R/calc_longterm_daily_stats.R
calc_longterm_daily_stats.RdCalculates 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 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 vector of percentiles to calculate. Set to NA if none required. Default c(10,90).
Numeric value of the number of days to apply a rolling mean. Default 1.
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).
Logical values indicating whether to include only years with complete data in analysis. Default FALSE.
Logical value indicating whether to include long-term calculation of all data. Default TRUE.
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.
Character string to label custom months. For example, if months = 7:9 you may choose
"Summer" or "Jul-Sep". Default "Custom-Months".
Logical value indicating whether to transpose rows and columns of results. 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.
A tibble data frame with the following columns:
month of the year, included 'Long-term' for all months, and 'Custom-Months' if selected
mean of all daily data for a given month and long-term over all years
median of all daily data for a given month and long-term over all years
maximum of all daily data for a given month and long-term over all years
minimum of all daily data for a given month and long-term over all years
each n-th percentile selected for a given month and long-term over all years
Default percentile columns:
annual 10th percentile selected for a given month and long-term over all years
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