US Migrating
type: Agent

Surface water and bottom sediment chemical data and landscape variable input datasets for predicting the occurrence of chemicals of emerging concern in 25 U.S. river basins in the Great Lakes basin
type: Dataset
contact point: Organization
  fn: Sarah M Elliott
keyword: freshwater
keyword: boosted-regression-tree
keyword: amerigeo
keyword: newyork
keyword: michigan
keyword: national
keyword: illinois
keyword: ckan
keyword: great-lakes
keyword: pesticide-and-herbicide-contamination
keyword: minnesota
keyword: wisconsin
keyword: north-america
keyword: surface-water
keyword: non-point-source-pollution
keyword: usgs-5a833fcfe4b00f54eb3297ee
keyword: sediment
keyword: amerigeoss
keyword: geoss
keyword: united-states
keyword: ohio
keyword: water-resources
keyword: pharmaceutical-contamination
keyword: geo
theme: {geospatial}
description: This data release includes concentrations of contaminants of emerging concern (CEC), by chemical class, for sites sampled within 25 river basins in the U.S. portion of the Great Lakes basin and associated watershed characteristics. The CEC data include concentrations in surface water and sediment samples that were collected during 2010-2014. During the first 3 years, sample sites near mostly urban areas were chosen. The last two years of study focused on other point sources and few nominal reference sites. Water and sediment samples were analyzed for a diverse suite of CECs including, but not limited to, pharmaceuticals, industrial chemicals, flame retardants, pesticides, fragrances, and plasticizers. Statistical models were developed to define the relationships between watershed characteristics within a river basin and the occurrence of specific CEC classes using boosted regression tree models.
issued: 2025-11-19T18:51:30.546810
modified: 20200827
spatial: Location

Original Metadata
type: Distribution
access URL: https://data.usgs.gov/datacatalog/metadata/USGS.5a833fcfe4b00f54eb3297ee.xml
media type: text/xml
description: The metadata original format
format: XML
issued: 2022-08-07T03:19:45.503018
modified: 2025-11-19T18:51:30.522186

Digital Data
type: Distribution
access URL: https://doi.org/10.5066/F7ZK5FXJ
media type: application/http
description: Landing page for access to the data
format: XML
issued: 2022-08-07T03:19:45.503024
modified: 2025-11-19T18:51:30.523094