3.1 Spatial and temporal variations of water quality characteristics
As shown in Fig. 2a, the change trend of the average water temperature (T) in Changxing River was summer (31.3 ℃) > autumn (22.6 ℃) > spring (14 ℃) > winter (7.6 ℃). pH was neutral to slightly alkalescent (7.0-7.9), which may be related to the nature of the upstream soil (Guo, 2017), or affected by the surface runoff of irrigation from farmland (Feng et al., 2017). The concentrations of DO in summer and autumn were 3.98 mg/L and 3.49 mg/L, respectively. They were both lower than the Class III standard limit (≥ 5 mg/L) of the surface water environmental quality standard (GB3838-2002), and significantly (p < 0.0001) lower than those in winter and spring (9.50, 7.77 mg/L). There was a significant negative correlation between DO and T (r = -0.790, p < 0.01), indicating that DO was generally higher in the dry season due to the influence of rainfall and temperature (Shi et al., 2017).
The concentration of TN in autumn was the highest (4.99 mg/L), followed by spring (4.50 mg/L), winter (4.31 mg/L) and summer (3.22 mg/L). The concentration of NH4+-N in autumn was also the highest (1.92 mg/L). In other seasons, NH4+-N concentrations also exceeded the limit of Class III of the environmental quality standard for surface water (≤ 1 mg/L). NO3−-N was the main form of inorganic nitrogen in the water body of Changxing River (58%). The concentrations of NO3−-N in summer and autumn (1.65 and 1.96 mg/L, respectively) were significantly lower than those in winter and spring (2.74 and 3.06 mg/L, respectively). The concentrations of TP in summer and autumn (0.39 and 0.44 mg/L, respectively) were higher than those in winter and spring (0.16 and 0.18 mg/L, respectively).
ANOVA analysis in Fig. 2b found that T, P, pH, ORP, NO2−-N, and NO3−-N didn’t change significantly among the four pollution types (p > 0.05). The concentrations of TDS, EC, and SAL in water samples from the discharge outlets of urban wastewater treatment plants (II) were 307 mg/L, 422 µS/cm and 0.24 ng/L, respectively, which were all higher than other pollution source types. It was mainly related to the effluent composition of the sewage treatment plant. The concentrations of TN, NH4+-N, TP, TOC, and CODMn were the highest at the monitoring points of the storm water outlets (III), indicating that the pollution of the storm water outlets (III) was relatively serious. The average concentrations of TN, NH4+-N, and TP in water samples from the storm water outlets (III) were 5.30, 2.19, and 0.55 mg/L, respectively, which were 1.2-1.7, 2.4-5.2 and 3.0-3.9 times higher than those for other pollution types (p < 0.01). According to the statistical analysis, the NH4+-N emissions of domestic sewage in Changxing County (597 tons) accounted for 89.6% of the total NH4+-N emissions in 2018, indicating that the rain sewage discharge at the storm water outlets (III) had an impact on the concentration increase of TN, NH4+-N and TP in Changxing River sections.
In addition, the lowest amount of DO was found at the estuary of Taihu Lake (I) during the autumn cyanobacteria bloom (2.20 mg/L) in Fig. 2c. Simultaneously, comparing with other seasons and pollution types, the concentrations of NH4+-N and TP were particularly prominent at the storm water outlets (III) in autumn (3.62 and 0.99 mg/L, respectively). The issue of commingling discharge of rain precipitation and municipal sewage at the storm water outlets (III) in autumn had a particularly significant impact on the nutrient level in Changxing River.
In general, the average concentrations of NH4+-N, TN, and TP in Changxing River in autumn were 1.92, 4.99, and 0.44 mg/L, respectively, which were the highest. The sites with the highest concentrations of nutrient pollution occurred in the storm water outlets (III) with NH4+-N, TN, and TP concentrations of 2.19, 5.30 and 0.55 mg/L, respectively.
3.2 Analysis of microbial community in Changxing river
The Shannon index characterizes the diversity of microbial community, whereas the Chao1 index represents the species richness in microbial communities (Ren et al., 2018). The results showed that seasonal variation was the main factor affecting the diversity of microbial community (Fig. 3). The diversity of aquatic microbial communities in summer was the highest, with Shannon and Chao1 indexes of 9.4 and 3,278, respectively. In summer, high temperature can enhance the activity of microorganisms, and surface runoff from precipitation can introduce microorganisms and nutrients from the upstream (Feng et al., 2016), contributing to the highest diversity.
The estuary of Taihu Lake (I) had the highest Shannon index (8.2), while the non-point source agricultural drainage areas (IV) had the lowest Shannon index (7.1). The Chao1 index of the discharge outlets of urban wastewater treatment plants (II) was the highest (1,974), while the Chao1 index of the non-point source agricultural drainage areas (IV) was the lowest (1502). According to the analysis, the geographic location of the estuary of Taihu Lake (I) and the effluent sludge of the urban wastewater treatment plants (II) both affected the diversity of the microbial population of the sewage body (Lu et al., 2016; Tang et al., 2016). In general, the diversity of the microbial community at the monitoring points of different pollution types was not significant. The functional redundancy between microbial groups and the hydraulic distribution of rivers may stabilize microbial diversity against environmental fluctuations (Zeglin, 2015).
Proteobacteria was the dominant phylum across all monitoring sites (accounting for 45.8% on average), followed by Bacteroidetes (18.9%), Cyanobacteria (12.8%), Firmicutes (4.6%), Actinobacteria (4.0%), Euryarchaeota (1.7%), Chloroflexi (1.6%), Acidobacteria (1.5%), Verrucomicrobia (1.0%), and Nitrospirae (0.9%). According to the Kruskal-Wallis Test, the dominant phyla in summer included Proteobacteria (40.9%), Bacteroidetes (21.0%), Euryarchaeota (6.1%). Further, the relative abundance of Euryarchaeota (6.12%, p < 0.001) and Nitrospirae (3.13%, p < 0.001) in summer were significantly higher than other seasons. Analysis of similarities (ANOSIM) revealed significant differences in the relative abundance of dominant microbial community (R = 0.62, p = 0.001) between different seasons.
Note that the relative abundance of Cyanobacteria was the highest at the non-point source agricultural drainage areas (IV, 32.3%) (Fig. 4) due to the influence of agricultural non-point source nitrogen pollution load. This phenomenon was especially prominent in autumn. At the estuary of Taihu Lake (I), Cyanobacteria were highly enriched, in autumn and spring, at the highest of 41.9% in spring. This was in good agreement with previous studies reporting the highest algae bloom in March at the estuary of Taihu Lake (I) (Hampel et al., 2018). At the same time, the backflow and retention of inflow-rivers are more frequent during normal and dry seasons (i.e., spring). Therefore, Cyanobacteria in Changxing River are attributed to the eutrophication of the non-point source agricultural drainage areas in autumn and backflow of algae in Taihu Lake in spring.
However, Proteobacteria was relatively abundant in water samples collected at the discharge outlets of urban wastewater treatment plants (II, 53.8%) and the storm water outlets (III, 55.2%), which may be related to their roles in nitrification, denitrification, and other functions.
At the genus level, more taxa showed distinctive differences in their relative abundances among different seasons or pollution types. The heatmap in Fig. 6 showed the genera with the top 80 relative abundances in Changxing River. Dominant genera included Microcystaceae (19.3%), Flavobacterium (9.6%), and Pseudomonas (8.9%).
Microcystis in the genera of Microcystaceae is one of the most dominant cyanobacteria found in the algae blooms at Taihu Lake, which has attracted great attention since it is culprit that secrets highly toxic and persistent microcystin (Shi et al., 2015). The microbial community analysis results showed that the relative abundance of Microcystaceae in spring and autumn (19.8% and 14.3%, respectively) was higher than that in summer and winter (2.4% and 9.7%, respectively). The two highest relative abundances were observed at the non-point source agricultural drainage areas (IV, 47.7%) in autumn and the estuary of Taihu Lake (I, 41.9%) in spring. Although Microcystaceae was relatively high in general at the non-point source agricultural drainage areas (IV) due to the input of agricultural non-point source nitrogen load (Paerl et al., 2016), only in the spring, the Microcystis at the estuary of Taihu Lake (I) had the highest relative abundance (41.9%). Previous investigations have shown March as the month with the heaviest cyanobacterial blooms in Taihu Lake (Hampel et al., 2018). During the dry season or the flat water period, backflow stagnation occurs frequently at the river channels around the lake. This likely explains why the Microcystaceae was highly enriched in the Taihu Lake in the spring. The optimal TN/TP ratio in water to promote algae blooms is between 13-35. When this ratio is below 13, cyanobacteria bloom can rarely occur. According to our water quality monitoring data, the TN/TP ratio at the estuary of Taihu Lake (I) was 8 in summer, and the other seasonal ratios were between 20 and 35, but there was no cyanobacteria bloom at the estuary of Taihu Lake (I) in winter. It indicated that the relatively high abundance of Microcystis at the estuary of Taihu Lake (I) in spring and autumn was mainly caused by algae backflow.
The relative abundance of Flavobacterium belonging to Bacteroidetes was relatively high in winter (11.0%), which may be related to the psychrophilic nature of several species in Flavobacterium (Lopes et al., 2016). In addition, Flavobacterium exhibited the highest relative abundances (15.6%-19.0%) at the discharge outlets of urban wastewater treatment plants (II) and the storm water outlets (III). Some Flavobacterium species can participate in denitrification, although this genus also contains fish pathogens(Liu et al., 2017b).
The relative abundances of Pseudomonas in winter and spring (7.5%-8.3%) were higher than in summer and autumn (0.5%-1.6%). Bacteria belonging to Pseudomonas were highly enriched at the discharge outlets of urban wastewater treatment plants (II, 12.6%-17.6%) and the storm water outlets (III, 12.0%-12.4%). Pseudomonas contains a diversity of heterotrophic bacteria and some of them are known to perform denitrification at low temperature (Yang et al., 2018b).
In addition to Flavobacterium and Pseudomonas, there were other denitrifying bacteria prevalent in Changxing River Acinetobacter, Rhodobacter, Dechloromonas, Thiobacillus, Hydrogenophaga, Aeromonas, Stenotrophomonas, Zoogloea, Comamonas, etc. (Zhang et al., 2011; Zhou et al., 2016b; Kim et al., 2018; Li et al., 2018b; Martinez-Santos et al., 2018; Zhou et al., 2019) showed high relative abundances in autumn and significant enrichment at the storm water outlets (III). Microorganisms can participate in ammonia oxidation alone (Fitzgerald et al., 2015), such as Sphingomonas and Nitrospirae, showed relatively low abundance (0.1% and 0.9%).
3.3 Correlation between microbial communities and environmental variables
Redundancy analysis (RDA) was conducted to evaluate relationships between relative abundances of dominant genera and environmental variables detected in the water samples. As shown in Fig. 7a, T, CODMn, DO, P, and NO2−-N had a relatively large impact on the seasonal distribution differences of the microbial community in Changxing River. Due to the large number of environmental variables with influence effects, the BIOENV analysis was used to identify the best combination of environmental variables. Therefore, T, P, TP, and CODMn were the highest combination and the interpretation quantity of the BIOENV analysis is 78.3%. Although the environmental variables had little influence on the distribution of microbial community in different pollution types in Changxing River. The microbial community structure at the storm water outlets (III) was still significantly affected by TP, T and CODMn in summer, and affected by NH4+-N in autumn (Fig. 7b).
As shown in Fig. 8a, Proteobacteria, Bacteroidetes and Firmicutes were positively correlated with EC, TP, TN, TDS, and SAL. Actinobacteria and Cyanobacteria were positively correlated with DO, NO3−-N, and P. Acidobacteria, Euryarchaeota, Chloroflexi, Acidobacteria, Verrucomicrobia and Nitrospirae were positively correlated with CODMn, T, ORP, and pH.
At Taihu Lake, Microcystis and Nostocaceae were highly abundant and their relative abundances were positively correlated with pH. Previous studies revealed that higher pH of the water body can promote the growth and reproduction of cyanobacteria (Unrein et al., 2010; Wood et al., 2015). Microcystis was also positively correlated to DO (Fig. 8b). In addition, Microcystis is more competitive for NH4+-N than most nitrifying bacteria (Paerl et al., 2014; Hampel et al., 2018), and serious accumulation of Microcystis may inhibit the nitrogen cycle of aquatic ecosystems.
3.4 Suggestion for remediation of Changxing River
According to the above results, restoration of the estuary of Taihu Lake (I) should focused on addressing the accumulation problem of cyanobacterial blooms caused by the backflow of cyanobacteria from Taihu Lake and strengthening the colonization of nitrifiers and denitrifiers. In the spring, the DO is sufficient and the pH is high. The pH of the water body can be lowered by increasing the hydraulic circulation in the detention area (Cerco et al., 2013), such as connecting water systems, ecological water replenishment and installing aeration push flow (Lilndenschmidt, 1999). Simultaneously, the cyanobacteria can be removed in situ by arranging enclosures, floating dam interceptions. In the autumn, the DO content is low and the NH4+-N content is high due to the eutrophication at the non-point source agricultural drainage areas (IV). Reoxygenation and capping zeolite or clay materials can be used to enhance the colonization of ammonia-oxidizing bacteria (Arnon et al., 2007; Chen et al., 2018). Moreover, the external load into the lake can be reduced by increasing rural sewage treatment and controlling agricultural non-point source pollution. Precise ecological dredging of sediments can also be carried out to effectively reduce the internal load and curb the release of nutrients from sediments.
This study found that the DO content at the storm water outlets (III) was low, especially in summer and autumn. The lowest DO was only 1.7 mg/L, impairing nitrifying bacteria. Current common rainwater restoration technologies include artificial aeration (Tang et al., 2009; He et al., 2012), aquatic plant restoration (Zeng et al., 2017; Liu et al., 2019), etc., but their effects on nitrification and denitrification is still limited (Lu et al., 2014). Effective nitrification requires high DO levels (e.g., >8 mg/L). At low DO levels (3 mg/L), ammonia nitrogen removal efficiency can be greatly hindered by 50% or more. Nitrobacteria generally turn to anaerobic respiration when the oxygen concentration is lower than 6.4 mg/L (Wang et al., 2015). Therefore, intermittent aeration may be needed to maintain the DO concentration between 5-6 mg/L at the storm water outlets (III). Biological processes can be integrated to bolster nitrifying bacteria populations and two successful cases include a novel water biofilm pretreatment process with reed addition (Feng et al., 2013) and bioactive thin layer coverage that enhances in situ microbial regeneration (Zhou et al., 2016b).