Data

Green and others (2021) developed a gradient boosted regression tree model to predict the mean groundwater age, or travel time, for shallow wells across a portion of the Great Lakes basin in the United States. Their study applied machine learning methods to predict ages in wells using well construction, well chemistry, and landscape characteristics. For a dataset of age tracers in 961 water sample

A multivariate regression model was developed to predict zero-order oxygen reduction rates (mg/L/yr) in aquifers across the State of Wisconsin. The model used a combination of dissolved oxygen concentrations and mean groundwater ages estimated with sampled age tracers from wells in the U.S. Geological Survey National Water Information System and previously published project reports from state agen

This data set was compiled to support the development of a model of oxygen reduction rates in Wisconsin groundwater wells; a model which is part of a Groundwater Nitrate Decision Support Tool for Wisconsin. Data were compiled from previously published studies with data collection from 1987 to 2009. Only data describing redox condition, groundwater age, depth to water, and well construction were co

This data release contains a netCDF file containing decadal estimates of nitrate leached from septic systems (kilograms per hectare per year, or kg/ha) in the state of Wisconsin from 1850 to 2010, as well as the python code and supporting files used to create the netCDF file. The netCDF file is used as an input to a Nitrate Decision Support Tool for the State of Wisconsin (GW-NDST; Juckem and othe

A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on several support models, including machine-learning models

A groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST relies on an ensemble of calibrated parameters to make nitrate predi

A Groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). Running and using the GW-NDST software involves downloading the software code (v

Data were collected during experiments to determine the effects of water chemistry on carbon dioxide toxicity to zebra mussels (Dreissena polymorpha). Water chemistry parameters were collected for the water used in the study. Data were collected to model the relationship of carbon dioxide and pH in various water chemistries. Measurements were made to describe the animals used in the study.

This dataset includes pipe-flow monitoring data in sewers used to analyze the water budget at RecoveryPark in Detroit, Michigan. These are provided as 3 text comma separated format files at sewer locations that drain the study area. In addition, there are 6 text comma separated format files containing the Rhodamine dye tracer concentrations collected in the combined sewer locations for this study.

This dataset contains raw sequence data collected from an eDNA metabarcoding project to detect freshwater mussel species across two sites in Georgia (Spring Creek and Flint River) and one drainage in Missouri (Big Piney River). The eDNA samples were collected from each stream using dead-end ultra filtration (D-HFUF) with eDNA extracted from filters. We used two previously published primer sets des

The role of disease in freshwater mussel declines has been largely ignored due to the lack of appropriate diagnostic tools and metabolomic markers of stress. Mussels in this study were either fed a prepared diet or unfed and their condition was assessed with the observed changes in fatty acid content of their tissue. This dataset contains quantitative fatty acid data from nonlethal (biopsy) sampli

Multibeam and sidescan sonar were collected for a total of 15 sites in the North Arm, Maxwell Bay, and St. Albans Bay of Lake Minnetonka, Minnesota, to determine whether hydroacoustics could be used in turbid rivers and lakes as a method of rapid detection for invasive zebra mussel (Dreissena polymorpha) infestations. Hydroacoustic data were collected in June, August, and the end of September, 202