View source: R/ErrorCrit_KGE2.R
ErrorCrit_KGE2 | R Documentation |
Function which computes an error criterion based on the KGE' formula proposed by Kling et al. (2012).
ErrorCrit_KGE2(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
InputsCrit |
[object of class InputsCrit] see |
OutputsModel |
[object of class OutputsModel] see |
warnings |
(optional) [boolean] boolean indicating if the warning messages are shown, default = |
verbose |
(optional) [boolean] boolean indicating if the function is run in verbose mode or not, default = |
In addition to the criterion value, the function outputs include a multiplier (-1 or +1) which allows
the use of the function for model calibration: the product CritValue * Multiplier is the criterion to be minimised (Multiplier = -1 for KGE2).
The KGE' formula is
KGE' = 1 - sqrt((r - 1)² + (γ - 1)² + (β - 1)²)
with the following sub-criteria:
r = is the linear correlation coefficient between Q[sim] and Q[obs]
γ = CV[sim] / CV[obs]
β = μ[sim] / μ[obs]
[list] list containing the function outputs organised as follows:
$CritValue | [numeric] value of the criterion |
$CritName | [character] name of the criterion |
$SubCritValues | [numeric] values of the sub-criteria |
$SubCritNames | [character] names of the components of the criterion |
$CritBestValue | [numeric] theoretical best criterion value |
$Multiplier | [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) |
$Ind_notcomputed | [numeric] indices of the time steps where InputsCrit$BoolCrit = FALSE or no data is available |
Laurent Coron, Olivier Delaigue
Gupta, H. V., Kling, H., Yilmaz, K. K. and Martinez, G. F. (2009).
Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling.
Journal of Hydrology, 377(1-2), 80-91, doi: 10.1016/j.jhydrol.2009.08.003.
Kling, H., Fuchs, M. and Paulin, M. (2012).
Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios.
Journal of Hydrology, 424-425, 264-277, doi: 10.1016/j.jhydrol.2012.01.011.
ErrorCrit
, ErrorCrit_RMSE
, ErrorCrit_NSE
, ErrorCrit_KGE
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$E) ## run period selection Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d")=="1990-01-01"), which(format(BasinObs$DatesR, format = "%Y-%m-%d")=="1999-12-31")) ## preparation of the RunOptions object RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J, InputsModel = InputsModel, IndPeriod_Run = Ind_Run) ## simulation Param <- c(X1 = 734.568, X2 = -0.840, X3 = 109.809, X4 = 1.971) OutputsModel <- RunModel(InputsModel = InputsModel, RunOptions = RunOptions, Param = Param, FUN = RunModel_GR4J) ## efficiency criterion: Kling-Gupta Efficiency InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_KGE2, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run]) OutputsCrit <- ErrorCrit_KGE2(InputsCrit = InputsCrit, OutputsModel = OutputsModel) ## efficiency criterion: Kling-Gupta Efficiency on square-root-transformed flows transfo <- "sqrt" InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_KGE2, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run], transfo = transfo) OutputsCrit <- ErrorCrit_KGE2(InputsCrit = InputsCrit, OutputsModel = OutputsModel) ## efficiency criterion: Kling-Gupta Efficiency above a threshold (quant. 75 %) BoolCrit <- BasinObs$Qmm[Ind_Run] >= quantile(BasinObs$Qmm[Ind_Run], 0.75, na.rm = TRUE) InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_KGE2, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run], BoolCrit = BoolCrit) OutputsCrit <- ErrorCrit_KGE2(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
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