ErrorCrit: Error criterion using the provided function

In airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling

Error criterion using the provided function

Description

Function which computes an error criterion with the provided function.

Usage

ErrorCrit(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)

Arguments

InputsCrit	[object of class InputsCrit] see CreateInputsCrit for details
OutputsModel	[object of class OutputsModel] see RunModel_GR4J or RunModel_CemaNeigeGR4J for details
warnings	(optional) [boolean] boolean indicating if the warning messages are shown, default = TRUE
verbose	(optional) [boolean] boolean indicating if the function is run in verbose mode or not, default = TRUE

Value

If InputsCrit is of class Single:

[list] containing the ErrorCrit_* functions outputs, see ErrorCrit_RMSE or ErrorCrit_NSE for details

If InputsCrit is of class Multi:

[list] of list containing the ErrorCrit_* functions outputs, see ErrorCrit_RMSE or ErrorCrit_NSE for details

If InputsCrit is of class Compo:

$CritValue	[numeric] value of the composite criterion
$CritName	[character] name of the composite criterion
$CritBestValue	[numeric] theoretical best criterion value
$Multiplier	[numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1)
$CritCompo$MultiCritValues	[numeric] values of the sub-criteria
$CritCompo$MultiCritNames	[numeric] names of the sub-criteria
$CritCompo$MultiCritWeights	[character] weighted values of the sub-criteria
$MultiCrit	[list] of list containing the ErrorCrit_* functions outputs, see ErrorCrit_NSE or ErrorCrit_KGE for details

Author(s)

Olivier Delaigue

See Also

CreateInputsCrit, ErrorCrit_RMSE, ErrorCrit_NSE, ErrorCrit_KGE, ErrorCrit_KGE2

Examples

library(airGR)

## loading catchment data
data(L0123001)

## preparation of the 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)

## simulation
Param <- c(X1 = 257.238, X2 = 1.012, X3 = 88.235, X4 = 2.208)
OutputsModel <- RunModel_GR4J(InputsModel = InputsModel,
                              RunOptions = RunOptions, Param = Param)

## single efficiency criterion: Nash-Sutcliffe Efficiency
InputsCritSingle <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE,
                                     InputsModel = InputsModel, RunOptions = RunOptions,
                                     Obs = list(BasinObs$Qmm[Ind_Run]),
                                     VarObs = "Q", transfo = "",
                                     Weights = NULL)
str(ErrorCrit(InputsCrit = InputsCritSingle, OutputsModel = OutputsModel))

## 2 efficiency critera:  RMSE and the Nash-Sutcliffe Efficiency
InputsCritMulti <- CreateInputsCrit(FUN_CRIT = list(ErrorCrit_RMSE, ErrorCrit_NSE),
                                    InputsModel = InputsModel, RunOptions = RunOptions,
                                    Obs = list(BasinObs$Qmm[Ind_Run], BasinObs$Qmm[Ind_Run]),
                                    VarObs = list("Q", "Q"), transfo = list("", "sqrt"),
                                    Weights = NULL)
str(ErrorCrit(InputsCrit = InputsCritMulti, OutputsModel = OutputsModel))

## efficiency composite criterion: Nash-Sutcliffe Efficiency mixing
##                                 both raw and log-transformed flows
InputsCritCompo <- CreateInputsCrit(FUN_CRIT = list(ErrorCrit_NSE, ErrorCrit_NSE),
                                    InputsModel = InputsModel, RunOptions = RunOptions,
                                    Obs = list(BasinObs$Qmm[Ind_Run], BasinObs$Qmm[Ind_Run]),
                                    VarObs = list("Q", "Q"), transfo = list("", "log"),
                                    Weights = list(0.4, 0.6))
str(ErrorCrit(InputsCrit = InputsCritCompo, OutputsModel = OutputsModel))

airGR documentation built on March 18, 2022, 6:47 p.m.