swh:1:snp:b14ede66c1ce5d036e4068297411cc78f06c6771
CreateCalibOptions.Rd
\encoding{UTF-8}
\name{CreateCalibOptions}
\alias{CreateCalibOptions}
\title{Creation of the CalibOptions object required but the Calibration functions}
\description{
Creation of the \emph{CalibOptions} object required by the \code{Calibration*} functions.
}
\usage{
CreateCalibOptions(FUN_MOD, FUN_CALIB = Calibration_Michel,
FUN_TRANSFO = NULL, IsHyst = FALSE, IsSD = FALSE, FixedParam = NULL,
SearchRanges = NULL, StartParamList = NULL,
StartParamDistrib = NULL)
}
\arguments{
\item{FUN_MOD}{[function] hydrological model function (e.g. \code{\link{RunModel_GR4J}}, \code{\link{RunModel_CemaNeigeGR4J}})}
\item{FUN_CALIB}{(optional) [function] calibration algorithm function (e.g. Calibration_Michel), default = \code{Calibration_Michel}}
\item{FUN_TRANSFO}{(optional) [function] model parameters transformation function, if the \code{FUN_MOD} used is native in the package, \code{FUN_TRANSFO} is automatically defined}
\item{IsHyst}{[boolean] boolean indicating if the hysteresis version of CemaNeige is used. See details}
\item{IsSD}{[boolean] boolean indicating if the semi-distributed lag model is used. See details}
\item{FixedParam}{(optional) [numeric] vector giving the values set for the non-optimised parameter values (NParam columns, 1 line)
\cr Example:
\tabular{llllll}{
\tab NA \tab NA \tab 3.34 \tab ... \tab NA \cr
}}
\item{SearchRanges}{(optional) [numeric] matrix giving the ranges of real parameters (NParam columns, 2 lines)
\cr Example:
\tabular{llllll}{
\tab [X1] \tab [X2] \tab [X3] \tab [...] \tab [Xi] \cr
[1,] \tab 0 \tab -1 \tab 0 \tab ... \tab 0.0 \cr
[2,] \tab 3000 \tab +1 \tab 100 \tab ... \tab 3.0 \cr
}}
\item{StartParamList}{(optional) [numeric] matrix of parameter sets used for grid-screening calibration procedure (values in columns, sets in line)
\cr Example:
\tabular{llllll}{
\tab [X1] \tab [X2] \tab [X3] \tab [...] \tab [Xi] \cr
[set1] \tab 800 \tab -0.7 \tab 25 \tab ... \tab 1.0 \cr
[set2] \tab 1000 \tab -0.5 \tab 22 \tab ... \tab 1.1 \cr
[...] \tab ... \tab ... \tab ... \tab ... \tab ... \cr
[set n] \tab 200 \tab -0.3 \tab 17 \tab ... \tab 1.0 \cr
}}
\item{StartParamDistrib}{(optional) [numeric] matrix of parameter values used for grid-screening calibration procedure (values in columns, percentiles in line)
\cr Example:
\tabular{llllll}{
\tab [X1] \tab [X2] \tab [X3] \tab [...] \tab [Xi] \cr
[value1] \tab 800 \tab -0.7 \tab 25 \tab ... \tab 1.0 \cr
[value2] \tab 1000 \tab NA \tab 50 \tab ... \tab 1.2 \cr
[value3] \tab 1200 \tab NA \tab NA \tab ... \tab 1.6 \cr
}}
}
\value{
[list] object of class \emph{CalibOptions} containing the data required to evaluate the model outputs; it can include the following:
\tabular{ll}{
\emph{$FixedParam } \tab [numeric] vector giving the values to allocate to non-optimised parameter values \cr
\emph{$SearchRanges } \tab [numeric] matrix giving the ranges of raw parameters \cr
\emph{$StartParamList } \tab [numeric] matrix of parameter sets used for grid-screening calibration procedure \cr
\emph{$StartParamDistrib} \tab [numeric] matrix of parameter values used for grid-screening calibration procedure \cr
}
}
\details{
Users wanting to use \code{FUN_MOD}, \code{FUN_CALIB} or \code{FUN_TRANSFO} functions that are not included in
the package must create their own \code{CalibOptions} object accordingly. \cr
## --- CemaNeige version
If \code{IsHyst = FALSE}, the original CemaNeige version from Valéry et al. (2014) is used. \cr
If \code{IsHyst = TRUE}, the CemaNeige version from Riboust et al. (2019) is used. Compared to the original version, this version of CemaNeige needs two more parameters and it includes a representation of the hysteretic relationship between the Snow Cover Area (SCA) and the Snow Water Equivalent (SWE) in the catchment. The hysteresis included in airGR is the Modified Linear hysteresis (LH*); it is represented on panel b) of Fig. 3 in Riboust et al. (2019). Riboust et al. (2019) advise to use the LH* version of CemaNeige with parameters calibrated using an objective function combining 75 \% of KGE calculated on discharge simulated from a rainfall-runoff model compared to observed discharge and 5 \% of KGE calculated on SCA on 5 CemaNeige elevation bands compared to satellite (e.g. MODIS) SCA (see Eq. (18), Table 3 and Fig. 6). Riboust et al. (2019)'s tests were realized with GR4J as the chosen rainfall-runoff model. \cr
If \code{InputsModel} parameter has been created for using a semi-distributed (SD) model (See \code{\link{CreateInputsModel}}), the parameter \code{isSD} should be set to \code{TRUE}.
}
\examples{
library(airGR)
## loading catchment data
data(L0123001)
## preparation of InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR,
Precip = BasinObs$P, PotEvap = BasinObs$E)
## calibration period selection
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "\%Y-\%m-\%d")=="1990-01-01"),
which(format(BasinObs$DatesR, format = "\%Y-\%m-\%d")=="1999-12-31"))
## preparation of RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J,
InputsModel = InputsModel, IndPeriod_Run = Ind_Run)
## calibration criterion: preparation of the InputsCrit object
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run])
## preparation of CalibOptions object
CalibOptions <- CreateCalibOptions(FUN_MOD = RunModel_GR4J, FUN_CALIB = Calibration_Michel)
## calibration
OutputsCalib <- Calibration(InputsModel = InputsModel, RunOptions = RunOptions,
InputsCrit = InputsCrit, CalibOptions = CalibOptions,
FUN_MOD = RunModel_GR4J,
FUN_CALIB = Calibration_Michel)
## simulation
Param <- OutputsCalib$ParamFinalR
OutputsModel <- RunModel(InputsModel = InputsModel, RunOptions = RunOptions,
Param = Param, FUN = RunModel_GR4J)
## results preview
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
## efficiency criterion: Nash-Sutcliffe Efficiency
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
## efficiency criterion: Kling-Gupta Efficiency
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_KGE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_KGE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
}
\author{
Laurent Coron, Olivier Delaigue, Guillaume Thirel, David Dorchies
}
\seealso{
\code{\link{Calibration}}, \code{\link{RunModel}}
}