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:

download_hydat()

This downloads 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 some hydrologic analysis.

Usage

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 ls("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 2022-07-21
##    Observations:                      31,351
##    Measurement flags:                 6,166
##    Parameter(s):                      Flow
##    Date range:                        1914-01-01 to 2021-12-31 
##    Station(s) returned:               1
##    Stations requested but not returned: 
##     All stations returned.
## # A tibble: 31,351 × 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 31,341 more rows
## # ℹ Use `print(n = ...)` to see 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 for hy_daily_flows():

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

PEI_stns

## [1] "01CA003" "01CB002" "01CB004" "01CB018" "01CC002" "01CC005" "01CC010" "01CC011"
## [9] "01CD005"

hy_daily_flows(station_number = PEI_stns)

##   Queried from version of HYDAT released on 2022-07-21
##    Observations:                      114,605
##    Measurement flags:                 20,524
##    Parameter(s):                      Flow
##    Date range:                        1961-08-01 to 2020-12-31 
##    Station(s) returned:               9
##    Stations requested but not returned: 
##     All stations returned.
## # A tibble: 114,605 × 5
##    STATION_NUMBER Date       Parameter Value Symbol
##    <chr>          <date>     <chr>     <dbl> <chr> 
##  1 01CA003        1961-08-01 Flow         NA <NA>  
##  2 01CB002        1961-08-01 Flow         NA <NA>  
##  3 01CA003        1961-08-02 Flow         NA <NA>  
##  4 01CB002        1961-08-02 Flow         NA <NA>  
##  5 01CA003        1961-08-03 Flow         NA <NA>  
##  6 01CB002        1961-08-03 Flow         NA <NA>  
##  7 01CA003        1961-08-04 Flow         NA <NA>  
##  8 01CB002        1961-08-04 Flow         NA <NA>  
##  9 01CA003        1961-08-05 Flow         NA <NA>  
## 10 01CB002        1961-08-05 Flow         NA <NA>  
## # … with 114,595 more rows
## # ℹ Use `print(n = ...)` to see 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 unify that selection and data extraction process into a single pipe:

search_stn_name("canada") %>%
  pull_station_number() %>%
  hy_daily_flows()

##   Queried from version of HYDAT released on 2022-07-21
##    Observations:                      86,056
##    Measurement flags:                 26,218
##    Parameter(s):                      Flow
##    Date range:                        1918-08-01 to 2021-12-31 
##    Station(s) returned:               7
##    Stations requested but not returned: 
##     All stations returned.
## # A tibble: 86,056 × 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 86,046 more rows
## # ℹ Use `print(n = ...)` to see more rows

We saw above that if we were only interested in a subset of dates we could use the start_date and end_date arguments. A date must be supplied to both these arguments in the form of YYYY-MM-DD. If you were interested in all daily flow data from station number “08LA001” for 1981, you would specify all days in 1981 :

hy_daily_flows(station_number = "08LA001", 
               start_date = "1981-01-01", 
               end_date = "1981-12-31")

This generally outlines the usage of the HYDAT functions within tidyhydat.

Real-time functions

In addition to the approved and vetted data in the HYDAT database ECCC also offers unapproved data that is subject to revision. tidyhydat provides three functions to access these data sources. Remember these are unapproved data and should treated as such:

• realtime_stations()
• realtime_dd()

Not every stations is currently part of the real-time network. Therefore realtime_stations() points to a (hopefully) updated ECCC data file of active real-time stations. We can use the realtime_stations() functionality to get a vector of stations by jurisdiction. For example, we can choose all the stations in Prince Edward Island using the following:

realtime_stations(prov_terr_state_loc = "PE")

hy_stations() and realtime_stations() perform similar tasks albeit on different data sources. hy_stations() extracts directly from HYDAT. In addition to real-time stations, hy_stations() outputs discontinued and non-real-time stations:

hy_stations(prov_terr_state_loc = "PE")

This is contrast to realtime_stations() which downloads all real-time stations. Though this is not always the case, it is best to use realtime_stations() when dealing with real-time data and hy_stations() when interacting with HYDAT. It is also appropriate to filter the output of hy_stations() by the REAL_TIME column.

realtime_dd(station_number = "08LG006")

realtime_dd(prov_terr_state_loc = "PE")

Search functions

You can also make use of auxiliary functions in tidyhydat called search_stn_name() and search_stn_number() to look for matches when you know part of a name of a station. For example:

search_stn_name("liard")

## # A tibble: 9 × 5
##   STATION_NUMBER STATION_NAME                      PROV_TERR_STATE_LOC LATITUDE LONGITUDE
##   <chr>          <chr>                             <chr>                  <dbl>     <dbl>
## 1 10AA001        LIARD RIVER AT UPPER CROSSING     YT                      60.1     -129.
## 2 10AA006        LIARD RIVER BELOW SCURVY CREEK    YT                      60.8     -131.
## 3 10BE001        LIARD RIVER AT LOWER CROSSING     BC                      59.4     -126.
## 4 10ED001        LIARD RIVER AT FORT LIARD         NT                      60.2     -123.
## 5 10ED002        LIARD RIVER NEAR THE MOUTH        NT                      61.7     -121.
## 6 10BE005        LIARD RIVER ABOVE BEAVER RIVER    BC                      59.7     -124.
## 7 10BE006        LIARD RIVER ABOVE KECHIKA RIVER   BC                      59.7     -127.
## 8 10ED008        LIARD RIVER AT LINDBERG LANDING   NT                      61.1     -123.
## 9 10GC004        MACKENZIE RIVER ABOVE LIARD RIVER NT                      61.9     -121.

Similarly, search_stn_number() can be useful if you are interested in all stations from the 08MF sub-sub-drainage:

search_stn_number("08MF")

## # A tibble: 53 × 5
##    STATION_NUMBER STATION_NAME                           PROV_TERR_STATE_LOC LATIT…¹ LONGI…²
##    <chr>          <chr>                                  <chr>                 <dbl>   <dbl>
##  1 08MF005        FRASER RIVER AT HOPE                   BC                     49.4   -121.
##  2 08MF035        FRASER RIVER NEAR AGASSIZ              BC                     49.2   -122.
##  3 08MF038        FRASER RIVER AT CANNOR                 BC                     49.1   -122.
##  4 08MF040        FRASER RIVER ABOVE TEXAS CREEK         BC                     50.6   -122.
##  5 08MF062        COQUIHALLA RIVER BELOW NEEDLE CREEK    BC                     49.5   -121.
##  6 08MF065        NAHATLATCH RIVER BELOW TACHEWANA CREEK BC                     50.0   -122.
##  7 08MF068        COQUIHALLA RIVER ABOVE ALEXANDER CREEK BC                     49.4   -121.
##  8 08MF072        FRASER RIVER AT LAIDLAW                BC                     49.3   -122.
##  9 08MF073        FRASER RIVER AT HARRISON MILLS         BC                     49.2   -122.
## 10 08MF001        ANDERSON RIVER NEAR BOSTON BAR         BC                     49.8   -121.
## # … with 43 more rows, and abbreviated variable names ¹​LATITUDE, ²​LONGITUDE
## # ℹ Use `print(n = ...)` to see more rows

Using joins

Sometimes it is required to make use of information from two tables from HYDAT. In some cases, we need to combine the information into one table using a common column. Here we will illustrate calculating runoff by combining the hy_stations tables with the hy_daily_flows table by the STATION_NUMBER column:

stns <- c("08NH130", "08NH005")
runoff_data <- hy_daily_flows(station_number = stns, start_date = "2000-01-01") %>%
  left_join(
    hy_stations(station_number = stns) %>%
      select(STATION_NUMBER, STATION_NAME, DRAINAGE_AREA_GROSS),
    by = "STATION_NUMBER") %>%
  ## conversion to mm/d
  mutate(runoff = Value / DRAINAGE_AREA_GROSS * 86400 / 1e6 * 1e3) 


ggplot(runoff_data) + 
  geom_line(aes(x = Date, y = runoff, colour = STATION_NAME)) +
  labs(y = "Mean daily runoff [mm/d]") +
  scale_colour_viridis_d(option = "C") +
  theme_minimal() +
  theme(legend.position = "bottom")

This is an effective way to make use of the variety of tables available in HYDAT.