knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE, eval = nzchar(Sys.getenv("hydat_eval")), fig.width=7, fig.height=7)
library(tidyhydat) library(dplyr) library(ggplot2)
This vignette will outline a few key options that will hopefully make
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 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.
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
hy_daily_flows(station_number = "08LA001")
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
PEI_stns <- hy_stations() %>% filter(HYD_STATUS == "ACTIVE") %>% filter(PROV_TERR_STATE_LOC == "PE") %>% pull_station_number() PEI_stns hy_daily_flows(station_number = PEI_stns)
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()
We saw above that if we were only interested in a subset of dates we could use the
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
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:
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")
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
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")
You can also make use of auxiliary functions in
search_stn_number() to look for matches when you know part of a name of a station. For example:
search_stn_number() can be useful if you are interested in all stations from the 08MF sub-sub-drainage:
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
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()
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.
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