Provides pooled results from a pooling group.
PoolEst(
x,
dist = "GenLog",
CDs,
QMEDEstimate,
UrbAdj = TRUE,
URBEXT = NULL,
Gauged = FALSE,
fseQMED = 1.5,
Uncertainty = TRUE
)A list of length 3. Element one is a data frame with columns; return period (a range from 2 - 1000), peak flow estimates (Q), growth factor estimates (GF), and factorial standard error (if Uncertainty = TRUE). The second element is the estimated Lcv and Lskew. The third provides distribution parameters for the frequency curve.
pooling group derived from the Pool function
a choice of distribution for the estimates. The choices are "GenLog", "GEV", "Kappa3", or "Gumbel"; the generalised logistic, generalised extreme value, Kappa3, and Gumbel distribution, respectively. The default is "GenLog"
catchment descriptors for the subject site. They can be derived from either GetCDs or CDsXML
estimate of the median annual maximum flow
Logical with a default of TRUE. If TRUE, the final LCV estimate is urban adjusted.
the catchment URBEXT (at the time of writing the current URBEXT is URBEXT2015), to be supplied if UrbAdj is TRUE and if the CDs argument is NULL.
Logical argument with a default of FALSE. This only impacts the uncertainty calculations. If it is set to TRUE, the top site of the group is considered the subject gauged site.
The factorial standard error for the QMED estimate. If Gauged = TRUE, the fse is estimated from the observed, otherwise the default is 1.5.
Logical with a default of TRUE. If TRUE, an extra column of factorial standard errors is returned in the results dataframe.
Anthony Hammond
PoolEst is a function to provide results from a pooling group derived using the Pool function. QMED (median annual maximum flow) needs to be supplied and can be derived from the QMED function for ungauged estimates or the annual maximum sample for gauged estimates. The method applied is based on FEH2025. The methods for estimating the L-moments and growth factors are outlined in the Flood Estimation Handbook (1999), volume 3. The estimation procedure assumes that the pooled AMAX samples are from the same underlying distribution (aside from the QMED scaling factor), that the distribution is correctly specified, that the individual samples are all independent and identically distributed, and that the samples are independent of each other. The urban adjustment (which is applied as default) assumes that the growth curve associated with an annual maximum flow sample is impacted by urbanisation and that this impact can be modelled as a function of the catchment URBEXT. A quantification of uncertainty is provided if Uncertainty is set to TRUE (the default). For more information see the Uncertainty function.
# Get some catchment descriptors and form a pooling group.
cds_27083 <- GetCDs(27083)
pool_27083 <- Pool(cds_27083)
#Get results assuming a GEV distribution
PoolEst(pool_27083, CDs = cds_27083, dist = "GEV", QMEDEstimate = 12, Uncertainty = FALSE)
Run the code above in your browser using DataLab