read_waterdata_continuous: Get Continuous USGS Water Data

In dataRetrieval: Retrieval Functions for USGS and EPA Hydrology and Water Quality Data

Get Continuous USGS Water Data

Description

Continuous data are collected via automated sensors installed at a monitoring location. They are collected at a high frequency and often at a fixed 15-minute interval. Depending on the specific monitoring location, the data may be transmitted automatically via telemetry and be available on WDFN within minutes of collection, while other times the delivery of data may be delayed if the monitoring location does not have the capacity to automatically transmit data. Continuous data are described by parameter name and parameter code (pcode). These data might also be referred to as "instantaneous values" or "IV".

Currently, the services only allow up to 3 years of data to be requested with a single request. If no "time" is specified, the service will return the last single year of data. If this is a bottleneck, please check back for new direct download functions that are expected to be available sometime in 2026.

Geometry output is not supported in the continuous data API endpoint.

Usage

read_waterdata_continuous(
  monitoring_location_id = NA_character_,
  parameter_code = NA_character_,
  properties = NA_character_,
  time_series_id = NA_character_,
  approval_status = NA_character_,
  unit_of_measure = NA_character_,
  qualifier = NA_character_,
  value = NA,
  last_modified = NA_character_,
  time = NA_character_,
  limit = NA,
  convertType = TRUE,
  no_paging = FALSE
)

Arguments

monitoring_location_id	A unique identifier representing a single monitoring location. This corresponds to the id field in the monitoring-locations endpoint. Monitoring location IDs are created by combining the agency code of the agency responsible for the monitoring location (e.g. USGS) with the ID number of the monitoring location (e.g. 02238500), separated by a hyphen (e.g. USGS-02238500). Multiple monitoring_location_ids can be requested as a character vector.
parameter_code	Parameter codes are 5-digit codes used to identify the constituent measured and the units of measure. A complete list of parameter codes and associated groupings can be found at https://api.waterdata.usgs.gov/ogcapi/v0/collections/parameter-codes/items. Multiple parameter_codes can be requested as a character vector.
properties	A vector of requested columns to be returned from the query. Available options are: geometry, continuous_id, time_series_id, monitoring_location_id, parameter_code, statistic_id, time, value, unit_of_measure, approval_status, qualifier, last_modified. The default (NA) will return all columns of the data.
time_series_id	A unique identifier representing a single time series. This corresponds to the id field in the time-series-metadata endpoint. Multiple time_series_ids can be requested as a character vector.
approval_status	Some of the data that you have obtained from this U.S. Geological Survey database may not have received Director's approval. Any such data values are qualified as provisional and are subject to revision. Provisional data are released on the condition that neither the USGS nor the United States Government may be held liable for any damages resulting from its use. This field reflects the approval status of each record, and is either "Approved", meaining processing review has been completed and the data is approved for publication, or "Provisional" and subject to revision. For more information about provisional data, go to https://waterdata.usgs.gov/provisional-data-statement/.
unit_of_measure	A human-readable description of the units of measurement associated with an observation.
qualifier	This field indicates any qualifiers associated with an observation, for instance if a sensor may have been impacted by ice or if values were estimated.
value	The value of the observation. Values are transmitted as strings in the JSON response format in order to preserve precision.
last_modified	The last time a record was refreshed in our database. This may happen due to regular operational processes and does not necessarily indicate anything about the measurement has changed. You can query this field using date-times or intervals, adhering to RFC 3339, or using ISO 8601 duration objects. Intervals may be bounded or half-bounded (double-dots at start or end). Examples: A date-time: "2018-02-12T23:20:50Z" A bounded interval: "2018-02-12T00:00:00Z/2018-03-18T12:31:12Z" Half-bounded intervals: "2018-02-12T00:00:00Z/.." or "../2018-03-18T12:31:12Z" Duration objects: "P1M" for data from the past month or "PT36H" for the last 36 hours Only features that have a last_modified that intersects the value of datetime are selected. See also Details below for more information.
time	The date an observation represents. You can query this field using date-times or intervals, adhering to RFC 3339, or using ISO 8601 duration objects. Intervals may be bounded or half-bounded (double-dots at start or end). Examples: A date-time: "2018-02-12T23:20:50Z" A bounded interval: "2018-02-12T00:00:00Z/2018-03-18T12:31:12Z" Half-bounded intervals: "2018-02-12T00:00:00Z/.." or "../2018-03-18T12:31:12Z" Duration objects: "P1M" for data from the past month or "PT36H" for the last 36 hours Only features that have a time that intersects the value of datetime are selected. If a feature has multiple temporal properties, it is the decision of the server whether only a single temporal property is used to determine the extent or all relevant temporal properties. See also Details below for more information.
limit	The optional limit parameter is used to control the subset of the selected features that should be returned in each page. The maximum allowable limit is 50000. It may be beneficial to set this number lower if your internet connection is spotty. The default (NA) will set the limit to the maximum allowable limit for the service.
convertType	logical, defaults to TRUE. If TRUE, the function will convert the data to dates and qualifier to string vector, and sepcifically order the returning data frame by time and monitoring_location_id.
no_paging	logical, defaults to FALSE. If TRUE, the data will be requested from a native csv format. This can be dangerous because the data will cut off at 50,000 rows without indication that more data is available. Use TRUE with caution.

Details

You can also use a vector of length 2 for any time queries (such as time or last_modified). The first value is the starting date (or datetime), the second value is the ending date(or datetime). NA's within the vector indicate a half-bound date. For example, time = c("2024-01-01", NA) will return all data starting at 2024-01-01. time = c(NA, "2024-01-01") will return all data from the beginning of the timeseries until 2024-01-01. By default, time is assumed UTC, although time zone attributes will be accommodated. As an example, setting time = as.POSIXct(c("2021-01-01 12:00:00", "2021-01-01 14:00"), tz = "America/New_York") will request data that between noon and 2pm eastern time on 2021-01-01. All time values RETURNED from the service are UTC with the exception of daily data, which returns time values in local dates.

Examples

site <- "USGS-451605097071701"
pcode <- "72019"

uv_data_trim <- read_waterdata_continuous(monitoring_location_id = site,
                           parameter_code = pcode,
                           properties = c("value", "time"),
                           time = as.POSIXct(c("2026-02-07 12:00",
                                               "2026-02-08 12:00"),
                                              tz = "America/Chicago"))

uv_data <- read_waterdata_continuous(monitoring_location_id = site,
                           parameter_code = pcode,
                           time = "P2D")


# Only return data that has been modified in last 7 days
multi_site2 <- read_waterdata_continuous(monitoring_location_id =  c("USGS-451605097071701",
                                                                     "USGS-14181500"),
                                               parameter_code = c("00060", "72019"),
                                               last_modified = "P7D")

# how to split up request into roughly 3 year chunks

site <- "USGS-0208458892"
pcode <- "00095" # Specific conductance
start <- as.Date("2013-01-01")
end <- as.Date("2025-12-31")

n_days <- difftime(end, start, units = "days")

# create a vector of dates that are about 3 years apart:
time_chunks <- seq(from = start,
                   to = end,
                   length.out = ceiling(n_days/(3*365.25)) + 1)


# create a list where each element starts at the beginning
# of a chunk, and ends the day before the next chunk:
time_df <- data.frame(start = time_chunks[-length(time_chunks)],
                      end = time_chunks[-1]-1)

#all_data <- data.frame()
#for(i in seq_along(time_df$start)){
#   sub_df <- read_waterdata_continuous(monitoring_location_id = site,
#                                       parameter_code = pcode,
#                                      time = c(time_df$start[i],
#                                                time_df$end[i]))
#   all_data <- rbind(all_data, sub_df)
# }

# Set the time to Eastern:
# all_data$time <- lubridate::force_tz(all_data$time, "America/New_York")

dataRetrieval documentation built on March 31, 2026, 5:07 p.m.