# Introduction to the dataRetrieval package

#### Laura A. DeCicco and Robert M. Hirsch

#### 27 May, 2026

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) hydrologic 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 USGS Water Data API.

For information on getting started in R and installing the package, see Getting Started. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

A quick workflow using `dataRetrieval` functions:

    library(dataRetrieval)
    # Choptank River near Greensboro, MD
    siteNumber <- "USGS-01491000"
    ChoptankInfo <- read_waterdata_monitoring_location(siteNumber)
    parameterCd <- "00060"

    # Raw daily data:
    rawDailyData <- read_waterdata_daily(monitoring_location_id = siteNumber,
                                         parameter_code = parameterCd,
                                         time = c("1980-01-01", "2010-01-01"))

    pCode <- read_waterdata_parameter_codes(parameter_code = parameterCd)

## 0.1 USGS Data API Access Tokens

USGS data are made available through the USGS water data APIs. You can register an API key for use with USGS water data APIs. There are now limits on how many queries can be requested per IP address per hour. If you find yourself running into limits, you can request an API token here: https://api.waterdata.usgs.gov/signup/

Then save your token in your .Renviron file like this:

    API_USGS_PAT = "my_super_secret_token"

You can use `usethis::edit_r_environ()` to edit find and open your .Renviron file. You will need to restart R for that variable to be recognized.

Table 1 describes the functions available in the `dataRetrieval` package.

Table 1: dataRetrieval functions
Name | Data Returned | Source
--- | --- | ---
read_waterdata | Time series data using user-specified queries | USGS Water Data API
read_waterdata_daily | Daily values | USGS Water Data API
read_waterdata_continuous | Instantaneous values | USGS Water Data API
read_waterdata_rating | Rating table for active streamgage | USGS Water Data API
read_waterdata_field_measurements | Surface-water measurements | USGS Water Data API
read_waterdata_peaks | Peak flow | USGS Water Data API
read_waterdata_field_measurements | Groundwater levels | USGS Water Data API
readNWISuse | Water use | NWIS
read_waterdata_stats_por, read_waterdata_stats_daterange | Statistical service | USGS Water Data API
read_waterdata_parameter_codes | Parameter code information | USGS Water Data API
read_waterdata_monitoring_location | Site information | USGS Water Data API
read_waterdata_samples | Discrete UGSS water quality data | USGS Samples Data
summarize_waterdata_samples | Discrete USGS water quality summary | USGS Samples Data
read_waterdata_combined_meta | Site search using user-specified queries | USGS Water Data API
read_waterdata_ts_meta | Data availability | USGS Water Data API
readWQPdata | User-specified queries | WQP
readWQPqw | Water quality data | WQP
whatWQPsites | Site search | WQP
whatWQPdata | Data availability | WQP
readWQPsummary | Summary data | WQP
whatWQPmetrics | Metric availability | WQP
whatWQPsamples | Sample availability | WQP

The arguments `startDate` and `endDate` have defaults to request the maximum data.

# 1 USGS Web Retrievals

In this section we’ll show how to get raw data into R. This data includes site information, measured parameter information, historical daily values, unit values (which include real-time data but can also include other sensor data stored at regular time intervals), groundwater level data, peak flow data, rating curve data, surface-water measurement data, water use data, and statistics data. The section Embedded Metadata shows instructions for getting metadata that is attached to each returned data frame.

The USGS organizes hydrologic data in a standard structure. Streamgages are located throughout the United States, and each streamgage has a unique ID (referred in this document and throughout the `dataRetrieval` package as `siteNumber`). Often (but not always), these ID’s are 8 digits for surface-water sites and 15 digits for groundwater sites. The first step to finding data is discovering this `siteNumber`.

Once the `siteNumber` is known, the next required input for USGS data retrievals is the “parameter code”. This is a 5-digit code that specifies the measured parameter being requested. For example, parameter code 00631 represents “Nitrate plus nitrite, water, filtered, milligrams per liter as nitrogen”, with units of “mg/l as N”.

Not every station will measure all parameters. A short list of commonly measured parameters is shown in Table 2.

Table 2: Common USGS Parameter Codes
pCode | shortName
--- | ---
00060 | Discharge [ft3/s]
00065 | Gage height [ft]
00010 | Temperature [C]
00045 | Precipitation [in]
00400 | pH

Two output columns that may not be obvious are “srsname” and “casrn”. Srsname stands for “Substance Registry Services”. Casrn stands for “Chemical Abstracts Service (CAS) Registry Number”.

For unit values data (sensor data measured at regular time intervals such as 15 minutes or hourly), knowing the parameter code and `siteNumber` is enough to make a request for data. For most variables that are measured on a continuous basis, the USGS also stores the historical data as daily values. These daily values are statistical summaries of the continuous data, e.g. maximum, minimum, mean, or median. The different statistics are specified by a 5-digit statistics code.

Some common codes are shown in Table 3.

Table 3: Commonly used USGS Stat Codes
StatCode | shortName
--- | ---
00001 | Maximum
00002 | Minimum
00003 | Mean
00008 | Median

Examples for using these site numbers, parameter codes, and statistic codes will be presented in subsequent sections.

## 1.1 Site Information

### 1.1.1 read_waterdata_monitoring_location

Use the `read_waterdata_monitoring_location` function to obtain all of the information available for a particular USGS site (or sites) such as full station name, drainage area, latitude, and longitude. `read_waterdata_monitoring_location` can also access information about multiple sites with a vector input.

    siteNumbers <- c("USGS-01491000", "USGS-01645000")
    siteINFO <- read_waterdata_monitoring_location(siteNumbers)

Site information is obtained from: https://api.waterdata.usgs.gov/ogcapi/v0/collections/monitoring-locations

### 1.1.2 read_waterdata_ts_meta

To discover what time series data is available for a particular USGS site, including measured parameters, period of record, and number of samples (count), use the `read_waterdata_ts_meta` function.

In the following example, we limit the retrieved data to only daily data.

    # Continuing from the previous example:
    # This pulls out just the daily, mean data:

    dailyDataAvailable <- read_waterdata_ts_meta(
      monitoring_location_id = siteNumbers,
      computation_period_identifier = "Daily",
      statistic_id = "00003"
    )

Table 4: Reformatted version of output from the read_waterdata_ts_meta function for the Choptank River near Greensboro, MD, and from Seneca Creek at Dawsonville, MD from the daily values service [Some columns deleted for space considerations]

monitoring_location_id | parameter_description | unit_of_measure | begin | end
--- | --- | --- | --- | ---
USGS-01491000 | Specific conductance, water, unfiltered, microsiemens per centimeter at 25 degrees Celsius | uS/cm | 2010-10-01 | 2012-05-09
USGS-01491000 | Dissolved oxygen, water, unfiltered, milligrams per liter | mg/l | 2023-04-21 | 2025-12-02
USGS-01491000 | Discharge, cubic feet per second | ft^3/s | 1948-01-01 | 2025-12-02
USGS-01645000 | Discharge, cubic feet per second | ft^3/s | 1930-09-26 | 2025-12-02
USGS-01491000 | Suspended sediment concentration, milligrams per liter | mg/l | 1980-10-01 | 1991-09-29
USGS-01491000 | Suspended sediment discharge, short tons per day | tons/day | 1980-10-01 | 1991-09-29
USGS-01491000 | Nitrate plus nitrite, water, in situ, milligrams per liter as nitrogen | mg/l | 2023-08-02 | 2025-12-02
USGS-01491000 | Temperature, water, degrees Celsius | degC | 2023-04-21 | 2025-12-02
USGS-01491000 | Turbidity, water, unfiltered, monochrome near infra-red LED light, 780-900 nm, detection angle 90 +-2.5 degrees, formazin nephelometric units (FNU) | _FNU | 2023-04-21 | 2025-12-02
USGS-01491000 | Temperature, water, degrees Celsius | degC | 2010-10-01 | 2012-05-09
USGS-01491000 | Specific conductance, water, unfiltered, microsiemens per centimeter at 25 degrees Celsius | uS/cm | 2023-04-21 | 2025-12-02

## 1.2 Parameter Information

To obtain all of the available information concerning a measured parameter (or multiple parameters), use the `read_waterdata_parameter_codes` function:

    # Using defaults:
    parameterCd <- "00618"
    parameterINFO <- read_waterdata_parameter_codes(parameter_code = parameterCd)

## 1.3 Daily Data

To obtain daily records of USGS data, use the `read_waterdata_daily` function.

    # Choptank River near Greensboro, MD:
    siteNumber <- "USSG-01491000"
    parameterCd <- "00060" # Discharge
    startDate <- "2009-10-01"
    endDate <- "2012-09-30"

    discharge <- read_waterdata_daily(monitoring_location_id = siteNumber,
                                      parameter_code = parameterCd,
                                      time = c(startDate, endDate))

The column “time” in the returned data frame is automatically imported as a variable of class “Date” in R.

Another example would be a request for mean and maximum daily temperature and discharge in early 2012:

    siteNumber <- "USGS-01491000"
    parameterCd <- c("00010", "00060") # Temperature and discharge
    statCd <- c("00001", "00003") # Mean and maximum
    startDate <- "2012-01-01"
    endDate <- "2012-05-01"

    temperatureAndFlow <- read_waterdata_daily(monitoring_location_id = siteNumber,
                                      parameter_code = parameterCd,
                                      statistic_id = statCd,
                                      time = c(startDate, endDate))

An example of plotting the above data:

    temperature <- temperatureAndFlow[temperatureAndFlow$parameter_code == "00010",]
    temperature <- temperature[temperature$statistic_id == "00001",]

    flow <- temperatureAndFlow[temperatureAndFlow$parameter_code == "00060",]

    par(mar = c(5, 5, 5, 5)) # sets the size of the plot window

    plot(temperature$time, temperature$value,
      ylab = "Maximum Temperture [C]",
      xlab = ""
    )
    par(new = TRUE)
    plot(flow$time,
      flow$value,
      col = "red", type = "l",
      xaxt = "n", yaxt = "n",
      xlab = "", ylab = "",
      axes = FALSE
    )
    axis(4, col = "red", col.axis = "red")
    mtext("Discharge [ft3/s]", side = 4, line = 3, col = "red")
    title("CHOPTANK RIVER NEAR GREENSBORO, MD")
    legend("topleft", unique(temperatureAndFlow$unit_of_measure),
      col = c("black", "red"), lty = c(NA, 1),
      pch = c(1, NA)
    )

## 1.4 Unit Data

Any data collected at regular time intervals (such as 15-minute or hourly) are known as “unit values”. Many of these are delivered on a real time basis and very recent data (even less than an hour old in many cases) are available through the function `read_waterdata_continuous`. Here is an example of a retrieval of such data.

    parameterCd <- "00060" # Discharge
    startDate <- "2012-05-12"
    endDate <- "2012-05-13"
    dischargeUnit <- read_waterdata_continuous(monitoring_location_id = siteNumber,
                                               parameter_code = parameterCd,
                                               time = c(startDate, endDate))

The retrieval produces a data frame that contains 96 rows (one for every 15 minute period in the day). They include all data collected from the `startDate` through the `endDate` (starting and ending with midnight locally-collected time). The dateTime column is converted to UTC (Coordinated Universal Time), so midnight EST will be 5 hours earlier in the dateTime column (the previous day, at 7pm).

## 1.5 Groundwater Level Data

Groundwater level measurements can be obtained with the `read_waterdata_field_measurements` function.

    siteNumber <- "USGS-434400121275801"
    groundWater <- read_waterdata_field_measurements(monitoring_location_id = siteNumber)

## 1.6 Peak Flow Data

Peak flow data are instantaneous discharge or stage data that record the maximum values of these variables during a flood event. They include the annual peak flood event but can also include records of other peaks that are lower than the annual maximum. Peak discharge measurements can be obtained with the `read_waterdata_peaks` function.

    siteNumber <- "USGS-01594440"
    peakData <- read_waterdata_peaks(monitoring_location_id = siteNumber)

## 1.7 Rating Curve Data

Rating curves are the calibration curves that are used to convert measurements of stage to discharge. Because of changing hydrologic conditions these rating curves change over time. Information on the returned data can be found with the `comment` function and attached attributes as described in the metadata section.

Rating curves can be obtained with the `read_waterdata_ratings` function.

    ratingData <- read_waterdata_ratings(monitoring_location_id = siteNumber,
                                        file_type = "base")
    comment(ratingData[[1]])

## 1.8 Surface-Water Measurement Data

These data are the discrete measurements of discharge that are made for the purpose of developing or revising the rating curve. Surface-water measurement data can be obtained with the `read_waterdata_field_measurements` function.

    surfaceData <- read_waterdata_field_measurements(monitoring_location_id = "USGS-01594440")

## 1.9 Water Use Data

Legacy water use data services have been retired. Check back in for developments on replacement functions.

## 1.10 Statistics Data

Retrieves site statistics from the USGS Water Data Statistics API. The `read_waterdata_stats_por` function retieves day-of-year and month-of-year daily data statistics from the `observationNormals` endpoint. The `read_waterdata_stats_daterange` function retieves calendar month, calendar year, and water year daily data statistics from the `observationIntervals` endpoint.

    discharge_stats_por <- read_waterdata_stats_por(
      monitoring_location_id = "USGS-05428500",
      parameter_code = "00060"
    )

    discharge_stats_daterange <- read_waterdata_stats_daterange(
      monitoring_location_id = "USGS-05428500",
      parameter_code = "00060"
    )

# 2 Water Quality Portal Web Retrievals

Water quality data sets available from the Water Quality Data Portal. These data sets can be housed in either the STORET database (data from EPA) and NWIS database (data from USGS). Because only USGS uses parameter codes, a “characteristic name” must be supplied. The `readWQPqw` function can take either a USGS parameter code, or a more general characteristic name in the parameterCd input argument. The Water Quality Data Portal includes data discovery tools and information on characteristic names. The following example retrieves specific conductance from a DNR site in Wisconsin.

    specificCond <- readWQPqw(
      "WIDNR_WQX-10032762",
      "Specific conductance",
      "2011-05-01", "2011-09-30"
    )

## 2.1 WQP

Just as with NWIS, the Water Quality Portal (WQP) offers a variety of ways to search for sites and request data. The possible Web service arguments for WQP site searches is found here.

### 2.1.1 Sites: whatWQPsites

To discover available sites in the WQP in New Jersey that have measured Chloride, use the function `whatWQPsites`.

    sitesNJ <- whatWQPsites(
      statecode = "US:34",
      characteristicName = "Chloride"
    )

### 2.1.2 Data: readWQPdata

To get data from the WQP using generalized Web service calls, use the function `readWQPdata`. For example, to get all the pH data in Wisconsin:

    dataPH <- readWQPdata(
      statecode = "US:55",
      characteristicName = "pH"
    )

### 2.1.3 Availability: whatWQPdata

The function `whatWQPdata` returns a data frame with information on the amount of data collected at a site. For example:

    type <- "Stream"
    sites <- whatWQPdata(countycode = "US:55:025", siteType = type)

This returns a data frame with all of the sites that were measured in streams in Dane County, WI. Also, in that table, there is a measure of `activityCount` (how often the site was sampled), and `resultCount` (how many individual results are available).

### 2.1.4 Samples: whatWQPsamples

The function `whatWQPsamples` returns information on the individual samples collected at a site. For example:

    site <- whatWQPsamples(siteid = "USGS-01594440")

This returns one row for each instance that a sample was collect.

### 2.1.5 Metrics: whatWQPmetrics

The function `whatWQPmetrics` provides metric information. This is only currently available for STORET data:

    type <- "Stream"
    sites <- whatWQPmetrics(countycode = "US:55:025", siteType = type)

# 3 Getting Started in R

This section describes the options for downloading and installing the `dataRetrieval` package.

## 3.1 New to R?

If you are new to R, you will need to first install the latest version of R, which can be found [here] (www.R-project.org).

At any time, you can get information about any function in R by typing a question mark before the functions name. This will open a file (in RStudio, in the Help window) that describes the function, the required arguments, and provides working examples. This will open a help file similar to the image below. To see the raw code for a particular code, type the name of the function, without parentheses.

    ?read_waterdata_parameter_codes

A simple R help file

Additionally, many R packages have vignette files attached (such as this paper). To see the list of vignettes in a package:

    # to see all available vignettes:
    vignette(package="dataRetrieval")

    #to open a specific vignette:
    vignette(topic = "qwdata_changes", package = "dataRetrieval")

# 4 Citations

## 4.1 Citing the dataRetrieval package

    citation(package = "dataRetrieval")

    ## To cite dataRetrieval in publications, please use:
    ##
    ##   De Cicco, L.A., Hirsch, R.M., Lorenz, D., Watkins,
    ##   W.D., Johnson, M., Blodgett, D.L., Hinman, E.D.,
    ##   Zemmels, J., 2026, dataRetrieval: R packages for
    ##   discovering and retrieving water data available
    ##   from Federal hydrologic web services, v.2.7.25,
    ##   doi:10.5066/P9X4L3GE
    ##
    ## A BibTeX entry for LaTeX users is
    ##
    ##   @Manual{,
    ##     author = {Laura DeCicco and Robert Hirsch and David Lorenz and Jordan Read and Jordan Walker and Lindsay Platt and David Watkins and David Blodgett and Mike Johnson and Aliesha Krall and Lee Stanish and Joseph Zemmels and Elise Hinman and Michael Mahoney},
    ##     title = {dataRetrieval: R packages for discovering and retrieving water data available from U.S. federal hydrologic web services},
    ##     publisher = {U.S. Geological Survey},
    ##     address = {Reston, VA},
    ##     version = {2.7.25},
    ##     institution = {U.S. Geological Survey},
    ##     year = {2026},
    ##     doi = {10.5066/P9X4L3GE},
    ##   }

## 4.2 Citing NWIS data

The requested format is:

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 https://dx.doi.org/10.5066/F7P55KJN

This can be created from the attributes of the data using the `create_NWIS_bib` function:

    dv <- read_waterdata_daily(monitoring_location_id = "USGS-04085427",
                               parameter_code = "00060",
                               time = c("2012-01-01", "2012-06-30"))

    NWIScitation <- create_NWIS_bib(dv)
    NWIScitation

    U.S. Geological Survey (2026). _USGS Water Data for the Nation: U.S. Geological Survey
    National Water Information System database_. doi:10.5066/F7P55KJN
    <https://doi.org/10.5066/F7P55KJN>, Accessed Mar 09, 2026.

Alternative output is available:

    print(NWIScitation, style = "Bibtex")

    @Manual{,
      title = {USGS Water Data for the Nation: U.S. Geological Survey National Water Information System database},
      author = {{U.S. Geological Survey}},
      doi = {10.5066/F7P55KJN},
      note = {Accessed Mar 09, 2026},
      year = {2026},
    }

    print(NWIScitation, style = "citation")

    U.S. Geological Survey, 2024, National Water Information System
    data available on the World Wide Web (USGS Water Data for the
    Nation), accessed Feb 09, 2024, at
    https://waterservices.usgs.gov/nwis/dv/?site=09010500&format=waterml,1.1&ParameterCd=00060&StatCd=00003&startDT=1851-01-01,
    https://dx.doi.org/10.5066/F7P55KJN

    A BibTeX entry for LaTeX users is

      @Manual{,
        title = {National Water Information System data available on the World Wide Web (USGS Water Data for the Nation)},
        author = {{U.S. Geological Survey}},
        doi = {10.5066/F7P55KJN},
        note = {Accessed Feb 09, 2024},
        year = {2024},
        url = {https://waterservices.usgs.gov/nwis/dv/?site=09010500&format=waterml,1.1&ParameterCd=00060&StatCd=00003&startDT=1851-01-01},
      }

## 4.3 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 obtained using the `create_WQP_bib` function:

    SC <- readWQPqw(siteNumbers = "USGS-05288705",
                    parameterCd = "00300")

    WQPcitation <- create_WQP_bib(SC)
    WQPcitation

    National Water Quality Monitoring Council (2024). _ Water
    Quality Portal_. doi:10.5066/P9QRKUVJ
    <https://doi.org/10.5066/P9QRKUVJ>, Accessed Feb 09, 2024,
    <https://www.waterqualitydata.us/data/Result/search?siteid=USGS-05288705&pCode=00300&mimeType=tsv&zip=yes>.

    print(WQPcitation, style = "Bibtex")

    @Manual{,
      title = { Water Quality Portal},
      author = {{National Water Quality Monitoring Council}},
      doi = {10.5066/P9QRKUVJ},
      note = {Accessed Feb 09, 2024},
      year = {2024},
      url = {https://www.waterqualitydata.us/data/Result/search?siteid=USGS-05288705&pCode=00300&mimeType=tsv&zip=yes},
    }

    print(WQPcitation, style = "citation")

    National Water Quality Monitoring Council, 2024, Water Quality
    Portal, accessed 02, 09, 2024,
    https://www.waterqualitydata.us/data/Result/search?siteid=USGS-05288705&pCode=00300&mimeType=tsv&zip=yes,
    https://doi.org/10.5066/P9QRKUVJ.

    A BibTeX entry for LaTeX users is

      @Manual{,
        title = { Water Quality Portal},
        author = {{National Water Quality Monitoring Council}},
        doi = {10.5066/P9QRKUVJ},
        note = {Accessed Feb 09, 2024},
        year = {2024},
        url = {https://www.waterqualitydata.us/data/Result/search?siteid=USGS-05288705&pCode=00300&mimeType=tsv&zip=yes},
      }

## 4.4 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.

# 5 Disclaimer

This information is preliminary and is subject to revision. It is being provided to meet the need for timely best science. The information is provided on the condition that neither the U.S. Geological Survey nor the U.S. Government may be held liable for any damages resulting from the authorized or unauthorized use of the information.