predictL.fitmodel

Source: R/predictL.fitmodel.r

Predicts the load and provides uncertainty estimates for each water year.

# S3 method for class 'fitmodel'
predictL(
  object,
  objfix = NULL,
  x,
  flow.error = list(me = 0, ce = 0),
  samp.unit = "hour",
  pvalue = 0.05
)

Arguments

object

GAM modelling object resulting from FitModel function.

objfix

GAM modelling object resulting from FitModel function when a correlation structure has been implemented.

x

load data resulting from the CreateData function.

flow.error

a list containing the flow measurement and cross-sectional error in terms of the coefficient of variation. Default: none.

samp.unit

Sampling unit for the loads calculation, "day" or "hour"

pvalue

for confidence intervals. Default: 0.05 (95 confidence intervals)

Value

a list of class 'PredictLoad' with elements annual annual loads estimates daily daily loads estimates Standard print and plot functions apply.

Details

Computes the loads estimates for each water year with standard error estimates according to the p-value, sampling unit and flow error specified. By default, the error due to flow rate is assumed to be zero. Error can be included as a coefficient of variation according to whether the error is due to the measurement of flow (me) or the position of the gauge in the river, which is referred to as "cross-sectional" (ce) error.

Note

Only water year calculations have been implemented.

References

Kuhnert, P.M., Henderson, B.L., Lewis, S.E., Bainbridge, Z.T., Wilkinson, S.N. and Brodie, J.E. (2012) Quantifying total suspended sediment export from the Burdekin River catchment using the loads regression estimator tool, Water Resources Research, 48, W04533,doi:10.1029/2011WR011080.

See also

ReadInData, CreateData, FitModel