Extract and Tidy Canadian 'Hydrometric' Data

government-data, hydrology, hydrometrics, r, r-package, rstats, tidy-data, water-resources



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This package is maintained by the Knowledge Management Branch of the British Columbia Ministry of Environment and Climate Change Strategy.

What does tidyhydat do?

  • Provides functions (hy_*) that access hydrometric data from the HYDAT database, a national archive of Canadian hydrometric data and return tidy data.
  • Provides functions (realtime_*) that access Environment and Climate Change Canada’s real-time hydrometric data source.
  • Provides functions (search_*) that can search through the approximately 7000 stations in the database and aid in generating station vectors
  • Keep functions as simple as possible. For example, for daily flows, the hy_daily_flows() function queries the database, tidies the data and returns a tibble of daily flows.


You can install tidyhydat from CRAN:


To install the development version of the tidyhydat package, you need to install the remotes package then the tidyhydat package

if(!requireNamespace("remotes")) install.packages("remotes")


A more thorough vignette can be found on the tidyhydat CRAN page.

When you install tidyhydat, several other packages will be installed as well. One of those packages, dplyr, is useful for data manipulations and is used regularly here. To use dplyr, it is required to be loaded by itself. A helpful dplyr tutorial can be found here.


HYDAT download

To use many of the functions in the tidyhydat package you will need to download a version of the HYDAT database, Environment and Climate Change Canada’s database of historical hydrometric data then tell R where to find the database. Conveniently tidyhydat does all this for you via:


This downloads (with your permission) the most recent version of HYDAT and then saves it in a location on your computer where tidyhydat’s function will look for it. Do be patient though as this takes a long time! To see where HYDAT was saved you can run hy_dir(). Now that you have HYDAT downloaded and ready to go, you are all set to begin looking at Canadian hydrometric data.

Most functions in tidyhydat follow a common argument structure. We will use the hy_daily_flows() function for the following examples though the same approach applies to most functions in the package (See help(package = "tidyhydat") for a list of exported objects). Much of the functionality of tidyhydat originates with the choice of hydrometric stations that you are interested in. A user will often find themselves creating vectors of station numbers. There are several ways to do this.

The simplest case is if you would like to extract only station. You can supply this directly to the station_number argument:

hy_daily_flows(station_number = "08LA001")
#>   Queried from version of HYDAT released on 2019-07-17
#>    Observations:                      29,890
#>    Measurement flags:                 5,922
#>    Parameter(s):                      Flow
#>    Date range:                        1914-01-01 to 2017-12-31 
#>    Station(s) returned:               1
#>    Stations requested but not returned: 
#>     All stations returned.
#> # A tibble: 29,890 x 5
#>    STATION_NUMBER Date       Parameter Value Symbol
#>    <chr>          <date>     <chr>     <dbl> <chr> 
#>  1 08LA001        1914-01-01 Flow        144 <NA>  
#>  2 08LA001        1914-01-02 Flow        144 <NA>  
#>  3 08LA001        1914-01-03 Flow        144 <NA>  
#>  4 08LA001        1914-01-04 Flow        140 <NA>  
#>  5 08LA001        1914-01-05 Flow        140 <NA>  
#>  6 08LA001        1914-01-06 Flow        136 <NA>  
#>  7 08LA001        1914-01-07 Flow        136 <NA>  
#>  8 08LA001        1914-01-08 Flow        140 <NA>  
#>  9 08LA001        1914-01-09 Flow        140 <NA>  
#> 10 08LA001        1914-01-10 Flow        140 <NA>  
#> # ... with 29,880 more rows

Another method is to use hy_stations() to generate your vector which is then given the station_number argument. For example, we could take a subset for only those active stations within Prince Edward Island (Province code: PE) and then create vector which is passed to the multi-parameter function hy_daily(). This function queries the flow, level, sediment load and suspended sediment concentration tables and combines them (if present) into one dataframe:

PEI_stns <- hy_stations() %>%
  filter(HYD_STATUS == "ACTIVE") %>%
  filter(PROV_TERR_STATE_LOC == "PE") %>%

#> [1] "01CA003" "01CB002" "01CB004" "01CC002" "01CC005" "01CC010" "01CC011"
#> [8] "01CD005"

hy_daily(station_number = PEI_stns)
#>   Queried from version of HYDAT released on 2019-07-17
#>    Observations:                      138,085
#>    Measurement flags:                 20,521
#>    Parameter(s):                      Flow/Level/Load/Suscon
#>    Date range:                        1961-08-01 to 2017-12-31 
#>    Station(s) returned:               8
#>    Stations requested but not returned: 
#>     All stations returned.
#> # A tibble: 138,085 x 5
#>    STATION_NUMBER Date       Parameter Value Symbol
#>    <chr>          <date>     <chr>     <dbl> <chr> 
#>  1 01CA003        1961-08-01 Flow         NA <NA>  
#>  2 01CA003        1961-08-02 Flow         NA <NA>  
#>  3 01CA003        1961-08-03 Flow         NA <NA>  
#>  4 01CA003        1961-08-04 Flow         NA <NA>  
#>  5 01CA003        1961-08-05 Flow         NA <NA>  
#>  6 01CA003        1961-08-06 Flow         NA <NA>  
#>  7 01CA003        1961-08-07 Flow         NA <NA>  
#>  8 01CA003        1961-08-08 Flow         NA <NA>  
#>  9 01CA003        1961-08-09 Flow         NA <NA>  
#> 10 01CA003        1961-08-10 Flow         NA <NA>  
#> # ... with 138,075 more rows

We can also merge our station choice and data extraction into one unified pipe which accomplishes a single goal. For example, if for some reason we wanted all the stations in Canada that had the name “Canada” in them we could unify those selection and data extraction processes into a single pipe:

search_stn_name("canada") %>%
  pull_station_number() %>%
#>   Queried from version of HYDAT released on 2019-07-17
#>    Observations:                      80,455
#>    Measurement flags:                 24,036
#>    Parameter(s):                      Flow
#>    Date range:                        1918-08-01 to 2019-05-31 
#>    Station(s) returned:               7
#>    Stations requested but not returned: 
#>     All stations returned.
#> # A tibble: 80,455 x 5
#>    STATION_NUMBER Date       Parameter Value Symbol
#>    <chr>          <date>     <chr>     <dbl> <chr> 
#>  1 01AK001        1918-08-01 Flow      NA    <NA>  
#>  2 01AK001        1918-08-02 Flow      NA    <NA>  
#>  3 01AK001        1918-08-03 Flow      NA    <NA>  
#>  4 01AK001        1918-08-04 Flow      NA    <NA>  
#>  5 01AK001        1918-08-05 Flow      NA    <NA>  
#>  6 01AK001        1918-08-06 Flow      NA    <NA>  
#>  7 01AK001        1918-08-07 Flow       1.78 <NA>  
#>  8 01AK001        1918-08-08 Flow       1.78 <NA>  
#>  9 01AK001        1918-08-09 Flow       1.5  <NA>  
#> 10 01AK001        1918-08-10 Flow       1.78 <NA>  
#> # ... with 80,445 more rows

These example illustrate a few ways that an vector can be generated and supplied to functions within tidyhydat.


To download real-time data using the datamart we can use approximately the same conventions discussed above. Using realtime_dd() we can easily select specific stations by supplying a station of interest:

realtime_dd(station_number = "08LG006")
#>   Queried on: 2019-09-03 16:51:45 (UTC)
#>   Date range: 2019-08-04 to 2019-09-03 
#> # A tibble: 17,412 x 8
#>    STATION_NUMBER PROV_TERR_STATE~ Date                Parameter Value
#>    <chr>          <chr>            <dttm>              <chr>     <dbl>
#>  1 08LG006        BC               2019-08-04 08:00:00 Flow       9.19
#>  2 08LG006        BC               2019-08-04 08:05:00 Flow       9.19
#>  3 08LG006        BC               2019-08-04 08:10:00 Flow       9.19
#>  4 08LG006        BC               2019-08-04 08:15:00 Flow       9.19
#>  5 08LG006        BC               2019-08-04 08:20:00 Flow       9.19
#>  6 08LG006        BC               2019-08-04 08:25:00 Flow       9.19
#>  7 08LG006        BC               2019-08-04 08:30:00 Flow       9.19
#>  8 08LG006        BC               2019-08-04 08:35:00 Flow       9.19
#>  9 08LG006        BC               2019-08-04 08:40:00 Flow       9.19
#> 10 08LG006        BC               2019-08-04 08:45:00 Flow       9.19
#> # ... with 17,402 more rows, and 3 more variables: Grade <chr>,
#> #   Symbol <chr>, Code <chr>

Another option is to provide simply the province as an argument and download all stations from that province:

realtime_dd(prov_terr_state_loc = "PE")


Plot methods are also provided to quickly visualize realtime data:

realtime_ex <- realtime_dd(station_number = "08LG006")


and also historical data:

hy_ex <- hy_daily_flows(station_number = "08LA001", start_date = "2013-01-01")


Getting Help or Reporting an Issue

To report bugs/issues/feature requests, please file an issue.

These are very welcome!

How to Contribute

If you would like to contribute to the package, please see our CONTRIBUTING guidelines.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.


Get citation information for tidyhydat in R by running:




Copyright 2017 Province of British Columbia

Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at


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