R/compute_annual_trends.R
compute_annual_trends.Rd
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:
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
)
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.
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.
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
.
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
). If not all months, seasonal total yield and volumetric flows will not be included.
Numeric vector of percentiles to calculate annually. Set to NA
if none required. Used for
calc_annual_stats()
function. Default c(10,90)
.
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)
.
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.
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.
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.
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.
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)
.
Numeric vector of two values, lower and upper percentiles, respectively indicating the limits of the
normal range. Default c(25,75)
.
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 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.
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.
Logical value indicating if annual trending plots should be included. Default TRUE
.
Numeric value of the significance level (ex. 0.05
) of when to plot a trend line. Leave blank for no line.
A list of tibbles and optional plots from the trending analysis including:
a tibble of the annual statistics used for trending
a tibble of the results of the zyp trending analysis
each ggplot2 object for each annual trended statistic
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.
if (FALSE) {
# 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)
}