Model Scripts and Water-Quality Data for Trends in the Rapid Creek Basin, South Dakota, 1970–2020

This page contains a zipped folder which contains all items necessary to run trend models and produce results published in U.S. Geological Scientific Investigations Report 2021–XXXX [Tatge, W.S., Hoogestraat, G., and Nustad, R.A., 2022, Water-Quality Data and Trends in the Rapid Creek Basin, South Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022-XXXX, XX p.]. To run the R-QWTREND program in R 6 files are required and each is included in this child page: prepQWdataV4.txt, runQWmodelV4XXUEP.txt, plotQWtrendV4XXUEP.txt, qwtrend2018v4.exe, salflibc.dll, and StartQWTrendV4.R (Vecchia and Nustad, 2020). The folder contains five items required to run the R–QWTREND trend analysis tool; a readme.txt file; an alldata.csv file; a finalsites2.csv file, a folder called "scripts", and a folder called "dataout". The "scripts" folder contains the scripts that can be used to reproduce the results found in the USGS Scientific Investigations Report referenced above. The "dataout" folder contains folders for each site evaluated for trends with .RData files with the naming convention of site_qw_MI, site_flow, site_qw_NUT, site_qw_SED, and site_qw_PHY for major ions, nutrients, sediment, and physical parameter constituents. R–QWTREND is a software package for analyzing trends in stream-water quality. The package is a collection of functions written in R (R Development Core Team, 2019), an open source language and a general environment for statistical computing and graphics. The following system requirements are necessary for using R–QWTREND: • Windows 10 operating system • R (version 3.4 or later; 64 bit recommended) • RStudio (version 1.1.456 or later). An accompanying report (Vecchia and Nustad, 2020) serves as the formal documentation for R–QWTREND. Vecchia, A.V., and Nustad, R.A., 2020, Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality: U.S. Geological Survey Open-File Report 2020–1014, 51 p., https://doi.org/10.3133/ofr20201014 R Development Core Team, 2019, R—A language and environment for statistical computing: Vienna, Austria, R Foundation for Statistical Computing, accessed December 7, 2020, at https://www.r-project.org.

                                            [
  "010:12"
]
                                        

                                            {
  "fn": "Wyatt S Tatge",
  "@type": "vcard:Contact",
  "hasEmail": "mailto:wtatge@usgs.gov"
}
                                        

                                            [
  {
    "@type": "dcat:Distribution",
    "title": "Digital Data",
    "format": "XML",
    "accessURL": "https://doi.org/10.5066/P9D8BSXR",
    "mediaType": "application/http",
    "description": "Landing page for access to the data"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Original Metadata",
    "format": "XML",
    "mediaType": "text/xml",
    "description": "The metadata original format",
    "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.61c20a67d34e2ca389d9e70b.xml"
  }
]
                                        

                                            [
  "Pennington County",
  "Rapid City",
  "Rapid Creek",
  "South Dakota",
  "USGS:61c20a67d34e2ca389d9e70b",
  "hydrology",
  "surface water quality",
  "trend analysis"
]
                                        

                                            {
  "name": "U.S. Geological Survey",
  "@type": "org:Organization"
}
                                        

                                            [
  "Geospatial"
]