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High radium (Ra) concentrations in potable portions of the Cambrian-Ordovician (C-O) aquifer system were investigated using water-quality data and environmental tracers ( 3H, 3Hetrit, SF6 , 14C and 4Herad) of groundwater age from 80 public-supply wells (PSWs). Groundwater ages were estimated by calibration of tracers to lumped parameter models and ranged from modern (1 Myr) in the most downgradient, confined portions of the potable system. More than 80 and 40 percent of mean groundwater ages were older than 1000 and 50,000 yr, respectively. Anoxic, Fe-reducing conditions and increased mineralization develop with time in the aquifer system and mobilize Ra into solution resulting in the frequent occurrence of combined...
These data represent the air-free pH and specific conductance per pore volume of effluent generated by the phosphate removal column experiment. Solid samples used for the columns are of modern and legacy iron and steel slag from the Chicago-Gary area of Illinois and Indiana, USA.
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Mississippi River near structure A5054 on Interstate 72 at Hannibal, Missouri, in 2014 and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position...
These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Mississippi River near structure A5076 on Missouri State Highway 34 at Cape Girardeau, Missouri, in 2014 and 2018. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal...
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 Pump station in the south; various sidings and turning basins along the CS&SC between Kedzie Avenue and South Halsted Street; and the Marine Safety Station harbor near the Chicago Harbor Lock on Lake Michigan. This survey is a continuation and enhancement of the bathymetric survey of the CS&SC in Cook County, Illinois, conducted...
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
Airborne electromagnetic (AEM), magnetic, and radiometric data were acquired November 2018 to February 2019 along 16,816 line-kilometers (line-km) over the Mississippi Alluvial Plain (MAP). Data were acquired by CGG Canada Services, Ltd. with three different helicopter-borne sensors: the CGG Canada Services, Ltd. Resolve frequency-domain AEM instrument that is used to map subsurface geologic structure at depths up to 100 meters, depending on the subsurface resistivity; a Scintrex CS-3 cesium vapor magnetometer that detects changes in deep (hundreds of meters to kilometers) geologic structure based on variations in the magnetic properties of different formations; and a Radiation Solutions RS-500 spectrometer that...
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River collected in 1975.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 1994.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River collected in 1975.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 2000.
Categories: Data;
Types: Citation;
Tags: Illinois,
Illinois River,
Iowa,
Minnesota,
Mississippi River,
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 2000.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 1989.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 1989.
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River System collected in 2000.
Categories: Data;
Types: Citation;
Tags: Illinois,
Illinois River,
Iowa,
Minnesota,
Mississippi River,
This dataset consists of digital scans of color infrared aerial photography from the Upper Mississippi River collected in 1975.
Measures used to assess trends in the 10th, 50th, and 90th quantiles of annual peak streamflow from 1916-2015 at 2,683 U.S. Geological Survey stations and within 191 4-digit HUCs in the conterminous United States. Linear quantile regression was applied to the selected quantiles of log-transformed annual peak streamflow to represent trends for a range of flood frequencies from small, common floods to large, infrequent floods. Comparative trends in pairs of quantiles were characterized as coherent, convergent, or divergent by comparing the slopes of linear quantile regression equations.
This data release contains relevant datasets used in the analysis for the Chesapeake Bay stressor identification project, for which results are described in Fanelli and others (2022). For this project, two existing information sources were compiled and summarized to identify key in-stream stressors reported by the scientific literature or through regulatory assessments to be likely affecting benthic macroinvertebrate community metrics in the Chesapeake Bay region: 1) the peer reviewed multi-stressor literature, in which the effects multiple in-stream stressors on benthic macroinvertebrate community metrics are simultaneously assessed; and 2) reported causes of biological impairment as listed by state or district...
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