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Data

The Upper Midwest Water Science Center collects, analyzes, and distributes data on a variety of water-related issues and resources. Much of our data is publicly available through the USGS National Water Information System (NWIS).

Filter Total Items: 236

PeakFQ input and output files for 299 streamgages in Wisconsin through water year 2020. PeakFQ input and output files for 299 streamgages in Wisconsin through water year 2020.

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.

Mercury Concentrations and Loads in United States and Canadian Tributaries of Lake Superior Mercury Concentrations and Loads in United States and Canadian Tributaries of Lake Superior

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...

Concentrations and laboratory quality-assurance data for six unregulated contaminants measured in source and finished drinking-water samples collected from public water systems throughout Minnesota by using ELISA and MS-based analytical methods Concentrations and laboratory quality-assurance data for six unregulated contaminants measured in source and finished drinking-water samples collected from public water systems throughout Minnesota by using ELISA and MS-based analytical methods

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...

Extreme gradient boosting machine learning models, suspended sediment, bedload, streamflow, and geospatial data, Minnesota, 2007-2019 Extreme gradient boosting machine learning models, suspended sediment, bedload, streamflow, and geospatial data, Minnesota, 2007-2019

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...

Water temperature data in the Milwaukee Estuary of Lake Michigan, Milwaukee County, Wisconsin Water temperature data in the Milwaukee Estuary of Lake Michigan, Milwaukee County, Wisconsin

This dataset contains water temperature data collected by boat tow on August 30, 2019 between approximately 8:00 AM and 12:15 PM Central Standard Time (CST) in the Milwaukee Estuary of Lake Michigan. The data includes measured water temperatures, depth of collection, water column depth, time of collection, and geospatial coordinates. The objective of this data collection was to produce...

Fluvial Erosion Hazard Rapid Geomorphic Assessment Data from the Marengo Watershed, Ashland County, Wisconsin Fluvial Erosion Hazard Rapid Geomorphic Assessment Data from the Marengo Watershed, Ashland County, Wisconsin

An extreme flood in 2016 caused widespread culvert blockages and road failures across northern Wisconsin, including extensive damage along steep tributaries and ravines in the Marengo River watershed. Along with the flooding, there were fluvial erosion hazards (FEH) associated with a large amount of erosion in headwater areas. Of special concern were FEHs associated with gullying, loss...

Input data, trained model data, and model outputs for predicting streamflow and base flow for the Mississippi Embayment Regional Study Area using a random forest model Input data, trained model data, and model outputs for predicting streamflow and base flow for the Mississippi Embayment Regional Study Area using a random forest model

This data release contains datasets developed for the purpose of training and applying random forest models to the Mississippi Embayment Regional Study Area. The random forest models are designed to predict total stream flow and baseflow as a function of a combination of watershed characteristics and monthly weather data. These datasets are associated with a report (SIR 2022-xxxx) and...

Hydrologic metrics, biological metrics, R scripts, and model archives associated with regression analyses used to quantify relations between altered hydrological and biological responses in rivers of Minnesota, 1945-2015 Hydrologic metrics, biological metrics, R scripts, and model archives associated with regression analyses used to quantify relations between altered hydrological and biological responses in rivers of Minnesota, 1945-2015

The U.S. Geological Survey (USGS) and the Minnesota Pollution Control Agency (MPCA) conducted a cooperative study to develop linear regression models that quantify relations among 173 hydrologic explanatory metrics in five categories (duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and 132 biological response metrics in six categories...

Groundwater data and age information from samples collected in Minnesota (ver. 3.0, December 2025) Groundwater data and age information from samples collected in Minnesota (ver. 3.0, December 2025)

Groundwater age distributions and susceptibility to natural and anthropogenic contaminants were assessed for selected wells, streambed piezometers, and springs in southeastern Minnesota. The data provide information to understand how long it will take to observe groundwater quality improvements from best management practices implemented at land surface to reduce losses of nitrate (and...

Source Identification of Mercury and Methylmercury using Stable Isotope Analysis in the Fox River, WI Source Identification of Mercury and Methylmercury using Stable Isotope Analysis in the Fox River, WI

The lower Fox River in Wisconsin is a heavily industrialized system and the major tributary to Green Bay within Lake Michigan. The region has been a listed as Area of Concern by the United States Environmental Protection Agency (USEPA), indicating severe impairment of the ecological health of the system. Remedial action has taken place along the river to remove extensive polychlorinated...

Total phosphorus and total dissolved phosphorous released from Green Ash (Fraxinus pennsylvanica) and Norway Maple (Acer platanoides) as they contribute to leachable phosphorus in leaf litter and impact phosphorus loads in urban stormwater Total phosphorus and total dissolved phosphorous released from Green Ash (Fraxinus pennsylvanica) and Norway Maple (Acer platanoides) as they contribute to leachable phosphorus in leaf litter and impact phosphorus loads in urban stormwater

The data set contains results from leaf litter samples analyzed for total phosphorus (TP) and total dissolved phosphorus (TDP) released from Green Ash (Fraxinus pennsylvanica) and Norway Maple (Acer platanoides) leaves in three medium-density urban residential basins in Madison, WI, USA during October and November of 2017 and 2018. Tables contain averages and standard deviations for all...

Great Lakes tributary pharmaceutical water samples from water year 2018 Great Lakes tributary pharmaceutical water samples from water year 2018

This data release provides water chemistry results and quality assurance data for samples collected from Great Lakes tributaries in the states of Minnesota, Wisconsin, Michigan, Indiana, Ohio, and New York. In total, 158 chemicals were analyzed which are primarily pharmaceuticals. Between one and four water samples were collected at 37 sampling locations between November 2017 and July...
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