Dynamic changes in total organic carbon (TOC) concentration in lakes and reservoirs affect the functions of aquatic ecosystems and are a key component of water quality management, especially in drinking water sources. The Danjiangkou Reservoir is the water source area of the Middle Route Project of the South-to-North Water Diversion in China. Its water quality is of critical importance to the safety of water diversion. TOC concentration and other environmental factors at 19 sampling sites in the Danjiangkou Reservoir were investigated quarterly during 2020–2021 to explore the differences at the spatio-temporal scales. A generalized additive model (GAM) was used to analyze the environmental factors correlated with the observed spatio-temporal variations of TOC concentration. The results showed that the comprehensive trophic level index (TLI) of the Danjiangkou Reservoir was under the state of intermediate nutrition, and the water quality was overall good. In terms of temporal patterns, TOC concentration was higher in both spring and summer and lower in other seasons. Spatially, TOC concentrations were found in descending order from the site of outlet, Han reservoir, entrance of reservoir, and Dan reservoir. The single-factor GAM model showed that TOC correlated with different environmental factors across spatio-temporal scales. Water temperature (WT), permanganate index (COD_Mn), and ammonia nitrogen (NH₄⁺-N) were significantly correlated with TOC in autumn, but only total nitrogen (TN) and transparency (SD) were significant in winter. Spatially, WT, chemical oxygen demand (COD), NH₄⁺-N, TN, and conductivity (Cond) correlated with TOC in the Dan reservoir, but WT, COD, NH₄⁺-N, total phosphorus (TP), and chlorophyll a (Chl.a) were significant in the Han reservoir. The multi-factor GAM model indicated that the environmental factors correlated with TOC concentration were mainly WT, TN, Cond, COD_Mn, and TP, among which WT and Cond showed a significant linear relationship with TOC concentration (edf = 1, p < 0.05), while TN, COD_Mn, and TP had a significant nonlinear relationship with TOC concentration (edf > 1, p < 0.05). Comprehensive trophic level index (TLI) and TOC concentration revealed a highly significant correlation (R² = 0.414, p < 0.001). Therefore, the GAM model could well explain the environmental factors associated with the spatio-temporal dynamics of TOC concentration, providing a reference for the evaluation of water quality and research on the carbon cycle in similar inland reservoirs.

In order to study the vertical distribution characteristics of phytoplankton in the Danjiangkou Reservoir, the water source of the Middle Route Project of the South-North Water Diversion, seven sampling sites were set up in the Reservoir for quarterly sampling from 2017 to 2019, and water environment surveys were conducted simultaneously. The results showed that 157 species (including varieties) were identified, belonging to 9 phyla and 88 genera. In terms of species richness, Chlorophyta had the largest number of species, accounting for 39.49% of the total species. The Bacillariophyta and Cyanobacteria accounted for 28.03% and 13.38% of the total species, respectively. From the whole Danjiangkou Reservoir, the total phytoplankton abundance varied from 0.09 × 10² to 20.01 × 10⁶ cells/L. In the vertical distribution, phytoplankton were mainly observed in the surface–thermospheric layer (I–II layer) and the bottom layer, while the Shannon–Wiener index showed a trend of gradually decreasing from the I–V layer. The Surfer model analysis showed that there was no significant stratification in the Q site’s water temperature (WT) and dissolved oxygen (DO) levels in the water diversion area during the dynamic water diversion process. A canonical correspondence analysis (CCA) showed that DO, WT, pH, electrical conductivity (Cond), chemical oxygen demand (COD_Mn), total phosphorus (TP), ammonia nitrogen (NH₄⁺-N), and total nitrogen (TN) had significant effects on the vertical distribution of phytoplankton (p < 0.05). A partial Mantel analysis showed that the vertical distribution of the phytoplankton community was related to WT, and the phytoplankton community structure at the other sites, except for Heijizui (H) and Langhekou (L), was affected by DO. This study has positive significance for exploring the vertical distribution characteristics of a phytoplankton community in a deep-water dynamic water diversion reservoir.

Supersaturated dissolved oxygen and magnetization (SDOXM) technology is a composite technology that combines supersaturated dissolved oxygen with water magnetization technologies. Compared with conventional water purification technology, the advantages introduced by such technology include obvious and efficient improvement in purified water quality without adding any chemicals, removing sludge and changing the original function of the river. In this study, taking the Middle-Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC) as a pilot project, the effects of the SDOXM composite process on microbial activity, phytoplankton community structure, and removal efficiency of the main nutritional indexes in the canal of the MR were evaluated. Aiming at static and flowing water bodies, this study was divided into two parts: static and dynamic experiments (two groups: a group with artificial aquatic plants and another group without artificial aquatic plants). The performance of the SDOXM system was assessed by monitoring the organic matter removal as well as the relative light unit (RLU) of ATP, changes in the community structure of phytoplankton, and the effects of artificial aquatic plants as a biofilm carrier on organic matter removal and microbial activity. During the study period, SDOXM technology was able to increase the concentration of dissolved oxygen (DO) in water and maintained the state of supersaturation for more than three days. The removal effect of organic matter from water was obvious. The community structure of phytoplankton changed from the Bacillariophyta-Cyanophyta type to the Bacillariophyta-Cyanobacteria type. Finally, the introduction of artificial aquatic plants has contributed to the improvement in water quality. Therefore, SDOXM technology can be used as a new water quality improvement technology to enhance the self-restoration ability of a river natural ecology.