[Objective] In 2024， the Xin’anjiang Reservoir experienced the largest inflow flood since its construction due to persistent and intense rainfall during the Meiyu season. The return periods of the maximum 5-day and 7-day inflow volumes both reached the 50-year level. This study conducts a post-event assessment based on the actual forecasting and operation process. [Methods] Multi-source and multi-model quantitative precipitation forecasts were assimilated to analyze the rainfall intensity characteristics of typical historical floods. Representative forecast rainfall time series were optimized under unfavorable， moderate， and favorable conditions with phased temporal distribution， extending forecast lead time while reducing rainfall uncertainty. The Xin’anjiang three-component runoff generation framework was applied to construct a basin-wide flood forecasting model， coupled with reservoir operation rules to form an integrated forecasting-operation modeling scheme. Hourly rolling forecasts were performed based on real-time rainfall and operational information. Considering multiple objectives such as controlling maximum reservoir level， ensuring downstream safety discharge， and managing flood-peak staggering with the mainstream， iterative forward-and-reverse scenario simulations generated 215 forecast scenarios， providing precise support for ten rounds of gate operation decisions. [Results] A comparative assessment of the two major floods in 2024 and 2020 shows that although the 2024 event involved larger rainfall and greater inflow volume， the forecasting was more refined， the regulation was earlier and more proactive， and the peak staggering with the Lan River was more precise. This demonstrates that the integrated forecasting-operation model can effectively support multi-objective risk control， achieving the systemic goal of “zero major disaster and zero casualty”. [Conclusion] The full-process summary highlights that dynamic and accurate forecasting is the key to scientific operation， comparative scenario analysis supports refined decision-making， and the principle of “early action， rapid response， and incremental adjustment” is more conducive to basin-wide flood risk reduction.

[Objective] This study aims to analyze the spatiotemporal distribution and probabilistic characteristics of multi-level meteorological droughts at the seasonal scale in Guangxi， China， with a focus on seasonal continuous drought events. The study quantitatively analyzes drought frequency trends， identifies the optimal probability distribution function for seasonal precipitation， and assesses the joint probability of consecutive seasonal droughts with the goal of providing more scientific basis for drought risk management in Guangxi. [Methods] Using daily precipitation data from 18 meteorological stations （1960-2020）， we calculated the Standardized Precipitation Index （SPI） for four seasonal scales and classified drought thresholds into four levels （mild， moderate， severe， and extreme）. The GAMLSS （Generalized Additive Models for Location， Scale and Shape） model compared six probability distributions （Gamma， Normal， Lognormal， Gumbel， Weibull， and Logistic） to fit precipitation sequences， and the Gamma function was selected as the optimal model based on the AIC （Akaike Information Criterion）. Five Copula functions （Clayton， Frank， Gaussian， Gumbel， and t-Copula） were used to construct the joint distribution of continuous seasonal drought， and the optimal Copula function was determined using the squared Euclidean distance （OSL）. Spatial interpolation techniques were applied to visualize regional drought probabilities. [Results] The SPI in spring showed a decreasing trend （-0.005 8/a）， indicating an increase in drought frequency， while the SPI in summer （0.007 6/a）， autumn （0.002 1/a）， and winter （0.015 3/a） showed an increasing trend， indicating a decrease in drought frequency. Based on the fitting results of the GAMLSS model using six probability distribution functions for the seasonal precipitation series in Guangxi， the gamma function appeared most frequently in the optimal and suboptimal distributions， indicating that the gamma function can effectively describe the characteristics of precipitation changes. The seasonal frequencies of different drought levels at various stations show that mild droughts （30%-48%） are more common in summer， while moderate droughts （20%-37%）， severe droughts （10%-27%）， and extreme droughts （5%-17%） are more likely to occur in autumn. The gamma distribution performs exceptionally well， with the difference between theoretical and empirical frequencies not exceeding 11%. Different regions in Guangxi exhibit significant differences in consecutive drought characteristics. Among the four consecutive seasons of spring-summer， summer-autumn， autumn-winter， and winter-spring， the probability of consecutive droughts， moderate droughts， severe droughts， and extreme droughts is higher and more widespread during the winter-spring season. The probability range for consecutive winter-spring droughts is 13.1%-20.9%， primarily distributed in the southern coastal areas of Guangxi， central Guangxi， and northeastern Guangxi， with the highest probability of drought occurring in the northwestern part of Wuzhou City. Regions with a higher probability of severe consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise. Regions with a higher probability of severe and extreme consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise， among which Liuzhou has the highest probability of severe and extreme consecutive droughts during the spring-summer season， with probabilities of 7.1% and 3.9%， respectively. [Conclusions] The study revealed differences in seasonal drought trends in Guangxi， with spring becoming increasingly dry， while other seasons exhibit a trend toward greater moisture. The robustness of the gamma function in precipitation modeling highlights its practicality in drought frequency analysis. Crucially， the Copula-based joint probability analysis identified winter and spring as the most susceptible periods for consecutive droughts， particularly in regions dominated by karst topography. These findings provide scientific basis for adaptive drought management strategies， emphasizing the need to prioritize addressing composite drought risks in regional water resource planning.

[Objective] The urban agglomeration in the middle reaches of Yangtze River Basin is a key region in the “Rise of Central China” strategy. Dense population and high-level industrialization have led to severe contradictions between water supply and demand. By calculating the connection values of regional water resources carrying capacity （WRCC）， this research aims to provide scientific references and empirical support for optimizing regional water resource allocation， promoting sustainable socioeconomic development， and informing policy practices for high-quality water conservancy development within the Yangtze River Economic Belt. [Methods] Based on multi-year statistical data from Hubei， Hunan， and Jiangxi provinces， we applied the fuzzy analytic hierarchy process （FAHP） to calculate indicator weights， set pair analysis （SPA） to evaluate the WRCC by quantifying the connection numbers between the system and carrying grades， and the standard deviational ellipse （SDE） method to analyze the spatial distribution pattern and evolution trajectory of WRCC. [Results] （1） The WRCC of the urban agglomeration in the middle reaches of Yangtze River were increasing， with the average connection number increasing by 0.20； （2） Water allocation and pollution control have been optimized， with connection numbers for water use per GDP unit and urban sewage treatment rate increasing by more than 0.70； （3） Northern cities exhibit lower WRCC， and the SDE centroid has shifted from the east to the northwest， indicating improved spatial balance in WRCC. [Conclusions] Although the WRCC of the study region has been continuously improving， there are still spatial differences. It is necessary to strengthen water resources regulation and control capabilities in the high-consumption industrial areas and high-population density areas in the northern part of the urban agglomeration. The findings provide scientific evidence and decision-making support for water resource optimization and regional coordinated management in the middle Yangtze River region.

[Objective] This study aims to reveal the seasonal concentration characteristics and spatial differentiation patterns of precipitation in Tianjin from 1980 to 2023 by quantifying long-term seasonal trends， characterizing the spatial patterns of Precipitation Concentration Degree （PCD） and Precipitation Concentration Period （PCP）， and establishing a bivariate risk assessment method based on PCD-PCP joint return periods using Copula functions. The innovation lies in the first application of Copula-based PCD-PCP coupled analysis to the hydrometeorological field of Tianjin， providing support for extreme flood prevention. [Methods] Daily precipitation data from 13 meteorological stations in Tianjin during 1980-2023 were employed. The Mann-Kendall trend test and Sen’s slope estimator were used to detect monotonic trends in seasonal and annual precipitation. The vector-based PCD and PCP indices were calculated to quantify precipitation concentration uniformity and peak timing. Inverse distance weighting （IDW） was applied to visualize spatial patterns. The distribution characteristics of PCD-PCP under specific scenarios were analyzed based on copula joint distribution. [Results] Seasonal precipitation in Tianjin is highly uneven. Summer dominates with a mean of 383.6 mm （70.1% of annual total）， while winter precipitation is extremely low （11.5 mm） but shows the highest interannual variability （extreme value ratio： 180.50）. Summer precipitation exhibits a significant increasing trend， which may elevate the risk of extreme precipitation events， whereas the increased variability of autumn precipitation could prolong the urban waterlogging risk window. Spatially， annual precipitation exhibits a stable “higher in the north and lower in the south” pattern across the 1980s-2010s. The spatial pattern of PCD shows limited variability， with values predominantly ranging from 0.68 to 0.73. A high-value zone is identified in the Binhai New Area （PCD≈0.73）， reflecting strong precipitation concentration within a short annual window， whereas lower values in Jizhou and Wuqing suggest a more even precipitation regime. In contrast， PCP exhibits a west-east gradient， increasing from approximately 201 in the west to 207 in the east （mid-to-late July）， indicating spatial asynchrony in precipitation concentration timing. Temporally， PCD shows substantial interannual fluctuations （0.50-0.85）， yet its long-term trend remains stable， as evidenced by decadal means ranging from 0.69 to 0.71. PCP also exhibits notable interannual variability （180-220） but demonstrates a significant decadal delay， progressing from 198.5 in the 1980s to 203.7 in the 2010s， a trend intrinsically linked to the phenomenon of summer rainfall shifting to autumn in the Beijing-Tianjin-Hebei region. The copula-based analysis reveals a non-independent relationship between PCD and PCP， whereby higher PCD values tend to coincide with PCP falling within the annual peak precipitation period. The 50-year precipitation event corresponds to the combination of high PCD and a specific PCP， indicating that this extreme scenario arises from the simultaneous deviation of both variables from their normal states. Under this scenario， PCD is significantly above the multi-year average， and PCP falls within the main summer flood season. This concurrence of high precipitation concentration and flood season timing will substantially elevate the risk of urban waterlogging and basin flooding. Therefore， responding to extreme precipitation events requires attention not only to increases in total precipitation but also to high temporal concentration and its coincidence with the main flood season. [Conclusion] This study systematically quantifies the seasonal concentration characteristics and spatial differentiation of precipitation across Tianjin. Summer dominates both the total amount and long-term trends. PCD is spatially homogeneous but interannually variable， whereas PCP shows a clear west-east gradient. Under the 50-year precipitation event， Tianjin faces credible extreme flood hazards. Future work should incorporate climate model projections to assess non-stationarity in the PCD-PCP dependence structure under warming scenarios.

[Objective] Current research on water demand prediction primarily focuses on improving prediction accuracy， while studies on interval prediction of water demand remain limited. This study aims to further improve prediction accuracy， reduce error interval and reflect the actual regional water demand by incorporating the Kolmogorov-Smirnov （K-S） normal interval estimation into BP （back propagation） neural network model. [Methods] In view of a wide range of water demand influencing factors， limited sample series， and significant demand fluctuations in Jiangsu Province， we coupled the K-S normal interval estimation with particle swarm optimization （PSO） and BP neural network. Specific processes are as follows： the degree of influence and the number of key factors were preliminarily identified through principal component analysis （PCA）， followed by the calculation of grey relational grades （GRG） to determine the final water demand influencing factor index. This index was utilized as input for both BP and PSO-BP neural networks. The final model was then selected by comparing performance indicators， including relative error， Nash-Sutcliffe efficiency （NSE）， and coefficient of determination （R²）. Using multiple fitting iterations of the PSO-BP neural network， the sample size was expanded， and the K-S normality test and normal interval estimation were performed to further narrow the relative error intervals of the water demand prediction results. [Results] 1） Eight primary influencing factors of water demand were identified for Jiangsu Province： population， GDP， added value of secondary industry， added value of tertiary industry， per capita urban domestic water consumption， per capita rural domestic water consumption， irrigation water quota per mu （1 mu≈666.7 m²）， and water consumption per 10 000 yuan of industrial added value. 2） Both BP and PSO-BP neural networks exhibited strong performance in fitting historical water demand data， demonstrating their feasibility for future water demand prediction. Specifically， the PSO-BP neural network outperformed the standard BP network in the relative error of water demand prediction. The maximum relative errors for the training， validation， and testing samples were 2.23%， 0.88%， and 1.19%， respectively， with an average training error of 1.03%. The NSE and R² reached 0.98 and 0.99， respectively. 3） The selection of sample size significantly influenced the prediction results of water demand. With the increase of the sample size， the average value of samples was closer to the real value， and the overall prediction results of samples were more stable. The increase of sample size would reduce the benefit of improving the accuracy of the overall prediction results. 4） The K-S normality test and normal interval estimation stabilized the prediction results， substantially narrowed the error intervals， and better reflected the actual water demand. At a 95% confidence level， the relative error intervals of water demand prediction in 2021， 2022， and 2023 in Jiangsu Province were reduced to -0.23%-0.09%， -0.28%-0.01%， and -0.28%-0.02%， respectively. [Conclusion] The KS-PSO-BP neural network coupled model significantly reduces the error range and provides more stable and accurate prediction results that closely align with actual water demand in Jiangsu Province. The model serves as an effective method for regional water demand prediction and offers valuable guidance for future water resources planning in Jiangsu Province.

[Objective] This study aims to clarify the driving mechanisms and spatiotemporal propagation characteristics of water level fluctuations in the river section about 40 km downstream of the Wudongde hydropower station during its operation. The primary objectives are to： （1） quantify the dual impacts of unsteady flow from the hydropower station and the backwater effect from the downstream Baihetan Reservoir； （2） reveal the spatial attenuation patterns of water level variation； and （3） propose safety thresholds for water level variation in navigable waters. [Methods] Twelve high-frequency water level monitoring stations （SD1-SD12） were deployed along the river section 40 km downstream of the dam， and water level data were collected at 5-minute intervals. Four intensive monitoring activities were conducted， covering key operational periods including the impoundment period， drawdown period， flood season， and low-water level operation of the Baihetan Reservoir. The correlations among flow variation from the Wudongde hydropower station， water level of the Baihetan Reservoir， and downstream water level variation were quantified using statistical methods， including linear regression and correlation analysis. In addition， the spatial gradients and temporal attenuation of daily and hourly water level variation were calculated and analyzed. [Results] 1） The water level fluctuations downstream of the Wudongde Dam exhibited a bidirectional coupled driving mechanism， consisting of unsteady flow and reservoir backwater effects. In the near-dam reach （0-15 km）， the station’s flow was the primary driver of water level variation， with the water level response coefficient remaining stable at 0.12-0.15 m per 100 m³/s （R²>0.99）. Conversely， the far-dam reach （> 35 km） was dominated by the water level of the Baihetan Reservoir， exhibiting slow-varying， reservoir-controlled behavior with relatively stable water levels. 2） Downstream water level fluctuations exhibited a three-stage attenuation pattern. In the near-dam reach （0-15 km）， water level variation decreased rapidly， with a maximum daily attenuation rate of 0.41‰， and was strongly correlated with flow fluctuations （R²=0.85）. In the transition zone （15-35 km）， the interaction of nonlinear waves increased the variability of the attenuation rate （0.02‰-0.31‰ per day）， leading to a sharp weakening or disappearance of the correlation with flow. In the far-dam reach （>35 km）， the backwater effects of the Baihetan Reservoir stabilized water levels. 3） Water level regulation at the Baihetan Reservoir exerted a dampening effect on wave peak propagation. For every 10 m decrease in reservoir water level， the propagation distance of the flow peak increased by an average of 2.3 km （R²=0.96）. The nighttime flow peak at the Wudongde Dam occurred between 16：00 and 24：00， and flow levels exceeded daytime peaks by more than 40%. When the daily and hourly flow variations at Wudongde exceeded 5 000 m³/s and 1 500 m³/s， respectively， the resulting water level variation （3.2 m/d and 1.2 m/h） exceeded the shipping safety thresholds （3.0 m/d and 1.0 m/h）. [Conclusion] Downstream water level fluctuations are governed by a bidirectional coupled mechanism of unsteady flow and reservoir backwater effects， and exhibit a distinct three-stage attenuation pattern. This study identified the nonlinear superposition phenomenon in the transition zone （15-35 km） for the first time based on prototype observations， revealing that opposing wave phases （flow waves and backwater waves） generated complex peak interference effects. Furthermore， navigation safety thresholds are determined， and a “spatiotemporal peak-staggering” management strategy is proposed. This strategy involves dynamic zoning control， such as restricting navigation in the high-risk near-dam reach （0-15 km， SD1-SD4） during the peak period of 16：00-24：00.

[Objective] This study aims to investigate the differentiated effects of various driving factors on the stage-specific characteristics of hydrological drought in the Jitai Basin under the influence of climate change and intensive human activities. [Methods] We collected meteorological and hydrological data from 1959 to 2023 from three typical watersheds (the Shushui, Wujiang, and Tongjiang Rivers) in the Jitai Basin, and adopted the Pettitt test to divide the study period into a baseline period, a transition period, and a change period. By using the improved two-parameter monthly water balance model, we analyzed the drought characteristics and the quantitative effects of driving factors in each stage, and clarified the dominant role of different driving factors as well as their nonlinear regulation mechanisms. [Results] 1) The runoff generation mechanisms of the three typical watersheds shifted around 1980 and 2008. Specifically, in baseline period (1959-1980), the underlying surface conditions of the watersheds were relatively stable, hydrological processes were dominated by natural climate drivers, and runoff variations were directly controlled by the precipitation-evaporation balance, with no obvious disturbance from human activities. In transition period (1981-2008 ), the intensifying regional human activities began to alter the original runoff generation mechanisms of the watersheds. In the change period (2009-2023), underlying surface modification and water conservancy project regulation became dominant factors. The runoff coefficient α increased significantly in transition period and then declined in the change period, which also indicated that the regulatory intensity of human activities on runoff exceeded natural fluctuations. In terms of drought characteristic variations, drought severity and duration decreased notably in the transition period compared with the baseline period, but rebounded in the change period; the average drought severity of the three typical watersheds increased by 46.2%, 26.9% and 25.9% respectively relative to the transition period. 2) By introducing a regulating coefficient of parameter C during wet and dry periods, the improved two-parameter monthly water balance model effectively improved the overall simulation accuracy of runoff series, especially for low-flow and drought months. The Nash-Sutcliffe efficiency coefficient (NSE) was higher than 0.7 and the correlation coefficient R exceeded 0.85 in both the baseline and transition periods, with the water balance error controlled within ±1%. In the change period, the measured runoff series was heavily disturbed by human activities, which increased the difficulty of simulating monthly-scale runoff series. Parameter calibration results showed that the value of C for each typical watershed in transition period was lower than that in baseline period, but rebounded in the change period, reflecting regular variations in the precipitation-evaporation relationship of the watersheds across different stages. High temperature and low rainfall in summer and autumn were critical driving factors of hydrological drought in the Jitai Basin, with strong sensitivity to drought severity. A 10% reduction in precipitation during this period led to an increase of 0.14-0.23 in drought severity, accompanied by a marginally diminishing effect. Nevertheless, compared with the baseline period, human activities played a dominant role in the change period, causing greater variations in runoff depth and drought severity than climate change factors. [Conclusion] The multi-stage quantitative method for driving factors constructed in this study reveals the nonlinear regulatory effects of climate change and human activities on hydrological drought severity in the Jitai Basin at different stages, clarifies the influence intensity, sensitivity and stage characteristics of each driving factor, and identifies the nonlinear regulation of these factors on drought severity.

[Objective] The operation of cascade reservoirs in the lower reaches of Jinsha River has significantly altered the inflow flood characteristics of the Three Gorges Reservoir (TGR), posing new requirements for the adaptability of existing flood control scheduling. This study aims to reveal changes in inflow flood processes and flood propagation characteristics within the TGR after the impoundment of cascade reservoirs in the lower reaches of Jinsha River, providing a theoretical basis and data support for scientific flood control scheduling of the reservoir. [Methods] Based on the measured hydrological and topographic data of the TGR from 2003 to 2020, mathematical statistical methods were employed to analyze changes in inflow flood characteristics before and after the impoundment of cascade reservoirs. A one-dimensional hydrodynamic model was adopted. After calibration and validation, multiple comparative scenarios were designed to conduct simulation and analysis of flood peak propagation processes in the TGR area. [Results] Statistical analysis of the measured data showed that around 2013, the average inflow flood volume of the TGR decreased by approximately 9.9%, while the rising and falling durations decreased by 4.9% and 9.9%, respectively, and the average rising and falling rates increased by 10.3% and 9.8%, respectively. These results indicated that the flood recession became faster, the flood peaks occurred earlier, the average peak discharge decreased, and the risk of extreme floods increased. The mathematical model results showed that, in terms of discharge characteristics, the flood peak propagation time was positively correlated with the flood peak discharge, while the influence of changes in baseflow was not significant. In terms of hydrograph shape, the flood peak propagation time was negatively correlated with the rising duration and positively correlated with the falling duration. In terms of boundary conditions, the flood peak propagation time was negatively correlated with the water level upstream of the dam. [Conclusion] The operation of cascade reservoirs significantly reduces inflow flood peak, and the attenuation effect on the flood hydrograph also leads to a significant increase in flood duration. The flood peak propagation is faster under conditions of lower peak discharge, longer rising duration, shorter falling duration, and higher water level upstream of the dam.

[Objective] The Hanjiang River Basin, as the core water source area of the Middle Route of the South-to-North Water Diversion Project, has runoff variations that are of great significance to water supply security and regional sustainable development. This study aims to identify the main driving factors of runoff evolution in the upper, middle, and lower reaches of the Hanjiang River Basin. By following the framework of “pattern identification-hydrological modeling-attribution analysis of runoff changes,” this study quantitatively and qualitatively assesses the impacts of climate change and human activities on runoff variations, thereby providing a scientific basis for rational water resources utilization and management decisions in the river basin. [Methods] Statistical methods, including linear regression, moving average, rescaled range (R/S) analysis, cumulative anomaly, Mann-Kendall trend test, and sliding t-test, were employed to identify the evolution patterns of hydrological elements. A distributed Xin’anjiang model was constructed to simulate and reconstruct natural runoff, and the contribution rates of climate change and human activities to runoff changes were quantified. [Results] The results showed that from 1959 to 2019, precipitation in the upper reaches exhibited a decreasing trend at a rate of -0.59 mm/a, whereas precipitation in the middle and lower reaches showed increasing trends at rates of 0.24 mm/a and 0.05 mm/a, respectively. Temperature differences among the three reaches were minimal. Runoff exhibited significant interannual variability, with an abrupt change occurring in 1990. The decline in runoff at the Xiantao station in the lower reaches was significantly larger than that at the Huangjiagang station in the middle reaches and the Shiquan station in the upper reaches. Climate change contributed to a reduction in runoff at Shiquan station by 75.97 mm, accounting for 59.98% of the total change. Human activities led to runoff reductions of 83.32 mm at Huangjiagang station and 78.45 mm at Xiantao station, with contribution rates of 54.89% and 77.20%, respectively. [Conclusion] The impact of human activities on runoff evolution is gradually intensifying and becomes more pronounced in the downstream areas. The upper reaches, characterized by higher elevation and dominated by forest and grassland with relatively limited human activities, experience a smaller degree of anthropogenic influence. In the middle reaches, higher population density and economic development drive greater water demand, while regulated water transfer from hydraulic engineering has led to an overall decline in runoff. In the lower reaches, intensive human modifications to the underlying surface, frequent human activities, high water demand, and large-scale regulated water transfers collectively result in a significant reduction in runoff. The findings of this study provide valuable insights for water resources development, utilization, and watershed planning in the Hanjiang River Basin.

[Objective] Although artificial intelligence-based water level forecasting methods have achieved promising results in predicting upstream water levels at various power stations, including the Three Gorges Reservoir, there remains room for improvement. To obtain more accurate water level predictions for the Three Gorges Reservoir, this study develops an ultra-short-term forecasting model with a 15-minute time scale based on deep learning techniques, providing enhanced technical support for real-time reservoir operation. [Methods] The dataset comprises four categories: (1) water level data from the Three Gorges Reservoir and downstream areas; (2) inflow and spillage flow rates of the Three Gorges; (3) total power output of the Three Gorges power plant; and (4) precipitation between Cuntan and the Three Gorges area. Four water level forecasting models, including a baseline model and three comparative models, were developed to predict water level changes over the next 24 hours. Each model was constructed using both LSTM and RNN neural networks. The primary distinctions among these models lie in the processing of input and output data as well as the temporal scales of the data. By comparing the performance of different models under varying conditions, we analyze how model configurations impact prediction accuracy. [Results and Conclusion] (1) Regardless of input conditions, water level forecasting models built with LSTM outperform those using RNN, achieving Mean Absolute Errors (MAE) of 3.58 to 4.40 cm and maximum absolute errors of 56.99 to 110.03 cm. (2) All four water level forecasting models constructed using LSTM exhibit good performance, with the best-performing model incorporating dynamic reservoir capacity and interval rainfall impacts, achieving an MAE of 3.58 cm and a maximum absolute error of 56.99 cm. (3) Differences in model input variables are the dominant factor affecting forecast accuracy across various conditions. Incorporating reservoir water level information allows the model to better account for dynamic reservoir capacity effects, while adding interval rainfall data provides more precise inflow estimates, significantly enhancing prediction accuracy. This approach reduces the MAE by 18.64% compared to the baseline model. This study demonstrates that integrating relevant hydrological and meteorological factors into LSTM-based models can substantially improve the precision of short-term water level forecasts, thereby supporting effective reservoir management.

[Objective] To safeguard freshwater intake security in the Yangtze River Estuary against frequent saltwater intrusion, this study aims to identify an optimal freshwater replenishment scheme that balances saltwater suppression effectiveness with water resource utilization efficiency. [Methods] To address extreme saltwater intrusion resulting from the combined effects of low runoff and strong tidal dynamics, a two-dimensional coupled hydrodynamic and salinity transport model was developed. Numerical scenarios incorporating various replenishment discharges and durations were designed based on actual dispatch strategies. Key evaluation indicators included the spatiotemporal distribution of salinity isolines and the duration of the available water intake window. The effectiveness of saltwater suppression was comprehensively evaluated by quantifying the variations in environmental responses under different replenishment strategies. [Results] Simulation results indicated that, influenced by the complex topography of the Yangtze River Estuary, the spatial distribution of replenishment effects exhibited non-uniform characteristics. Under cascade replenishment schemes, the seaward retreat rate of salinity isohalines was approximately 1.52-1.59 km/(500 m³/s) in the North Channel and 1.75-1.92 km/(500 m³/s) in the South Channel. Salinity levels at the intakes of Chenhang Reservoir and Qingcaosha Reservoir showed an overall decreasing trend, with decay rates of approximately 0.03‰/(500 m³/s) and 0.05‰/(500 m³/s), respectively. Intake salinity exhibited an approximately linear relationship with replenishment discharge, with the Qingcaosha Reservoir demonstrating a relatively higher degree of responsiveness. In contrast, the relationship between the available water intake window and the replenishment duration was non-linear, exhibiting characteristics of marginal utility. The findings suggested that maintaining a replenishment discharge of approximately 9 900 m³/s might provide strong assurance for water intake, while a replenishment duration of around 13 days was likely to achieve optimal benefits. Furthermore, strong offshore winds tended to amplify frontal saltwater intrusion in the North Channel. [Conclusion] Increasing discharge from the Three Gorges Reservoir effectively suppresses saltwater intrusion and contributes positively to mitigating salinity hazards in the Yangtze River Estuary. However, replenishment performance is constrained by multiple factors, including the replenishment mechanisms and offshore wind fields. Optimization of replenishment strategies should consider both discharge magnitude and duration, as prolonged duration does not necessarily result in proportional benefits. Moreover, compared with the North Branch and South Channel, replenishment effects in the North Channel and at Qingcaosha Reservoir are more susceptible to wind field influences. These findings provide technical support for decision-making on water replenishment scheduling during extreme dry seasons.

[Objective] As a region characterized by extensive permafrost, the Qinghai-Xizang Plateau has undergone significant environmental changes under global climate change. Surface water dynamics serve as sensitive indicators of permafrost degradation. This study investigates surface water changes over the past 30 years in a typical permafrost degradation area of the eastern Qinghai-Xizang Plateau, distinguishes variations between permafrost and seasonally frozen ground zones, and analyzes their relationships with temperature and precipitation. [Methods] Landsat 5 and Landsat 8 satellite images from 1995 to 2024 (August data only) were processed using Google Earth Engine (GEE) to remove clouds and high-reflectance interference through median-pixel compositing. An empirical annual mean ground temperature model, corrected for slope and aspect, was applied to classify permafrost and seasonally frozen ground zones. Surface water bodies were extracted using the Normalized Difference Water Index (NDWI) with an Otsu global-local thresholding method. The results were further refined using slope and hillshade data derived from the ASTER Global Digital Elevation Model (GDEM). Surface water bodies were classified by area into four categories: ≤0.001,(0.001,0.01],(0.01,1],and (1,100] km². Monthly temperature and precipitation data from local meteorological stations were used to analyze correlations with water body metrics. [Results] Permafrost and seasonally frozen ground zones accounted for approximately 63% and 37% of the study area, respectively, with a classification accuracy of 88.1% as confirmed by field surveys. Between 1995 and 2024, the total number of water bodies increased by 40%, mainly driven by small water bodies (≤0.01 km²), while the total water surface area expanded by 29%, dominated by large water bodies ((1,100] km²). In permafrost zones, the number of water bodies increased by 85%, primarily due to small water bodies formed by thaw-induced subsidence, whereas the area increased by 28%. Seasonally frozen ground zones showed a moderate 16% increase in the total number of water bodies and a 28% increase in area, largely attributable to larger water bodies. Correlation analysis revealed significant positive relationships between temperature and water body metrics (r>0.75), with smaller water bodies exhibiting the highest temperature sensitivity. Conversely, precipitation generally had weak or negative correlations with water dynamics, particularly in permafrost zones, where heavy rainfall often promoted drainage and lake outflow. Seasonally frozen ground zones showed limited sensitivity to precipitation due to higher infiltration rates. [Conclusion] Rising temperatures primarily drive the expansion of surface water, exceeding the effects of precipitation. Permafrost zones are highly sensitive to warming, as indicated by rapid increases in small water bodies, whereas seasonally frozen ground zones maintain stable water body counts with area expansion driven by larger lakes. Precipitation plays a secondary or even negative role in water dynamics. The distinct responses of water bodies under different freeze-thaw conditions highlight the complexity of hydrological changes driven by climate warming, providing crucial insights for future environmental predictions and resource management on the Qinghai-Xizang Plateau.

[Objective] As the core water source area of the Middle Route of the South-to-North Water Diversion Project, runoff variations in the Danjiang River Basin directly influence water transfer capacity and source water security. Current research primarily relies on manually defined meteorological parameters, limiting scenario diversity and resulting in an insufficient scientific basis, yet studies on future runoff evolution remain scarce. This study aims to analyze the impact of future climate change on runoff in the Danjiang River Basin to provide a scientific basis for water resource management and the operation of the South-to-North Water Diversion Project. [Methods] This study first used the CN05.1 meteorological dataset and observed daily runoff data to construct and calibrate a SWAT hydrological model, simulated runoff variations during the historical period, and verified the model accuracy. On this basis, future meteorological data from six high-performing global climate models (GCMs) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were bias-corrected using the Delta method to better represent the climatic characteristics of the Danjiang River Basin. Meanwhile, the PLUS model was applied to simulate two land use change scenarios to reflect potential future land use dynamics. The bias-corrected climate data were then combined with different land use scenarios and input into the SWAT model to simulate the spatiotemporal evolution of future runoff. [Results] (1) The SWAT model demonstrated excellent performance in simulating monthly streamflow at Jingziguan and Danfeng stations, with R² values exceeding 0.9 and NSE values above 0.8. The GCMs accurately captured the evolution patterns of temperature extremes and precipitation in the region, with correlation coefficients exceeding 0.85 for temperature and 0.7 for precipitation. (2) In the future, both temperature and precipitation in the Danjiang River Basin were projected to increase. Across all scenarios, temperature increases followed the pattern: late period>mid period>near period, with the most pronounced change under the high carbon scenario, where the late-period temperature rise reached 7.11 ℃, 2.72 times that under the low carbon scenario. Precipitation generally showed a continuous upward trend, with the largest increase (11.63%) under the low carbon scenario. The fastest increase occurred in summer, while winter precipitation under the low carbon scenario increased by 10.38%. (3) Runoff in the Danjiang River Basin exhibited significant spatiotemporal variability. The annual average runoff shifted from a decrease in the near period to an increase in the far period. Seasonal variations indicated significant increases in spring and winter, and decreases in summer and autumn, with the most pronounced increases in January and December and the most notable decreases in July and September. Spatially, downstream runoff increased markedly, with widespread growth in the mid to far period under the low carbon scenario, and prolonged decreases under the high carbon scenario. [Conclusion] (1) In the near term, the annual average runoff shows a downward trend with frequent fluctuations. Under the medium carbon scenario, the maximum annual runoff reduction reaches 25.32%. The high carbon scenario exhibits 16 abrupt changes during the study period without stable recovery, resulting in coexisting risks of extreme floods and droughts due to long-term runoff variability. (2) In the mid to long term, runoff generally recovers, although significant differences remain among scenarios. Under the low and medium carbon scenarios, runoff increases by up to 20.34%, which supports water supply security for the South-to-North Water Diversion Middle Route Project and meets the water demand of the basin’s ecosystems. In contrast, under the high carbon scenario, runoff increases by less than 1.00%, and supply risks persist. (3) The low carbon scenario is most favorable for the long-term development of the basin, while the high carbon scenario poses the greatest risks. Runoff recovery occurs earliest under the low carbon scenario, ensuring ecological water demand and water security. By contrast, under the high carbon scenario, recovery is slow, and fluctuations are frequent, increasing the probability of extreme droughts or floods.

[Objective] This study aims to scientifically recognize and evaluate the equilibrium of domestic, ecological, and production water use in Yangtze River Basin from the perspectives of water and soil spatial matching and differences in per capita water use. [Methods] The Gini coefficient and Lorenz asymmetry coefficient were used to analyze the disequilibrium of water use and its sources. Furthermore, the matching degree index was used to analyze the matching degree between water use, regional area, and population. [Results] The water usage per unit area in Yangtze River Basin was 92.7 mm, and the per capita water use was 1 194.0 L/d. Among these, production water use was the highest, followed by domestic water use, while ecological water replenishment was the lowest. Analysis based on water use per unit area and per capita water use showed that, overall, water use was higher in the eastern region, followed by the central region, and lower in the western region. Based on the administrative divisions, Yangtze River Basin was divided into 18 sub-regions according to provincial administrative boundaries. The Gini coefficients and Lorenz asymmetry coefficients for domestic, ecological, production, and total water use in Yangtze River Basin were calculated from the perspectives of water and soil spatial matching and differences in per capita water use. The Gini coefficients for the spatial distribution of domestic, ecological, production, and total water use in Yangtze River Basin were 0.42, 0.53, 0.51, and 0.49, respectively. The Gini coefficients for per capita water use were 0.10, 0.37, 0.25, and 0.21, respectively. Further analysis using matching degree index to evaluate the matching degree between water use, regional area, and population revealed that the matching degrees for domestic, ecological, production, and total water use with regional area were 0.83, 0.80, 0.81, and 0.81, respectively, and with population were 0.97, 0.90, 0.92, and 0.93, respectively. [Conclusion] Differences in water use are constrained by the inherent endowment of water resources, and the uneven spatial distribution of water resources directly leads to the disequilibrium in water use. The spatial distribution of domestic, ecological, production, and total water use in Yangtze River Basin exhibits disequilibrium, while per capita water use is relatively balanced, with a high degree of matching between water use, regional area, and population. Water resource management must balance “people-oriented” and “spatial equity” principles, coordinating domestic, ecological, and production water use through technological advancements and institutional innovations to reduce disparities in water use per unit area and per capita water use. The research findings can provide important support for the rational utilization of water resources and the realization of human-water harmony.

[Objective] This paper aims to reveal the hydrological evolution patterns of transboundary rivers on the western Yunnan Plateau (the Lancang River, Nu River, and Irrawaddy River) during 1956-2016, to quantify the spatial differentiation characteristics of changes in water resources in the three major river systems, and to establish a water quantity prediction method based on multi-scale periodic analysis. [Methods] Based on precipitation and runoff data of the three major river systems in Southwest China from 1956 to 2016, the Mann-Kendall trend test method was used to analyze the long-term variation trends of hydrological elements. The Morlet wavelet analysis method was applied to identify the multi-scale periodic characteristics of hydrological sequences, and the phase extrapolation method was employed to predict future water quantity variation trends. [Results] The water yield modulus of the study area reached 78.83×10⁴ m³/km²; however, all three river systems exhibited significant decreasing trends. Among them, the attenuation rate of the Irrawaddy River (-0.175×10⁸ m³/a) was significantly higher than that of the Lancang River (-0.024×10⁸ m³/a). A dominant 24-year hydrological variation period was identified at the regional scale, and the year 2016 was located at the end of the low-frequency phase of this cycle. Combined with phase extrapolation, the results indicated that future water quantity may continue to remain relatively low. The Lancang River exhibited secondary periodic oscillations of 7-12 years, which differed from the single dominant periodic pattern observed in the Nu River and the Irrawaddy River, revealing the hydrological response heterogeneity of the Lancang River caused by its specific underlying surface conditions. Precipitation showed a significant correlation with water resources (R²>0.75); however, asynchronous characteristics were observed in the Lancang River due to its specific underlying surface conditions. [Conclusion] This study systematically quantifies the spatial differentiation characteristics of hydrological evolution in the Lancang River, Nu River, and Irrawaddy River systems, establishes a water quantity prediction method based on multi-scale periodic analysis, and further reveals the secondary periodic oscillation characteristics of the Lancang River and its differences from the Nu River and Irrawaddy River, providing new scientific evidence for transboundary river water resources management in Southwest China. The results indicate that water resources of transboundary rivers on the western Yunnan Plateau may show a persistently low trend in the future, highlighting the need to strengthen transboundary water resources coordination and to formulate adaptive water resources allocation strategies.

[Objective] This study aims to address the issues of uneven spatiotemporal distribution of water resources and the difficulty in developing integrated urban-rural water supply in mountainous cities. Based on the connotation of integrated urban-rural water supply and the characteristics of its different development modes, this study innovatively constructs a coupling coordination evaluation indicator system and a zoning model for integrated urban-rural water supply. Taking the typical mountainous city of Chongqing as a case study, water supply zoning patterns with distinct regional characteristics are identified, and differentiated development schemes for urban-rural water supply are proposed. [Methods] Eight indicators were selected from three dimensions—current status of rural water supply engineering systems, natural geographical conditions, and socio-economic development. An “engineering-natural-economic” coupling coordination evaluation indicator system for integrated urban-rural water supply was constructed, and the Delphi method was used to determine the indicator weights. Considering the mutual constraints and synergistic effects among the three subsystems, a coupling zoning model for integrated urban-rural water supply was constructed. [Results] (1) The coupling coordination degree of each district and county ranged from 0.245 to 0.877. The coupling coordination degree intervals for the urban pipeline extension mode, regional pipeline interconnection mode, regional integrated block mode, and single-village upgraded point mode were [0.8, 1], [0.75, 0.80), [0.60, 0.75), and (0, 0.60), respectively. (2) All eight districts and counties under the urban pipeline extension mode were located in the main metropolitan area. These areas had relatively flat terrain and high population density, which was conducive to the construction of large-scale water supply projects and pipeline networks. Eight districts and counties under the regional pipeline interconnection mode were mostly located in the main metropolitan area, with a small number in the Three Gorges Reservoir area of northeastern Chongqing. These areas had abundant but unevenly distributed water resources. Interconnection of regional main water supply pipelines could achieve regional water resource complementarity and pipeline network connectivity. Five districts and counties under the regional integrated block mode were distributed in the main metropolitan area and the Three Gorges Reservoir area of northeastern Chongqing. In northeastern Chongqing, small reservoirs and ponds served as the main water sources, and the scale of water supply projects was small but had integration potential. Integrating surrounding small water supply projects could enhance regional water supply security. Thirteen districts and counties under the single-village upgraded point mode were mainly located in the Three Gorges Reservoir area of northeastern Chongqing and the Wuling Mountain area of southeastern Chongqing. Due to the large terrain relief in mountainous areas, water supply projects were significantly constrained by terrain. Rural areas were remote with dispersed population, making it difficult for large-scale water supply to cover them. This mode was suitable for point-based water supply targeting individual villages. [Conclusion] (1) Four development modes suitable for integrated urban-rural water supply in Chongqing City are proposed, namely the urban pipeline extension mode, regional pipeline interconnection mode, regional integrated block mode, and single-village upgraded point mode. (2) According to the zoning results, the urban pipeline extension mode relies on its high urbanization rate to achieve full water supply coverage. The regional pipeline interconnection mode addresses elevation difference issues through interconnected pipeline networks, the regional integrated block mode forms intensive water supply units by integrating small water sources, and the single-village upgraded point mode solves drinking water problems in areas with complex terrain through decentralized water supply. The research findings provide technical support for the construction of integrated urban-rural water supply in Chongqing City and are of significant importance for ensuring regional water supply security and promoting the high-quality development of the Chengdu-Chongqing Twin-City Economic Circle.

[Objective] This study aims to develop a comprehensive diagnostic method for evaluating the water balance status across water resources, ecosystems, and socio-economic systems in the context of large-scale water management projects. The focus is on the potential water source areas of the West Route of South-to-North Water Diversion Project, analyzing the interactions between natural water balances, socio-economic demands, and ecological considerations. [Methods] The research centered on quantifying and assessing the coordination and sustainability of these systems in the West Route’s water source region from 2005 to 2020. An analytical framework based on the principles of water balance was constructed, incorporating four key components: natural water supply and demand, socio-economic water needs, ecological water consumption, and the competition between ecological and socio-economic systems within the river basin. This framework was used to quantify the water balance status by evaluating water availability, ecological functioning, and socio-economic demands over the study period. Statistical methods and multidimensional analysis were applied to calculate the coupling coordination degree, which measures the extent of coordination between water resource management, ecological protection, and socio-economic development. The study relied on regional hydrological records, socio-economic data, and ecological assessments to ensure robust and reliable results. [Results] From 2005 to 2020, the water balance of the West Route’s water source areas remained relatively stable. Importantly, the region maintained a steady equilibrium in water resources, with significant improvements in the coordination between water resources, socio-economic development, and ecological systems. The coupling coordination degree among these three systems showed a clear upward trend, reflecting the growing harmony between water management, ecological conservation, and socio-economic growth. The research highlighted that the ecological system within the water source areas effectively adapted to changes in water availability, demonstrating resilience in sustaining water use. Moreover, there was a substantial positive synergy between water resource management and ecological protection, which contributed to the stability and improvement of the regional water balance. Additionally, the study showed that the competition between ecological and socio-economic water demands became more balanced, shifting toward a more integrated approach. The region’s ecological protection strategies became better aligned with water resource management policies, resulting in improved sustainability in both ecological and economic terms. [Conclusion] The findings suggest that enhanced water use efficiency, combined with adaptive ecological protection measures, has played a pivotal role in achieving these positive trends. The study’s innovative approach—integrating natural water balance, socio-economic factors, and ecological needs—provides a comprehensive framework for evaluating the sustainability of water resources in large-scale inter-basin water diversion projects. The findings demonstrate that coupling water resource management with ecological protection is not only feasible but essential for ensuring the long-term sustainability of water source areas. In conclusion, this study underscores the importance of adopting an integrated approach to water resource management, one that recognizes the interdependencies between natural, economic, and ecological systems. The research highlights that coordinated water management, paired with adaptive ecological conservation strategies, is critical to achieving sustainable development and ensuring the resilience of water source areas in large-scale water transfer projects. Furthermore, the study suggests that such integrated management models can serve as a blueprint for other regions facing similar water resource and environmental challenges, ultimately supporting the global pursuit of water sustainability.

[Objective] In recent years, excessive exploitation of groundwater resources has led to severe depletion of water resources in the Dusitu River Basin, limiting the healthy development of the local ecological environment and economy. Therefore, accurately acquiring the long-term spatiotemporal change characteristics of water storage is crucial for the sustainable utilization of water resources. [Methods] This study employed the Bayesian three-cornered hat method to integrate three GRACE Mascon products, combined with the soil water and snow water components simulated by the GLDAS model, to generate high-precision groundwater storage change results for the Dusitu River Basin. The results were validated for accuracy using measured groundwater level data from 2018 to 2021 and the water body area of Bulong Lake extracted from satellite remote sensing. The cross wavelet transform method was further introduced to analyze the synergistic effects of precipitation, temperature, and evapotranspiration factors on groundwater storage changes in the time-frequency domain. [Results] From 2003 to 2021, terrestrial water storage and groundwater storage in the Dusitu River Basin decreased significantly at rates of -6.71 mm/a and -7.88 mm/a, respectively. Spatially, the groundwater depletion trend intensified from west to east, with the declining rate increasing from -5.71 mm/a to -9.31 mm/a. After 2018, groundwater depletion accelerated, with the decline rate increasing from -7.37 mm/a to -9.52 mm/a. The trends and seasonal characteristics of measured groundwater levels were consistent with GRACE results, with an average correlation coefficient of 0.56. The area of Bulong Lake continuously decreased at a rate of approximately -2 698 m²/a, showing significant seasonal fluctuations, which was largely consistent with the trends of groundwater storage changes in the river basin. Cross wavelet analysis showed that precipitation and groundwater storage were significantly positively correlated at the 1-month scale, while temperature and evapotranspiration were significantly negatively correlated. [Conclusion] This study significantly improves the inversion accuracy of water storage changes through multi-source GRACE data fusion, clarifies the severe reality of continuous and intensifying groundwater over-exploitation in the Dusitu River Basin, and highlights regional water resources and ecological pressures. Furthermore, precipitation is the main source of groundwater recharge, while temperature and evapotranspiration exacerbate its consumption. The research findings provide reliable technical methods and data support for water resource management in the river basin.

The Three Gorges Reservoir (TGR) is located in the transitional zone between the upper and middle reaches of the mainstream Yangtze River and has strong storage regulation capacity. Since its operation, it has achieved significant comprehensive benefits and has played a prominent role in flood control, power generation, navigation, and water resources utilization in the basin. With the successive completion and operation of several giant reservoirs in the upper reaches of the Yangtze River and the in-depth implementation of the national high-quality development strategy, the operation of the TGR is facing a more complex hydrometeorological environment and higher multi-objective requirements. Meanwhile, the construction and operation of the upstream reservoir system have significantly altered the inflow and sediment regime of the TGR, increasing the complexity of its operation and regulation. This paper reviews the status and comprehensive utilization demands of water resources of the TGR, summarizes the achievements of water resources utilization optimization and operation practices over the years, and analyzes the comprehensive utilization benefits of water resources from the aspects of flood control, power generation, navigation, ecology, and water resources utilization. By integrating medium- and long-term hydrological forecasting results, promoting potential exploitation and efficiency enhancement of the TGR is an inevitable approach to further improving the comprehensive utilization benefits of water resources. Under the new requirements of adhering to the simultaneous prevention and control of droughts and floods and strengthening cross-regional allocation and regulation of water resources between wet and dry conditions, measures are proposed to further tap the potential and enhance efficiency of the TGR, including accelerating the construction of the “three lines of defense” for rainfall and flood monitoring and forecasting, strengthening research on the unified joint operation of key reservoir systems in the Yangtze River basin under extreme inflow conditions, and promoting the development of the Digital Twin Three Gorges system.

[Objective] Numerous influencing factors contribute to the imbalance between the calculated inflow and outflow discharges in the reach between the Three Gorges and Gezhouba Dams. Analyzing the significance of individual influencing factors and identifying the key drivers underlying this imbalance are of considerable importance for formulating power generation plans and conducting hydrological analysis of the Three Gorges-Gezhouba cascade hydropower stations. [Methods] Historical records of discharge and power output in the Three Gorges Reservoir Area were collected from 2018 to 2023. Based on the calculation logic of inflow and outflow discharges, 19 potential influencing factors that may affect the inflow-outflow imbalance in the reach between the two dams were selected. Grey relational analysis (GRA) and random forest (RF) model were employed to identify the key factors contributing to the inflow-outflow discharge imbalance between the Three Gorges and Gezhouba Dams. [Results] The results of GRA showed that the grey relational grade of the total power generation discharge of the Gezhouba Dam reached 0.696, ranking first. The grey correlation degree of the power generation flow of the Three Gorges Dam was 0.695, ranking second. The grey correlation degrees of the total active power of Gezhouba Dam, the total power generation flow of the Three Gorges Dam, and the total active power of the Three Gorges Dam were 0.661, 0.651, and 0.636, respectively, ranking third, fourth, and fifth. For RF model, two methods—rank assignment summation and normalization summation—were adopted to integrate the two indicators, namely %IncMSE (percentage increase in mean squared error) and IncNodePurity (increase in node purity). The results indicated that in both methods, the total power generation discharge of the Gezhouba Dam and the storage-release discharge of the Gezhouba Dam ranked first and second, respectively, in terms of importance. Specifically, the normalization summation method not only reflected the importance ranking of different influencing factors, but also demonstrated that the relative importance of each factor through specific indicator values. Among these factors, the total power generation discharge of the Gezhouba Dam scored the highest (1.25), followed by its storage-release discharge (1.22). In contrast, the total power generation discharge of the Three Gorges Hydropower Station, which ranked third, had a significantly lower score (0.61) than the storage-release discharge of the Gezhouba Dam, which ranked second. [Conclusion] The total power generation discharge of Gezhouba Dam is the key influencing factor causing the inflow-outflow discharge imbalance. This is mainly attributed to the following reasons: 1) the Gezhouba Dam launched its capacity expansion and renovation project in 2013, with the total installed capacity of its 19 generating units increasing by 475 000 kilowatts. However, the NHQ curve adopted for calculating the power generation discharge of the units still remains the original factory curve without any updates, which leads to calculation errors in power generation discharge. 2) The head loss of the Gezhouba Dam is derived from the calculation based on the inflow discharge, instead of being accurately determined for each individual unit, and this calculation method will also induce certain errors. 3) Due to the complex flow conditions in front of the Gezhouba Dam, there are often differences in water head between the left and right banks. Nevertheless, water-head data from a single monitoring station are applied uniformly in power generation discharge calculations, which may further contribute to calculation errors.