View source: R/compute_annual_trends.R
compute_annual_trends  R Documentation 
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()
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 
Data frame of daily data that contains columns of dates, flow values, and (optional) groups (e.g. station numbers).
Leave blank or set to 
dates 
Name of column in 
values 
Name of column in 
groups 
Name of column in 
station_number 
Character string vector of seven digit Water Survey of Canada station numbers (e.g. 
zyp_method 
Character string identifying the prewhitened trend method to use from 
basin_area 
Upstream drainage basin area, in square kilometres, to apply to observations. Three options: (1) Leave blank if (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 
water_year_start 
Numeric value indicating the month ( 
start_year 
Numeric value of the first year to consider for analysis. Leave blank or set well before start date (i.e.

end_year 
Numeric value of the last year to consider for analysis. Leave blank or set well after end date (i.e.

exclude_years 
Numeric vector of years to exclude from analysis. Leave blank or set to 
months 
Numeric vector of months to include in analysis. For example, 
annual_percentiles 
Numeric vector of percentiles to calculate annually. Set to 
monthly_percentiles 
Numeric vector of percentiles to calculate monthly for each year. Set to 
stats_days 
Numeric vector of the number of days to apply a rolling mean on basic stats. Default 
stats_align 
Character string identifying the direction of the rolling mean on basic stats from the specified date, either by
the first ( 
lowflow_days 
Numeric vector of the number of days to apply a rolling mean on low flow stats. Default 
lowflow_align 
Character string identifying the direction of the rolling mean on low flow stats from the specified date,
either by the first ( 
timing_percent 
Numeric vector of percents of annual total flows to determine dates. Used for 
normal_percentiles 
Numeric vector of two values, lower and upper percentiles, respectively indicating the limits of the
normal range. Default 
complete_years 
Logical values indicating whether to include only years with complete data in analysis. Default 
ignore_missing 
Logical value indicating whether dates with missing values should be included in the calculation. If

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 
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 
include_plots 
Logical value indicating if annual trending plots should be included. Default 
zyp_alpha 
Numeric value of the significance level (ex. 
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:
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: 13791389.
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: 22042221.
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: 18071829.
Zhang, X., Vincent, L.A., Hogg, W.D. and Niitsoo, A., 2000. Temperature and Precipitation Trends in Canada during the 20th Century. AtmosphereOcean 38(3): 395429.
Zhang, X., Zwiers, F.W., 2004. Comment on “Applicability of prewhitening to eliminate the influence of serial correlation on the MannKendall test” by Sheng Yue and Chun Yuan Wang. Water Resources Research 40. https://doi.org/10.1029/2003WR002073.
zyppackage
,
calc_all_annual_stats
## 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)
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