View source: R/compute_annual_frequencies.R
compute_annual_frequencies | R Documentation |
Performs a flow volume frequency analysis on annual statistics from a daily streamflow data set. Defaults to a low
flow frequency analysis using annual minimums. Set use_max = TRUE
for annual high flow frequency analyses. Calculates
statistics from all values, unless specified. Function will calculate using all values in 'Values' column (no grouped analysis).
Analysis methodology replicates that from HEC-SSP. Returns a list of
tibbles and plots.
compute_annual_frequencies(
data,
dates = Date,
values = Value,
station_number,
roll_days = c(1, 3, 7, 30),
roll_align = "right",
use_max = FALSE,
use_log = FALSE,
prob_plot_position = c("weibull", "median", "hazen"),
prob_scale_points = c(0.9999, 0.999, 0.99, 0.9, 0.5, 0.2, 0.1, 0.02, 0.01, 0.001,
1e-04),
fit_distr = c("PIII", "weibull"),
fit_distr_method = ifelse(fit_distr == "PIII", "MOM", "MLE"),
fit_quantiles = c(0.975, 0.99, 0.98, 0.95, 0.9, 0.8, 0.5, 0.2, 0.1, 0.05, 0.01),
plot_curve = TRUE,
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
complete_years = FALSE,
ignore_missing = FALSE,
allowed_missing = ifelse(ignore_missing, 100, 0)
)
data |
A data frame of daily data that contains columns of dates and flow values. Groupings and the |
dates |
Name of column in |
values |
Name of column in |
station_number |
Character string vector of seven digit Water Survey of Canada station numbers (e.g. |
roll_days |
Numeric value of the number of days to apply a rolling mean. Default |
roll_align |
Character string identifying the direction of the rolling mean from the specified date, either by the first
( |
use_max |
Logical value to indicate using maximums rather than the minimums for analysis. Default |
use_log |
Logical value to indicate log-scale transforming of flow data before analysis. Default |
prob_plot_position |
Character string indicating the plotting positions used in the frequency plots, one of |
prob_scale_points |
Numeric vector of probabilities to be plotted along the X axis in the frequency plot. Inverse of
return period. Default |
fit_distr |
Character string identifying the distribution to fit annual data, one of |
fit_distr_method |
Character string identifying the method used to fit the distribution, one of |
fit_quantiles |
Numeric vector of quantiles to be estimated from the fitted distribution.
Default |
plot_curve |
Logical value to indicate plotting the computed curve on the probability plot. Default |
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, |
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 |
Numeric value between 0 and 100 indicating the percentage of missing dates allowed to be
included to calculate a statistic (0 to 100 percent). If |
A list with the following elements:
Freq_Analysis_Data |
Data frame with computed annual summary statistics used in analysis. |
Freq_Plot_Data |
Data frame with co-ordinates used in frequency plot. |
Freq_Plot |
ggplot2 object with frequency plot. |
Freq_Fitting |
List of fitted objects from fitdistrplus. |
Freq_Fitted_Quantiles |
Data frame with fitted quantiles. |
compute_frequency_analysis
## Not run:
# Working examples (see arguments for further analysis options):
# Compute an annual frequency analysis using default arguments
results <- compute_annual_frequencies(station_number = "08NM116",
start_year = 1980,
end_year = 2010)
# Compute an annual frequency analysis using default arguments (as listed)
results <- compute_annual_frequencies(station_number = "08NM116",
roll_days = c(1,3,7,30),
start_year = 1980,
end_year = 2010,
prob_plot_position = "weibull",
prob_scale_points = c(.9999, .999, .99, .9, .5,
.2, .1, .02, .01, .001, .0001),
fit_distr = "PIII",
fit_distr_method = "MOM")
# Compute a 7-day annual frequency analysis with "median" plotting positions
# and fitting the data to a weibull distribution (not default PIII)
results <- compute_annual_frequencies(station_number = "08NM116",
roll_days = 7,
start_year = 1980,
end_year = 2010,
prob_plot_position = "median",
fit_distr = "weibull")
## End(Not run)
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