Calibration of the parameters of one catchment or a network of sub-catchments

Calibration algorithm that optimizes the error criterion selected as objective function using the provided functions.

Usage

# S3 method for class 'GRiwrmInputsModel'
Calibration(
  InputsModel,
  RunOptions,
  InputsCrit,
  CalibOptions,
  useUpstreamQsim = TRUE,
  ...
)

# S3 method for class 'InputsModel'
Calibration(InputsModel, CalibOptions, ...)

Calibration(InputsModel, ...)

Arguments

InputsModel

[object of class InputsModel or GRiwrmInputsModel] see CreateInputsModel

RunOptions

[object of class RunOptions or GRiwrmRunOptions] see CreateRunOptions

InputsCrit

[object of class InputsCrit or GRiwrmInputsCrit] see CreateInputsCrit

CalibOptions

[object of class CalibOptions or GRiwrmCalibOptions] see CreateCalibOptions for details

useUpstreamQsim

boolean describing if simulated (TRUE) or observed (FALSE) flows are used for calibration. Default is TRUE

...

further arguments passed to airGR::Calibration, see details

Value

Depending on the class of InputsModel argument (respectively InputsModel or GRiwrmInputsModel object), the returned value is respectively:

• an OutputsCalib object (See airGR::Calibration for more details on this object)

• a GRiwrmOutputsCalib object which is a list of OutputsCalib objects with one item per modeled sub-catchment

Details

This function can be used either for a catchment (with an InputsModel object), for a network (with a GRiwrmInputsModel object), or for an ungauged node cluster (with a Ungauged object).

Argument classes should be consistent to the usage:

• a InputsModel argument of class InputsModel must be followed by a RunOptions argument of class RunOptions, an InputsCrit argument of class InputsCrit and a CalibOptions of class CalibOptions

• an InputsModel argument of class GRiwrmInputsModel must be followed by a RunOptions argument of class GRiwrmRunOptions, an InputsCrit argument of class GRiwrmInputsCrit and a CalibOptions of class GRiwrmCalibOptions

See also

CreateGRiwrm(), CreateInputsModel.GRiwrm(), CreateInputsCrit(), CreateCalibOptions()

Examples

# Loading catchment data
data(Severn)

#############################################################################
# EXAMPLE 1 - Basic calibration workflow                                   #
#############################################################################

# Creating catchment network
nodes <- Severn$BasinsInfo[, c("gauge_id", "downstream_id",
                               "distance_downstream", "area")]
nodes$model <- "RunModel_GR4J"
rename_columns <- list(id = "gauge_id",
                       down = "downstream_id",
                       length = "distance_downstream")
griwrm <- CreateGRiwrm(nodes, rename_columns)
griwrm
#>      id  down length    area         model donor
#> 4 54095 54001     42 3722.68 RunModel_GR4J 54095
#> 5 54002 54057     43 2207.95 RunModel_GR4J 54002
#> 6 54029 54032     32 1483.65 RunModel_GR4J 54029
#> 3 54001 54032     45 4329.90 RunModel_GR4J 54001
#> 2 54032 54057     15 6864.88 RunModel_GR4J 54032
#> 1 54057  <NA>     NA 9885.46 RunModel_GR4J 54057

# Preparation of InputsModel object
BasinsObs <- Severn$BasinsObs
DatesR <- BasinsObs[[1]]$DatesR
PrecipTot <- cbind(sapply(BasinsObs, function(x) {x$precipitation}))
PotEvapTot <- cbind(sapply(BasinsObs, function(x) {x$peti}))
Qobs <- cbind(sapply(BasinsObs, function(x) {x$discharge_spec}))
Precip <- ConvertMeteoSD(griwrm, PrecipTot)
PotEvap <- ConvertMeteoSD(griwrm, PotEvapTot)
InputsModel <- CreateInputsModel(griwrm, DatesR, Precip, PotEvap)
#> CreateInputsModel.GRiwrm: Processing sub-basin 54095...
#> CreateInputsModel.GRiwrm: Processing sub-basin 54002...
#> CreateInputsModel.GRiwrm: Processing sub-basin 54029...
#> CreateInputsModel.GRiwrm: Processing sub-basin 54001...
#> CreateInputsModel.GRiwrm: Processing sub-basin 54032...
#> CreateInputsModel.GRiwrm: Processing sub-basin 54057...

# Calibration period selection
# Set aside warm-up period and use the rest for calibration
IndPeriod_Run <- seq(
  which(InputsModel[[1]]$DatesR ==
        (InputsModel[[1]]$DatesR[1] + 365 * 24 * 60 * 60)),
  length(InputsModel[[1]]$DatesR)
)
IndPeriod_WarmUp <- seq(1, IndPeriod_Run[1] - 1)

# Preparation of RunOptions object
RunOptions <- CreateRunOptions(
  InputsModel,
  IndPeriod_WarmUp = IndPeriod_WarmUp,
  IndPeriod_Run = IndPeriod_Run
)

# Calibration criterion: preparation of the InputsCrit object
InputsCrit <- CreateInputsCrit(
  InputsModel = InputsModel,
  FUN_CRIT = ErrorCrit_KGE2,
  RunOptions = RunOptions,
  Obs = Qobs[IndPeriod_Run, ],
  transfo = "sqrt"
)

# Preparation of CalibOptions object
CalibOptions <- CreateCalibOptions(InputsModel)

if (interactive()) { # Too long for CRAN check...
  # Calibration
  OutputsCalib <- suppressWarnings(
    Calibration(InputsModel, RunOptions, InputsCrit, CalibOptions)
  )

  # Simulation
  OutputsModels <- RunModel(
    InputsModel,
    RunOptions = RunOptions,
    Param = extractParam(OutputsCalib)
  )
}