Current assessments of aquatic ecosystem health in the middle and lower Yangtze River largely focus on single-factor indicators， limiting their ability to capture cumulative disturbance effects. To address this gap， this study develops a basin-scale framework for evaluating physical integrity. Five core functions—hydrological connectivity， flood regulation， physical habitat structure， water-quality purification， and ecological continuity—were identified. Seven categories of anthropogenic stressors were spatially mapped and weighted to construct an Index of Physical Integrity （IPI）， accompanied by high-resolution mapping. A Human Activity Index （HAI） was also calculated to quantify disturbance intensity， enabling a quantitative analysis of IPI sensitivity to human pressures and offering a new tool for large-scale integrity assessment. Results show a persistent spatial gradient of “low in urban areas， moderate in plains， and high in hills.” From 2015 to 2020， the area of extremely low IPI patches expanded by nearly 70%. The IPI–HAI relationship follows a four-phase nonlinear pattern： （i） a collapse threshold at HAI = 0.35； （ii） a recovery zone in the range of 0.35<HAI≤0.50； （iii） a high-resilience window at 0.50<HAI≤0.70； and （iv） marginal decline when HAI>0.75. Seasonal differences were evident： wet-season IPI values exceeded dry-season levels by 0.10~0.30 on average， with differences around lake clusters reaching 0.20. About 93% of the region exhibited declining seasonal integrity， primarily driven by flood–vegetation interactions. Based on these findings， a zoned regulation strategy is proposed： “push beyond 0.35—cross 0.50—hold 0.75.” This framework provides an operational， quantitative reference for water-ecological management and restoration， while offering a transferable pathway for assessing physical integrity in other large river systems.

The purpose of this study was to investigate the carbon sequestration effect of Spirulina platensis and its water purification efficiency under the condition of agricultural irrigation backwater culture in Jingdian Irrigation District. The effects of different CO₂ volume fractions （0.03% as control group， 1.0%， 2.0%， 3.0%， 4.0% and 5.0%） on the growth， biomass， quality and carbon sequestration of Spirulina platensis were studied by using agricultural irrigation water as culture water， and the improvement effect of irrigation water quality under the optimal CO₂ volume fraction was evaluated. The results showed that with the prolongation of culture time， the growth rate， biomass， carbon content， carbon fixation rate， soluble protein and sugar content of spirulina in each CO₂ volume fraction treatment group were significantly higher than those in the control group. The growth rate and carbon sequestration rate showed a trend of increasing first and then decreasing. When the volume fraction of CO₂ was 4.0%， the growth rate， biomass， carbon content， carbon fixation rate， soluble protein and sugar content （intracellular polysaccharide and extracellular polysaccharide ） of spirulina reached the highest level， which were 153.1%， 147.1%， 81.7%， 374.1% and 56.5% （35.1%， 27.4%） higher than those of the control group， respectively.The removal rates of COD_Cr， BOD₅， NH₃-N， TP and TN in the effluent were 75.64%， 90.49%， 28.20%， 68.42% and 90.73%， respectively， after 90 days of culture under the optimum CO₂ volume fraction of 4.0%. The concentrations of pH， COD_Cr， BOD₅， TP and TN all meet the Class III standard limits in the “Surface Water Environmental Quality Standard” （GB3838-2002）. This study provides a theoretical basis for the application of Spirulina platensis in CO₂ fixation and water purification under the condition of agricultural irrigation.

The distribution of water temperature in front of the reservoir dam is one of the key factors determining the effectiveness of stratified water intake through stoplogs in reservoirs. However， most methods for predicting vertical water temperature rely on numerical simulations， which are limited in practical engineering applications due to their low computational efficiency and extensive parameter settings. To quickly predict the vertical water temperature in front of the reservoir dam， this paper proposes a vertical water temperature prediction method based on the Transformer structure. By unifying the time series mean and variance within the sliding window to the same distribution type， this method addresses the issue of time series distribution skewness and improves the traditional models. Training and validation were conducted using vertical water temperature distribution data from Xiluodu Reservoir from January to May during 2020–2023. Finally， the errors of the traditional Transformer model and the improved model were compared. The research results show that the traditional Transformer model can simulate the vertical water temperature distribution trend well， but the simulation effect is slightly worse in the thermocline and deep water layers. The root mean square error （RMSE） of the vertical water temperature in the validation set is 0.286℃， and the mean absolute error （MAE） is 0.203℃. After unifying the time series mean and variance within the sliding window to the same distribution type， the RMSE of the vertical water temperature in the validation set of the improved model is 0.169℃， and the MAE is 0.107℃. The simulation accuracy has been significantly improved compared to the traditional model. This study provides a method for predicting vertical water temperature in front of the reservoir dam， offering a vertical water temperature prediction tool for the formulation of stratified water intake schemes through stoplogs in practical engineering.

In the seasonal freeze-thaw agricultural regions of northern China， the spring freezing-thawing period is a critical stage for the output of nitrogen non-point source pollution. Freezing-thawing processes profoundly affect the migration paths and source-sink relationships of nitrate by altering soil hydrological processes and nitrogen transformation environments， while traditional concentration monitoring methods struggle to accurately analysis the multi-source mixed contributions under complex freeze-thaw conditions. This study focused on the Heidingzi River Basin， a typical seasonal freeze-thaw agricultural region， and conducted a systematic research during the frozen soil thawing period （March–April） in 2014. A total of 17 sampling sites were set up， including main channels， tributaries， rural drainage ditches， and confluence areas with different underlying surfaces. Water samples were collected 4 times， corresponding to the early snowmelt stage， late snowmelt stage， rainfall runoff stage， and late thaw stage， respectively. Combined with nitrogen and oxygen isotope （δ1?N， δ1?O） tracing technology， the sources and migration mechanisms of nitrate were analyzed. The results showed that the sources and migration paths of nitrate during the frozen soil thawing period exhibited significant stage-specific characteristics. During the early snowmelt stage （mid-March）， rural domestic sewage and compost in areas near the river were the main contributors. The mean δ1?N value in the main channel was 6.65‰， and the average nitrate concentration was 4.02 mg/L. In the late snowmelt stage （late March）， the proportion of soil nitrogen input increased， coupled with denitrification in the river channel. The mean δ1?N value in the main channel rose to 11.77‰， and the average nitrate concentration decreased to 3.81 mg/L. During the rainfall runoff stage （early April）， nitrate from deep soil flowed into the river through interflow， leading to a significant increase in δ1?N and δ1?O values in the main channel， reaching 14.97‰ and 12.31‰ respectively， with the nitrate concentration dropping to 2.68 mg/L. In the late thaw stage （late April）， groundwater runoff became the dominant transport pathway. The mean δ1?N value in the main channel reached 18.66‰， and the concentration decreased to 2.39 mg/L. This study reveals the nitrate migration paths during the freezing-thawing period in seasonal freezing-thawing agricultural regions based on nitrogen and oxygen isotope tracing， providing a key theoretical basis for the precise prevention and control of agricultural non-point source pollution in cold regions and offering a methodological reference for the application of isotope tracing in similar regions.

An interception and slow-release eco-dam is a soil and water conservation engineering measure that integrates geotextiles， sand and gravel， and willow stakes. And a reasonable filter layer design is significance for reducing operational and maintenance costs and improving project efficiency of dam. This study carried out orthogonal experimental with 3 factors and 3 levels， and the factors included permeability pressure （5， 10 and 15 kPa）， consolidation pressure （12， 24 and 36 kPa） and muddy water concentration （3%， 6% and 9%）. The horizontal permeability coefficient and amount of clogging of filter body， the permeability and silt-clogging characteristics of comparative hierarchical combination and uniformly combined filter body were observed in the study process， and range analysis and sensitivity analysis were carried out. The results show that： ①The horizontal permeability coefficient of the uniformly combined filter body with the range of 0.000 6~0.004 cm/s decreases monotonically with increasing permeability pressure， and increases at first and then decreases as consolidation pressure rises， and decreases at first and then increasing with higher muddy water concentration. With the increase of seepage pressure， consolidation pressure and turbid water concentration， the horizontal permeability coefficient of the layered composite filter body （0.001~0.006 cm/s） varies within a narrower range， resulting in minimal disruption to water flow through the dam body. ② Range analysis indicates that the order of primary and secondary factors affecting the uniform composite filter was permeability pressure > consolidation pressure > muddy water concentration. However， for the layered composite filter， the order was muddy water concentration > consolidation pressure > permeability pressure. Sensitivity analysis further corroborates that the layered composite filter significantly mitigates the sensitivity of the horizontal permeability coefficient to changes in permeability pressure and consolidation pressure by leveraging complementary permeation mechanisms across its layers， and its sensitivity to muddy water concentration gradually decreases as the concentration increases. ③The clogging rate of the layered （2.22%~3.14%） combined filter layer was moderately lower than that of the uniform filter （2.36%~3.25%） when the concentration of muddy water was 3% to 9%. The accumulated siltation volume in the layered composite filter was significantly less than that in the uniform filter during the long-term operation of the dam， which will improve the stability and extend the service life of the dam. The study confirms the effectiveness of the layered composite filter design and proposes a new filter configuration scheme for interception and slow-release ecological dams， thereby providing a scientific basis for their design.

The Yangtze River Basin is a vital ecological and economic zone in China， and its carbon storage dynamics are crucial for regional carbon balance. This study integrates the PLUS and InVEST models， combined with geographic detectors and multi-scenario simulations， to analyze the evolution characteristics and driving mechanisms of carbon storage in the Yangtze River Basin from 2000 to 2020， and to predict carbon storage in the basin in 2030. The results indicate that the carbon storage in the Yangtze River Basin increased from 424 million tons in 2000 to 442 million tons in 2020， with an uneven spatial distribution and forests contributing over 55%. Elevation， slope， temperature， and gross domestic product （GDP） are the primary driving factors， with their interactions exhibiting nonlinear enhancement. Multi-scenario predictions show that carbon storage in 2030 is sensitive to climate pathways， with the SSP5-8.5 scenario yielding the highest carbon storage （49.2~49.3 billion tons）， while the impact of land-use policies is relatively minor. The study reveals that climatic factors dominate carbon storage changes， while land-use policies regulate land cover structure. The research provides a scientific basis for low-carbon development in the basin.

The implementation of basin ecological compensation holds significant importance for enhancing water resource utilization efficiency and promoting ecological conservation and high-quality development. However， the rationality of compensation standards has remained a persistent challenge in compensation practices. Building upon the context of China’s Grain for Green Project （a large-scale afforestation/grassland restoration initiative）， this study innovatively explores a framework for calculating basin ecological compensation standards from a generalized water resource perspective. The proposed methodology integrates three core components： ① a water footprint-based compensation model to quantify ecological service value flows and determine compensation direction， ② a total cost revision model for accounting ecological protection expenditures， and ③ a water resource valuation method to establish market-oriented pricing mechanisms. By coupling these models with game theory simulations of inter-basin negotiation processes， the research examines compensation rationality through a case study of the Yanhe River Basin. The findings demonstrate that the water footprint model effectively identifies ecological service supply-demand relationships， calculating the minimum compensation the downstream parties are willing to accept from the upstream at 43 million yuan. The total cost revision model reveals significant disparities between the downstream payment willingness （upper limit of 331 million yuan） and the upstream cost recovery thresholds （minimum of 192 million yuan）. Cooperative game modeling yields Nash equilibrium solutions： when the downstream pays 199 million yuan of ecological compensation to the upstream， and the upstream provides 63 million yuan of ecological compensation to the downstream as ecological compensation， the overall benefits of the basin can be maximized. The study validates that coupling multiple calculation methods to assess compensation willingness， combined with game-theoretic analysis of cooperative equilibria， provides a robust reference framework for implementing horizontal ecological compensation mechanisms. This approach offers viable solutions for balancing ecological protection and regional development in water resource governance.

In order to reduce the cost of solidifying river and lake sediments while achieving resource utilization of agricultural waste， this study focused on four common materials： rice straw， cement， fly ash， and Bacillus compound. Through a four-factor and three-level orthogonal experiment （rice straw 1%~3%， cement 0~10 g/kg， fly ash 0~10 g/kg and Bacillus compound 0.01~1 g/L） to investigate how different material ratios affect sediment solidification efficiency and the overlying water environment. Results indicated that the solidification materials significantly influenced both the overlying water environment and sediment properties， with the solidification materials increased the concentrations of COD， TN， and TP in the overlying water by 17.03%~404.89%， 2.16%~53.04% and 23.48%~758.70%， respectively， while reduced endogenous DOM input and humification levels in the overlying water； high cement addition elevated CDOM concentration. Solidification materials increased sediment particle size and strength， with compaction increasing by 91.12%~210.77% compared to CK， while moisture content decreased by 29.96%~68.30； the addition of cement significantly increased the median particle size， compaction， and compressive strength of the sediment （p<0.01）， while the addition of straw significantly reduced the sediment moisture content （p<0.05）. Scanning electron microscopy revealed that the solidified material enhanced the sediment’s skeletal structure and porosity through gel product formation and fiber “bridging” effects， thereby improving the micro-stability. At the same time， the solidification materials changed the state of nutrient salts in the sediment， increasing the content of SOM， STN and SAP by 11.93%~271.37%， 7.43%~60.32%， and 11.12%~304.51%， respectively， compared to CK， where Z7， Z8 and Z9 may be unsuitable for aquatic plant growth due to excessively high nutrient concentrations. Comprehensive evaluation identified that Z6 （rice straw 1%， cement 5 g/kg， fly ash 10 g/kg and Bacillus compound 0.1 g/L） not only showed high sediment compaction and compressive strength but also effectively controlled nutrient release， balancing engineering strength requirements with ecological safety， providing a feasible solution for low-cost and eco-friendly sediment stabilization technology. This holds significant importance for promoting the resource utilization of agricultural waste and the industrialization of river and lake sediment remediation.

To efficiently and accurately conduct groundwater pollution source inversion， this paper employs deep learning methods， specifically the Long Short-Term Memory （LSTM） model and Multilayer Perceptron （MLP）， to establish proxy models for pollution transport simulation. The DREAM-MCMC algorithm is then applied， using an adaptive update strategy to identify the groundwater pollution source inversion results. Finally， sensitivity analysis is used to discuss the inversion outcomes， thereby constructing a comprehensive groundwater pollution source inversion system. Two numerical examples are used to validate the proposed system. The results show that the LSTM-based proxy model achieves higher accuracy in simulating the model. Specifically， in Example 1， the three evaluation metrics—coefficient of determination （R2）， Mean Squared Error （MSE）， and Mean Relative Error （MRE）—reach 0.999 9， 0.03 and 0.001， respectively， while in Example 2， the values are 0.883 4， 333.65 and 0.362. In comparison， the proxy model built using the MLP method in Example 1 has values of 0.999 1， 0.76 and 0.005， and in Example 2， the values are 0.810 3， 665.42 and 0.262. These results demonstrate that the proxy model built using LSTM achieves higher approximation accuracy for the simulation model. By combining the DREAM-MCMC algorithm with the adaptive update strategy， and comparing it to the inversion method without the adaptive update strategy， the results indicate that the method with the adaptive update strategy generally exhibits lower relative errors in the inversion outcomes， confirming that this strategy significantly improves the inversion accuracy. Finally， the sensitivity analysis of the inversion results further elucidated the relationship between them. The results from the two numerical examples prove that this system can efficiently and accurately solve groundwater pollution source inversion problems， providing new insights into addressing groundwater pollution.

This study focuses on the application of reservoir operation regulations to guide reservoir management， addressing the challenges of efficient and accurate retrieval and intelligent reasoning when dealing with complex operational guidelines. Traditional retrieval approaches， such as expert regulation libraries and knowledge graphs， exhibit limitations in handling complex regulations， including insufficient retrieval accuracy， weak reasoning capabilities， and the lack of natural language interaction， which fail to meet the requirements of modern reservoir operation decision-making. To address these issues， this paper develops a retrieval-augmented generation （RAG） system and decision-making framework for complex reservoir operation regulations based on large language models （LLMs）. By leveraging high-dimensional vector processing techniques， an efficient vectorization method for handling reservoir regulations is proposed， establishing a domain-specific knowledge base. Prompt engineering tailored to regulatory characteristics is designed， and logical reasoning capabilities are enhanced through chain-of-thought （CoT） and code-first strategies. A knowledge base system is implemented using the open-source ChatGLM4 model， employing efficient retrieval and information-matching mechanisms. Through the integration of vector databases and prompt engineering， deep injection of regulatory knowledge is achieved， significantly improving retrieval accuracy， efficiency， and reasoning performance. Experimental results demonstrate that， compared with traditional methods， the LLM-based retrieval-augmented approach achieves superior performance across multiple evaluation metrics， with an average answer similarity score of 0.94， answer relevance of 0.90， answer correctness of 0.75， and contextual precision of 0.92， providing an intelligent and high-precision pathway for applying reservoir operation regulations in practical reservoir management.

Uneven regional economic development and intensified global climate change increasingly challenge the safe and stable operation of water networks. These systems face dual uncertainties from stochastic runoff fluctuations and dynamic water demands， rendering traditional deterministic optimization methods ineffective under extreme conditions. To enhance robustness and flexibility of water networks in extreme scenarios， this study proposes a min-max-min two-stage robust optimization model based on Two-stage Robust Optimization theory. Using a Box Uncertainty Set to represent uncertainties in reservoir inflows and demands， the model incorporates operational constraints of intakes， storage facilities， conveyance networks， and receiving zones， forming a coordinated multi-unit framework. Leveraging Column and Constraint Generation （C&CG） and strong duality， the problem is decomposed into master and subproblems for dynamic solution. A case study on the Beibu Gulf Guangdong Water Resource Allocation Project， supported by runoff simulations， validates the approach through numerical analyses. Results show： ① the optimization model improves system robustness and water use efficiency under extreme scenarios compared to deterministic approaches； ② adjusting uncertainty parameters enables flexible scheduling to meet diverse hydrological conditions； ③ storage facilities can operate safely and stably across typical hydrological years， confirming the long-term stability and applicability of the model. This research offers a scientific decision-support tool that enhances resilience and intelligent scheduling in water networks， with significant practical value for improving resource allocation efficiency and water security.

In order to clarify the change characteristics of compound drought and hot events （CDHE） in Beijing-Tianjin-Hebei region and provide theoretical reference for disaster prevention and mitigation and coping with climate change， using the grid data of monthly precipitation and temperature from June to August during 1961–2023 in Beijing-Tianjin-Hebei region， firstly， drought and hot events were identified by Standardized Precipitation Index （SPI） and Standardized Temperature Index （STI）， and then Copula and survival Kendall return periods were used to explore the variation of summer CDHE and their return periods. The results showed that： ① The intensity， frequency and occurrence range of drought and hot events in Beijing Tianjin Hebei region have all shown an increasing trend since 1994， and the change of hot events was more significant than that of drought events； ② Before 1994， CDHE rarely occurred in the region， and many types of CDHE had zero occurrences. After 1994， the occurrence frequency significantly increased and covered all types of CDHE， but the majority were mild cases such as P1T1 and P2T1； ③ The analysis of survival Kendall return periods show that when the intensity of both drought and hot events does not exceed the moderate level， the return periods of CDHE formed thereby are mostly no more than 50 years； when the intensity of at least one of the two reaches the severe level or above， the return periods of CDHE are mostly over 50 years； if the severity of CDHE is no less than 6， then the return periods of them are mostly over 100 years； ④ The spatial pattern of survival Kendall return periods distribution of CDHE indicates that areas north of the 39°N latitude are more prone to CDHE； ⑤ A comparison analysis between the AND return periods of CDHE and its actual occurrence situation indicates that： the AND return period not only presents logical contradictions but also significantly underestimates the risk of CDHE. Currently， compared with other definitions of bivariate return periods based on Copula functions， the survival Kendall return period is a more rigorous and reasonable calculation method for quantifying the risk of compound drought and hot events.

Against the backdrop of global climate change， the suddenness， extremity and abnormality of climate events are becoming increasingly prominent. Studying the evolution of extreme climate indices in the Three Gorges Reservoir Area （TGRA） is conducive to deepening the understanding of extreme climate events in the reservoir area and can provide certain technical support for disaster prevention and mitigation in the reservoir area and the optimal scheduling of reservoirs. Based on the meteorological data of 19 meteorological stations in the TGRA， this paper selects 13 extreme climate indices and uses the Mann-Kendall trend and mutation test to focus on analyzing the spatiotemporal evolution characteristics of extreme climate indices before and after the construction of the Three Gorges Reservoir. Further， based on the contribution degree of multiple linear regression， the influence mechanisms of horizontal distance and vertical height difference on the extreme temperature index were analyzed， and the influence ranges of both were clarified. The results show that： ① Over the years， the indices of TN90p， TX90p and TNn in the reservoir area have increased significantly， while CSDI， FD0， TN10p and TX10p have decreased significantly； ② The indices of SU35， TN90p， TX90p， RX5day and R95p in the reservoir area have sudden change points before and after the construction of the Three Gorges Reservoir， and the influence of the reservoir area on the above indices is relatively significant. ③ The areas where the linear tendency rates of WSDI， SU35， TN90p， TX90p， TNn and TNx in the reservoir area increase are mainly concentrated near the reservoir area， while the areas where they decrease are mainly concentrated far from the reservoir area. However， the variation areas of the CSDI， TN10p and TX10p indices are the opposite. ④ The horizontal distance and vertical height difference between the station and the water body in the reservoir area have a significant regulatory effect on extreme temperature indices. The maximum horizontal influence distance in the reservoir area is approximately 1.0~1.5 km， and the maximum vertical influence distance is approximately 150~190 m. Within the transverse influence range， SU35 can be increased by 7.17 d/10 a and TNx by 0.88 ℃/10 a. ⑤ The contribution of horizontal distance to the influence of extreme temperature indices ranges from 45% to 87%， while the contribution of vertical height difference is 13% to 55%. ⑥The water body of the reservoir area has a significant heat storage effect in summer and a heat release process in winter.

Most studies on the regularity of abrupt drought-flood alternation events typically adopt a single data source. To evaluate the applicability of multi-source fusion data in identifying such events， this study employs optimal interpolation method to fuse observed， reanalyzed， and satellite precipitation data， constructing a multi-source precipitation fusion sequence for the Xiaoqing River basin spanning 1956-2021. Furthermore， methods including the Mann-Kendall test， BEAST change point detection， and wavelet analysis are used to examine the spatiotemporal evolution of long-term and short-term drought-flood abrupt transition events by calculating the standardized drought-wet abrupt alternation index （SDWAI）. Results indicate that the multi-source fusion data significantly outperforms dual-source fusion data in terms of accuracy， with monthly R2 values showing improvement across all months. Notably， the increase in August reached 0.30， demonstrating greater precision in characterizing precipitation dynamics at the station. Temporally， analysis based on multi-source fusion data reveals that both long-term and short-term SDWAI exhibit an upward trend during July–August， while short-term SDWAI shows a downward trend during June–July and August–September. The future trends for the long-term and short-term periods from August to September align with the past 66-year trend， whereas the future trends for the short-term periods from June to July and July to August diverge from the historical trend. The most probable abrupt change years identified at various scales through multi-source data fusion （1997 for long-term scale； 1980 for June–July， 1987 for July–August， and 1998 for August–September for short-term scale） align closely with results based on observed data. The primary cycle for the long cycle is 18 years， while the dominant cycles for the short cycles of June–July， July–August， and August–September are 33 years， 12 years， and 40 years respectively. Spatially， the long-term trend shows a shift from flooding to drought， with a pattern of “high in the west， low in the center， high in the east.” The transition from drought to flooding is pronounced in the east and west， while the shift from flooding to drought is prominent in the central region. In the short term， June–July exhibits an overall transition from flooding to drought， with a spatial shift from flooding to drought in the west transitioning to drought to flooding in the east. July–August predominantly featured a shift from drought to flooding， with the central region experiencing a relatively strong transition from flooding to drought， while the eastern and western regions primarily shifted from drought to flooding. August–September primarily saw a transition from flooding to drought， with the northwest being a high-intensity zone for drought-to-flooding and the southeast being a high-intensity zone for flooding-to-drought. Furthermore， the spatial distribution of abrupt drought-to-flood transition events highly correlates with SDWAI values. Regions with high SDWAI values predominantly experienced drought-to-flood alternation， while areas with low SDWAI values were dominated by flood-to-drought alternation.

The upper reaches of the Yangtze River are a vulnerable area to climate change， and climate change will further exacerbate the frequency of droughts and floods. In order to further explore the evolution laws and influencing factors of hydro meteorological drought in the upper reaches of the Yangtze River， based on monthly meteorological data from the upper Yangtze River Basin， the Standardized Precipitation Evapotranspiration Index （SPEI） was calculated to identify meteorological drought events and analyze their evolutionary characteristics. Subsequently， utilizing observed daily runoff data from seven hydrological stations within the basin， the Streamflow Drought Index （SRI） was derived via an optimal cumulative distribution function to examine variation patterns in hydrological drought events. The propagation characteristics between meteorological and hydrological droughts were quantitatively analyzed using the Maximum Pearson Correlation Coefficient （MPCC） across various time scales and the cross-wavelet transform method. Moreover， the XGBoost-SHAP method was employed to investigate the influencing factors of hydrometeorological drought events. Results demonstrate a marked northwest-southeast gradient in meteorological drought frequency （lower in the northwest， higher in the southeast） with eastward-increasing intensity； cumulative drought intensity and duration distributions were fundamentally consistent， whereas drought peak values exhibited an approximately inverse spatial pattern relative to intensity. On the whole， hydrological droughts occurred more frequently in summer and winter than in spring， with long-duration events constituting 36.9% of the total drought events. Propagation exhibited a significant temporal lag with pronounced spatiotemporal heterogeneity， jointly modulated by watershed attributes and seasonal climate （accelerated summer responses， pronounced winter lags）. Critically， meteorological droughts depended more on local drivers （precipitation， temperature， PET）， while hydrological droughts were predominantly modulated by large-scale climate oscillations （ENSO， PDO， solar activity）.

As a classic hydrological method for simplifying river channel confluence routing， the Muskingum method is particularly important in watershed flood forecasting and runoff generation-confluence analysis. However， in watersheds where the impact of interval runoff generation is significant or the upstream is a reservoir-controlled station， the Muskingum method has problems such as difficulties in parameter calibration and insufficient forecasting accuracy. To address these issues， this paper proposes a flood simulation framework that combines the random forest model with the formula-based Muskingum method based on reach characteristics. This method takes CMFD precipitation data and ERA5-Land evapotranspiration data as inputs， uses the random forest to explore the nonlinear relationships among precipitation， evapotranspiration， and runoff， and simulates the interval runoff generation process in data-scarce areas. Flood routing calculations were conducted by integrating the Muskingum method with parameters estimated based on reach characteristics. Finally， the interval simulated discharge and river channel routing discharge are superimposed to construct a complete flood hydrograph at the downstream cross-section. The results show that the CMFD precipitation data demonstrates good applicability at both the station and watershed scales in the study area； the random forest model exhibits excellent performance during both the training and validation periods， with Nash-Sutcliffe efficiency coefficients （NSE） mostly above 0.9； compared with the traditional schemes that only adopt the lumped rainfall-runoff model or solely perform channel routing， the coupled method proposed in this study significantly improves the simulation accuracy of the outlet cross-section discharge， and the fitting performance of the peak discharge and peak occurrence time is obviously enhanced. This study provides an effective approach to solving the difficulties in flood forecasting for upstream basins regulated by reservoirs and interval ungauged basins， and has strong practicality and promotion value.

Evaluating the spatial equilibrium state of regional agricultural water resources and proposing optimization strategies are of great value for improving the efficiency of water and soil resource allocation and ensuring food security. Based on the analysis of the connotation characteristics， identification criteria and economic theory of the spatial equilibrium of agricultural water resources， an evaluation index system for the spatial equilibrium of agricultural water resources was constructed， and an optimization model was established by integrating multi-objective programming and NSGA-II algorithm. The data of 14 cities （prefectures） in Hunan Province from 2013 to 2022 were selected for empirical analysis. The study found that： ① Yiyang and Yongzhou realize the spatial equilibrium of agricultural water resources， and are at the level of adaptation equilibrium； Xiangxi， Zhangjiajie， Huaihua and Chenzhou are in idle spatial imbalance； the eight cities of Changsha， Zhuzhou， Xiangtan， Shaoyang， Loudi， Yueyang， Changde and Hengyang belong to the shortage spatial imbalance. ② The optimization results show that the agricultural water supply and consumption in the equilibrium area should be reduced by 671 million m³， the agricultural water supply and consumption in the idle imbalance area should be increased by 716 million m³， and the agricultural water supply and consumption in the shortage imbalance area should be reduced by 1.659 billion m³. Through the coordinated regulation of supply and demand， the total water supply and consumption can be reduced by 1.613 billion m³， and the agricultural water supply and consumption efficiency can be further improved. ③ Based on the comprehensive evaluation and optimization results， a differentiated regulation strategy oriented to supply and demand matching is proposed. The adaptive equilibrium area should strengthen the system resilience， improve water resources efficiency and agricultural productivity through technological upgrading and management innovation， and achieve high-quality balance. The idle spatial imbalance area needs to activate the resource potential， focus on the development of high value-added agriculture and promote water rights trading， and promote the transformation of idle water resources value. In the shortage spatial imbalance area， it is necessary to strengthen water use constraints， tap water source potential， strictly abide by the upper limit of water resource development and ecological red line， and prevent system risks.

This paper proposes a new generating unit-water supply valve coordinated operation strategy for the transient process of energy dissipation power stations within long water conveyance systems of water supply projects. By constructing a transient process simulation model of energy dissipation power stations with water supply valves， systematic comparison and analysis of transient processes of generating units under both coordinated and non-coordinated valve operation modes were conducted. The research results show that coordinated valve operation can effectively improve the transient process of generator units， specifically manifested as： significantly reducing water hammer pressure under large fluctuation conditions， with the maximum pressure reduced by 22.42%； effectively suppressing power output fluctuations of disturbed units during hydraulic interference conditions， with output swing amplitude reduced by 91.28%； substantially improving unit regulation quality under small fluctuation conditions， with speed regulation time shortened by 20.19% and the maximum speed deviation reduced by 19.13%. For long water conveyance system energy dissipation power stations without surge chambers， the coordinated operation strategy of generating units and water supply valves can effectively address the challenge of unsatisfactory regulation quality during small fluctuations， providing new design perspectives for eliminating surge chambers in such power stations. The research results provide essential technical support for the safe and efficient operation of energy dissipation power stations with long water conveyance systems under surge-chamber-free conditions.

With the advancement of new-type power systems dominated by renewable energy sources （RES） such as wind and solar， the inherent intermittency and stochasticity of RES generation impose higher demands on flexible regulation powers. This study proposed an optimized operation method for pumped-storage power stations （PSPS） aimed at facilitating RES accommodation through peak shaving and valley filling. Two operation objectives were considered separately： maximizing PSPS benefits and minimizing grid residual load fluctuations. The model employed an adaptive genetic algorithm （AGA） to optimize PSPS operation. A PSPS in Hunan Province was selected as a case study， with simulation analysis conducted under representative load scenarios. The results show that， under 12 representative daily load scenarios， the maximal power benefit strategy achieves an average daily revenue of 2.9142 million CNY， and considering spinning reserve requirements significantly enhances operational profitability. Compared to the scenario where the PSPS is not put into operation， the minimal load fluctuation strategy reduces the average daily standard deviation of residual load from 2864 MW to 2423 MW （a 16% reduction）， and the average daily coefficient of variation from 0.27 to 0.22 （a 17% reduction）. The findings provide technical support for improving the efficiency and benefits of PSPS operations.

During the grid-connected operation of multi-unit common water conveyance system of hydropower station， there are hydraulic and electrical co-interference and mutual interference among the units dynamic regulation， which seriously affects the dynamic regulation performance of the units. To address this issue， this paper conducts an in-depth study on the hydraulic and electrical characteristics of grid-connected operation units for multi-unit common water conveyance system of hydropower station， establishes a mathematical model for the grid-connected operation of such systems， and proposes a multi-objective coordinated optimization operation method. Firstly， the dynamic characteristics of the grid-connected operation coupling system of typical hydropower station are studied. Further， NSGA-III algorithm is used to optimize and simulate the dynamic characteristics of the coupling system. The results show that： the larger deviation of inertia time constant and hydraulic loss of water flow in the headrace pipeline between units， the greater the influence on the dynamic regulation performance of the coupling system. When the system load deviation is distributed to the units with smaller inertia time constant and hydraulic loss in the diversion pipeline， the coupling system can obtain better regulation performance. The multi-objective coordinated optimization strategy proposed in this paper can effectively coordinate the dynamic response performance of each unit， obtain the comprehensive performance of the coupling system optimal， and lay a good theoretical and technical foundation for the optimization operation of multi-unit grid-connected of hydropower station.

Aiming at the problems of insufficient fault feature extraction and difficulty in efficiently identifying fault types during the operation of the shaft system of a hydropower unit， a fault diagnosis method for the shaft system of a hydropower unit is proposed based on the optimization of the variational modal decomposition （VMD） parameters by the multi-strategy improved triangular topology aggregation optimization algorithm （ITTAO） in conjunction with a convolutional neural network and a bidirectional long and short-term memory network （CNN-BiLSTM）. Firstly， the ITTAO algorithm is used to optimize the modal component parameter K and the penalty factor α of the VMD decomposition to realize the adaptive decomposition of the vibration signal. Secondly， the vibration signal is decomposed by using the optimal VMD parameters， and the time-frequency features of the optimal intrinsic mode function （IMF） components are extracted to construct the multidimensional fusion feature matrix. Finally， the extracted features are fed into the CNN-BiLSTM diagnostic model， and its powerful spatio-temporal feature extraction capability is utilized to realize deep mining and accurate classification of fault features. The example verification shows that the method proposed in this paper can fully extract the fault features of the vibration signal， which can effectively improve the accuracy and stability of fault diagnosis.

To reduce the wear and operational risks to turbines caused by high sediment concentrations in rivers with heavy sediment load， this paper proposes an innovative scheme for sediment discharge and water intake in low-head hydropower plants， specifically suited for riverbanks. The scheme is based on the concept of “using reservoirs instead of ponds” and aims to improve the reliability and water resource utilization efficiency of hydropower projects. By optimizing the layout of hydraulic structures and flow patterns， it achieves efficient sorting and sedimentation of sediments. At the intake point near the riverbank of low-head hydropower plants， guiding walls are installed to narrow the river width and enhance the water flow’s ability to carry sediments， facilitating the process of sediment concentration and removal. Additionally， sediment blocking weirs are set up， including the return water sediment blocking weir and the intake sediment blocking weir. The return water weir is used for further deposition of coarse-grained particles， while the intake weir intercepts finer suspended sediments， achieving a multi-stage sedimentation process. By guiding the flow of water back to the intake， the sedimentation path is lengthened， which allows further sediment deposition in the return flow zone. This process effectively enhances overall sediment discharge efficiency within limited space and ultimately ensures the precise extraction of low-sediment water from the surface. Model test results show that this scheme effectively utilizes the natural conditions of river length and width to achieve sediment sorting based on particle size. Coarse-grained sediments settle in the upstream reservoir， while the return water sediment blocking weir distributes and separates the sediment. The return water passes through the intake sediment blocking weir for secondary screening， allowing the upper layers of low-sediment water to enter the intake. This scheme features efficient sand prevention， multi-method sediment clearing， eco-friendly design， and ease of operation and maintenance. It maximizes the utilization of natural river conditions， ensuring the efficient and stable operation of the hydropower station while also fully leveraging the benefits of water resources. It holds significant potential for broader application， particularly in sediment-laden river regions such as those in the northwest and southwest of China.

A hydrodynamic simulation model was developed for the cascade water transfer system in the follow-up optimization project of the Hanjiang-Rongjiang-Lianjiang water system interconnection. The system coupled pumps， pipes， valves， pools， and weirs. The model was built with the method of characteristics for one-dimensional unsteady flow and included the main hydraulic boundaries. A solution for the coupled conditions between regulating pools and overflow weirs was formulated. A simulation platform was created with the VB.net language based on the engineering parameters. The start-up process from still water to the design flow was simulated to analyze system behavior and pump–valve coordination. Results showed that the optimized scheme can effectively suppress hydraulic transients. The pressure distribution along the whole line and water level variations of tanks met the requirements of safe operation. A safe and stable start-up was achieved. The study provided reference for the design and operation scheduling of similar complex cascade water transfer projects.

In order to study the rule of change of the spiral flow along the downstream of cyclones with different guide vane heights， the guide vane height was taken as a single control variable， and the method of combining physical test and numerical simulation was used to analyse the attenuation law of its downstream. The results show that the average circumferential flow velocity is continuously attenuated by the along-range resistance， and increases with the increase of the guide vane height. Within the range of 500mm from the outlet section， the higher the height of the guide vane， the larger the increase of the average vortex， and the average vortex of the section is rapidly attenuated when the spiral flow develops to the downstream. When the height of the guide vane is 40 mm， the along-range attenuation rate of the downstream section pressure and the coefficient of friction have been improved obviously. The swirl number presents an exponential attenuation along the axial direction， and the influence of the guide vane height on its attenuation rate is small. When the height of the guide vane H is between 30mm–35mm， the cyclone has both high performance and low energy consumption， which is a more economical and efficient parameter of the spinning structure.

In order to study the sediment abrasion characteristics of the Pelton turbine distributor， the Volume of Fluid （VOF） model and Discrete Phase Model （DPM） are used to simulate the solid-liquid two-phase flow in the distributor， and the Oka model is used to evaluate the sediment abrasion. The study reveals the distribution law and abrasion of sediment with different particle sizes in the distributor. It is found that the sediment accumulates in the area 0.1D away from the outer wall of the distributor （D is the characteristic diameter of the pipe）， and due to the influence of the secondary flow at the bifurcation， the sediment accumulates at the side of the nozzle near the crescent rib. In addition， due to the influence of gravity， the sediment settles to the bottom of the distributor. Abrasion is concentrated on the nozzle outlet， needle， bottom and crescent rib. The abrasion at the nozzle outlet is the most serious， and the abrasion range is more than 50%. Water ripple abrasion patterns can be seen on the spray needle， which is consistent with the actual engineering situations. Slight abrasion exists on the upstream side of crescent rib. Under the same concentration， the larger the sediment particle size， the larger and more uneven the abrasion range at the nozzle outlet， and the worse the stability of the jet at the nozzle outlet. This study clarifies the sediment accumulation and abrasion influencing factors in the distributor are clarified， which provides an important theoretical basis for the anti-abrasion structure design of Pelton turbine and the formulation of sand control measures.

To address the unsatisfactory control performance of traditional PID in governing systems of pelton turbines with mechanical hysteresis， this paper proposes a cascade control strategy combining Dynamic Matrix Control （DMC） and Fractional-Order PID （FOPID）. Considering the mechanical hysteresis of hydraulic actuators， a mathematical model of the pelton turbine governing system under small disturbances is established. The FOPID controller is adopted as the inner-loop control， while DMC is introduced as the outer-loop control， forming a DMC-FOPID cascade control method for the pelton turbine governing system. Furthermore， by integrating quantum-bit Bloch sphere coordinate encoding， somersault foraging strategy， and opposition-based learning， the Crested Porcupine Optimizer （CPO） is enhanced， resulting in an Improved Crested Porcupine Optimizer （ICPO） with superior optimization capabilities. The ICPO is employed to tune and optimize the FOPID parameters， and control simulations are conducted based on Simulink. The results demonstrate that the proposed cascade control method significantly improves the control performance of the pelton turbine governing system.

In order to make full use of low-head energy， low-head pumping station reverse power generation is an effective way to realize low-head energy utilization. In this paper， the shaft tubular pump device is taken as the object， and the whole flow channel numerical simulation is carried out for the normal pump condition and the reverse power generation condition， and the transient characteristics of the reverse power generation condition are compared and studied. The results show that under the reverse power generation condition， the high efficiency point appears at the flow condition of 1.18 Q _bep， and the high efficiency range is about 1.43 times that of the pump condition. Under the condition of reverse power generation， there are more positive vortex cores at the hub of the front guide vane body. As the impeller continues to rotate， the positive and negative vortices are mixed with each other. The variation of pressure pulsation under the two working conditions is basically similar， but the C_P amplitude under the reverse power generation condition is higher as a whole. It is about 15 % higher than that under the pump condition. As the flow rate increases， the axial force on the impeller blade also gradually increases. Compared with the pump operating condition， the axial force fluctuates more drastically with time and shows a stronger periodicity. The radial force also shows three clear cycles with the pump condition， and multiple irregular wavelet peaks appear at different angles. The comparative analysis of the axial force and the radial force shows that the flow characteristics are more complex than the pump conditions. The research results can provide reference for the safe and stable operation of reverse power generation of low head energy by using shaft tubular pump device.

High dam reservoir slopes subjected to long-term high water levels and excavation unloading are prone to creep， tensile cracking， and sliding failure， threatening the safety of dams and related infrastructure. This study focuses on the H1 landslide mass and Deformation body No. 1 at the Yangqu Hydropower Station. Field monitoring shows continuous slow deformation under high water levels， indicating clear creep characteristics. To analyze slope deformation and excavation-related risks， a three-dimensional numerical stability method was developed for the impoundment period. In addition， a Long Short-Term Memory （LSTM） network was used to predict displacement time series from monitoring data. This approach effectively captures the temporal characteristics and deformation trends in the creep stage. The results indicate that， under high water levels， the middle and upper parts of Zone I of the H1 landslide mass are the main deformation area. The unexcavated zone of Deformation body No. 1 has shown initial signs of sliding. Several high-risk areas exhibit a clear potential for instability. By combining numerical simulations with LSTM-based displacement predictions， this study clarifies the potential instability mechanisms of reservoir bank slopes under high water levels and excavation disturbance. The findings provide a scientific basis for slope stability evaluation and safe operation of hydropower projects.

Under rainfall conditions， slopes with weak interlayers and drainage gallery systems are prone to seepage-induced softening and expansion of plastic zones， threatening slope stability. This study achieves coordinated regulation of weak interlayer evolution and slope stability by optimizing drainage gallery layouts. Based on numerical simulations， the effects of different rainfall intensities and drainage gallery burial positions on slope deformation， plastic zone expansion， stress distribution， and stability were systematically analyzed. The results show that， within the the depth range of 10 m from the ground surface， placing the drainage gallery at the middle depth significantly reduces toe displacement and pore pressure accumulation under rainfall， while altering the seepage path of groundwater. However， positioning the gallery top at the crest of the secondary slope leads to soil wetting and vertical settlement. The drainage gallery layout causes the maximum principal stress to shift from the slope toe to various regions around the drainage gallery， and different layouts have obvious impacts on slope stability. Under the “b” drainage gallery layout， the slope safety factor reaches a maximum of 2.41. This study further elucidates the mechanism by which optimized drainage gallery layouts regulate seepage and mechanical responses of weak interlayers， providing theoretical support and engineering references for enhancing slope stability under rainfall conditions.

In response to the limitations of using fixed design-stage characteristic water levels in traditional risk assessments， this study investigates the statistical patterns of upstream reservoir water levels at both daily and annual timescales， based on 63 years of measured data from the operation period of a typical concrete dam. The Weibull empirical formula is used to perform unbiased estimation of daily water level exceedance probabilities， and the corresponding exceedance probability curves are plotted to characterize daily water level fluctuations， serving as inputs for water level parameters under seismic scenarios. For the annual maximum water levels， three distributions—three-parameter Burr XII， three-parameter lognormal， and Pearson Type III （P-III）—are applied for fitting and calibration of characteristic water levels under flood conditions during the operational period. The results show that the three-parameter Burr XII distribution provides the best fitting performance. This study offers a more scientific and reasonable method for estimating water level parameters to support the calculation of annual structural failure probabilities under earthquake and flood conditions.

This paper proposes a dam risk reasoning method driven by multi-source monitoring data and intelligent algorithms. The method couples the improved D-S evidence theory with the Bayesian Network （BN）. To address the limitation of strong subjectivity in basic probability assignment （BPA） acquisition of D-S evidence theory， the method quantifies measurement uncertainties via cloud models to generate BPA， dynamically adjusts fusion rules based on conflict factors， and converts fused BPA into BN root node prior probabilities. Conditional probability tables are determined using probability decomposition to construct a multi-level BN reasoning network for forward probability inference of dam risk states. An engineering case of a dam shows the method fuses 245 deformation， 48 seepage， and 40 stress-strain measurement data， yielding a leaf node risk probability of 0.855， and the corresponding risk level is “normal”， validating its feasibility for multi-source data fusion and precise risk inference in dam engineering.

To address the challenge of accurately characterizing the seepage field in the mountainous rock mass surrounding water diversion tunnels， this study proposes a three-dimensional seepage field inversion method integrating finite element computation， a Kriging surrogate model， and the Particle Swarm Optimization （PSO） algorithm. By constructing a Kriging surrogate model to replace computationally intensive finite element analyses， high-precision approximation of the seepage field is achieved with relatively limited sample data. The global search capability of the PSO algorithm is further employed to rapidly optimize the input boundary conditions to the model. A case study involving the inversion of boundary conditions of the seepage field in a mountainous rock mass surrounding a water diversion tunnel demonstrates the following： The proposed method significantly reduces computational costs while yielding permeability parameters and boundary water head values closer to the measured seepage field. In high-overburden tunnel sections， the inverted external water pressure exhibits a consistent overall trend with code-specified calculations. However， this method better captures the influence of local drainage measures and formation heterogeneity on the seepage field. The proposed approach provides robust technical support for seepage control and safety evaluation of water diversion tunnels.

The deformation law of rock mass under high water pressure is difficult to clarify， which is a technical bottleneck affecting the safe operation of large hydropower stations. In order to study the influence of reservoir water level changes on rock mass deformation and mechanical behavior， a self-developed test device for simulating rock mass deformation in deep water environment was used to conduct circulating water pressure tests on rock masses with different porosities under high water pressure conditions. This study focuses on the variation characteristics of strain rate and elastic modulus of Yangxin limestone with different porosities under the circulating water pressure environment， and analyzes the variation laws of strain rate and elastic modulus of rock masses with different porosities under the action of water pressure. The results show that： ① The strain of Yangxin limestone shows a positive correlation with water pressure. With the increase of the initial porosity， the strain of Yangxin limestone gradually increases. ② The strain rate of Yangxin limestone shows a positive correlation with the external water pressure， and the strain rate variation range of the rock mass with low porosity is smaller. With the increase of the number of water pressure cycles， the deformation of the rock mass gradually stabilizes. ③ With the increase of water pressure， the elastic modulus of rock masses with different porosities increases accordingly， and decreases otherwise. The smaller the porosity of the rock mass， the greater the overall elastic modulus.

Dam deformation monitoring data is affected by factors such as aging， temperature and reservoir water level， and has nonlinear and non-stationarity characteristics. In order to improve the accuracy and generalization ability of dam deformation prediction， an earth-rock dam deformation prediction model based on Variational Mode Decomposition （VMD） and Tornado Optimization with Coriolis force （TOC） self-attention model （Transformer） and Gated Recurrent Unit （GRU） is proposed. Firstly， the original monitoring data is decomposed into modal components of different frequencies by VMD， and the decomposed high-frequency components are denoised by wavelet transform threshold. Then， TOC is used to efficiently search for hyperparameters， and the global features are extracted by Transformer model. GRU strengthens the local time series dynamic modeling， and constructs the TOC-Transformer-GRU （VMD-TTG） deformation prediction model based on modal decomposition. Taking 110 phases of deformation monitoring data of an earth-rock dam as an example， the VMD-TTG model is compared with the Partial Least Squares （PLS）， TOC-Transformer-GRU and VMD-TOC-Transformer models. The results show that the Mean Absolute Error （MAE） and Mean Absolute Percentage Error （MAPE） are both within 0.494， the root mean square error （RMSE） is within 0.590， and the coefficient of determination （R² ） is above 94.2%. The stability and reliability of dealing with nonlinear relationship are better than other models.

In urban box culvert in-situ rehabilitation projects， the selection of construction timing directly affects the control of project duration， cost， and risk losses. Existing timing decisions often rely on empirical judgment， making it difficult to balance the complex influences of multiple attributes. This study proposes a reverse order risk-loss matching mechanism between construction sections and construction windows， based on the risks associated with culvert sections and diversion during construction windows. On this basis， alternative timing schemes are generated by incorporating decision-making preference attributes. Furthermore， a multi-objective optimization decision-making model for construction timing is developed by coupling the Analytic Hierarchy Process （AHP） with the Ordinal Priority Approach （OPA）， considering key factors such as risk losses， construction duration， and cost. A case study of a culvert rehabilitation project is conducted to demonstrate the application of the proposed AHP-OPA method. The results show that the risk-avoidance-prioritized scheme is the optimal recommendation， which realizes the optimal allocation of construction cost and construction period. This approach provides a scientific reference for construction timing decisions in box culvert rehabilitation projects.