Timeseries data from 'TURKEY CREEK NEAR MARYVILLE, SC (USGS 02136361)' (gov_usgs_nwis_02136361)

Data collected to assess water quality conditions in the natural creeks, aquifers and lakes in the Austin area. This is raw data, provided directly from our Water Resources Monitoring database (WRM) and should be considered provisional. Data may or may not have been reviewed by project staff. A map of site locations can be found by searching for LOCATION.WRM_SAMPLE_SITES; you may then use those WRM_SITE_IDs to filter in this dataset using the field SAMPLE_SITE_NO.

These data describe microbiological analyses performed on groundwater samples from domestic drinking water supply collected from 42 groundwater wells in the Central Valley of California. Samples were collected between January 2014 and April 2014 for the Groundwater Ambient Monitoring and Assessment (GAMA) program priority basin assessment of the Madera, Chowchilla, and Kings (MACK) groundwater sub-basins’ shallow aquifers. A total of 75 wells were sampled for the MACK study unit between August 2013 and April 2014. Samples for this dataset were vacuum filtered and plated on MI and mEI agars prior to incubation to promote colony growth. Colonies were tallied by their species into columns for various fecal indicator bacteria (FIBs): total coliforms (TCs), Escherichia coli (E. coli), enterococci. Non-target growths were also counted and tallied. Six additional replicate samples were collected for quality assurance. Of the 579 total FIB colonies detected, 106 were selected for polymerase chain reaction (PCR) analysis with the goal of sequencing their DNA. Selected colonies consisted of both target and non-target growths and were taken from 14 samples collected at 13 different wells. DNA sequencing was successful for 34 of the sampled colonies out of a total of 59 submitted. Results for these analyses were reported in FASTA format with the number of bases and their starting position indicated for each batch.

This data release contains eight datasets and metadata related to streamwater constituent load estimation and E. coli bacteria concentration predictions at 15 watersheds in DeKalb County, Georgia for 2012 to 2016 (the water-quality model calibration data goes through 9/22/2017 and the water-quality assurance samples goes through 11/7/2017). Loads were estimated for 15 constituents: biochemical oxygen demand, chemical oxygen demand, total suspended solids, suspended sediment concentration, total nitrogen, total nitrate plus nitrite, total phosphorus, dissolved phosphorus, total organic carbon, total calcium, total magnesium, total copper, total lead, total zinc, and total dissolved solids. The data release includes the following eight datasets: (1) daily base-flow separation results that were used as explanatory variables in the load estimation models; (2) water-quality assurance sample concentrations; (3) laboratory standard reference sample concentrations; (4) water-quality outliers that were excluded from the calibration datasets used in regression models for estimating streamwater constituent loads and E. coli bacteria concentrations; (5) calibration datasets containing explanatory variables for modeling constituent loads; (6) model coefficients and model diagnostic statistics used to estimate streamwater constituent loads, including portable document format files (pdf) with reports and plots for evaluating model fits; (7) time-step data used for estimating loads from the model coefficients; and (8) annual and period of record streamwater constituent load and yield estimates, including the 95-percent confidence intervals of the estimates.

Nutrient reduction on the landscape scale often focuses on actions that reduce the movement of nitrogen (N) and phosphorus (P) from agricultural lands into streams and rivers. However, processing of N and P in streams and rivers can be substantial and increasing these in-stream processing rates could result in reductions or transformations of nutrients to less labile or less mobile forms. We hypothesize that buffer conditions could influence the microbial community and sediment characteristics of streams and rivers and thereby influence in-stream N and P processing rates. As a result, we predict that variation in buffer land cover (from agricultural to wetlands to forest) causes differences in processing rates. To test this prediction, we measured inorganic nutrient transformation in the water column and sediment flux of inorganic N and P in streams draining predominantly agricultural landscapes in the Fox River and Duck Creek watersheds (WI, USA) repeatedly during the 2018 growing season.

The data included here were gathered to determine the effects of cattle grazing on wetland water quality in the Klamath National Wildlife Refuge in Oregon. Surface water samples from sites representing a range of grazing histories were collected between June and October in 2017 and 2018. Samples were analyzed for nutrients (ammonia, nitrate plus nitrite, nitrite, and orthophosphate), total coliforms, E. coli, enterococci, and estrogenicity by U.S. Geological Survey laboratories. Basic water quality parameters such as temperature, pH, turbidity and specific conductance were also collected in the field during each site visit. Quality assurance samples (blanks and replicates) as well as method information is also included in the data release.