Data

The U.S. Geological Survey developed two steady-state finite-difference regional groundwater-flow models using the MODFLOW-NWT computer code. These models simulate flow in the area of historical iron mining on and around the portion of the Mesabi Iron Range that is in the St. Louis River basin in northeastern Minnesota. The models are composed of 8 layers each; the upper four representing unconsol

Fish collected for taxonomic and systematic purposes are often preserved and then archived in museum collections. Preserved fish are commonly first fixed in a formalin solution and then transferred to ethanol for long-term storage. The wet preservation method can potentially introduce mercury (Hg) contamination or unintentionally extract Hg from tissue. An experiment was designed to test the utili

Nutrient and sediment regression information (diagnostics and coefficients) and estimated load data from 30 tributaries to the Great Lakes, beginning of the program (water year 2011) to water year 2013.

This model archive contains R source code for the Weighted-Multiple Linear Regression Program (WREG), input files, and associated output files needed to recreate regression models that are discussed in the report: Levin, S.B. and Sanocki, C.A., Methods for estimating flood magnitude and frequency for unregulated streams in Wisconsin, U.S. Geological Survey Scientific Investigations Report 2022-511

5-day composite river water samples were collected from two sites: Menomonee River (U.S. Geological Survey station number 04087142) and Underwood Creek (U.S. Geological Survey station number 04087088) in Milwaukee, Wisconsin. 5-day composite wastewater (raw sewage) influent samples were also collected from the Jones Island Water Reclamation Facility (U.S. Geological Survey station number 430125087

This topobathymetric digital elevation model (TBDEM) mosaic represents the topography and bathymetry for the Milwaukee River Estuary in Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas. The TBDEM was produced in support of modeling and for developing a physical habitat framework to help with understanding the effects from multidirectional currents and seiche

A series of Jupyter notebooks documenting a self-guided, interactive curriculum for the PEST++ family of software codes for uncertainty analysis, parameter estimation, and management optimization. For a currently maintained version of these materials, please visit https://github.com/gmdsi/GMDSI_notebooks.

Four digital water-surface profile maps for a 14-mile reach of the Mississippi River near Prairie Island in Welch, Minnesota from the confluence of the St. Croix River at Prescott, Wisconsin to upstream of the United States Army Corps of Engineers (USACE) Lock and Dam No. 3 in Welch, Minnesota, were created by the U.S. Geological Survey (USGS) in cooperation with the Prairie Island Indian Communit

This dataset includes U.S. Geological Survey (USGS) flood-frequency analysis software PeakFQ input and output files for 299 streamgages in Wisconsin. Input files for each streamgage include peak streamflow data through 2020 and PeakFQ specification files. Output files are text files (.prt) with flood-frequency results.

In 2021, the U.S. Geological Survey (USGS) Mercury Research Laboratory (MRL) conducted a large-scale assessment of mercury (Hg) concentrations and Hg stable isotope values in tributaries of Lake Superior in order to define the sources and amounts of Hg entering the lake. Water samples were collected monthly from 18 tributaries in the United States from April through October in 2021 and during 2022

The U.S. Geological Survey, in cooperation with the Minnesota Department of Health, conducted a study to determine the occurrence of six unregulated contaminants in source and finished drinking-water samples collected from 67 public water supply systems throughout Minnesota. Minnesota relies on groundwater and surface water sources for drinking water. Land use, such as wastewater discharge and agr

A series of machine learning (ML) models were developed for Minnesota. The ML models were trained and tested using suspended sediment, bedload, streamflow, and geospatial data to predicted suspended sediment and bedload. Suspended sediment, bedload, and streamflow data were collected during water years 2007 through 2019. The ML models were used to improve understanding of sediment transport proces