FloodnetAmax: Estimate flood quantiles using annual maxima

In floodnetProject16/floodnetRfa: FloodNet Regional Frequency Analysis

Description

Return the flood quantile, standard deviation, of an at-site frequency analysis of floods based on annual maxima.

Usage

FloodnetAmax(
  x,
  period = c(2, 5, 10, 20, 50, 100),
  distr = NULL,
  nsim = 2000,
  level = 0.95,
  out.model = FALSE,
  verbose = TRUE
)

Arguments

x	Hydrometric data. Vector of annual maxima.
period	Return period for which the flood quantiles are estimated.
distr	Distribution. One of 'gev','gno','glo' or 'pe3'
nsim	Number of bootstrap samples used for inference.
level	Confidence level.
out.model	Logical. Should the model be output. This corresponds to the output of FitAmax. Otherwise only the estimated flood quantiles are returned.
verbose	Logical. Should message and warnings be returned.

Details

Estimation is carried out by L-moments and a best distribution is selected using Akaike Information Criterion (AIC) among the Generalized Extreme Value (GEV), Generalized logistic (GLO), the Generalized Normal (GNO) and the Pearson type 3 distributions. A preference is given to the GEV when the AIC of the other distributions is not greater than at least two AIC. Inference on the estimated flood quantiles is performed by parametric bootstraps.

If verbose == TRUE, a Mann-Kendall and a Pettitt's test are used to verify the presence of trend and change points in the data. If the data fails one of the them at significance level 0.05, a warning is issued.

References

Helsel, D. R., & Hirsch, R. M. (2002). Statistical Methods in Water Resources. In Techniques of Water-Resources Investigations of the United States Geological Survey. Retrieved from http://water.usgs.gov/pubs/twri/twri4a3/

Hosking, J. R. M., & Wallis, J. R. (1997). Regional frequency analysis: an approach based on L-moments. Cambridge Univ Pr.

See Also

AmaxData, floodnetMdl.

Examples

 an <- DemoData('amax')
 fit <- FloodnetAmax(an, period = c(20,50))
 summary(fit)

floodnetProject16/floodnetRfa documentation built on Oct. 24, 2020, 9:19 a.m.