Integrated modeling for evaluating microbial pollution in an urban freshwater coastal river

Urban coastal rivers face complex interactions between combined sewer overflows (CSOs), river discharge, and water quality, yet the fate of microbial contaminants as controlled by urban stormwater runoff and CSOs remains underexplored. This study presents an integrated modeling framework that combines urban hydrologic, 3-dimensional (3D) river hydrodynamic, sediment transport, and microbial fate and transport models. The framework is applied to the Buffalo River in Buffalo, New York, to assess the impacts of various dynamic conditions on E. coli concentrations. The model was calibrated and verified with E. coli and total suspended solids (TSS) data collected in 1993, 2000, and 2020. Model performance was within acceptable limits, with Percent Bias (PBIAS) ranging from −10.3 to 14.8 and index of agreement (d) exceeding 0.88 for both TSS and E. coli concentrations across low, average, and high-water level scenarios. In 2020, despite lower CSO discharges, peak E. coli concentrations were higher than in 2000, primarily due to significantly lower river discharge that reduced the river's capacity for dilution. The results also show that a significant seiche event on November 15, 2020 caused a temporary reduction in E. coli concentrations, with values at a downstream location decreasing from 20 CFU/mL to 0.04 CFU/mL over only 3 hours. However, while seiches can cause short-term dilution, the effects are transient and quickly reversed by subsequent CSO discharges. Additionally, a scenario in which water level in 2020 was lowered by 1 meter (m) was shown to decrease daily E. coli deposition by 39%, and the total E. coli in the river by 37%, while E. coli resuspension increased but remained a secondary contributor to overall contamination. This integrated modeling framework provides a valuable tool for predicting E. coli concentrations and managing water quality risks in urban rivers and potential impacts on urban waterways, especially in the context of future climate variability.