtained by SWT transformation can simplify the YOLOX model without loss of accuracy， which provides a reference for the development of embedded installation of PCCP broken wire monitoring system.

The migration issue is a key issue in water conservancy and hydropower projects， which is related to social stability and rural revitalization. In this paper， the factors influencing the willingness of reservoir migrants to transfer in farmland and the willingness of farmers in resettlement areas to transfer out of farmland and their coupling coordination relationship are studied by using geographic detectors， factor analysis method and coupling coordination degree model. The results show that ① community integration status in resettlement sites， distance to farmland， skills training in farming and other skills， farmland value， number of agricultural laborers in households， and non-agricultural employment opportunities play a major role in influencing migrants’ willingness to transfer in farmland； non-agricultural employment level， degree of concern about damage to land rights and interests， availability of idle land， non-agricultural employment opportunities， knowledge of land transfer policies， and expection for income from land transfer play a major influence on the willingness of farmers in the resettlement area to transfer their farmland. ② There is a two-by-two interaction relationship between the influencing factors， in which the explanatory power of the factors is significantly enhanced after any two factors interact. The interaction between the distance to farmland and the integration situation in the resettlement area has the greatest influence on the migrants' willingness to transfer to farmland； the interaction between the degree of fragmentation of farmland， whether there is idle land， and non-agricultural employment opportunities are related to the impact on land rights and interests， has the greatest influence on the willingness of residents in the resettlement area to transfer out of farmland， and the per capita family cultivated land area of the resettlement area residents’ willingness to transfer out of farmland has a stealthy role. ③ There is a strong correlation between the migrants’ willingness to transfer in farmland and the resettlement area residents’ willingness to transfer out of farmland， which are mutually reinforcing and are in the basic coordination stage of farmland transfer willingness exceeding.

In order to study the internal flow law of centrifugal pump during cavitation process and optimize its cavitation performance， this paper proposes an intelligent optimization method combining neural network and genetic algorithm on the basis of combining traditional optimization methods. Through the Plackett Burman experimental design， three optimization design variables are selected from 7 design parameters of the centrifugal pump， including impeller inlet and outlet diameter， inlet and outlet placement angle， number of blades， and blade wrap angle. The significance of the three optimized design variables’ impact on cavitation performance from large to small is ranked as follows：blade outlet width＞blade wrap angle ＞impeller inlet and outlet diameter. The Latin hypercube sampling method is used to extract 30 groups of design schemes， and the corresponding NPSH values are obtained by numerical simulation. The neural network model is established， and the optimal design variable combination and the optimal NPSH value are obtained by combining the genetic algorithm to optimize within the specified range. By taking the optimized parameters for numerical simulation calculation， the NPSH of the optimized centrifugal pump decreases by 43.1% under the same working conditions， indicating that the anti-cavitation performance of the optimized centrifugal pump was significantly improved.

In order to improve the diagnosis efficiency of water pump rub-impact failure， the vibration characteristics of axial flow pump operating under the condition of insufficient clearance between impeller and pump housing are taken as the research object. According to the force situation of the axial flow pump during rub-impact collision， the vibration characteristics of abnormal vibration caused by centrifugal force， the reaction force of water on impeller， the collision friction force and various exciting external forces are analyzed. And they are verified by numerical simulation and model test. It is concluded that when the clearance between the impeller and the pump housing is insufficient， the rub-impact vibration characteristics of axial-flow pump are mainly manifested in the integer multiples of the frequency spectrum diagram. The odd multiples and the integer multiples of the blade frequency are more prominent than other frequencies. There are noise frequency and high frequency components. When the friction is more severe， you can see 1/2 frequency bisecting frequency components. The research results have certain guiding significance in the research on pump vibration characteristics and pump station fault diagnosis.

In order to improve the accuracy of dam displacement prediction， this paper proposes a novel comprehensive prediction method based on deep learning. Initially， a multi-level data denoising technology based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise（CEEMDAN） and Singular Spectrum Analysis （SSA） is introduced. This effectively eliminates the noise and outliers in the monitoring data， improving data quality， and providing more reasonable dam deformation data for subsequent predictions. Subsequently， a deep learning model based on Convolutional Neural Networks （CNN） and Gated Recurrent Units （GRU） is constructed. The CNN is used to extract rich features from the monitoring data， and the GRU is utilized to capture and process the long-term dependencies in the time series data. To enhance the model’s performance， a self-attention mechanism is introduced to help the model better handle and recognize complex patterns in the data. Compared with other prediction methods， experimental results show that this method significantly improves the accuracy and stability of dam displacement predictions， providing a new approach for the field of dam deformation monitoring.

When the pump-turbine starts at low head conditions， the S-shaped characteristics are obvious at the speed-no-load point， and the macro-parameters of the pump-turbine units are easy to oscillate. In order to investigate the internal flow mechanism of the pump-turbine during rapid stabilization process under low head start-up conditions， misaligned guide vanes are set up， and the governor regulation is introduced in the three-dimensional simulation. Then， the macro-parameters， pressure fluctuations， and flow pattern evolutions during the entire start-up process are analyzed. The results show that at the initial stage， the guide vanes are opened synchronously and the rotational speed is relatively small， and a large range of stall vortex is generated in the runner blade passages， resulting in low-frequency and high-amplitude pressure fluctuations. With the increase in rotational speed， the flow patterns gradually become steady and the pressure fluctuations have obvious decreases. After entering the regulating stage， the operating point enters the S-shaped region， and the pressure fluctuations show high-frequency and high amplitude characteristics. The misaligned guide vanes destroy the high-speed water ring generated in the vaneless space， promoting the rapid stability of the unit.

Traditionally， data uploading mostly uses the sender as a client to initiate a connection request toward the upper-level server by using the active PUSH to complete the data transmission. However， when there are a large number of power stations and various types of data with different communication conditions， this way undoubtedly opens a back door for the upper-level server， which brings certain security risks. In this paper， a receiver-initiated method is proposed for power station data transmission control， in which the upper-level data center initiates the request， the power station or branch center responds and completes the data transmission in a reverse PULL mode. The communication port on the central side is no longer exposed， which reduces the risk of the central side network being attacked. Consequently， the Application-layer Data Reliable Transport Protocol （ADRTP） is designed to improve the efficiency of data transmission through a series of control mechanisms and adjusting the maximum packet length L _{max .}

In view of the problem of water， machine， electricity and other factors， and the early fault characteristics submerged by electromagnetic and noise， a vibration fault warning method of hydroelectric generating sets based on improved VMD and GRU is designed in this paper. First， the BES algorithm is used to optimize the parameters of variational mode VMD to obtain the optimal number of decomposition layers， penalty factor and mode number. Then， the optimal VMD algorithm is adopted to extract the early vibration fault features of hydroelectric generating sets， and finally， the extracted early vibration features are input into the GRU neural network prediction algorithm for training， validation and testing. Simulation results and engineering examples show that this method can extract the early weak vibration characteristics of hydroelectric generating sets effectively and quickly and accurately， and achieve the early fault warning of hydroelectric generating sets， which has high engineering application value.

To tackle the problem that the amount of hydropower unit condition monitoring data is gradually increasing and the data quality is poor， this paper proposes a cleaning method of hydropower unit condition monitoring data based on improved K-Dimensional Tree （ KD-Tree ） and Density-Based Spatial Clustering of Applications with Noise （ DBSCAN ）. Firstly， KD-Tree is established for the input data. Then DBSCAN is used to scan the nearest neighbor samples to complete the clustering. After the clustering is completed， the noise points will be separated， and the noise points will be removed to complete the cleaning of the condition monitoring data of the hydropower unit. 1 088 data of swing of upper guide on the condition monitoring system of a hydropower station are selected， and 100 random data are inserted at the same time interval. The clustering performance and time performance are compared with the conventional DBScan， K-means and OCSVM algorithms. The method proposed in this paper has the highest recognition accuracy of 97.78%， and the least consumption time of 0.007 732 s. It has the best data cleaning effect， and can significantly reduce the calculation time.

Although cavitation models are necessary in the study and design of fluid machinery， etc.， researchs on the numerical cavitation models suitable for high altitudes are unavailable. In this paper， firstly， the key input parameters in Zwart-Gerbera-Belamri（ZGB） cavitation model， such as initial radius of bubble and volume fraction of gas nucleus， are analyzed and expressed with the altitudes in order to make the model applicable to high altitudes environments. Secondly， the applicability of the modified ZGB model is verified though the error analysis between the numerical calculated results under different working conditions， and the experimental data in the reference. Finally， numerical calculations for the NACA0009 hydrofoil at 0~5 km altitudes， are carried out by using the modified model. The results show that under the same working conditions， with the increase in altitude， the ambient air pressure decreases， the initial radius of bubble increases， the volume fraction of air nucleus decreases， the maximum pressure coefficient of the pressure surface remains basically unchanged， the minimum pressure coefficient of the suction surface increases slightly， and the cavity length increases significantly. When the altitude is 5 km， the cavity length increases to about 81% of the chord length. The growth rate of cavity length increases with altitude. The growth rate reaches the peak value of 0.17 at 4 km and then starts to decrease.

In response to the growing demand of green development in beautiful rural construction， this paper proposes a scheme of hydro-photovoltaic-storage complementary ultra micro power generation lighting system using siphon turbine and photovoltaic panel as power generation devices and battery energy storage. The siphon turbine uses steady-state numerical simulation to calculate output and efficiency， combined with water level data to calculate power generation， photovoltaic panel area method combined with solar radiation data to estimate monthly power generation， and calculates the electricity provided to night lighting and power grid. The construction costs， economic benefits and emission reduction benefits of the system are analyzed， and the results show that the system has practical popularization prospect and emission reduction benefits.