- 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:
install.packages("tidyhydat")
To install the development version of the tidyhydat package, you can
install directly from the rOpenSci development server:
install.packages("tidyhydat", repos = "https://dev.ropensci.org")
More documentation on tidyhydat can found at the rOpenSci doc page:
https://docs.ropensci.org/tidyhydat/
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 actually use dplyr in
a session you must explicitly load it. A helpful dplyr tutorial can be
found
here.
library(tidyhydat)
library(dplyr)
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:
download_hydat()
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 can take a long
time! To see where HYDAT was saved you can run hy_default_db(). Now
that you have HYDAT downloaded and ready to go, you are all set to begin
looking at Canadian hydrometric data.
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 = "08MF005")
#> Queried on: 2024-10-04 21:22:54.830085 (UTC)
#> Date range: 2024-09-04 to 2024-10-04
#> # A tibble: 17,574 × 8
#> STATION_NUMBER PROV_TERR_STATE_LOC Date Parameter Value Grade Symbol Code
#> <chr> <chr> <dttm> <chr> <dbl> <chr> <chr> <chr>
#> 1 08MF005 BC 2024-09-04 08:00:00 Flow 1830 <NA> <NA> 1
#> 2 08MF005 BC 2024-09-04 08:05:00 Flow 1830 <NA> <NA> 1
#> 3 08MF005 BC 2024-09-04 08:10:00 Flow 1830 <NA> <NA> 1
#> 4 08MF005 BC 2024-09-04 08:15:00 Flow 1840 <NA> <NA> 1
#> 5 08MF005 BC 2024-09-04 08:20:00 Flow 1840 <NA> <NA> 1
#> 6 08MF005 BC 2024-09-04 08:25:00 Flow 1830 <NA> <NA> 1
#> 7 08MF005 BC 2024-09-04 08:30:00 Flow 1830 <NA> <NA> 1
#> 8 08MF005 BC 2024-09-04 08:35:00 Flow 1830 <NA> <NA> 1
#> 9 08MF005 BC 2024-09-04 08:40:00 Flow 1830 <NA> <NA> 1
#> 10 08MF005 BC 2024-09-04 08:45:00 Flow 1830 <NA> <NA> 1
#> # ℹ 17,564 more rows
Or we can use realtime_ws:
realtime_ws(
station_number = "08MF005",
parameters = c(46, 5), ## see param_id for a list of codes
start_date = Sys.Date() - 14,
end_date = Sys.Date()
)
#> All station successfully retrieved
#> All parameters successfully retrieved
#> # A tibble: 4,632 × 10
#> STATION_NUMBER Date Name_En Value Unit Grade Symbol Approval Parameter Code
#> <chr> <dttm> <chr> <dbl> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 08MF005 2024-09-20 00:00:00 Water temperature 17.0 °C -1 <NA> Provisional/Provisoire 5 TW
#> 2 08MF005 2024-09-20 01:00:00 Water temperature 17.0 °C -1 <NA> Provisional/Provisoire 5 TW
#> 3 08MF005 2024-09-20 02:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 4 08MF005 2024-09-20 03:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 5 08MF005 2024-09-20 04:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 6 08MF005 2024-09-20 05:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 7 08MF005 2024-09-20 06:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 8 08MF005 2024-09-20 07:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 9 08MF005 2024-09-20 08:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 10 08MF005 2024-09-20 09:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> # ℹ 4,622 more rows
tidyhydat provides two methods to download realtime data.
realtime_dd() provides a function to import .csv files from
here. realtime_ws() is an
client for a web service hosted by ECCC. realtime_ws() has several
difference to realtime_dd(). These include:
- Speed: The
realtime_ws()is much faster for larger queries (i.e. many stations). For single station queries torealtime_dd()is more appropriate. - Length of record:
realtime_ws()records goes back further in time. - Type of parameters:
realtime_dd()are restricted to river flow (either flow and level) data. In contrastrealtime_ws()can download several different parameters depending on what is available for that station. Seedata("param_id")for a list and explanation of the parameters. - Date/Time filtering:
realtime_ws()provides argument to select a date range. Selecting a data range withrealtime_dd()is not possible until after all files have been downloaded.
Plot methods are also provided to quickly visualize realtime data:
realtime_ex <- realtime_dd(station_number = "08MF005")
plot(realtime_ex)
and also historical data:
hy_ex <- hy_daily_flows(station_number = "08MF005", start_date = "2013-01-01")
plot(hy_ex)
To report bugs/issues/feature requests, please file an issue.
These are very welcome!
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:
To cite package 'tidyhydat' in publications use:
Albers S (2017). "tidyhydat: Extract and Tidy Canadian Hydrometric Data." _The Journal of Open Source Software_, *2*(20). doi:10.21105/joss.00511 <https://doi.org/10.21105/joss.00511>,
<http://dx.doi.org/10.21105/joss.00511>.
A BibTeX entry for LaTeX users is
@Article{,
title = {tidyhydat: Extract and Tidy Canadian Hydrometric Data},
author = {Sam Albers},
doi = {10.21105/joss.00511},
url = {http://dx.doi.org/10.21105/joss.00511},
year = {2017},
publisher = {The Open Journal},
volume = {2},
number = {20},
journal = {The Journal of Open Source Software},
}
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
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.