{
  "accessLevel": "public",
  "bureauCode": [
    "020:00"
  ],
  "contactPoint": {
    "fn": "Heather Golden",
    "hasEmail": "mailto:golden.heather@epa.gov"
  },
  "description": "Real-time USGS nitrate data are collected to map short-term changes in nitrate concentrations across locations in the US: https://waterwatch.usgs.gov/wqwatch/?pcode=00630\nCAMELS data are “a large-sample watershed-scale hydrometeorological dataset for the contiguous USA” (see https://gdex.ucar.edu/dataset/camels.html)\nBasinATLAS for catchment attributes related to land cover, soils, and geology: https://developers.google.com/earth-engine/datasets/tags/hydroatlas\nDAYMET meteorological data for temperature and precipitation: https://daymet.ornl.gov/. This dataset is not publicly accessible because: Publicly available data. It can be accessed through the following means: https://waterwatch.usgs.gov/wqwatch/?pcode=00630\r\nhttps://gdex.ucar.edu/dataset/camels.html\r\nhttps://developers.google.com/earth-engine/datasets/tags/hydroatlas\r\nhttps://daymet.ornl.gov/. Format: Real-time USGS nitrate data, CAMELS streamflow data, BasinATLAS catchment attribute data, and DAYMET meteorological data. \n\nThis dataset is associated with the following publication:\nPandit, A., H. Golden, J. Christensen, C. Lane, and A. Husic. Deep Learning Prediction and Interpretation of Riverine Nitrate Export Across the Mississippi River Basin.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 61(8): e2024WR039207, (2025).",
  "distribution": [],
  "identifier": "https://doi.org/10.23719/1531755",
  "keyword": [
    "Deep learning",
    "LSTM",
    "Watershed",
    "machine learning",
    "nitrate"
  ],
  "license": "https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html",
  "modified": "2024-09-26",
  "programCode": [
    "020:000"
  ],
  "publisher": {
    "name": "U.S. EPA Office of Research and Development (ORD)",
    "subOrganizationOf": {
      "name": "U.S. Environmental Protection Agency",
      "subOrganizationOf": {
        "name": "U.S. Government"
      }
    }
  },
  "references": [
    "https://doi.org/10.1029/2024wr039207"
  ],
  "rights": null,
  "title": "RivNitrateLSTM"
}