compute_annual_trends: Calculate prewhitened nonlinear annual trends on streamflow...
In fasstr: Analyze, Summarize, and Visualize Daily Streamflow Data

compute_annual_trends

R Documentation

Calculate prewhitened nonlinear annual trends on streamflow data

Description

Calculates prewhitened nonlinear trends on annual streamflow data. Uses the zyp package to calculate trends. Review zyp for more information Calculates statistics from all values, unless specified. Returns a list of tibbles and plots. All annual statistics calculated using the calc_all_annual_stats() function which uses the following fasstr functions:

calc_annual_stats()
calc_annual_lowflows()
calc_annual_cumulative_stats()
calc_annual_flow_timing()
calc_monthly_stats()
calc_annual_normal_days()

Usage

compute_annual_trends(
  data,
  dates = Date,
  values = Value,
  groups = STATION_NUMBER,
  station_number,
  zyp_method,
  basin_area,
  water_year_start = 1,
  start_year,
  end_year,
  exclude_years,
  months = 1:12,
  annual_percentiles = c(10, 90),
  monthly_percentiles = c(10, 20),
  stats_days = 1,
  stats_align = "right",
  lowflow_days = c(1, 3, 7, 30),
  lowflow_align = "right",
  timing_percent = c(25, 33, 50, 75),
  normal_percentiles = c(25, 75),
  complete_years = FALSE,
  ignore_missing = FALSE,
  allowed_missing_annual = ifelse(ignore_missing, 100, 0),
  allowed_missing_monthly = ifelse(ignore_missing, 100, 0),
  include_plots = TRUE,
  zyp_alpha
)

Arguments

`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.
`zyp_method`	Character string identifying the prewhitened trend method to use from `zyp`, either `'zhang'` or `'yuepilon'`. `'zhang'` is recommended over `'yuepilon'` for hydrologic applications (Bürger 2017; Zhang and Zwiers 2004). Required.
`basin_area`	Upstream drainage basin area, in square kilometres, to apply to observations. Three options: (1) Leave blank if `groups` is STATION_NUMBER with HYDAT station numbers to extract basin areas from HYDAT. (2) A single numeric value to apply to all observations. (3) List each basin area for each group/station in groups (can override HYDAT value if listed) as such `c("08NM116" = 795, "08NM242" = 10)`. If group is not listed the HYDAT area will be applied if it exists, otherwise it will be `NA`.
`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`). If not all months, seasonal total yield and volumetric flows will not be included.
`annual_percentiles`	Numeric vector of percentiles to calculate annually. Set to `NA` if none required. Used for `calc_annual_stats()` function. Default `c(10,90)`.
`monthly_percentiles`	Numeric vector of percentiles to calculate monthly for each year. Set to `NA` if none required. Used for `calc_monthly_stats()` function. Default `c(10,20)`.
`stats_days`	Numeric vector of the number of days to apply a rolling mean on basic stats. Default `c(1)`. Used for `calc_annual_stats()` and `calc_monthly_stats()` functions.
`stats_align`	Character string identifying the direction of the rolling mean on basic stats 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'`. Used for `calc_annual_stats()`, `calc_monthly_stats()`, and `calc_annual_normal_days()` functions.
`lowflow_days`	Numeric vector of the number of days to apply a rolling mean on low flow stats. Default `c(1,3,7,30)`. Used for `calc_lowflow_stats()` function.
`lowflow_align`	Character string identifying the direction of the rolling mean on low flow stats 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'`. Used for `calc_lowflow_stats()` function.
`timing_percent`	Numeric vector of percents of annual total flows to determine dates. Used for `calc_annual_flow_timing()` function. Default `c(25,33.3,50,75)`.
`normal_percentiles`	Numeric vector of two values, lower and upper percentiles, respectively indicating the limits of the normal range. Default `c(25,75)`.
`complete_years`	Logical values indicating whether to include only years with complete data in analysis. 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`.
`allowed_missing_annual`	Numeric value between 0 and 100 indicating the percentage of missing dates allowed to be included to calculate an annual 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. Only for annual means, percentiles, minimums, and maximums.
`allowed_missing_monthly`	Numeric value between 0 and 100 indicating the percentage of missing dates allowed to be included to calculate a monthly 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.Only for monthly means, percentiles, minimums, and maximums.
`include_plots`	Logical value indicating if annual trending plots should be included. Default `TRUE`.
`zyp_alpha`	Numeric value of the significance level (ex. `0.05`) of when to plot a trend line. Leave blank for no line.

Value

A list of tibbles and optional plots from the trending analysis including:

`Annual_Trends_Data`	a tibble of the annual statistics used for trending
`Annual_Trends_Results`	a tibble of the results of the zyp trending analysis
`Annual_*`	each ggplot2 object for each annual trended statistic

References

References:

Büger, G. 2017. On trend detection. Hydrological Processes 31, 4039–4042. https://doi.org/10.1002/hyp.11280.
Sen, P.K., 1968. Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association Vol. 63, No. 324: 1379-1389.
Wang, X.L. and Swail, V.R., 2001. Changes in extreme wave heights in northern hemisphere oceans and related atmospheric circulation regimes. Journal of Climate, 14: 2204-2221.
Yue, S., P. Pilon, B. Phinney and G. Cavadias, 2002. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological Processes, 16: 1807-1829.
Zhang, X., Vincent, L.A., Hogg, W.D. and Niitsoo, A., 2000. Temperature and Precipitation Trends in Canada during the 20th Century. Atmosphere-Ocean 38(3): 395-429.
Zhang, X., Zwiers, F.W., 2004. Comment on “Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test” by Sheng Yue and Chun Yuan Wang. Water Resources Research 40. https://doi.org/10.1029/2003WR002073.

Examples

## Not run: 

# Working examples:

# Compute trends statistics using a data frame and data argument with defaults
flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
trends <- compute_annual_trends(data = flow_data,
                                zyp_method = "zhang")

# Compute trends statistics using station_number with defaults
trends <- compute_annual_trends(station_number = "08NM116",
                                zyp_method = "zhang")
                      
# Compute trends statistics and plot a trend line if the significance is less than 0.05
trends <- compute_annual_trends(station_number = "08NM116",
                                zyp_method = "zhang",
                                zyp_alpha = 0.05)
                      
# Compute trends statistics and do not plot the results
trends <- compute_annual_trends(station_number = "08NM116",
                                zyp_method = "zhang",
                                include_plots = FALSE)


## End(Not run)

fasstr documentation built on Sept. 30, 2024, 9:24 a.m.