This function has been superseded by the calc_annual_extremes() function.
Calculates annual n-day minimum and maximum values, and the day of year and date of occurrence of daily flow values from a daily streamflow data set. Calculates statistics from all values, unless specified. Returns a tibble with statistics.
calc_annual_peaks(
data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
station_number,
roll_days = 1,
roll_days_low = NA,
roll_days_high = NA,
roll_align = "right",
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
months_low = NA,
months_high = NA,
transpose = FALSE,
complete_years = FALSE,
ignore_missing = FALSE,
allowed_missing = ifelse(ignore_missing, 100, 0)
)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.
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.
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.
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.
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.
Numeric value of the number of days to apply a rolling mean. Default 1.
Numeric value of the number of days to apply a rolling mean for low flows. Will override 'roll_days' argument
for low flows. Default NA.
Numeric value of the number of days to apply a rolling mean for high flows. Will override 'roll_days' argument
for high flows. Default NA.
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'.
Numeric value indicating the month (1 through 12) of the start of water year for
analysis. Default 1.
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.
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.
Numeric vector of years to exclude from analysis. Leave blank or set to NULL to include all years.
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).
Numeric vector of specified months for window of low flows (3 for March, 6:8 for Jun-Aug). Will override 'months'
argument for low flows. Default NA.
Numeric vector of specified months for window of high flows (3 for March, 6:8 for Jun-Aug). Will override 'months'
argument for high flows. Default NA.
Logical value indicating whether to transpose rows and columns of results. Default FALSE.
Logical values indicating whether to include only years with complete data in analysis. Default FALSE.
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.
Numeric value between 0 and 100 indicating the percentage of missing dates allowed to be
included to calculate a statistic (0 to 100 percent). If 'ignore_missing = FALSE' then it defaults to 0 (zero missing dates allowed),
if 'ignore_missing = TRUE' then it defaults to 100 (any missing dates allowed); consistent with
ignore_missing usage. Supersedes ignore_missing when used.
A tibble data frame with the following columns:
calendar or water year selected
annual minimum for selected n-day rolling mean, direction of mean specified by roll_align
day of year for selected annual minimum of n-day rolling mean
date (YYYY-MM-DD) for selected annual minimum of n-day rolling mean
annual maximum for selected n-day rolling mean, direction of mean specified by roll_align
day of year for selected annual maximum of n-day rolling mean
date (YYYY-MM-DD) for selected annual maximum of n-day rolling mean
Default columns:
annual 1-day mean minimum (roll_align = right)
day of year of annual 1-day mean minimum
date (YYYY-MM-DD) of annual 1-day mean minimum
annual 1-day mean maximum (roll_align = right)
day of year of annual 1-day mean maximum
date (YYYY-MM-DD) of annual 1-day mean maximum
Transposing data creates a column of 'Statistics' and subsequent columns for each year selected. 'Date' statistics not transposed.
# Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
if (file.exists(tidyhydat::hy_downloaded_db())) {
# Calculate annual 1-day (default) peak flow data with
# default alignment ('right')
calc_annual_peaks(station_number = "08NM116")
# Calculate custom 3-day peak flow data with 'center' alignment
calc_annual_peaks(station_number = "08NM116",
roll_days = 3,
roll_align = "center")
}
#> Note: this function has been superseded by the 'calc_annual_extremes()' function. This function is still supported but no longer receives active development, as better solutions now exist.
#> 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.
#> Note: this function has been superseded by the 'calc_annual_extremes()' function. This function is still supported but no longer receives active development, as better solutions now exist.
#> 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: 72 × 8
#> STATION_NUMBER Year Min_3_Day Min_3_…¹ Min_3_Da…² Max_3…³ Max_3…⁴ Max_3_Da…⁵
#> <chr> <dbl> <dbl> <dbl> <date> <dbl> <dbl> <date>
#> 1 08NM116 1949 NA NA NA NA NA NA
#> 2 08NM116 1950 NA NA NA NA NA NA
#> 3 08NM116 1951 NA NA NA NA NA NA
#> 4 08NM116 1952 NA NA NA NA NA NA
#> 5 08NM116 1953 NA NA NA NA NA NA
#> 6 08NM116 1954 NA NA NA NA NA NA
#> 7 08NM116 1955 NA NA NA NA NA NA
#> 8 08NM116 1956 NA NA NA NA NA NA
#> 9 08NM116 1957 NA NA NA NA NA NA
#> 10 08NM116 1958 NA NA NA NA NA NA
#> # … with 62 more rows, and abbreviated variable names ¹Min_3_Day_DoY,
#> # ²Min_3_Day_Date, ³Max_3_Day, ⁴Max_3_Day_DoY, ⁵Max_3_Day_Date