Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States

Newcomer, Michelle; Bouskill, Nick; Wainwright, Haruko; Maavara, Taylor; Arora, Bhavna; Woodburn, Erica; Dwivedi, Dipankar; Williams, Kenneth; Steefel, Carl; Hubbard, Susan

doi:10.15485/1647366

Title: Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States

Dataset
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Abstract

The purpose of this work was to quantify trends in water quality, total nitrogen deposition, vegetation, and land-use trends for the Continental United States (CONUS). This dataset contains gap-filled daily and yearly in-stream carbon (C) and nitrogen (N) concentrations, discharge, and calculated exports from United States Geological Survey (USGS) National Water Information System (NWIS) stations across the United States of six different nitrogen parameters (Supplementary Table A1), one carbon parameter, and temperature (USGS, 2016, 2018) (https://waterdata.usgs.gov/nwis). The final water quality dataset is merged with the normalized differenced vegetation index (NDVI), total deposition (TDEP), landcover, and elevation datasets. All data are available at the CONUS scale as well as at the scale of hydrologic unit codes: (HUC) HUC8, HUC6, HUC4, and HUC2 watersheds. There are two zip files associated with this data package. I split the data into two equal sized zip files to comply with the data size limits, however the datasets are the same within each zip file. All data files can be read in directly into the R software.

Authors:

;

; Maavara, Taylor;

; Woodburn, Erica;

;

Lawrence Berkeley National Laboratory

Publication Date:: 2020-01-01

Other Number(s):: paf_517

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Watershed Function SFA

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES

Keywords:: nitrogen; carbon; water quality; concentration; exports; NDVI; total wet and dry deposition trends merged with water quality and NDVI trends; EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; Patriculate/Dissolved Organic Carbon; Total Nitrogen; surface water temperature; total atmospheric nitrogen deposition; phosphate; nitrate; ammonia; surface water oxygen; land use; EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER > LAND USE/LAND COVER CLASSIFICATION > VEGETATION INDEX > NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI); EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION

Geolocation:: 51.5643,-66.3452|21.555,-66.3452|21.555,-127.555|51.5643,-127.555|51.5643,-66.3452

OSTI Identifier:: 1647366

DOI:: https://doi.org/10.15485/1647366

Project Location:

Citation Formats


                    Newcomer, Michelle, Bouskill, Nick, Wainwright, Haruko, Maavara, Taylor, Arora, Bhavna, Woodburn, Erica, Dwivedi, Dipankar, Williams, Kenneth, Steefel, Carl, and Hubbard, Susan. Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States.  United States: N. p., 2020. 
        Web.  doi:10.15485/1647366.

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                    Newcomer, Michelle, Bouskill, Nick, Wainwright, Haruko, Maavara, Taylor, Arora, Bhavna, Woodburn, Erica, Dwivedi, Dipankar, Williams, Kenneth, Steefel, Carl, & Hubbard, Susan. Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States.  United States.  doi:https://doi.org/10.15485/1647366

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                    Newcomer, Michelle, Bouskill, Nick, Wainwright, Haruko, Maavara, Taylor, Arora, Bhavna, Woodburn, Erica, Dwivedi, Dipankar, Williams, Kenneth, Steefel, Carl, and Hubbard, Susan. 2020.  
"Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States".  United States.  doi:https://doi.org/10.15485/1647366.  https://www.osti.gov/servlets/purl/1647366. Pub date:Wed Jan 01 00:00:00 EST 2020

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@article{osti_1647366,

  title        = {Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States},

  author       = {Newcomer, Michelle and Bouskill, Nick and Wainwright, Haruko and Maavara, Taylor and Arora, Bhavna and Woodburn, Erica and Dwivedi, Dipankar and Williams, Kenneth and Steefel, Carl and Hubbard, Susan},

  abstractNote = {The purpose of this work was to quantify trends in water quality, total nitrogen deposition, vegetation, and land-use trends for the Continental United States (CONUS). This dataset contains gap-filled daily and yearly in-stream carbon (C) and nitrogen (N) concentrations, discharge, and calculated exports from United States Geological Survey (USGS) National Water Information System (NWIS) stations across the United States of six different nitrogen parameters (Supplementary Table A1), one carbon parameter, and temperature (USGS, 2016, 2018) (https://waterdata.usgs.gov/nwis). The final water quality dataset is merged with the normalized differenced vegetation index (NDVI), total deposition (TDEP), landcover, and elevation datasets. All data are available at the CONUS scale as well as at the scale of hydrologic unit codes: (HUC) HUC8, HUC6, HUC4, and HUC2 watersheds. There are two zip files associated with this data package. I split the data into two equal sized zip files to comply with the data size limits, however the datasets are the same within each zip file. All data files can be read in directly into the R software.},

  doi          = {10.15485/1647366},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2020},

  month        = {1}

}

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DOI: https://doi.org/10.15485/1647366

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