# tidyhydat: An Introduction

#### Sam Albers

#### 2019-12-02

## Package loading

In addition to tidyhydat, this vignette makes use of the dplyr package for data manipulations and ggplot2 for plotting.

    library(tidyhydat)
    library(dplyr)
    library(ggplot2)

# `tidyhydat` package

This vignette will outline a few key options that will hopefully make `tidyhydat` useful.

## 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 2019-10-16
    ##    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 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" "01CC002" "01CC005" "01CC010" "01CC011"
    ## [8] "01CD005"

    hy_daily_flows(station_number = PEI_stns)

    ##   Queried from version of HYDAT released on 2019-10-16
    ##    Observations:                      106,357
    ##    Measurement flags:                 18,928
    ##    Parameter(s):                      Flow
    ##    Date range:                        1961-08-01 to 2017-12-31
    ##    Station(s) returned:               8
    ##    Stations requested but not returned:
    ##     All stations returned.
    ## # A tibble: 106,357 x 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 106,347 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 2019-10-16
    ##    Observations:                      81,915
    ##    Measurement flags:                 24,622
    ##    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: 81,915 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 81,905 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.

### Meterological Service of Canada datamart - `realtime_dd()`

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")

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")

## 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 x 5
    ##   STATION_NUMBER STATION_NAME               PROV_TERR_STATE_~ LATITUDE LONGITUDE
    ##   <chr>          <chr>                      <chr>                <dbl>     <dbl>
    ## 1 10AA001        LIARD RIVER AT UPPER CROS~ YT                    60.1     -129.
    ## 2 10AA006        LIARD RIVER BELOW SCURVY ~ YT                    60.8     -131.
    ## 3 10BE001        LIARD RIVER AT LOWER CROS~ 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 ~ BC                    59.7     -124.
    ## 7 10BE006        LIARD RIVER ABOVE KECHIKA~ BC                    59.7     -127.
    ## 8 10ED008        LIARD RIVER AT LINDBERG L~ NT                    61.1     -123.
    ## 9 10GC004        MACKENZIE RIVER ABOVE LIA~ 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: 50 x 5
    ##    STATION_NUMBER STATION_NAME              PROV_TERR_STATE_~ LATITUDE LONGITUDE
    ##    <chr>          <chr>                     <chr>                <dbl>     <dbl>
    ##  1 08MF005        FRASER RIVER AT HOPE      BC                    49.4     -121.
    ##  2 08MF040        FRASER RIVER ABOVE TEXAS~ BC                    50.6     -122.
    ##  3 08MF062        COQUIHALLA RIVER BELOW N~ BC                    49.5     -121.
    ##  4 08MF065        NAHATLATCH RIVER BELOW T~ BC                    50.0     -122.
    ##  5 08MF068        COQUIHALLA RIVER ABOVE A~ BC                    49.4     -121.
    ##  6 08MF001        ANDERSON RIVER NEAR BOST~ BC                    49.8     -121.
    ##  7 08MF002        BOULDER CREEK NEAR LAIDL~ BC                    49.3     -122.
    ##  8 08MF003        COQUIHALLA RIVER NEAR HO~ BC                    49.4     -121.
    ##  9 08MF004        FRASER RIVER ABOVE THOMP~ BC                    50.2     -122.
    ## 10 08MF006        WAHLEACH CREEK NEAR LAID~ BC                    49.3     -122.
    ## # ... with 40 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]") +
      theme_minimal()

# License

    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

       http://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.