UKFE (version 2.0.0)

Uncertainty: Uncertainty quantification for gauged and ungauged pooled estimates

Description

Uncertainty for both the gauged and ungauged case are quantified specifically (bespoke) for the pooling group according to methods detailed in Hammond, A. (2021). Sampling uncertainty of UK design flood estimation. Hydrology Research. 1357-1371. 52 (6). Note that this function only quantifies sampling (aleatoric) uncertainty. It does not quantify uncertainty associated with models, model choices applied, or hydrometric data. The method assumes that AMAX samples within the pooling group are independent of each other and serially independent and identically distributed. The default ungauged QMED fse is 1.5. This is the FSE for the QMED 2025 regression model for all catchments suitable for QMED estimation. If Gauged = TRUE, the assumption is that the top site in the pooling group is the gauged subject site. In the Gauged case the pooling group is bootstrapped (parametrically) 200 times to create 200 pooling groups. Then the PoolEst function is applied to each of the 200 resampled pooling groups along with 200 resampled QMED from the gauged subject site. The FSE is calculated from the range of 200 estimates for each return period. In the ungauged case, each gauge is bootstrapped (parametrically) w x 200 times, where w is the weighting of the gauge. The growth factors for the associated 200 LMoment ratios are calculated and multiplied by a sampled QMED based on the fseQMED value. i.e SampledQMED = exp(rnorm(1, log(QMEDEstimate), log(fseQMED)). Then the FSEs are calculated across the 200 results for each return period.

Usage

Uncertainty(
  x,
  dist = "GenLog",
  Gauged = FALSE,
  QMEDEstimate = NULL,
  fseQMED = 1.5
)

Value

A dataframe with 11 rows and two columns. Return period in the first column and factorial standard error in the second.

Arguments

x

the pooled group derived from the Pool() function.

dist

a choice of distribution to use for the estimates. Choices are "GEV", "GenLog", "Gumbel", or "Kappa3". The default is "GenLog".

Gauged

a logical argument with a default of FALSE. If FALSE the uncertainty is quantified for the ungauged case. If TRUE it is quantified for the gauged case.

QMEDEstimate

the QMED estimate for the ungauged case.

fseQMED

the factorial standard error of the QMED estimate for an ungauged assessment. The default is 1.45.

Author

Anthony Hammond

Examples

# Derive a pooling group
pool_203018 <- Pool(GetCDs(203018))

# Calculate the factorial standard errors as if it it were ungauged.
Uncertainty(pool_203018, QMEDEstimate = QMED(GetCDs(203018)))