`R/calc_longterm_daily_stats.R`

`calc_longterm_daily_stats.Rd`

Calculates the long-term mean, median, maximum, minimum, and percentiles of daily flow values for over all months and all data (Long-term) from a daily streamflow data set. Calculates statistics from all values, unless specified. Returns a tibble with statistics.

```
calc_longterm_daily_stats(
data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
station_number,
percentiles = c(10, 90),
roll_days = 1,
roll_align = "right",
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
complete_years = FALSE,
include_longterm = TRUE,
custom_months,
custom_months_label,
transpose = FALSE,
ignore_missing = FALSE
)
```

- data
Data frame of daily data that contains columns of dates, flow values, and (optional) groups (e.g. station numbers). Leave blank or set to

`NULL`

if using`station_number`

argument.- dates
Name of column in

`data`

that contains dates formatted YYYY-MM-DD. Only required if dates column name is not 'Date' (default). Leave blank or set to`NULL`

if using`station_number`

argument.- values
Name of column in

`data`

that contains numeric flow values, in units of cubic metres per second. Only required if values column name is not 'Value' (default). Leave blank if using`station_number`

argument.- groups
Name of column in

`data`

that contains unique identifiers for different data sets, if applicable. Only required if groups column name is not 'STATION_NUMBER'. Function will automatically group by a column named 'STATION_NUMBER' if present. Remove the 'STATION_NUMBER' column beforehand to remove this grouping. Leave blank if using`station_number`

argument.- station_number
Character string vector of seven digit Water Survey of Canada station numbers (e.g.

`"08NM116"`

) of which to extract daily streamflow data from a HYDAT database. Requires`tidyhydat`

package and a HYDAT database. Leave blank if using`data`

argument.- percentiles
Numeric vector of percentiles to calculate. Set to

`NA`

if none required. Default`c(10,90)`

.- roll_days
Numeric value of the number of days to apply a rolling mean. Default

`1`

.- roll_align
Character string identifying the direction of the rolling mean from the specified date, either by the first (

`'left'`

), last (`'right'`

), or middle (`'center'`

) day of the rolling n-day group of observations. Default`'right'`

.- water_year_start
Numeric value indicating the month (

`1`

through`12`

) of the start of water year for analysis. Default`1`

.- start_year
Numeric value of the first year to consider for analysis. Leave blank or set well before start date (i.e.

`1800`

) to use from the first year of the source data.- end_year
Numeric value of the last year to consider for analysis. Leave blank or set well after end date (i.e.

`2100`

) to use up to the last year of the source data.- exclude_years
Numeric vector of years to exclude from analysis. Leave blank or set to

`NULL`

to include all years.- months
Numeric vector of months to include in analysis. For example,

`3`

for March,`6:8`

for Jun-Aug or`c(10:12,1)`

for first four months (Oct-Jan) when`water_year_start = 10`

(Oct). Default summarizes all months (`1:12`

).- complete_years
Logical values indicating whether to include only years with complete data in analysis. Default

`FALSE`

.- include_longterm
Logical value indicating whether to include long-term calculation of all data. Default

`TRUE`

.- custom_months
Numeric vector of months to combine to summarize (ex.

`6:8`

for Jun-Aug). Adds results to the end of table. If wanting months that overlap calendar years (ex. Oct-Mar), choose`water_year_start`

that begins before the first month listed. Leave blank for no custom month summary.- custom_months_label
Character string to label custom months. For example, if

`months = 7:9`

you may choose`"Summer"`

or`"Jul-Sep"`

. Default`"Custom-Months"`

.- transpose
Logical value indicating whether to transpose rows and columns of results. Default

`FALSE`

.- ignore_missing
Logical value indicating whether dates with missing values should be included in the calculation. If

`TRUE`

then a statistic will be calculated regardless of missing dates. If`FALSE`

then only those statistics from time periods with no missing dates will be returned. Default`FALSE`

.

A tibble data frame with the following columns:

- Month
month of the year, included 'Long-term' for all months, and 'Custom-Months' if selected

- Mean
mean of all daily data for a given month and long-term over all years

- Median
median of all daily data for a given month and long-term over all years

- Maximum
maximum of all daily data for a given month and long-term over all years

- Minimum
minimum of all daily data for a given month and long-term over all years

- P'n'
each n-th percentile selected for a given month and long-term over all years

Default percentile columns:

- P10
annual 10th percentile selected for a given month and long-term over all years

- P90
annual 90th percentile selected for a given month and long-term over all years

Transposing data creates a column of "Statistics" and subsequent columns for each year selected.

```
# Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
if (file.exists(tidyhydat::hy_downloaded_db())) {
# Calculate long-term statistics using data argument with defaults
flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
calc_longterm_daily_stats(data = flow_data,
start_year = 1980)
# Calculate long-term statistics using station_number argument with defaults
calc_longterm_daily_stats(station_number = "08NM116",
start_year = 1980)
# Calculate long-term statistics regardless if there is missing data for a given year
calc_longterm_daily_stats(station_number = "08NM116",
ignore_missing = TRUE)
# Calculate long-term statistics for water years starting in October
calc_longterm_daily_stats(station_number = "08NM116",
start_year = 1980,
water_year_start = 10)
# Calculate long-term statistics with custom years and percentiles
calc_longterm_daily_stats(station_number = "08NM116",
start_year = 1981,
end_year = 2010,
exclude_years = c(1991,1993:1995),
percentiles = c(25,75))
# Calculate long-term statistics and add custom stats for July-September
calc_longterm_daily_stats(station_number = "08NM116",
start_year = 1980,
custom_months = 7:9,
custom_months_label = "Summer")
}
#> Warning: One or more calculations included missing values and NA's were produced. If desired, filter data for complete years or months, or use the 'ignore_missing' or 'allowed_missing' arguments (if applicable) to ignore or allow some missing values.
#> # A tibble: 14 × 8
#> STATION_NUMBER Month Mean Median Maximum Minimum P10 P90
#> <chr> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 08NM116 Jan 1.13 0.930 9.5 0.160 0.564 1.75
#> 2 08NM116 Feb 1.15 0.965 5.81 0.140 0.507 1.95
#> 3 08NM116 Mar 1.83 1.31 17.5 0.380 0.660 3.61
#> 4 08NM116 Apr 8.59 6.43 53.5 0.505 1.46 18.5
#> 5 08NM116 May 25.5 22.8 95.4 2.55 10 45.2
#> 6 08NM116 Jun 21.9 19.3 86.2 0.450 6.09 39.7
#> 7 08NM116 Jul 6.28 3.92 76.8 0.332 1.16 14.1
#> 8 08NM116 Aug 2.03 1.62 13.3 0.427 0.848 3.72
#> 9 08NM116 Sep 2.14 1.62 14.6 0.364 0.785 4.19
#> 10 08NM116 Oct 2.08 1.71 15.2 0.267 0.856 3.79
#> 11 08NM116 Nov 2.04 1.65 11.7 0.260 0.600 3.99
#> 12 08NM116 Dec 1.28 1.07 7.30 0.244 0.530 2.24
#> 13 08NM116 Long-term 6.34 1.84 95.4 0.140 0.700 20
#> 14 08NM116 Summer 3.50 1.95 76.8 0.332 0.873 7.10
```