Poyang Lake is the largest freshwater lake in China and a globally important wetland with various functions. Exploring the multidecadal trend of water quality and hydroclimatic conditions is important for understanding the adaption of the lake system under the pressure from multiple anthropogenic and meteorological stressors. The present study applied the Mann–Kendall trend analysis and Pettitt test to detect the trend and breakpoints of hydroclimatic, and water quality parameters (from the 1980s to 2018) and the trend of monthly–seasonal ammonia (NH₄-N) and total phosphorus (TP)concentrations (from 2002 to 2018) in Poyang Lake. Results showed that Poyang Lake had undergone a highly significant warming trend from 1980 to 2018, with a warming rate of 0.44 °C/decade in terms of annual daily mean air temperature. The wind speed and water level of the lake presented a highly significant decreasing trend, whereas no notable trend was detected for precipitation variations. The annual mean total nitrogen (TN), NH₄-N, TP, and permanganate index (CODMₙ) concentrations showed significant upward trends from the 1980s to 2018. Remarkable abrupt shifts were detected for TN, NH₄-N, and CODMₙ in around 2003. They were in accordance with the water level breakpoint of the lake, thus implying the important role of hydrological conditions in water quality variations in floodplain lakes. A significant increasing trend has been detected for Chl-a variations during wet season from 2008 to 2018, which could be attributed to the increasing trend of nutrient concentration during the nutrient-limited phase of Poyang Lake. These hydroclimatic and water quality trends suggest a high risk of increasing phytoplankton growth in Poyang Lake. This study thus emphasizes the need for adaptive lake eutrophication management for floodplain lakes, particularly the consideration of the strong trade-off and synergies between hydroclimatic conditions and water quality variations.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

In this study, the Songgang River (SR) was selected as a typical tributary that is heavily polluted by rapid urbanization and industrialization. The polycyclic aromatic hydrocarbon (PAH) distribution at five representative sampling sites from different urban functional areas was studied. The chemical and physical properties and spatial and vertical distribution of PAHs in sediments were investigated. PAH source identification and the ecological risks of the sediments were evaluated. The results suggested that the industrial zone and dense residential and commercial areas were the most contaminated areas of the SR, as the chemical and physical properties of total organic carbon content in sediments was the highest at the dense residential and commercial areas (0.1–4.5%); however, the acid volatile sulfide, total nitrogen, and total phosphorus contents were the highest in the industrial zone, with ranges of 700.0–1618.4 mg/kg dw, 22.4–3543.9 mg/kg dw, and 82.3–4550.7 mg/kg dw, respectively. The spatial distribution of residual PAHs in the sediment cores showed a wide variation among different urban functional areas, and the vertical characterization (0–300 cm) depicted a significant decreasing trend with depth and with an abrupt increase at 180 cm. The concentration of ∑16 PAHs ranged from 208.7 to 7709.8 ng/g dw, with the highest concentrations obtained in the industrial zone. The low molecular weight-PAHs (153–6720 ng/g dw) were predominant in the sediments. Furthermore, there were combined sources (biomass burning: 40.3%; fossil fuel combustion: 25.5%; mixed source: 21.5%; oil pollution: 12.7%) and a long term accumulation effect, with anthropogenic activities and industrial pollution as the major contributing sources. The concentrations of Nap, Acy, Ace, Flu, and Ant exceeded the lower limit of the sediment quality criteria, and higher toxic equivalent concentration values of the total carcinogenic PAHs were observed nearby the midstream of the SR, which may cause adverse biological effects and implies a need for regular monitoring.

Uncertainty assessment of parameters associated with non-point source pollution mechanism modeling are crucial for improving the effectiveness of pollution controlling. In this study, an approach based on Bayesian inference and integrated Markov chain Monte Carlo and multilevel factorial analysis has been developed, and it can not only apply straightforward Bayesian inference to assess parameter uncertainties, but also quantitatively investigate the main and interactive effects of multiple parameters on the model response variables by measuring the specific variations of model outputs. Its applicability and advantages are presented through the application of the Soil and Water Assessment Tool to Shitoukoumen Reservoir Catchment in northeast China. This study investigated the uncertainties of a set of sensitive parameters and their multilevel effects on model response variables, including average annual runoff (AAR), average annual sediment (AAS) and average annual total nitrogen (AAN). Results revealed that (i) soil conservation service runoff curve number for moisture condition II (CN2) had a positive effect on all response variables; (ii) available water capacity of the soil layer (SOL_AWC) had a negative effect on all response variables; (iii) the universal soil loss equation support practice (USLE_P) had a positive effect on AAS and AAN, and little effect on AAR; while the nitrate percolation coefficient (NPERCO) had a positive effect on AAN, and little effect on AAS and AAR; and (iv) the interactions amongst parameters had obvious interdependent effects on the model response variables, for example, the interaction between CN2 and SOL_AWC had a major impact on AAR. The above findings can improve the simulating and predicting capabilities of non-point source pollution mechanism model. Overall, this study highlights that the proposed approach represents a promising solution for uncertainty assessment of model parameters in non-point source pollution mechanism modeling.

Lake eutrophication has become a serious environmental problem in China. Manipulations covering more elements of trophic pyramid are methods for lakes to obtain clear water state and should be studied in detail. In the present study, Meishan Dongpo Lake was divided into two parts, and a combined biomanipulation project was conducted in one part (RLake), and the other part was used as a control (CLake). Species of submerged-plant, fish, macrobenthos, and zooplankton were screened and a certain number of them were added to adjust the eco-chain in RLake. After restoration, the coverage of submerged macrophytes reached >85%; zooplankton greater than 0.6 mm in size increased in number, and the ratio of zooplankton biomass to chlorophyll-a (Chl-a) concentration increased. The dominant fish species changed, and disturbance of the sediment was reduced. The average density of mollusks in RLake was 111.5 ± 19.8 ind m⁻², which was much higher than that in CLake (36.7 ± 2.1 ind m⁻²). Water quality and clarity were substantially improved, and nutrient concentrations, particularly total phosphorus, total nitrogen, and Chl-a were significantly reduced. The aquatic community parameters were negatively correlated with the nutrient parameters and Chl-a. The ecological restoration have adjusted the aquatic ecosystem in RLake, and many positive feedback effects among the aquatic communities made them remove internal nutrients and Chl-a more efficiently.

High concentrations of microcystins (MCs) in sediment pose a serious hazard to aquatic and terrestrial organisms. Hence, we investigated the seasonal variation of dominant MCs (MC-LR, MC-RR and MC-YR) in sediments of Lake Taihu over four seasons for the first time. Sediment MCs varied seasonally (p < 0.01) with concentrations highest in August and lowest in February. The MCs were dominated by MC-LR (61.47%) with the content ranging from 0.02 to 2.37 μg/g dry weight in sediment. The three MC congeners and their proportions were significantly correlated with latitude and longitude. Meiliang Bay in the north had the highest MCs of all sites, while the eastern part of the lake had a high level especially in August. Variation of MC-LR and MC-RR concentrations was significantly correlated (p < 0.05) with water temperature, dissolved total organic carbon, cyanobacteria density, total suspended solid particles, and total organic carbon and total nitrogen in sediment, while MC-YR was negatively correlated (p < 0.01) with nutrients in the water column and heavy metals in sediments. An ecological risk assessment suggested the MCs already pose significant adverse effects on Potamopyrgus antipodarum; although the adverse effects on humans were weak, children were at greater risk than adults.

Organ carbon are often used to enhance denitrification in wastewater treatment. However, their possible effects on microbial interactions are very limited. In this work, an anaerobic ammonium oxidation (anammox) coupled with sulfur autotrophic/mixotrophic denitrification (SAD/SMD) system was used to investigate the changes in microbial interactions among the microbial communities under different nutrient condition. The removal efficiency of total nitrogen increased from 70% (SAD) to 97% (SMD). The Illumina sequencing analysis indicated that Planctomycetes was the most dominant bacterial phylum in anammox system. Thiobacillus and Sulfurimonas, two typical autotrophic denitrifiers, decreased significantly from 31.9% to 17.7%–12.2% and 9.3%, when the nutrient condition changed from SAD to SMD (P < 0.05). Meanwhile, some heterotrophic or mixotrophic denitrifying bacteria, including Gemmobacter, Pseudomonas and Thauera increased significantly (P < 0.05). Molecular ecological network (MEN) analysis showed that the addition of organic carbon substantially altered the overall architecture of the network. Compared with SAD, the SMD had shorter path lengths, indicating higher transfer efficiencies of information and materials among different microorganism. The addition of organic carbon increased the microbial interaction complexity of Proteobacteria. The links of Thiobacillus, which was a typical sulfur-oxidizing autotrophic denitrifying bacteria, significantly reduced (P < 0.05) with the addition of organic carbon, while the links of the heterotrophic bacteria Geobacter significantly increased (P < 0.05). This study provided new insights into our understanding of the shifts in the bacteria community and their microbial interactions under different nutrient conditions (SAD and SMD) in sulfur-supported denitrification system.

Improper land-use changes may lead to a loss of soil resources and cause environmental pollution. Chinese Torreya plantation (hereafter CTP) is an important cash tree plantation for nuts production in the mountainous areas of subtropical China. The increasing development of CTPs, to increase seed production, can result in the complete erasure of local natural vegetation.In this study, the vulnerability to soil erosion, loss of soil organic carbon (SOC) and nutrients in CTPs due to land-use change were evaluated. The results indicated that the rates of diffusive soil erosion in the young CTPs with extreme precipitation were about six-fold higher than with the natural vegetation. At sites with a similar slope, there was no significant difference in soil erosion levels between the young and old CTPs. The old CTPs did not hold significantly higher levels of SOC and soil total nitrogen (STN) in their topsoil when compared with the young CTPs. The natural mixed broadleaved subtropical forests lost about 35% of their SOC and 25% of their STN after they were converted into CTPs, but the CTPs had higher soil total phosphorus. The C: N ratios at the different sites were close to 11:1, but the N: P ratios were diverse. There were high levels of organic carbon, nitrogen and phosphorus in stream water. Adequate coverage of natural vegetation within or around the CTPs should be maintained to decrease soil erosion and nutrient loss. Suggestions to develop CTPs while protecting the environment are discussed. Overall, it was determined that aspects of the current management practices and strategies for developing CTPs should be changed to decrease soil erosion and nutrient loss.

Nitrogen (N) plays an important role in agriculture crop production but the increasing application of nitrogen increases the possibilities of groundwater contamination through nitrate leaching. Nitrate leaching is the inevitable part of agriculture production which occurs during nitrogen fertilization. Hence, the quantification of nitrogen fertilizer is required to reduce nitrate leaching. In this study, nitrogen transformation and transport such as ammonium (NH₄⁺) and nitrate (NO3−) at different soil depths and maize crop growth stages were measured during field experiments for two sowing dates (timely and delay) and four N fertilization levels under irrigated (year 2013 and 2014) and rainfed (year 2012 and 2014) conditions for maize crop. NH₄⁺, NO3− and total nitrogen concentrations were measured using spectrophotometer at 410 nm and Kjeldahl method at varying soil depths and maize crop growth stages. Thereafter, nitrogen balance approach was used to estimate the NO3− leaching. Results indicated that NO3− leaching in irrigated condition was higher 109% in N₇₅, 179% in N₁₀₀, and 292% in N₁₂₅ level respectively in comparison to the N₀ level in timely sowing date, while in delayed sowing date, leaching was higher 54% in N₇₅, 123% in N₁₀₀, and 184% in N₁₂₅ level respectively in comparison to N₀ level. In rainfed, the NO3− leaching was higher 30% in N₆₀, 59% in N₈₀, and 99% in N₁₀₀ level respectively in comparison to N₀ level for the timely sowing date, while in delayed sowing, leaching was higher 23% in N₆₀, 44% in N₈₀, and 78% in N₁₀₀ level respectively in comparison to N₀ level. The results indicate that leaching losses were less in timely sowing dates for both rainfed and irrigated maize. The study further reveals that sowing dates combination with N levels could be an effective management strategy to reduce NO3− leaching by minimizing the N fertilization.

In this study, the seasonal characteristics of microbial community compositions at different sites in a river under anthropogenic disturbances (Maozhou River) were analyzed using Illumina HiSeq sequencing. Taxonomic analysis revealed that Proteobacteria was the most abundant phylum in all sites, followed by Actinobacteria, Bacteroidetes, Chloroflexi, Acidobacteria and Firmicutes. The variations of the community diversities and compositions between the seasons were not significant. However, significant differences between sites as well as water and sediment samples were observed. These results indicated that sites under different levels of anthropogenic disturbances have selected distinct bacterial communities. pH, dissolved oxygen (DO), concentrations of total nitrogen (TN) and heavy metals were the main factors that influence the diversity and the composition of bacterial community. Specifically, the relative abundance of Proteobacteria was negatively correlated with pH and DO and positively correlated with TN, while Actinobacteria and Verrucomicrobia showed the opposite pattern. Moreover, positive correlations between the relative abundances of Firmicutes and Bacteroidetes and the concentration of heavy metals were also found. Results of functional prediction analysis showed no significant differences of the carbon, nitrogen and phosphorus metabolism across the sites and seasons. Potential pathogens such as Vibrio, Arcobacter, Acinetobacter and Pseudomonas were found in these samples, which may pose potential risks for environment and human health. This study reveals the effect of anthropogenic activities on the riverine bacterial community compositions and provides new insights into the relationships between the environmental factors and the bacterial community distributions in a freshwater ecosystem under anthropogenic disturbances.