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README.Rmd
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---
title: "README"
output:
md_document:
variant: gfm
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/",
warning = FALSE,
message = FALSE,
fig.height = 7,
fig.width = 7
)
library(dataRetrieval)
```
# dataRetrieval <img src="man/figures/hex_logo.png" class="logo" alt="dataRetrieval" style="width:90px;height:auto;" align="right" />
[](https://cran.r-project.org/package=EGRET)
[](https://cran.r-project.org/package=dataRetrieval)
[](https://cran.r-project.org/package=dataRetrieval)
The `dataRetrieval` package was created to simplify the process of loading hydrologic data into the R environment. It is designed to retrieve the major data types of U.S. Geological Survey (USGS) hydrology data that are available on the Web, as well as data from the Water Quality Portal (WQP), which currently houses water quality data from the Environmental Protection Agency (EPA), U.S. Department of Agriculture (USDA), and USGS. Direct USGS data is obtained from a service called the National Water Information System (NWIS).
# Call for volunteers
We are recruiting volunteers to participate in user testing of dataRetrieval, the goal being to ensure that we continue to meet users' needs and find areas for improvement.
For over ten years, the USGS has developed and maintained the R package dataRetrieval, which is designed to provide easy programmatic access to USGS water data. Over the next year we will be implementing updates to the package functionality as part of a larger effort to modernize USGS APIs and web services. Part of successfully ensuring these functionality updates meet the needs of our users involves user-centered design, which is why we're reaching out to you.
We are looking for R users at any experience level with dataRetrieval - from beginner to seasoned expert - and using dataRetrieval with any size data sets - from small, targeted data pulls to large and complex automated workflows. We are particularly interested in hearing from users who are pulling data using NWIS functions, such as readNWISdata, whatNWISdata, etc.
Participation in user testing will take about an hour. We will ask a set of questions to better understand how you use dataRetrieval and why, and we will ask users to walk us through a pre-determined coding example with dataRetrieval. Interviews will take place in February. There are no right or wrong answers - think of it as you’re testing us! We'll use your feedback to improve the usability and functionality of dataRetrieval and its user resources.
Please email [email protected] by January 30, 2025 if you are interested in participating, and please share this invitation with others who might also be interested. We will start contacting people in early February to schedule interviews.
# Introduction
:warning: USGS discrete water-quality data availability and format are changing. Beginning March 11, 2024 USGS data obtained from legacy services will not include new USGS data or recent updates to existing data. To view the status of changes in data availability and code functionality, visit: <https://doi-usgs.github.io/dataRetrieval/articles/Status.html>
:warning: All documentation on <https://doi-usgs.github.io/dataRetrieval> assume you have the development version of dataRetrieval installed. To do that:
```{r eval=FALSE}
library(remotes)
install_github("DOI-USGS/dataRetrieval",
build_vignettes = TRUE,
build_opts = c("--no-resave-data",
"--no-manual"))
```
If you have additional questions about these changes, email [email protected].
# What would you like to do?
1. Get instantaneous USGS discharge data. Start here: `?readNWISuv`
2. Get daily USGS discharge data. Start here: `?readNWISdv`
3. Get USGS groundwater data. Start here: `?readNWISgwl`
4. Get discrete water quality data. Start here: `?readWQPdata`
4. Discover USGS data (not including discrete water quality data). Start here: `?whatNWISdata`
6. Find Hydro Network-Linked Data Index (NLDI) data. Start here: `?findNLDI`
For additional tutorials, see:
[Basic Tutorial](https://doi-usgs.github.io/dataRetrieval/articles/tutorial.html)
[dataRetrieval Introduction 1](https://rconnect.usgs.gov/NMC_dataRetrieval_1)
[dataRetrieval Introduction 2](https://rconnect.usgs.gov/NMC_dataRetrieval_2)
# Installation of dataRetrieval
To install the `dataRetrieval` package, you must be using R 3.0 or greater and run the following command:
```{r eval=FALSE}
install.packages("dataRetrieval")
```
To get cutting-edge changes, install from GitHub using the `remotes` packages:
```{r eval=FALSE}
library(remotes)
install_github("DOI-USGS/dataRetrieval",
build_vignettes = TRUE,
build_opts = c("--no-resave-data",
"--no-manual"))
```
# Reporting bugs
Please consider reporting bugs and asking questions on the Issues page:
[https://github.com/DOI-USGS/dataRetrieval/issues](https://github.com/DOI-USGS/dataRetrieval/issues)
# Citations
## Citing the dataRetrieval package
```{r cite, eval=TRUE}
citation(package = "dataRetrieval")
```
## Citing NWIS data
U.S. Geological Survey, 2023, National Water Information System data available on the World Wide Web (USGS Water Data for the Nation), accessed [April 26, 2023], at http://waterdata.usgs.gov/nwis/. http://dx.doi.org/10.5066/F7P55KJN
This can be done using the `create_NWIS_bib` function:
```{r}
dv <- readNWISdv("09010500", "00060")
NWIScitation <- create_NWIS_bib(dv)
NWIScitation
print(NWIScitation, style = "Bibtex")
```
## Citing WQP data
Citations for specific datasets should use this format:
National Water Quality Monitoring Council, YYYY, Water Quality Portal, accessed mm, dd, yyyy, hyperlink_for_query, https://doi.org/10.5066/P9QRKUVJ.
This can be done using the `create_WQP_bib` function:
```{r}
SC <- readWQPqw(siteNumbers = "USGS-05288705",
parameterCd = "00300")
WQPcitation <- create_WQP_bib(SC)
WQPcitation
print(WQPcitation, style = "Bibtex")
```
## Citing Water Quality Portal itself
General Water Quality Portal citations should use the following:
Water Quality Portal. Washington (DC): National Water Quality Monitoring Council, United States Geological Survey (USGS), Environmental Protection Agency (EPA); 2021. https://doi.org/10.5066/P9QRKUVJ.
# Package Support
The Water Mission Area of the USGS supports the development and maintenance of `dataRetrieval`, and most likely further into the future. Resources are available primarily for maintenance and responding to user questions. Priorities on the development of new features are determined by the `dataRetrieval` development team. This software was last released with USGS record: IP-147158.
```{r disclaimer, child="DISCLAIMER.md", eval=TRUE}
```