HyMETT (version 1.1.3)

POR_distribution_metrics: Calculates various metrics that describe the distribution of a time series of streamflow

Description

Calculates various metrics that describe the distribution of a time series of streamflow, which can be of any time step.

Usage

POR_distribution_metrics(value, quantile_type = 8, na.rm = TRUE)

Value

A data.frame with FDC quantiles, and distribution metrics. See Details. This function calculates various metrics that describe the distribution of a time series of streamflow, which can be of any time step.

Arguments

value

'numeric' vector of values (assumed to be streamflow) at any time step.

quantile_type

'numeric' value. The distribution type used in the stats::quantile function. Default is 8 (median-unbiased regardless of distribution). Other types common in hydrology are 6 (Weibull) or 9 (unbiased for normal distributions).

na.rm

'boolean' TRUE or FALSE. Should NA values be removed before computing. If NA values are present and na.rm = FALSE, then function will return NAs. Default is TRUE.

Details

Metrics computed include:

p_n

Flow-duration curve (FDC) percentile where n = 1, 5, 10, 25, 50, 75, 90, 95, and 99

POR_mean

Period of record mean

POR_sd

Period of record standard deviation

POR_cv

Period of record coefficient of variation

POR_min

Period of record minimum

POR_max

Period of record maximum

LCV

L-moment coefficient of variation

Lskew

L-moment skewness

Lkurtosis

L-moment kurtosis

References

Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p. [Also available at https://doi.org/10.3133/sir20145231.]

Asquith, W.H., Kiang, J.E., and Cohn, T.A., 2017, Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities: U.S. Geological Survey Scientific Investigation Report 2017–5038, 93 p. [Also available at https://doi.org/10.3133/sir20175038.]

Asquith, W.H., 2021, lmomco---L-moments, censored L-moments, trimmed L-moments,
L-comoments, and many distributions. R package version 2.3.7, Texas Tech University, Lubbock, Texas.

See Also

lmoms, quantile

Examples

POR_distribution_metrics(value = example_obs$streamflow_cfs)