CreateInputsCrit {airGR} | R Documentation |
Creation of the InputsCrit
object required to the ErrorCrit_*
functions. This function is used to define whether the user wants to calculate a single criterion, multiple criteria in the same time, or a composite criterion, which averages several criteria.
CreateInputsCrit(FUN_CRIT, InputsModel, RunOptions, Qobs, Obs, VarObs = "Q", BoolCrit = NULL, transfo = "", Weights = NULL, Ind_zeroes = NULL, epsilon = NULL, warnings = TRUE, verbose = TRUE)
FUN_CRIT |
[function (atomic or list)] error criterion function (e.g. |
InputsModel |
[object of class InputsModel] see |
RunOptions |
[object of class RunOptions] see |
Qobs |
(deprecated) [numeric (atomic or list)] series of observed discharges [mm/time step] |
Obs |
[numeric (atomic or list)] series of observed variable ([mm/time step] for discharge or SWE, [-] for SCA) |
VarObs |
(optional) [character (atomic or list)] names of the observed variable ( |
BoolCrit |
(optional) [boolean (atomic or list)] boolean (the same length as |
transfo |
(optional) [character (atomic or list)] name of the transformation (e.g. |
Weights |
(optional) [numeric (atomic or list)] vector of weights necessary to calculate a composite criterion (the same length as |
Ind_zeroes |
(deprecated) [numeric] indices of the time steps where zeroes are observed |
epsilon |
(optional) [numeric (atomic or list)] small value to add to all observations and simulations when |
warnings |
(optional) [boolean] boolean indicating if the warning messages are shown, default = |
verbose |
(deprecated) [boolean] boolean indicating if the function is run in verbose mode or not, default = |
Users wanting to use FUN_CRIT
functions that are not included in the package must create their own InputsCrit object accordingly.
The syntax of the power transformation allows a numeric or a string of characters. For example for a squared transformation, the following can be used: transfo = 2
, transfo = "2"
or transfo = "^2"
. Negative values are allowed. Fraction values are not allowed (e.g., "-1/2"
must instead be written "-0.5"
).
In order to make sure that KGE and KGE2 remain dimensionless and not impacted by zero values, the Box-Cox transformation (transfo = "boxcox"
) uses the formulation given in Equation 10 of Santos et al. (2018). Lambda is set to 0.25 accordingly.
The epsilon value is useful when "log"
or "inv"
transformations are used (to avoid calculation of the inverse or of the logarithm of zero). The impact of this value and a recommendation about the epsilon value to use (usually one hundredth of average observation) are discussed in Pushpalatha et al. (2012) for NSE and in Santos et al. (2018) for KGE and KGE'.
We do not advise computing KGE or KGE' with log-transformation as it might be wrongly influenced by discharge values close to 0 or 1 and the criterion value is dependent on the discharge unit. See Santos et al. (2018) for more details and alternative solutions (see the references list below).
Users can set the following arguments as atomic or list: FUN_CRIT
, Obs
, VarObs
, BoolCrit
, transfo
, Weights
. If the list format is chosen, all the lists must have the same length.
Calculation of a single criterion (e.g. NSE computed on discharge) is prepared by providing to CreateInputsCrit
arguments atomics only.
Calculation of multiple criteria (e.g. NSE computed on discharge and RMSE computed on discharge) is prepared by providing to CreateInputsCrit
arguments lists except for Weights
that must be set as NULL
.
Calculation of a composite criterion (e.g. the average between NSE computed on discharge and NSE computed on log of discharge) is prepared by providing to CreateInputsCrit
arguments lists including Weights
.
ErrorCrit_RMSE
cannot be used in a composite criterion since it is not a unitless value.
[list] object of class InputsCrit containing the data required to evaluate the model outputs; it can include the following:
$FUN_CRIT | [function] error criterion function (e.g. ErrorCrit_RMSE , ErrorCrit_NSE ) |
$Obs | [numeric] series of observed variable(s) ([mm/time step] for discharge or SWE, [-] for SCA) |
$VarObs | [character] names of the observed variable(s) |
$BoolCrit | [boolean] boolean giving the time steps considered in the computation |
$transfo | [character] name of the transformation (e.g. "" , "sqrt" , "log" , "inv" , "sort" , "boxcox" or a number for power transformation) |
$epsilon | [numeric] small value to add to all observations and simulations when "log" or "inv" transformations are used [same unit as Obs ] |
$Weights | [numeric] vector (same length as VarObs ) giving the weights to use for elements of FUN_CRIT [-] |
When Weights = NULL
, CreateInputsCrit
returns an object of class Single that is a list such as the one described above.
When Weights
contains at least one NULL
value and Obs
contains a list of observations, CreateInputsCrit
returns an object of class Multi that is a list of lists such as the one described above. The ErrorCrit
function will then compute the different criteria prepared by CreateInputsCrit
.
When Weights
is a list of at least 2 numerical values, CreateInputsCrit
returns an object of class Compo that is a list of lists such as the one described above. This object will be useful to compute composite criterion with the ErrorCrit
function.
To calculate composite or multiple criteria, it is necessary to use the ErrorCrit
function. The other ErrorCrit_*
functions (e.g. ErrorCrit_RMSE
, ErrorCrit_NSE
) can only use objects of class Single (and not Multi or Compo).
Olivier Delaigue, Laurent Coron, Guillaume Thirel
Pushpalatha, R., Perrin, C., Le Moine, N. and Andréassian, V. (2012).
A review of efficiency criteria suitable for evaluating low-flow simulations.
Journal of Hydrology, 420-421: 171-182. doi:10.1016/j.jhydrol.2011.11.055.
Santos, L., Thirel, G. and Perrin, C. (2018).
Technical note: Pitfalls in using log-transformed flows within the KGE criterion.
Hydrol. Earth Syst. Sci., 22, 4583-4591. doi:10.5194/hess-22-4583-2018.
RunModel
, CreateInputsModel
, CreateRunOptions
, CreateCalibOptions
, ErrorCrit
library(airGR) ## loading catchment data data(L0123001) ## preparation of the InputsModel object InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$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$Qmm[Ind_Run]), VarObs = "Q", transfo = "", Weights = NULL) str(InputsCritSingle) invisible(ErrorCrit(InputsCrit = InputsCritSingle, OutputsModel = OutputsModel)) ## 2 efficiency criteria: RMSE and Nash-Sutcliffe Efficiency InputsCritMulti <- CreateInputsCrit(FUN_CRIT = list(ErrorCrit_RMSE, ErrorCrit_NSE), InputsModel = InputsModel, RunOptions = RunOptions, Obs = list(BasinObs$Qmm[Ind_Run], BasinObs$Qmm[Ind_Run]), VarObs = list("Q", "Q"), transfo = list("", "sqrt"), Weights = NULL) str(InputsCritMulti) invisible(ErrorCrit(InputsCrit = InputsCritMulti, OutputsModel = OutputsModel)) ## efficiency composite criterion: Nash-Sutcliffe Efficiency mixing ## both raw and log-transformed flows InputsCritCompo <- CreateInputsCrit(FUN_CRIT = list(ErrorCrit_NSE, ErrorCrit_NSE), InputsModel = InputsModel, RunOptions = RunOptions, Obs = list(BasinObs$Qmm[Ind_Run], BasinObs$Qmm[Ind_Run]), VarObs = list("Q", "Q"), transfo = list("", "log"), Weights = list(0.4, 0.6)) str(InputsCritCompo) invisible(ErrorCrit(InputsCrit = InputsCritCompo, OutputsModel = OutputsModel))