Impact of Wastewater Effluent on Aquatic Microbial Communities in Urban Rivers

Thesis Abstract

Urban rivers are increasingly influenced by municipal wastewater discharges, which alter microbial community structure, function, and resilience, with implications for ecosystem health and water quality. This study investigates how wastewater effluent shapes aquatic microbial communities in urban rivers, addressing the problem of degraded microbial diversity and altered biogeochemical processes linked to anthropogenic inputs. The aims are to (i) quantify changes in microbial diversity, community composition, and functional potential downstream of wastewater outlets; (ii) identify environmental drivers (nutrients, contaminants, hydraulic regime) associated with microbial shifts; and (iii) assess the relationship between microbial dynamics and indicators of water quality and ecosystem health. Specific objectives include (a) characterizing bacterial and archaeal taxa using 16S rRNA gene amplicon sequencing across a transect from upstream control sites to multiple downstream wastewater-impacted sites; (b) profiling microbial functional genes (nitrogen, phosphorus cycling, and xenobiotic degradation) via metagenomic sequencing; (c) measuring physicochemical parameters (conductivity, pH, turbidity, dissolved oxygen, nutrients, micropollutants) and standard water quality indicators (BOD, COD, total coliforms); (d) evaluating temporal variation across wet and dry seasons with repeated sampling at six sites over a 12-month period; and (e) applying multivariate statistics and structural equation modeling to link environmental drivers with microbial community dynamics and biogeochemical function. A cross-sectional and longitudinal observational design will be employed, with the population comprising microbial communities in the upper, mid, and lower reaches of three urban rivers receiving varying intensities of municipal wastewater effluent. A stratified random sampling approach will select six monitoring sites per river (three upstream reference sites and three downstream impact sites), with monthly sampling yielding 72 sample events. Data collection will integrate high-throughput sequencing (Illumina MiSeq 16S rRNA V3–V4 region for taxonomic profiling; metagenomic shotgun sequencing for functional potential) and quantitative assays for nutrients (nitrate, ammonium, phosphate), organic matter (COD/BOD), turbidity, and indicators of microbial contamination (coliform counts). Analytical techniques will include alpha and beta diversity analyses (Shannon, Simpson indices; Bray-Curtis dissimilarity), differential abundance testing (DESeq2), functional annotation (KEGG, COG), and multivariate ordination (PCA, NMDS). Regression and generalized linear models will quantify relationships between environmental variables and microbial metrics, while structural equation modeling (SEM) will test hypothesized causal pathways linking effluent characteristics, microbial community shifts, and biogeochemical processes such as nitrogen and phosphorus cycling. The theoretical framework will draw on the Community Assembly Theory (niche-based and neutral processes) and the Pollution-Induced Community Change model to interpret observed patterns, with support from the Eco-Engineering Theory to relate microbial responses to ecosystem functioning. Expected findings include a decline in microbial alpha diversity downstream of effluent discharges, enrichment of taxa associated with nutrient loading and contaminant degradation, and elevated abundance of genes related to xenobiotics and nitrogen cycling in downstream sites. Seasonal variation is anticipated, with stronger perturbations during wet seasons due to dilution and dilution-adjusted pollutant loads. The study is expected to reveal clear links between physicochemical stressors (ammonium, nitrate, phosphates, dissolved organic carbon, and trace organics) and microbial community reorganization, along with measurable shifts in biogeochemical potential (e.g., enhanced nitrification-denitrification capacity or impaired phosphorus removal) downstream. The contribution to knowledge lies in integrating taxonomic, functional, and environmental data to elucidate how wastewater effluent reorganizes aquatic microbiomes and affects ecosystem services in urban rivers, thereby informing microbial-based indicators of river health and guiding wastewater management strategies. Conclusions will emphasize the need for improved source control and treatment efficiency to mitigate microbial community disruption, and recommendations will focus on implementing upstream natural treatment buffers, optimizing municipal wastewater treatment to reduce micropollutants, and establishing microbial indicators for routine river health monitoring.