This dataset contains data tables of laboratory quality-control data associated with environmental samples analyzed for microbiological constituents at the Ohio Water Microbiology Laboratory of the U.S. Geological Survey (USGS) during federal fiscal years 2012-2017 (October 1, 2011 through September 30, 2017). The environmental samples were collected across the United States by the USGS National Water Quality Assessment Project and other projects in Water Science Centers. The microbiological constituents include total coliforms, Escherichia coli (E. coli), enterococci, coliphage (F-specific and somatic), aerobic endospores, and actinomycetes. These quality-control data can be used to assess the quality of microbiological data for the associated environmental samples.

This dataset contains data tables of laboratory quality-control data associated with environmental samples analyzed for microbiological constituents at the Ohio Water Microbiology Laboratory of the U.S. Geological Survey (USGS). The environmental samples were collected across the United States by USGS National Projects and projects in Water Science Centers. These quality-control data can be used to assess the quality of microbiological data for the associated environmental samples.

This dataset contains data tables of laboratory quality-control data associated with environmental samples analyzed for microbiological constituents at the Ohio Water Microbiology Laboratory of the U.S. Geological Survey (USGS). The environmental samples were collected across the United States by USGS National Projects and projects in Water Science Centers. These quality-control data can be used to assess the quality of microbiological data for the associated environmental samples.

We deployed a sampler to characterize water quality from a household well tapping a shallow fractured dolomite aquifer in northeast Wisconsin. The sampler was deployed from January to May 2017, and monitored temperature, nitrate, chloride, specific conductance, and fluorescent dissolved organic matter on a minute time step; water was directed to sequential microbial filters during three recharge periods that ranged from 5 to 20 days. Results from the automated sampler demonstrate the dynamic nature of the household water quality, especially with regard to microbial targets, which were shown to vary 1 to 2 orders of magnitude during a single sampling event. We believe assessments of pathogen occurrence and concentration, and related assessments of drinking well vulnerability, would be improved by the time-integrated characterization provided by this sampler. This data release provides the data collected during this study and use for analyses described by Owens et al., 2018.

We deployed a sampler to characterize water quality from a household well tapping a shallow fractured dolomite aquifer in northeast Wisconsin. The sampler was deployed from January to May 2017, and monitored temperature, nitrate, chloride, specific conductance, and fluorescent dissolved organic matter on a minute time step; water was directed to sequential microbial filters during three recharge periods that ranged from 5 to 20 days. Results from the automated sampler demonstrate the dynamic nature of the household water quality, especially with regard to microbial targets, which were shown to vary 1 to 2 orders of magnitude during a single sampling event. We believe assessments of pathogen occurrence and concentration, and related assessments of drinking well vulnerability, would be improved by the time-integrated characterization provided by this sampler. This data release provides the data collected during this study and use for analyses described by Owens et al., 2018.

This dataset includes concentrations of culture-based fecal indicator concentrations, microbial source tracking marker concentrations, results from Bayesian statistical analysis. This dataset is associated with the following publication: McMinn, B., A. Korajkic, J. Kelleher, A. Diedrich, A. Pemberton, J. Willis, M. Sivaganesan, B. Shireman, A. Doyle, and O. Shanks. Quantitative fecal pollution assessment with bacterial, viral, and molecular methods in small stream tributaries. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 951: 175740, (2024).