[Objective] This study aims to evaluate the trophic status and spatiotemporal variation trends of water quality in Xiangjiaba Reservoir. The research results are expected to be used to trace pollutant sources in the water of its upstream areas, assess the effectiveness of ecological protection policies, and provide direct data support for the construction and protection of the ecological barrier in the upper reaches of the Yangtze River. [Methods] Hierarchical cluster analysis, Mann-Kendall time-series trend analysis, and Spearman correlation analysis were employed to analyze the trophic status, spatiotemporal changes in water quality, and influencing factors based on monitoring data from 11 mainstream cross-sections and 13 tributary cross-sections of Xiangjiaba Reservoir collected from March 2021 to February 2024. [Results] (1) Total nitrogen (TN) and total phosphorus (TP) in the mainstream of Xiangjiaba Reservoir were affected by upstream inflow, non-point source and point source pollution within the basin, and secondary release from bottom sediments during the study period, while TN and TP in the tributaries mainly originated from non-point source pollution within the basin. (2) Significant spatial differences were observed in the water quality and eutrophication level of Xiangjiaba Reservoir. Concentrations of TN, TP, and permanganate index (COD_Mn) in the lower reaches of the mainstream were higher than those in the upper reaches, while the Secchi depth (SD) was lower. Meanwhile, the water flow velocity (WFV) in the lower reaches of the mainstream was relatively low, which limited pollutant diffusion and transport and favored phytoplankton growth, resulting in a significantly higher trophic level index (TLI) and chlorophyll-a (Chl-a) concentration in the lower reaches than those observed in the upper reaches. Tributary monitoring group 4 was strongly affected by point source pollution from Suijiang County in the upstream, where the TLI and concentrations of Chl-a, TN, TP, and COD_Mn were the highest, followed by group 2, whereas groups 3 and 1 showed relatively lower values. The TLI, TP, SD, and COD_Mn in the mainstream and tributaries of Xiangjiaba Reservoir generally showed improving trends, while Chl-a showed a deteriorating trend. TN in the mainstream and group 2 tributary monitoring cross-sections showed an upward trend. (3) Water quality of the mainstream and tributaries of Xiangjiaba Reservoir showed pronounced seasonal variations. TLI, TN, TP, and COD_Mn increased significantly with increasing precipitation during the wet season, while SD decreased. The water storage during dry season caused TN accumulation, which reached its peak in November. Pollutants such as TN, TP, and COD_Mn released in the bottom sediments migrated upward due to the decrease in surface water temperature (WT) in autumn and winter, increasing the concentrations of TN, TP, and COD_Mn in surface waters. Rapid phytoplankton proliferation caused a sharp increase in Chl-a concentration. [Conclusion] The cascade reservoirs in the lower reaches of the Jinsha River exert a substantial interception effect on sediment and pollutants in the water. The concentrations of TP and COD_Mn have decreased. However, the relatively high TP and TN concentrations and lower WFV facilitate phytoplankton growth, resulting in an increased Chl-a concentration in Xiangjiaba Reservoir. In the future, reservoir management should be strengthened. Exogenous nitrogen and phosphorus inputs should be reduced, and bottom sediment dredging should also be strengthened.

[Objective] Taking the Chezhegou basin in the intensively agricultural Huaibei Plain as a case study, this research scientifically evaluates the water ecological health from the perspective of ecosystem integrity, considering the unique watershed characteristics of agricultural intensive areas. This study aims to provide practical technical support for the ecological restoration of lake-like rivers in similar regions, and offer a scientific basis for regional water ecological security and sustainable management. [Methods] An evaluation framework for aquatic ecology in agricultural-intensive area was constructed in consideration of water resources, water environment, and water ecology (WRE). Seven key indicators were selected using principal component analysis (PCA, cumulative variance explanation rate >97%) and entropy weight method, considering data accessibility, indicator frequency (≥0.05), and alignment with national standards. The final indicators included: water resource utilization rate, water exchange cycle, comprehensive trophic level index, phytoplankton diversity index, aquatic plant coverage, phytoplankton density, and natural riparian ratio. Statistical analyses (ANOVA, correlation analysis) were also performed. [Results] (1) The Chezhegou basin exhibited distinct lake-type river features: water exchange cycles ranged from 110 to 179 days (mean 119 days) due to low slope (0.2‰), dam interception, and tributary backwater, forming a “semi-stagnant water” state. Water resource utilization rate averaged 43%, reflecting high reliance on agricultural irrigation. Water level (mean 26.40 m) was positively correlated with rainfall (r=0.78, p<0.01) but showed significant lag effects (4-28 hours, mean 12.6 hours) and asynchronous responses to rainfall intensity, attributed to artificial dam regulation. (2) Physicochemical parameters showed significant spatiotemporal variability: TN (0.40-9.51 mg/L, mean 2.52 mg/L), TP (0.002-1.46 mg/L, mean 0.137 mg/L), COD_Mn (1.2-17.8 mg/L, mean 4.86 mg/L), and Chl-a (10.7-23.4 μg/L, mean 18.3 μg/L) fluctuated seasonally, with higher values in the wet season (except TN). Spatially, Chl-a, TP, and COD_Mn were significantly higher in the midstream than upstream and downstream. The TLI ranged from 50 to 60 (mild eutrophication), with midstream points reaching moderate eutrophication (TLI=62.3-65.1) in June-July 2023. (3) Eight aquatic plant species were identified, with emergent plants (e.g., Phragmites australis) accounting for 50%. Phytoplankton included 7 phyla and 71 species, dominated by Chlorophyta (46.48%) and Bacillariophyta (22.54%). Phytoplankton density averaged 721.45×10⁴ ind./L, and the Shannon index ranged from 1.86 to 2.213 (mean 1.92), indicating low biodiversity. Chlorophyta abundance was positively correlated with TN (r=0.68, p<0.01) and TP (r=0.72, p<0.01), reflecting eutrophication-driven community succession. (4) The health assessment results showed that the overall water ecological health score averaged 58.22, classified as Grade III (Moderate). Seasonally, summer scores (mean 54.42) were significantly lower than spring (60.72), autumn (59.51), and winter (59.01) (p<0.05), driven by higher summer TLI (mean 62.3) and lower phytoplankton diversity. Interannually, scores declined from 58.38 (2022) to 56.17 (2023) and recovered to 60.10 (2024), consistent with eutrophication dynamics. [Conclusions] The results confirm that the Chezhegou basin’s moderate health status is primarily constrained by eutrophication and low biodiversity. The assessment system, with a cumulative variance explanation rate of 97.202%, demonstrates highly scientific rigor and practicality, offering a replicable tool for similar ecosystems. Future research should enhance monitoring of zooplankton and benthic invertebrates to improve food chain representation.

[Objective] Danjiangkou Reservoir is the core water source of China’s South-to-North Water Diversion Middle Route Project, with a 378.82 km² water-level-fluctuation zone (WLFZ) where agricultural planting covers 45.39% of the 158-170 m area, threatening adjacent reservoir bay water quality. Existing studies lack clarity on region-specific planting impacts and risks from pathways like rainfall runoff and submergence. This study aimed to: (1) quantify total nitrogen (TN) and total phosphorus (TP) changes in soils and bay waters before/after planting and rainfall; (2) measure TN/TP release rates from soils under submergence via simulations; (3) provide targeted support for WLFZ water quality protection. [Methods] A total of 10 topsoil samples (0-15 cm) and 9 bay water samples (0.5 m below surface) were collected during pre-planting (Sept. 6-7, 2024), post-planting/pre-rainfall (Oct. 22-23, 2024), and post-planting/post-rainfall (Nov. 16-17, 2024). Soil TN/TP and water quality indicators were tested following national standards. Static immersion experiments used soil columns (5 cm height) with 2 L reservoir water, sampling every other day until concentration stabilization. [Results] (1) Soil TN concentrations rose by 159-890 mg/kg, with the mean value increasing from 790 mg/kg (pre-planting, mostly Grade Ⅴ-Ⅵ, low nutrient level) to 1 246 mg/kg (post-planting, mostly Grade Ⅲ-Ⅳ, medium level). Soil TP concentrations increased by 46-546 mg/kg, with the mean rising from 608 mg/kg (pre-planting) to 669 mg/kg (post-planting); only unfertilized sites showed no increase or a decrease. After rainfall, soil TN decreased by an average of 266 mg/kg (range: 80-698 mg/kg), with the largest drop (698 mg/kg) in Shengwan Town. Soil TP decreased by an average of 149 mg/kg (range: 58-332 mg/kg), with the largest decline (332 mg/kg) in Jiuchong Town.(2) Rainfall led to significant water quality deterioration: the proportion of Ⅰ-Ⅱ class water (per GB3838-2002) dropped from 88.81% (pre-rainfall) to 33.33% (post-rainfall). Water TN increased by an average of 14% (range: 0.07-0.47 mg/L). Water TP surged by an average of 255% (range: 0.01-0.10 mg/L). This indicated that TP (dominated by particulate phosphorus) was more vulnerable to rainfall erosion than TN.(3) Planting significantly enhanced TN and TP release from soils. Annual TN release rates increased by 65%-386%: from 16.1 mg/(m²·d) to 26.62 mg/(m²·d) (Jiuchong Town D2-166), 16.77 mg/(m²·d) to 81.51 mg/(m²·d) (Xianghua Town D1-166), and 7.36 mg/(m²·d) to 33.1 mg/(m²·d) (Cangfang Town D3-163). Annual TP release rates increased by 6%-232%: from 3.59 mg/(m²·d) to 3.79 mg/(m²·d) (Jiuchong Town D2-166), 0.38 mg/(m²·d) to 1.26 mg/(m²·d) (Xianghua Town D1-166), and 0.48 mg/(m²·d) to 1.10 mg/(m²·d) (Cangfang Town D3-163). Nutrient release followed a consistent pattern: rapid release in the early stage and gradual stabilization later, though release amounts varied significantly across different planting sites. [Conclusion] This study innovatively clarifies region-specific pollution risks and nutrient release of agricultural planting in the Danjiangkou Reservoir WLFZ. Agricultural planting increases soil TN/TP accumulation, while rainfall runoff and submergence accelerate their migration to water bodies—with TP more susceptible to rainfall erosion. The marked rise in nutrient release rates post-planting elevates water quality risks during WLFZ submergence. Targeted recommendations include: (1) strengthening intensive water quality monitoring in high-risk bays (Xianghua, Shengwan, Jiuchong Towns) during peak planting seasons (April-May, October-November); (2) implementing strict fertilizer controls and regular inspections in these key regions; (3) prioritizing measures to reduce particulate phosphorus loss and mitigate eutrophication. These findings fill gaps in region- and pathway-specific pollution risk assessments and provide critical support for safeguarding the South-to-North Water Diversion Project’s water quality.

[Objective] Nitrogen, a critical limiting nutrient in aquatic ecosystems, exhibits spatiotemporal heterogeneity that profoundly influences water quality dynamics and eutrophication evolution in the Danjiangkou Reservoir. This study aims to clarify the spatiotemporal differentiation patterns and driving mechanisms of key nitrogen forms in Danjiangkou Reservoir, focusing on seasonal (non-flood vs. flood) and vertical (surface, middle, bottom) variations. It focuses on critical yet underexplored issues, including seasonal dynamics of nitrogen forms, vertical data gaps, and tributary-reservoir coupling, to directly support the water quality security goals of the South-to-North Water Diversion Project. [Methods] This study systematically collected surface water samples from tributaries discharging into the reservoir and stratified samples (surface, middle, and bottom layers) during the non-flood (March 2024) and the flood (September 2024) seasons. By quantifying total nitrogen, nitrate, ammonium, and dissolved organic nitrogen, we investigated the spatiotemporal differentiation mechanisms of nitrogen forms. [Results] In the non-flood season, nitrate nitrogen ($\mathrm{NO}_{3}^{-}-\mathrm{N}$) was the dominant form of nitrogen in the water of the Danjiangkou Reservoir area and its inflow tributaries, accounting for 63.3% to 88.6% of the total nitrogen and holding an absolute advantage. In the longitudinal direction of the reservoir area, after the inflow from the Han Reservoir entered the Danjiangkou Reservoir, the concentration of $\mathrm{NO}_{3}^{-}-\mathrm{N}$ generally showed a decreasing trend along the direction of water flow. In the vertical direction, the average concentration of $\mathrm{NO}_{3}^{-}-\mathrm{N}$ followed the order of bottom layer > middle layer > surface layer, which may be attributed to photochemical denitrification in the surface water. Dissolved organic nitrogen (DON) was the second most abundant form of nitrogen; its concentration in the Han Reservoir was significantly higher than that in the Dan Reservoir. Vertically, DON concentration showed a decreasing trend toward the bottom in the Han Reservoir, while it showed an increasing trend toward the bottom in the Dan Reservoir. This phenomenon may be caused by the adsorption of DON by fine suspended sediments and their transport to the reservoir bottom under the slow flow conditions of the Dan Reservoir. After entering the flood season, DON concentrations in the inflow tributaries increased significantly. In both the Danjiangkou Reservoir area and its tributaries, the dominant forms of nitrogen became $\mathrm{NO}_{3}^{-}-\mathrm{N}$ and DON, with $\mathrm{NO}_{3}^{-}-\mathrm{N}$ accounting for 13.90% to 90.44% and DON accounting for 1.04% to 74.18%. Compared with the non-flood season, the content of $\mathrm{NO}_{3}^{-}-\mathrm{N}$ decreased significantly, which may be due to the enhanced photochemical denitrification in the surface water and microbial denitrification in the bottom water of the reservoir during the flood season. In the longitudinal direction, the distribution of $\mathrm{NO}_{3}^{-}-\mathrm{N}$ showed no obvious regularity; however, in the vertical direction, the average concentration of $\mathrm{NO}_{3}^{-}-\mathrm{N}$ still followed the order of bottom layer > middle layer > surface layer. [Conclusion] The results show that nitrate nitrogen is the main form of nitrogen in the water body during the non-flood season of the reservoir. After entering the flood season, the content of dissolved organic nitrogen increases significantly and jointly dominates the occurrence of nitrogen in the water body with nitrate nitrogen. Longitudinally, after the water from the Han Reservoir enters the Danjiangkou Reservoir, the concentration of nitrate nitrogen generally shows a decreasing trend along the direction of water flow, reflecting the regulatory effect of the hydrodynamic process on the transport of nitrogen. Vertically, the average concentration of nitrate nitrogen in both the non-flood season and the flood season shows the typical pattern of bottom layer > middle layer > surface layer, and the vertical difference in the flood season is more significant. This pattern may be closely related to the reduction of nitrate nitrogen by photochemical denitrification in the surface water body and the inhibition of vertical mixing due to thermal stratification in the flood season.

[Objective] In order to clarify the spatiotemporal distribution characteristics of total nitrogen (TN) and total phosphorus (TP) loads from non-point source pollution in the Guanshan River watershed, as well as to identify their major pollution source contributions, and simultaneously to address the problem of insufficient estimation accuracy of the traditional export coefficient model when applied to watersheds with complex terrain conditions, this study introduced a rainfall factor (α) and a topography factor (β) to improve the traditional export coefficient model. Based on this improved model, the nitrogen and phosphorus loads from non-point source pollution in the Guanshan River watershed from 2021 to 2024 were estimated, and their temporal and spatial variation characteristics were systematically evaluated and analyzed. [Methods] In this study, the rainfall factor (α) was extracted by utilizing the daily runoff data recorded at the hydrological station located at the watershed outlet of the Guanshan River watershed during the period from 2021 to 2024, in combination with the observed rainfall data collected from the Dama Station, Xihe Station, Yuanjiahe Station, and Gushan Hydrological Station. Meanwhile, the topography factor (β) was extracted based on the Digital Elevation Model (DEM) data of the Guanshan River watershed. Subsequently, both the rainfall factor (α) and the topography factor (β) were incorporated into the framework of the traditional export coefficient model, thereby constructing an improved export coefficient model with enhanced applicability to the study area. [Results] (1) The improved export coefficient model effectively enhanced the simulation accuracy of nitrogen and phosphorus load estimation. Specifically, the NSE coefficients for total nitrogen and total phosphorus increased significantly from 0.18 and -2.65 to 0.98 and 0.93, respectively, while the relative error was reduced from a maximum value of 291.89% to a controlled range within 10%, demonstrating a substantial improvement in model performance.(2) During the period from 2021 to 2024, the total nitrogen and total phosphorus loads in the Guanshan River watershed decreased by 67.84% and 80.06%, respectively. These reductions further revealed the contribution rates of nitrogen and phosphorus loads from three major source categories, namely land use sources, rural domestic sources, and livestock sources. Among these categories, land use sources contributed the largest proportion, accounting for 81.32% to 94.94% of the total nitrogen and phosphorus loads. Within land use types, forest land made the highest contribution to both nitrogen and phosphorus loads, while the total nitrogen load intensity from cropland reached 2 778.63 kg/km², and the total phosphorus load intensity from construction land reached 709.30 kg/km². (3) On the temporal scale, both total nitrogen and total phosphorus loads exhibited an overall declining trend throughout the period from 2021 to 2024. On the spatial scale, Baihe Town and Guanshan Town were identified as the key priority areas for nitrogen and phosphorus pollution prevention and control within the watershed, primarily due to their diverse land use types and relatively higher intensity of human activities compared to other regions. [Conclusions] This study successfully constructed an improved export coefficient model by incorporating both the rainfall factor and the topography factor, which effectively enhanced the estimation accuracy of nitrogen and phosphorus loads from non-point source pollution in the Guanshan River watershed. The results demonstrate that the total nitrogen and total phosphorus loads in the Guanshan River watershed generally showed a decreasing trend from 2021 to 2024, thereby verifying the positive effects of the water source protection measures implemented in the region. However, it should be noted that the effectiveness of pollution control remains jointly influenced by multiple interacting factors, including interannual rainfall variability, changes in land use types, and livestock activities. Therefore, in the future, it is necessary to adopt precise zoned and categorized management strategies tailored to different sub-regions and pollution source types. This study provides a quantitative scientific basis for the effective prevention and control of non-point source pollution in the Guanshan River watershed, and in doing so, offers a valuable scientific reference for safeguarding the long-term water quality security of the South-to-North Water Diversion Project.

[Objective] To address water quality deterioration in Dianchi Lake caused by combined agricultural and urban non-point source pollution as well as confluence of rainwater and polluted water， this study constructed a Bayesian Network （BN） risk assessment framework. This framework integrates pollution identification， spatial tracing， and probabilistic inference to support “zoning management and targeted restoration” strategies in Dianchi Lake. [Method] Water quality data from 10 national control sections （2021-2024） in Dianchi Lake were pre-processed by eliminating outliers and interpolating missing values. Total Phosphorus （TP） was identified as the typical pollutant via Spearman correlation analysis. A BN structure was constructed based on TP concentrations using a hybrid algorithm： a Most Weight Supported Tree （MWST） derived from the Mutual Information matrix， node ordering via Breadth-First Search （BFS）， and structural optimization using the K2 score function. Parameters were learned using the Expected Maximization （EM） algorithm after discretizing data according to the Surface Water Environmental Quality Standard （GB3838-2002）. Model performance was evaluated using Leave-One-Out cross-validation. The validated BN was applied to assess water quality risk through forward prediction， sensitivity analysis， reverse tracing， and causal chain identification. [Result] The model achieved an average validation accuracy exceeding 80%. In 2025， the probability of lake-wide water quality exceeding Class IV standards is <15%. By 2035， the probabilities of exceeding Class III standards are projected as follows： DQ （66%）， LJY （59%）， GYSD （42%）， CHZX （41%）， DCN （38%）， HKX （29%）， BKY （26%）， GYSZ （22%）， and GYSX （14%）. Sensitivity analysis indicated that water quality at HKX is most significantly influenced by HWZ （0.469 2）， BYK （0.367 5）， and GYSZ （0.186 7）. When HKX water quality is Class V， the probability of Class V conditions at BYK， GYSZ， GYSD， LJY， and HWZ exceeds 40%； when HKX is Class IV， the probability of Class IV conditions at BYK， GYSZ， GYSD， LJY， HWZ， and DCN exceeds 80%. The identified causal pollution chain is HWZ→BYK→GYSZ→GYSD→LJY. [Conclusion] The MWST-BFS-K2 hybrid algorithm effectively quantified water quality risk in Dianchi Lake. In 2025， the risk of exceeding Class IV standards is extremely low lake-wide. By 2035， DQ faces high risk； LJY， GYSD， and CHZX face medium risk； while DCN， HKX， BYK， and GYSZ face low risk. The risk of exceeding Class III standards at GYSX is negligible. The pollutant migration path follows “HWZ→BYK→GYSZ→GYSD→LJY.” Management should prioritize blocking pollution transmission from GYSZ to GYSD. Water quality fluctuations at HWZ， BYK， and GYSZ significantly impact HKX. Key pollution sources for Haikou River include BYK， GYSZ， GYSD， LJY， HWZ， and GYSX in 2025， with DCN replacing GYSX as a priority area by 2035. This framework provides a scientific basis for the ecological management of plateau lakes.

[Objective] Significant sediment deposition occurs at the estuaries of small and medium-sized rivers in the Three Gorges Reservoir Area （TGRA）， which can easily lead to endogenous pollution. Investigating the water environment pollution risks associated with sediment deposition in these typical rivers is of great significance for the water environment protection of the TGRA. [Method] Taking the Nixi River and Zhuyi River—typical small and medium-sized rivers located in the perennial backwater zone—as study subjects， this study evaluated the water environment pollution risks through sediment deposition surveys and analyses of the physicochemical properties， nutrient contents， and heavy metals in the sediments. [Results] （1） Significant sediment deposition was observed at the estuaries of both rivers， with silt accounting for over 76% of the sediment. Sampling sites closer to the estuaries exhibited higher proportions of clay and silt， and lower proportions of sand. （2） In the Nixi River， the spatial distribution of total nitrogen， hydrolyzable nitrogen， and available phosphorus showed a consistent trend， increasing from the upstream section to the estuary. Conversely， in the Zhuyi River， the average total organic carbon content in the sediment was higher than that in the Nixi River， but it decreased from upstream to the estuary. （3） The maximum comprehensive sediment pollution indices for the two rivers were 0.7 and 0.8， respectively， indicating a low overall risk. However， the maximum mass fractions of organic nitrogen reached 0.110 7% and 0.103 1%， respectively， indicating slight exceedance and a potential risk of release into the water body. Organic pollution in the Nixi River was primarily affected by the confluence and reservoir water level fluctuations， whereas in the Zhuyi River， it was mainly driven by human activities in the upstream urban areas of the bay. （4） The maximum potential ecological risk indices for multiple heavy metals were 68.07 and 123.94， respectively， indicating low pollution levels. [Conclusion] The overall water environment risk in the Nixi and Zhuyi rivers is currently low. However， sudden water quality deterioration occasionally occurs， primarily caused by the exceedance of phosphorus-containing substances and easily oxidizable small molecules. Further improvement and management of the water environment require not only controlling agricultural non-point source pollution but also emphasizing sediment dredging and endogenous pollution control. Additionally， comprehensive measures must be implemented in the Zhuyi River to reduce low-molecular-weight pollutants and prevent sudden water pollution incidents.

[Objective] The intrinsic mechanisms underlying the spatiotemporal heterogeneity of nutrient removal efficiency and the regulatory role of aquatic plant rhizosphere effects in micro-scale surface flow constructed wetlands （SFCWs） remain unclear. This study aims to address the following issues： （1） Elucidate the spatiotemporal distribution patterns of nitrogen （N） and phosphorus （P） removal efficiency； （2） Reveal the correlation mechanisms among microbial community structure， metabolic potential， and N/P removal； and （3） Evaluate the effects of the plant rhizosphere and three typical plant species on microbial community structure and N/P metabolic potential， providing a basis for the design and maintenance of micro-scale SFCWs. [Method] Using a specific wetland as a case study， water quality monitoring and high-throughput microbial sequencing were employed to systematically analyze the spatiotemporal characteristics of N/P removal and their microbial driving mechanisms. The regulatory mechanisms of substrate types and plant rhizospheres on microbial community composition and metabolic potential were also clarified. [Results] （1） The ammonia nitrogen removal rate remained stable （89.3%-95.8%）， while the total nitrogen removal rate exhibited seasonal variation： summer （75.6%） > autumn （64.9%） > spring （54.3%） > winter （21.9%）. This process was closely related to the succession of functional bacterial communities and changes in metabolic potential. N-cycling functional bacteria， including Kosakonia， Bacillus， Noviherbaspirillum， Ellin6067， and Anaeromyxobacter， were significantly enriched in spring and summer， resulting in significantly higher N metabolic potential compared to autumn and winter. （2） The total phosphorus removal rate， co-regulated by microbial action and adsorption/sedimentation， showed seasonal variation （summer 74.9% > spring 65.6% > autumn 59.8% > winter 46.7%）. Microbial influence on seasonal fluctuations was evidenced by the significant enrichment of P-cycling functional bacteria， such as Massilia， Bacillus， Saccharimonadales， and Gemmatimonas， in spring and summer， with P metabolic potential significantly higher than in autumn and winter. （3） Spatially， N/P metabolic potential demonstrated stability. Although substrate types （gravel， non-rhizosphere soil， and rhizosphere soil） significantly altered bacterial community composition， no significant differences in N/P metabolic potential were observed among substrates. This provides empirical evidence for the weakened rhizosphere boundary effect and the maintenance of metabolic homeostasis via functional redundancy at specific scales in micro-scale wetlands. [Conclusion] In space-constrained SFCWs with low pollution loads， water temperature dominates the biochemical reaction rates of N/P transformation. Alkaline pH and an appropriate increase in total nitrogen concentration synergistically promote P removal. Microbial community distribution is influenced by nutrient substrates and environmental factors. Based on these findings， the following optimization strategies are proposed： （1） Install a pre-treatment unit for total phosphorus at the inlet to mitigate the risk of endogenous release caused by substrate saturation； （2） Utilize aquatic plant root systems to promote the enrichment and spread of denitrifying bacteria， while reducing the reliance on precise plant species configuration； （3） Based on the succession characteristics of functional bacteria， apply targeted inoculation of highly efficient microbial agents for N/P removal； and （4） Maintain stable system operation through water temperature regulation， pH optimization， and nutrient load management.

[Objective] Promoting the natural spawning of fish through reservoir operation is an important and effective measure for enhancing the ecological benefits of reservoirs. From 2011 to 2025, the Three Gorges Reservoir (TGR) conducted 24 ecological operation tests over 15 consecutive years to promote the spawning of the four major Chinese carps (FMCC) and facilitate the recovery of fish resources. However, early-stage fish resource monitoring data indicate that the responses of FMCC to each ecological operation test vary, with spawning effects being pronounced in some cases but suboptimal in others. Therefore, attention should be focused on the schooling behavior of the parent fish of FMCC in the Yichang river section, and appropriate hydrodynamic conditions constitute a key ecological basis for their spawning. [Methods] To determine the appropriate ecological flow for FMCC parent fish schooling in the Yichang river section, this study began with the ecohydraulics requirements of the parent fish schooling, proposed a hydrodynamic suitability curve based on previous monitoring results and existing literature, established a three-dimensional hydrodynamic model and a Physical Habitat Simulation Model (PHABSIM) of the spawning site, analyzed the hydraulic habitat suitability of FMCC under different flow conditions, and identified the ecological flow range suitable for parent fish schooling. [Results] By simulating the weighted usable volume (WUV) of FMCC spawning schooling habitats under different outflows from the TGR, the spatial response characteristics of the schooling habitat were quantitatively evaluated. Overall, WUV first increased and then decreased as the flow of the spawning site increased. At a flow of 14 000 m³/s, WUV reached its maximum, accounting for 71.7% of the percent usable volume (PUV) of the study area. Under this flow, conditions were favorable for forming a larger, more concentrated, and well-connected schooling-suitable habitat. Under high flow conditions exceeding 22 000 m³/s, the increased flow velocity and intensified vertical velocity gradient hindered the formation of stable FMCC spawning schooling, significantly reducing the suitable habitat volume. Therefore, to promote parent fish schooling, flow should not be too high. The optimal flow range should be 10 000-20 000 m³/s, accounting for more than 64.3% of PUV, which was conducive to forming a three-dimensional habitat suitable for FMCC schooling and maintaining high ecological stability. The suitable flow velocity and depth ranges for parent fish spawning schooling in the Yichang river section were 0.9-1.4 m/s and 3.0-5.0 m, respectively. FMCC habitat suitability in the study area exhibited distinct vertical and horizontal spatial distribution patterns. At a flow of 14 000 m³/s, the average velocity in the upper layer was 1.10 m/s, while in the lower layer it was 0.75 m/s. For the upper-middle layer, flow velocity, depth, and comprehensive suitability index were 0.90, 0.91, and 0.84 respectively, whereas for the bottom layer, they were 0.89, 0.65 and 0.57. The upper-middle layer outperformed the bottom layer, particularly in terms of depth and comprehensive suitability index, indicating that the upper-middle layer provided more stable and suitable habitat conditions for FMCC. [Conclusion] Using an unstructured irregular triangular mesh, a three-dimensional hydrodynamic model of the FMCC spawning site in the Yichang river section is established. The model accuracy meets the requirements, enabling accurate simulation of the hydrodynamic characteristics of the spawning site under different flow conditions. Before spawning, parent fish tend to occupy the upper-middle layer, and their behavior is more sensitive to flow conditions. The flows of 10 000-20 000 m³/s favor parent fish schooling, with the most suitable range being 12 000-16 000 m³/s. The findings provide a scientific basis for the TGR to precisely regulate ecological water management during key life history stages, such as parent fish schooling, thereby enhancing the ecological benefits of the reservoir.

[Objective] Soil erosion and non-point source pollution have become increasingly prominent in the Danjiangkou Reservoir area, affecting the water quality of inflow rivers and posing a threat to the water security of the Danjiangkou Reservoir area. Existing studies have not thoroughly analyzed the influence of landscape patterns at different scales on water quality. This study aims to supplement research on the differentiated effects of landscape pattern indices at different scales on water quality in the Danjiangkou Reservoir area, thereby providing a reference for developing scientifically sound water quality protection and improvement measures. [Methods] We took the Shibanhe small watershed in the Danjiangkou Reservoir area as the research object. Based on the spatial pattern characteristics of land use, we adopted spatial analysis, mathematical statistics and Mantel test to reveal the spatial differentiation characteristics of different water quality indicators, investigate the main landscape pattern indices affecting water quality at scales such as subwatershed, river buffer zone, and circular buffer zone, and explore the mechanisms of landscape background on surface water quality. [Results] (1) The concentrations of total nitrogen (TN) and nitrate nitrogen ( ${NO}_{3}^{-}-N$) in the surface water of the Shibanhe small watershed were relatively high, mainly distributed in the central and southeastern parts of the watershed where cultivated land and residential areas were concentrated. Orchards near the river also served as important potential sources of river water pollution. (2) At different scales, the proportions of cultivated land and forest land had a significant impact on river water quality, and their correlation was more significant at scales of subwatershed, 100 m river buffer zone, and 200 m river buffer zone. At the subwatershed scale, patch density (PD) had a highly significant correlation with TN and ${NO}_{3}^{-}-N$. Landscape pattern indices, such as contagion index (CONTAG), cohesion index (COHESION), Shannon’s diversity index (SHDI), and Shannon’s evenness index (SHEI), had certain effects on water quality at all scales, and their effects were greater at subwatershed and 100 m rive buffer zone scales. (3) The effects of landscape background on river water quality had a significant scale effect. The subwatershed and 100 m river buffer zone scales were the key scales affecting river water quality, where landscape structure and landscape pattern exerted the greatest influence. [Conclusion] Management and regulation of landscape structure and landscape patterns at scales of subwatershed and 100 m river buffer zone—especially strengthening the monitoring and management of landscape fragmentation—are of great significance for improving river water quality in the Danjiangkou Reservoir area. Future research should strengthen long-term water quality monitoring to reveal dynamic change patterns of regional water quality and seasonal differences in their driving factors.

[Objective] Hyperspectral remote sensing technology offers a new approach for non-contact, real-time sensing of water quality parameters. Existing research has shortcomings in developing dedicated sensing equipment and constructing multi-parameter collaborative inversion algorithms. This study aims to systematically explore the spectral response characteristics of five key water quality parameters—chemical oxygen demand (COD), total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH₃-N)—based on a self-developed hyperspectral water sensing instrument, and to establish an adaptive hyperspectral sensing algorithm optimization framework for multiple water quality parameters. This framework aims to overcome the adaptability limitations of traditional single algorithms in complex water environments and provide technical support for achieving 24/7 continuous online water quality monitoring. [Methods] First, continuous spectral data and corresponding measured values of water quality parameters from a large number of water samples were collected using the self-developed hyperspectral water sensing instrument. Through spectral analysis, the absorption, reflectance characteristics, and differential patterns of COD, TSS, TP, TN, and NH₃-N within the visible to near-infrared spectral range were revealed, and the sensitive characteristic bands for each parameter were selected accordingly. On this basis, a multi-level, multi-type inversion model system was constructed. At the empirical model level, single-band regression, band ratio, and normalized difference index were employed to establish statistical relationships between spectral features and water quality parameters. At the machine learning level, BP neural network, random forest (RF), and XGBoost were introduced to fully exploit the nonlinear mapping relationships within the hyperspectral data. Furthermore, an adaptive algorithm optimization framework was proposed. By comparing the inversion accuracy and stability of various models across different water quality parameters and concentration ranges, this framework automatically matched the optimal inversion algorithm for each parameter, thereby achieving the optimal configuration for multi-parameter collaborative sensing. An independent dataset partitioning strategy was adopted for model training and validation, with the coefficient of determination (R²) and mean absolute percentage error (MAPE) as the core evaluation indicators to ensure the objectivity and reliability of the assessment results. [Results] The constructed adaptive algorithm optimization framework achieved excellent performance in the inversion of all five water quality parameters. In the training and validation datasets for the optimal algorithms, the R² values of the corresponding optimal models for each parameter ranged from 0.88 to 0.99, exhibiting extremely high fitting accuracy and generalization capability. From a practical accuracy perspective, 100% (COD), 91% (TSS), 90% (TP), 90% (TN), and 95% (NH₃-N) of total samples had a MAPE below 30%, fully meeting the practical requirements for water quality monitoring. Specifically, the inversion accuracy for the COD parameter was the highest, with all samples meeting the accuracy threshold, indicating that hyperspectral data possessed exceptional characterization capability for organic pollutant concentrations. NH₃-N followed closely, with 95% of samples meeting the accuracy requirement, reflecting significant spectral response characteristics of ammonia nitrogen in specific bands. The compliance rates for TSS, TP, and TN all exceeded 90%, verifying the universality and robustness of the framework in the inversion of different types of water quality parameters. Compared with traditional single-model methods, the adaptive optimization strategy significantly improved the overall accuracy and stability of multi-parameter collaborative inversion, effectively overcoming the adaptability deficiencies of single algorithms under complex water conditions. [Conclusion] This study proposes and validates an adaptive hyperspectral sensing algorithm optimization framework for multi-parameter water quality monitoring based on a self-developed hyperspectral water sensing instrument. The core innovations of this optimization framework lies in the following: first, it breaks through the conventional paradigm of “one algorithm fits all parameters” in traditional water quality hyperspectral inversion by implementing a multi-model competitive optimization mechanism, achieving automatic matching of the optimal algorithm for each parameter. Second, it integrates empirical models and machine learning models into a unified optimization system, balancing the model interpretability with nonlinear fitting capability. Third, the research findings demonstrate strong engineering application prospects and can directly support the construction of 24/7 continuous online water quality monitoring systems.

[Objective] This study investigates the synergistic and antagonistic effects of multiple factors on water self-purification capacity and examines self-purification efficiency of water under the combined influence of multiple factors, aiming to overcome the limitations of previous studies and provide new quantitative evidence for understanding water self-purification capacity in complex aquatic environments. [Methods] To investigate the interactions among multiple factors affecting water self-purification capacity, orthogonal experiments were conducted on water samples collected from the northwest side of a lake in Wuhan, which was affected by mixed pollution from domestic sewage and industrial wastewater and contained a microbial community. The orthogonal experiment results were analyzed using a combination of response surface methodology (RSM) and structural equation modeling (SEM) to reveal the nonlinear interaction mechanisms among typical influencing factors, including meteorological conditions, pollutant concentration background values, and biological activity. [Results] The results of orthogonal experiments showed that water self-purification efficiency (η), nitrification rate (r_N), and oxygen mass transfer efficiency (K_La) of water all varied nonlinearly across experimental groups, with maximum values observed at approximately temperature (T)=25 ℃, dissolved oxygen concentration (DO)=6 mg/L, flow rate (v)=0.1 m/s, microbial abundance (M)=5×10⁷ CFU/mL, and chemical oxygen demand (C)=100 mg/L. RSM analysis indicated that at the optimal parameter combination (T=24.8 ℃, DO=5.9 mg/L, v=0.27 m/s, C<100 mg/L, and M=4.7×10⁷ CFU/mL), η significantly increased to 83.24%, r_N exceeded 1 mg/(L·h), and K_La reached its maximum. In addition, in the binary factor interactions, the most significant interaction term was T×DO, with a synergistic contribution of 45.52%. SEM path analysis showed that v and T influenced the water self-purification process through both direct effect and indirect effect. Paths: v➝DO➝η; v➝DO➝Mi( microbial activity, including r_N and M)➝η; T➝DO➝η; T➝Mi➝η; T➝DO➝Mi➝η, where the direct effect of v on water self-purification process was 0.41, and the indirect effect was 0.25; and the direct effect of T on water self-purification process was 0.35, and the indirect effect was 0.25. The total effect of T and v on water self-purification process increased by 0.25 compared with the direct effect of each factor alone. [Conclusion] The results confirm that there is a synergistic amplification mechanism and significant threshold effects among different environmental influencing factors. Binary factor interactions not only show significant effects, but also factors originally negatively correlated with water self-purification capacity can significantly reduce their inhibitory influence on water self-purification efficiency after complex interactions with other factors. Additionally, factors such as flow rate and temperature affect the water self-purification process both directly and indirectly through their effects on other influencing factors. These findings provide a new quantitative basis for evaluating water self-purification ability and its controlling factors in complex aquatic environments.

[Objective] The time series of reservoir water quality indices,especially dissolved oxygen content, exhibit strong nonlinearity,high complexity,and uncertainty,which lead to insufficient accuracy of single prediction models.This study aims to construct a high-precision hybrid prediction model that integrates time series decomposition,intelligent optimization,and residual correction,thereby significantly improving the prediction accuracy of dissolved oxygen (DO) content and providing reliable support for water environment management and pollution early warning. [Methods] The core procedures of the proposed hybrid prediction model are as follows. 1) Data decomposition and reconstruction. Singular spectrum analysis (SSA) was applied to decompose the dissolved oxygen time series, and the series was reconstructed into trend components, periodic components, and residual components to reduce sequence complexity and highlight features at different frequencies. 2) An improved dung beetle optimizer (IDBO) which integrates piecewise chaotic mapping and opposition-based learning strategies was designed to enhance population diversity and initialization quality. The improved IDBO was used to optimize key hyperparameters of the GRU network, including the number of hidden layer neurons and the initial learning rate. 3) Component prediction and residual correction. The GRU model optimized by IDBO was used to predict the trend component and periodic components separately. A residual series prediction difference correction method (DCM) was proposed. The residual component was first predicted using GRU, and the difference sequence between the predicted values and the observed values was calculated. Variational mode decomposition (VMD) was then applied to the difference sequence to fully extract high-frequency detail information. Each decomposed component was predicted using GRU and aggregated to obtain the predicted difference values. Finally, the predicted differences were compensated into the initial residual prediction to obtain the corrected residual prediction results. 4) Model integration and validation. The prediction results of the three components were aggregated to obtain the final DO prediction values. Measured dissolved oxygen data from Daheiting Reservoir in Tangshan, Hebei Province were used for experiments. The dataset contained 2352 records with a sampling interval of four hours. Root mean square error (RMSE), mean absolute error (MAE), mean relative error (MRE), and the coefficient of determination (R²) were used as evaluation metrics. The proposed model was compared with GRU, SSA-GRU, SSA-DBO-GRU, SSA-IDBO-GRU, and models reported in the literature such as LSTM and PSO-GRU. [Results] The proposed SSA-IDBO-GRU-DCM hybrid model achieved the best performance among all comparative models. The prediction errors were significantly reduced, with an RMSE of 0.580 2 mg/L, an MAE of 0.329 2 mg/L, an MRE of 0.0269, and an R² of 0.918 8. Ablation experiments confirmed that the proposed IDBO improvement strategies effectively enhanced hyperparameter optimization accuracy. The residual difference correction method (DCM) significantly improved the prediction performance of the residual component and was the key factor contributing to the overall accuracy improvement. These results fully demonstrated the effectiveness and superiority of the “decomposition-optimization-correction” framework. [Conclusion] SSA effectively decouples the complex characteristics of water quality time series. IDBO efficiently and accurately optimizes GRU hyperparameters. The proposed VMD-GRU-based residual difference correction method (DCM) is the key innovation for improving overall prediction accuracy. The proposed model significantly improves the prediction accuracy of dissolved oxygen content and provides an efficient and reliable new approach for reservoir dissolved oxygen prediction. Future work can extend this framework to the prediction of other key water quality parameters such as ammonia nitrogen and total phosphorus, and further explore the integration of natural evolutionary strategies to improve computational efficiency and generalization ability.

[Objective] Microplastics are widely present in reservoirs across China, posing threats to water quality safety and the stability of reservoir ecological functions. Accurately assessing the current status of microplastic pollution in China’s reservoirs, analyzing their migration patterns and environmental behavior, and scientifically evaluating the associated ecological risks are essential prerequisites for implementing effective management and control measures. [Methods] This study systematically reviewed recent data on microplastic pollution in China’s reservoirs, summarized the impact of reservoir operation on microplastic transport behaviors, analyzed associated ecological and health risks, and proposed feasible prevention and control strategies based on current plastic restriction policies. [Results] 1) Research on microplastic pollution in China’s reservoirs primarily focused on the Yangtze River and its tributaries, followed by the Xiaolangdi Reservoir on the Yellow River, the Erdaozha Reservoir on the Haihe River, and the cascade reservoirs in the Shaying River Basin. 2) Field investigations revealed that the abundance of microplastics in the Jiayan Reservoir was relatively high, with water column microplastic abundance ranging from approximately 11 000 to 61 700 particles/m³ and sediment microplastic abundance ranging from 2 600 to 15 700 particles/kg. The Three Gorges Reservoir received considerable attention regarding its microplastic pollution status, with water column microplastic abundance ranging from 800 to 6 214 particles/m³ and sediment microplastic abundance ranging from 1 031 to 63 081 particles/kg. The Guanyinyan Reservoir on the Jinsha River and the cascade reservoirs in the middle and lower reaches of the Hanjiang River exhibited a relatively moderate level of microplastic abundance, while other reservoirs showed comparatively lower levels. 3) A diverse range of microplastic types was detected in reservoirs, predominantly smaller than 1 mm. Microplastic shapes included fibers, fragments, films, and microbeads. The primary polymer types identified were polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), polyamide (PA), and polyvinyl chloride (PVC). 4) In terms of microplastic origin, secondary microplastics constituted the majority in reservoirs, mainly derived from plastic waste associated with daily life, fishing and shipping, agricultural irrigation, and tourism activities. The primary sources of microplastics in reservoirs were upstream areas and tributary inflows. Additionally, rainfall and agricultural irrigation facilitated the transport of land-based microplastics into reservoir waters via surface runoff, while atmospheric deposition contributed to the settling of microplastics from the air into reservoir water bodies. [Conclusion] Reservoirs in China are generally polluted by microplastics, and diverse microplastic types pose potential threats to the ecological environment. Reservoir operations significantly affect the environmental behavior and transport of microplastics through dam interception and changes in hydrological and hydrodynamic conditions, indirectly influencing the ecological and environmental effects of microplastics. Currently, effective prevention and control measures for microplastic pollution in reservoirs are insufficient and face significant challenges. We recommend to strengthen the monitoring of microplastic pollution in reservoirs and to develop prevention, control, and removal technologies to alleviate microplastic pollution in reservoirs and ensure the health of reservoir ecosystems.

[Objective] This study focuses on the practical demand for advanced nitrogen and phosphorus removal from the tail water of urban wastewater treatment plants. Aiming at the problem of low carbon-to-nitrogen ratios in urban wastewater treatment that result in unsatisfactory nitrogen removal efficiency, this study investigates the effects of different combinations of emergent plants and composite substrates on nitrogen and phosphorus removal from tail water through experiments. The application potential of natural manganese sand as a substrate is evaluated, providing theoretical and practical support for the optimization of constructed wetland technology and the resource utilization of manganese ore. [Methods] Three emergent plants, Acorus calamus L., Iris wilsonii C. H. Wright, and Scirpus validus Vahl were selected. Three experimental groups were established based on pairwise plant combinations, including Gp1 (Iris wilsonii C. H. Wright + Scirpus validus Vahl), Gp2 (Iris wilsonii C. H. Wright + Acorus calamus L.), and Gp3 (Scirpus validus Vahl + Acorus calamus L.). A composite substrate without plants was used as the blank control group (BC). The composite substrate consisted of natural manganese sand, zeolite, and ceramsite mixed at a ratio of 1∶3∶1. Constructed wetland systems were built using transparent polyethylene cylindrical columns with a height of 500 mm and a diameter of 160 mm to simulate the tail water treatment process of wastewater treatment plants. The experiment lasted for 70 days. During the experimental period, water quality indicators including total nitrogen, total phosphorus, ammonia nitrogen, and nitrate nitrogen were measured regularly. High-throughput sequencing was used to analyze the structure of microbial communities in plant root zones. [Results] All three plant combinations effectively removed nitrogen and phosphorus pollutants from the tail water, and the Gp3 group (Scirpus validus Vahl + Acorus calamus L.) showed the best performance. The total phosphorus removal rate reached 93.2%, the total nitrogen removal rate was 77.7%, the ammonia nitrogen removal rate was 91.7%, and the nitrate nitrogen removal rate was 70.6%. Pollutant concentrations in all experimental groups decreased rapidly during the first 30 days and then tended to stabilize, while the purification performance of the blank control group was significantly poorer. Microbial community analysis showed that the Gp3 group exhibited the highest microbial diversity and richness, with a Shannon index of 7.24 and unique OTUs accounting for 69.15%. The dominant phyla were Proteobacteria and Bacteroidetes, which together accounted for nearly 80%. Among them, Gammaproteobacteria played a key role in the denitrification process, and its relative abundance in the Gp3 group reached 29.2%, which was the highest among the three groups. [Conclusion] The synergistic effects of plant combinations and root-associated microbial communities in constructed wetlands are the key to efficient nitrogen and phosphorus removal, and the combination of Scirpus validus Vahl and Acorus calamus L.performs particularly well in advanced tail water treatment. The composite substrate containing manganese sand shows potential application value, while the specific mechanisms by which it promotes plant growth and microbial community formation still require further investigation. This study confirms the optimal purification performance of the Scirpus validus Vahl and Acorus calamus L. combination and the potential application value of manganese sand as a substrate, providing a reference for plant selection and targeted microbial cultivation in constructed wetlands for wastewater treatment plant tail water.

[Objective] As the core water source of the middle route of the South-to-North Water Transfer Project, the spatiotemporal distribution of water temperature in Danjiangkou Reservoir directly affects the aquatic ecological processes and water quality evolution within the reservoir area. This study aims to clarify the spatiotemporal distribution patterns of water temperature in Danjiangkou Reservoir through prototype observations across the entire reservoir, to identify thermal stratification types, and to reveal the factors influencing differences in thermal structure between the Danjiang Reservoir and the Hanjiang Reservoir, thereby providing a scientific basis for reservoir water quality management, ecological protection, and so on. [Methods] In 2023, prototype observations of water temperature were carried out in Danjiangkou Reservoir during four typical hydrological periods, including the dry season (February), the normal flow season (June), and the flood season (September and October). A total of 16 observation sections were deployed throughout the entire reservoir, including one section in front of the dam, seven along the mainstream of the Hanjiang River, and eight along the mainstream of the Danjiang River. Based on the observation data, multiple discriminant methods such as water residence time (T_r), runoff-storage capacity ratio (α), reservoir width-depth ratio (R), and densimetric Froude number (Fr) were comprehensively applied to systematically analyze the thermal stratification structure of the reservoir and its spatiotemporal evolution characteristics, and to further explore the influence mechanisms of meteorological, hydrological, and topographic factors on thermal stratification. [Results] (1) The vertical thermal stratification structure of Danjiangkou Reservoir exhibited a significant seasonal variation pattern: during the dry season (February), the water body was well mixed with no obvious stratification. During the normal flow season (June), stable stratification formed, and increased air temperature and enhanced inflow strengthened vertical mixing of the water body, resulting in a double-thermocline type vertical water temperature structure in the Han Reservoir, with a surface-to-bottom temperature difference of approximately 20 ℃. During the flood seasons (September-October), the thermocline deepened, and thermal stratification was the most stable and exhibited greater thickness. (2) The reservoir’s surface water temperature was highly correlated with air temperature (R²=0.976), whereas variations in middle and bottom water temperatures exhibited a lag, regulated by heat transfer within the water body and hydrological processes. (3) The Dan Reservoir and the Han Reservoir exhibited significantly different hydrological and hydrothermal characteristics. The Han Reservoir had a shorter water residence time (257 days), a larger runoff-storage capacity ratio (α=1.47), and stronger hydrodynamic forcing, exhibiting characteristics of a riverine reservoir. Its thermocline was mainly controlled by inflow dynamics, with isotherms showing an inclined pattern. The Dan Reservoir had a longer water residence time (336 days), a smaller runoff-storage capacity ratio (α=1.04), and slower water flow conditions, showing characteristics of a lacustrine reservoir. Its thermocline was primarily controlled by solar radiation and meteorological conditions, with more horizontally distributed isotherms and a more stable and persistent stratification structure. (4) Operation of the intake in front of the dam had an impact on the local thermal structure, and clustering of isotherms was observed at depths near the intake. [Conclusion] Through systematic prototype observations, this study comprehensively reveals the complex spatiotemporal thermal stratification structure of Danjiangkou Reservoir, particularly confirming the existence of a double thermocline during the normal flow season and the essential differences in stratification mechanisms between the Dan Reservoir and the Han Reservoir. This study innovatively demonstrates that two thermal stratification modes, lacustrine (Danjiang Reservoir) and riverine (Hanjiang Reservoir), coexist within the Danjiangkou Reservoir, providing an important foundation for understanding migration and transformation of nitrogen and phosphorus, algal growth, and seasonal water quality changes in the reservoir area.

[Objective] Minimum ecological flow (e-flow) targets are increasingly used as enforceable constraints in basin management, but their spatiotemporal reliability and ecological representativeness remain insufficiently evaluated at large scales. This study aims to quantify e-flow compliance across the Yangtze River Basin (YRB), identify the drivers of noncompliance and spatial heterogeneity, examine how compliance aligns with river ecological environment conditions, and propose targeted recommendations for improving goal setting, monitoring, and assessment. [Methods] The daily e-flow compliance records were compiled for 114 key control cross-sections from the Yangtze River Water Resources Commission’s monthly monitoring bulletins between January 2023 and July 2024. Compliance was summarized as (i) whether each cross-section met the minimum target throughout the full study period, and (ii) the number of noncompliant days at each cross-section and by month. For ecological environment linkage, 40 e-flow cross-sections were matched with nearby national automated surface-water quality stations, and dissolved oxygen, permanganate index, total nitrogen, total phosphorus, and water-quality class were examined. Subsequently, a four-quadrant diagnostic framework was constructed using mean noncompliance days and the mean share of days classified as Class Ⅳ to Inferior Ⅴ. [Results] Throughout the study period, 71 of 114 cross-sections (62%) fully met the minimum e-flow targets, whereas 43 cross-sections (38%) experienced noncompliance ranging from 1 to 170 days (mean 25.8 d; median 5.0 d). Compliance exhibited a pronounced seasonal unimodal pattern, with lower performance in winter and spring and higher performance in summer and autumn. Specifically, 901 noncompliance days occurred from January to March and from November to December, compared to only 118 days from April to October. Notably, all cross-sections met targets in August. Interannual variability was substantial. From January to July, the number of noncompliance days decreased from 814 in 2023 to 335 in 2024, and the monthly average number of noncompliant cross-sections declined from 18.8 to 10.5. Spatially, heterogeneity was strong among secondary basins, and the left bank outperformed the right bank. Mechanistically, major contributors included seasonal unevenness in precipitation and runoff, differences in dam regulation, reduced mainstream-to-lake diversion affecting the Dongting system, intensive agricultural withdrawals in lake-dominated right-bank regions, and governance and measurement challenges in cross-province water allocation. For the 40 paired sites, pollutant indicators showed no significant monotonic relationship with e-flow compliance, and the total phosphorus could even appear lower in low-flow and noncompliant months due to particulate phosphorus dynamics. The quadrant analysis indicated that 60% of sites fell into high-match zones, but 16 sites showed notable mismatches, suggesting that e-flow compliance was a necessary but insufficient condition for good ecological environment status and that relying solely on flow as a warning indicator remained uncertain. [Conclusion] Large-scale e-flow compliance in the YRB is generally favorable but exhibits strong seasonal, interannual, and governance-linked spatial heterogeneity. To improve ecological relevance and management effectiveness, the following recommendations are proposed: (i) shifting from fixed single-value targets to higher time-resolution, multi-objective, and adaptively updated e-flow targets; (ii) optimizing monitoring networks to better cover ecological hotspots (e.g., key spawning habitats), implementing flexible temporal resolution, and conducting emergency monitoring during rapid ecological events; (iii) transitioning from flow-only, section-based assessment toward integrated basin-scale evaluation that couples flow, water quality, habitat, and biodiversity outcomes.

[Objective] Heavy metal pollution in sediments is a major factor contributing to the deterioration of lake water quality. To accurately assess the sources and potential ecological risks of heavy metals in lake sediments, it is necessary to conduct source analysis and risk assessment at the watershed scale. [Methods] Concentrations of Cr, Ni, Cu, Zn, As, Cd, and Pb in soil and sediments were measured at the small watershed scale in the western lake area of Taihu Lake, and a comprehensive ecological risk evaluation of heavy metals was performed using the enrichment factor (EF), geoaccumulation index (I_geo), and potential ecological risk index. [Results] The heavy metal contents in sediments were generally higher than those in soil. Moreover, the heavy metal contents in sediments from the northern lake area were higher than those in the central and southern lake areas. About 88.4% of the increase in heavy metal content in sediments came from exogenous inputs such as terrestrial rivers and runoff discharged into the lake. Additionally, the EF and I_geo demonstrated that the sediments experienced various degrees of heavy metal accumulation and pollution. The ecological risk values of Cr, Ni, Cu, and Zn were significantly higher than those of the corresponding elements in soil, indicating a relatively high potential ecological risk. Finally, the assessment using the potential ecological risk index showed that Cd exhibited a relatively high ecological risk value, and the sediments exhibited moderate to high comprehensive ecological risks. [Conclusion] Overall, the potential ecological risks of heavy metals in sediments from the western lake area of Taihu Lake are attributed to terrestrial inputs, including surface soil erosion. By coupling comparative analysis of exogenous and endogenous pollution levels of heavy metals at the small watershed scale of the lake, this study provides important management information and a scientific basis for heavy metal control in the Taihu Lake watershed.

[Objective] Identifying the key landscape pattern factors that affect water quality is of great significance for integrated watershed water quality management. [Methods] Based on the water quality data from January 2014 to August 2024, redundancy analysis (RDA) and Pearson correlation analysis were applied to investigate the relationship between landscape pattern indices and ammonium nitrogen concentration in the Gaoguan Reservoir Basin during the wet and non-flood periods. RDA was used to identify the key landscape pattern indices,and Pearson correlation analysis was used to quantify the intensity and significance of correlation coefficients between ammonium nitrogen concentration and landscape pattern indices. [Results] The results were as follows: (1) In the Gaoguan Reservoir Basin,the area of forest land was the largest,accounting for more than 84.9% of the whole area and significantly contributing to the improvement of water quality. (2) The absolute values of correlation coefficients between landscape pattern indices and ammonium nitrogen concentration in the non-flood period were always higher than those in the wet period,and the same trend was observed for landscape composition and land-use areas. (3) In the wet and non-flood periods,with the increase of landscape diversity,splitting degree,and degree of fragmentation,the risk of surface runoff carrying pollutants into water bodies increased and aggravated the ammonium nitrogen pollution. Largest Patch Index (LPI) presented a negative correlation with ammonia nitrogen content in wet period, but a positive correlation in level period. Conversely, Contagion (CONTAG) exhibited a opposite relationship with ammonia nitrogen content, and a significant positive correlation in the non-flood period; in other words,the better integrity of the landscape and the lower degree of fragmentation can reduce the output of ammonium nitrogen during the flood period. During the non-flood period,the closer the pollution-source landscape type was to the water body,the more severe the impact on water quality due to its proximity. [Conclusion] Overall,forest land exhibits a more pronounced effect on water quality improvement in the Gaoguan Reservoir watershed compared with other land-use types.During the non-flood period,landscape pattern indices demonstrate a more significant capacity to regulate and influence water quality relative to the wet period. However,in general,water quality in the reservoir is primarily governed by landscape integrity during the wet period,whereas during the non-flood period,it is mainly controlled by pollution-source patches located closer to the water body.The results will be of great significance for the integrated watershed management and water quality improvement of the Gaoguan Reservoir in the future.

[Objective] As a vital ecological barrier in Northwest China, the river ecosystem health of Zhangye City is of critical importance to regional ecological security. This study aims to provide a comprehensive understanding of the aquatic ecological health of rivers in Zhangye City across different seasons. [Methods] A survey of benthic macroinvertebrates was conducted in 2023 at 136 sampling sites along seven rivers in Zhangye City. The benthic macroinvertebrate-based index of biological integrity (B-IBI) system for rivers in Zhangye City was constructed by selecting 23 candidate biological parameters from five categories that increased in sensitivity with the level of disturbance. B-IBI values of each river were then calculated for different seasons to evaluate their ecological health. [Results] A total of 159 benthic species were identified across both the wet and dry seasons. These species belonged to 5 phyla, 8 classes, 17 orders, and 51 families. Arthropods were the dominant taxa in both seasons, particularly Baetis sp. and Orthocladius sp. The analysis revealed significant differences in benthic macroinvertebrate communities between the dry and wet seasons across rivers in Zhangye City (r=0.09,p<0.05). The B-IBI results indicated that the overall ecological health of the rivers was satisfactory, with minimal seasonal variation. The proportion of sites classified as “healthy” during the dry and wet seasons was 42.39% and 42.71%, respectively. [Conclusion] Despite the currently favorable state of aquatic ecological health in Zhangye City, ecological degradation remains a risk due to ongoing climate change and human activities. To enhance the stability and health of the river ecosystem, it is necessary to strengthen monitoring and management efforts, optimize water resource allocation, and conduct further research on the long-term adaptability of benthic macroinvertebrate communities to extreme weather events and human activities.