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The U.S. Geological Survey (USGS) currently operates and maintains data collection sites in the Central Midwest Water Science Center (Illinois, Iowa, and Missouri) for acquiring information about surface water, ground water, water quality, and precipitation to provide necessary information for our cooperators in this Center.

 

Filter Total Items: 180

Aquaculture and irrigation water-use model (AIWUM) version 1.1 estimates and related datasets for the Mississippi Alluvial Plain

This data release contains monthly and annual water-use estimates from the aquaculture and irrigation water-use model (AIWUM) version 1.1 for the Mississippi Alluvial Plain, April 1999 to October 2019. Aquaculture and irrigation estimates contained in this data release are representative of groundwater withdrawal for six different categories: aquaculture, cotton, corn, rice, soybeans, and all othe

Bathymetry of Bubbly Creek and Chicago Sanitary and Ship Canal Sidings in Cook County, Illinois, July 2023

These data are high-resolution bathymetry (riverbed elevation) in compressed LAS (*.laz) format, generated from the July 17–19, 2023, hydrographic survey of Bubbly Creek and various sidings, harbors, and turning basins on the Chicago Sanitary and Ship Canal (CS&SC) in Cook County, Illinois. The survey includes all Bubbly Creek from the confluence with the CS&SC in the north to the Racine Avenue Pu

North Branch Chicago River and North Shore Channel Bathymetry in Cook County, Illinois, July 2023

These data are high-resolution bathymetry (riverbed elevation) in compressed LAS (*.laz) format, generated from the July 17–18, 2023, hydrographic survey of the North Branch Chicago River and North Shore Channel in Cook County, Illinois. The survey extends from near the North Avenue Turning Basin and Goose Island in the south, upstream to the Metropolitan Water Reclamation District (MWRD) Wilmette

Seepage Meter Data Collected at Crystal Lake, City of Crystal Lake, Illinois, 2020

Seepage meters measurements were collected at three locations along the northern shoreline and at three locations along the southern shoreline of Crystal Lake, located in the City of Crystal Lake, Illinois on October 28-30, 2020, and November 4-5, 2020. Seepage measurements directly measure the flux for the area captured by the seepage meter. A positive (gaining) flux is assumed when the volume in

Peak Streamflow Data, Climate Data, and Results from Investigating Hydroclimatic Trends and Climate Change Effects on Peak Streamflow in the Central United States, 1921–2020

Peak-flow frequency analysis is crucial in various water-resources management applications, including floodplain management and critical structure design. Federal guidelines for peak-flow frequency analyses, provided in Bulletin 17C, assume that the statistical properties of the hydrologic processes driving variability in peak flows do not change over time and so the frequency distribution of annu

Monitoring Data to Support the Operation of the Electric Dispersal Barrier System on the Chicago Sanitary and Ship Canal at Romeoville, Illinois, October 1, 2017, to September 30, 2018

The U.S. Geological Survey monitors water surface flow reversals, commercial vessel traffic, and temperature and specific conductance in the U.S. Army Corps of Engineers Electric Dispersal Barrier System, EDBS, on the Chicago Sanitary and Ship Canal, Chicago, Illinois. This data release is the 2018 water year summary of the EDBS monitoring data. Water surface flow reversals at the EDBS are monitor

Reconnaissance of Per- and Polyfluoroalkyl Substances (PFAS) in Selected Groundwater and Surface Water Sites in McHenry County, Illinois, 2020

Data were collected at 19 groundwater monitoring wells and 3 surface water locations across McHenry County, Illinois, in 2020 by staff from the U.S. Geological Survey (USGS) Central Midwest Water Science Center. Quality control samples (2 blanks and 1 replicate) were also collected to assess data reliability and precision. Samples were submitted to the USGS National Water Quality Laboratory in Den

Geographic Data for the Estimation of Peak Flow Statistics for Illinois

The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting methods, results, and applications of an updated flood-frequency study for the State of Illinois. The study developed regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based

Elevation, Flow Accumulation, Flow Direction, and Stream Definition Data in Support of the Illinois StreamStats Upgrade to the Basin Delineation Database

The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation and the Illinois Department of Transportation, prepared hydro-conditioned geographic information systems (GIS) layers for use in the Illinois StreamStats application. These data were used to delineate drainage basins and compute basin characteristics for updated peak flow and flow duration regression equa

Bathymetric and Supporting Data for Selected Water Supply Lakes in Missouri, 2022

Water supply lakes are the primary source of water for many communities in northern and western Missouri. Therefore, accurate and up-to-date estimates of lake capacity are important for managing and predicting adequate water supply. Many of the water supply lakes in Missouri were previously surveyed by the U.S. Geological Survey (USGS) in the early 2000s (Richards, 2013) and in 2013 (Huizinga, 201

Velocity Survey at Cross Sections in the Illinois River below Starved Rock Lock and Dam near Utica, Illinois, June 16, 2021

In support of U.S. Geological Survey invasive carp research examining aggregations of invasive carp in the tail water of dams, water velocity measurements were made at cross sections in the Illinois River below Starved Rock Lock and Dam on June 16, 2021. A total of 16 cross sections were surveyed, with two transects per cross section. Water depth and crew safety limited the extent of the survey. T

Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

This data release contains one dataset and one model archive in support of the journal article, "Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies," by Jennifer C. Murphy and Jeffrey G. Chanat. The model archive contains scripts (run in R) to reproduce the four machine learning models (logistic regression, linear and quadratic dis