View source: R/ErrorCrit_NSE.R
ErrorCrit_NSE | R Documentation |
Function which computes an error criterion based on the NSE formula proposed by Nash & Sutcliffe (1970).
ErrorCrit_NSE(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 NSE).
[list] list containing the function outputs organised as follows:
$CritValue | [numeric] value of the criterion |
$CritName | [character] name 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
Nash, J. E. and Sutcliffe, J. V. (1970). River flow forecasting through conceptual models. Part 1 - A discussion of principles. Journal of Hydrology, 10(3), 282-290, doi: 10.1016/0022-1694(70)90255-6.
ErrorCrit_RMSE
, ErrorCrit_KGE
, ErrorCrit_KGE2
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$DatesR, format = "%Y-%m-%d")=="1999-12-31")) ## preparation of the RunOptions object RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J, InputsModel = InputsModel, IndPeriod_Run = Ind_Run) ## simulation Param <- c(X1 = 734.568, X2 = -0.840, X3 = 109.809, X4 = 1.971) OutputsModel <- RunModel(InputsModel = InputsModel, RunOptions = RunOptions, Param = Param, FUN = RunModel_GR4J) ## efficiency criterion: Nash-Sutcliffe Efficiency InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run]) OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel) ## efficiency criterion: Nash-Sutcliffe Efficiency on log-transformed flows transfo <- "log" InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run], transfo = transfo) OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel) ## efficiency criterion: Kling-Gupta Efficiency above a threshold (quant. 75 %) BoolCrit <- BasinObs$Qmm[Ind_Run] >= quantile(BasinObs$Qmm[Ind_Run], 0.75, na.rm = TRUE) InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel, RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run], BoolCrit = BoolCrit) OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.