Dataset Information

Modeling Contaminant Microbes in Rivers During Both Baseflow and Stormflow.

ABSTRACT: Rivers transport contaminant microorganisms (including fecal indicator bacteria and human pathogens) long distances downstream of diffuse and point sources, posing a human health risk. We present a mobile-immobile model that incorporates transport as well as immobilization and remobilization of contaminant microbes and other fine particles during baseflow and stormflow. During baseflow conditions, hyporheic exchange flow causes particles to accumulate in streambed sediments. Remobilization of stored particles from streambed sediments occurs slowly during baseflow via hyporheic exchange flow, while remobilization is vastly increased during stormflow. Model predictions are compared to observations over a range of artificial and natural flood events in the dairy contaminated Topehaehae Stream, New Zealand. The model outputs closely matched timing and magnitude of E. coli and turbidity observations through multiple high-flow events. By accounting for both state-of-flow and hyporheic exchange processes, the model provides a valuable framework for predicting particle and contaminant microbe behavior in streams.

SUBMITTER: Drummond JD

PROVIDER: S-EPMC9286818 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Modeling Contaminant Microbes in Rivers During Both Baseflow and Stormflow.

Drummond J D JD Aquino T T Davies-Colley R J RJ Stott R R Krause S S

Geophysical research letters 20220418 8

Rivers transport contaminant microorganisms (including fecal indicator bacteria and human pathogens) long distances downstream of diffuse and point sources, posing a human health risk. We present a mobile-immobile model that incorporates transport as well as immobilization and remobilization of contaminant microbes and other fine particles during baseflow and stormflow. During baseflow conditions, hyporheic exchange flow causes particles to accumulate in streambed sediments. Remobilization of st ...[more]

PMID: 35866058

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Project description:Since sewage is a hotspot for antibiotic resistance genes (ARGs), the identification of ARGs in environmental waters impacted by sewage, and their correlation to fecal indicators, is necessary to implement management strategies. In this study, sewage treatment plant (STP) influent samples were collected and analyzed using quantitative polymerase chain reaction (qPCR) to investigate the abundance and correlations between sewage-associated markers (i.e., Bacteroides HF183, Lachnospiraceae Lachno3, crAssphage) and ARGs indicating resistance to nine antibiotics (belonging to aminoglycosides, beta-lactams, sulfonamides, macrolides, and tetracyclines). All ARGs, except bla VIM, and sewage-associated marker genes were always detected in untreated sewage, and ermF and sul1 were detected in the greatest abundances. intl1 was also highly abundant in untreated sewage samples. Significant correlations were identified between sewage-associated marker genes, ARGs and the intl1 in untreated sewage (τ = 0.488, p = 0.0125). Of the three sewage-associated marker genes, the BIO-ENV procedure identified that HF183 alone best maximized correlations to ARGs and intl1 (τ = 0.590). Additionally, grab samples were collected from peri-urban and urban sites along the Brisbane River system during base and stormflow conditions, and analyzed for Escherichia coli, ARGs, the intl1, and sewage-associated marker genes using quantitative polymerase chain reaction (qPCR). Significant correlations were identified between E. coli, ARGs, and intl1 (τ = 0.0893, p = 0.0032), as well as with sewage-associated marker genes in water samples from the Brisbane River system (τ = 0.3229, p = 0.0001). Of the sewage-associated marker genes and E. coli, the BIO-ENV procedure identified that crAssphage alone maximized correlations with ARGs and intl1 in river samples (τ = 0.4148). Significant differences in E. coli, ARGs, intl1, and sewage-associated marker genes, and by flow condition (i.e., base vs. storm), and site types (peri-urban vs. urban) combined were identified (R = 0.3668, p = 0.0001), where percent dissimilarities between the multi-factorial groups ranged between 20.8 and 11.2%. Results from this study suggest increased levels of certain ARGs and sewage-associated marker genes in stormflow river water samples compared to base flow conditions. E. coli, HF183 and crAssphage may serve as potential indicators of sewage-derived ARGs under stormflow conditions, and this merits further investigation. Data presented in this study will be valuable to water quality managers to understand the links between sewage pollution and ARGs in urban environments.

Dataset Information

Modeling Contaminant Microbes in Rivers During Both Baseflow and Stormflow.

Publications

Modeling Contaminant Microbes in Rivers During Both Baseflow and Stormflow.

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