fasstr: calc_longterm_daily_stats – R documentation

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calc_longterm_daily_stats

Calculate long-term summary statistics from daily mean flows

Description

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.

Usage

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
)

Arguments

`data`	Data frame of daily data that contains columns of dates, flow values, and (optional) groups (e.g. station numbers). Leave blank 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 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 to use the first year of the source data.
`end_year`	Numeric value of the last year to consider for analysis. Leave blank to use the last year of the source data.
`exclude_years`	Numeric vector of years to exclude from analysis. Leave blank to include all years.
`months`	Numeric vector of months to include in analysis (e.g. `6:8` for Jun-Aug). Leave blank to summarize all months (default `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`.

Value

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.

Examples

# 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
calc_longterm_daily_stats(station_number = "08NM116",
                          start_year = 1981,
                          end_year = 2010,
                          exclude_years = c(1991,1993:1995))
                  
# Calculate long-term statistics for 7-day flows for July-September months only, 
# with 25 and 75th percentiles
calc_longterm_daily_stats(station_number = "08NM116",
                          roll_days = 7,
                          months = 7:9,
                          percentiles = c(25,75),
                          ignore_missing = TRUE,
                          include_longterm = FALSE) # removes the Long-term numbers 
                    
# 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")                  
                          
}

fasstr

Analyze, Summarize, and Visualize Daily Streamflow Data

v0.3.2

Apache License 2.0

Authors

Jon Goetz [aut, cre] (<https://orcid.org/0000-0002-4993-1119>), Carl James Schwarz [aut], Robin Pike [ctb], Province of British Columbia [cph]

Initial release