Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/CreateInputsCrit.R
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.
1 2 3 4 5 
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 applied to the variables (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.
## — Period of calculation
Criteria can be calculated over discontinuous periods (i.e. only over winter periods, or when observed discharge is below a certain threshold). To do so, please indicate in Bool_Crit
which indices must be used for calcullation. Discontinuous periods are allowed in the Bool_Crit
argument.
## — Transformations
Transformations are simple functions applied to the observed and simulated variables used in order to change their distribution. Transformations are often used in hydrology for modifying the weight put on errors made for high flows or low flows. The following transformations are available:
""
: no transformation is used (default case)
"sqrt"
: squared root transformation
"log"
: logarithmic transformation (see below regarding the specific case of KGE or KGE2)
"inv"
: inverse transformation
"sort"
: sort transformation (the simulated and observed variables are sorted from lowest to highest)
"boxcox"
: BoxCox transformation (see below for details)
numeric: power transformation (see below for details)
We do not advise computing KGE or KGE' with logtransformation 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).
In order to make sure that KGE and KGE2 remain dimensionless and are not impacted by zero values, the BoxCox transformation (transfo = "boxcox"
) uses the formulation given in Equation 10 of Santos et al. (2018). Lambda is set to 0.25 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"
).
## — The epsilon value
The epsilon value is useful when "log"
or "inv"
transformations are used (to avoid calculation of the inverse or of the logarithm of zero). If an epsilon value is provided, then it is added to the observed and simulated variable time series at each time step and before the application of a transformation. The epsilon value has no effect when the "boxcox"
transformation is used. 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'.
## — Single, multiple or composite criteria calculation
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 ] 
$Weights  [numeric] vector (same length as VarObs ) giving the weights to use for elements of FUN_CRIT [] 
When Weights = NULL
, CreateInputsCrit
returns an object of class Single that is a list such as the one described above.
When Weights
contains at least one NULL
value and Obs
contains a list of observations, CreateInputsCrit
returns an object of class Multi that is a list of lists such as the one described above. The ErrorCrit
function will then compute the different criteria prepared by CreateInputsCrit
.
When Weights
is a list of at least 2 numerical values, CreateInputsCrit
returns an object of class Compo that is a list of lists such as the one described above. This object will be useful to compute composite criterion with the ErrorCrit
function.
To calculate composite or multiple criteria, it is necessary to use the ErrorCrit
function. The other ErrorCrit_*
functions (e.g. ErrorCrit_RMSE
, ErrorCrit_NSE
) can only use objects of class Single (and not Multi or Compo).
Olivier Delaigue, Laurent Coron, Guillaume Thirel
Pushpalatha, R., Perrin, C., Le Moine, N. and Andréassian, V. (2012).
A review of efficiency criteria suitable for evaluating lowflow simulations.
Journal of Hydrology, 420421, 171182, doi: 10.1016/j.jhydrol.2011.11.055.
Santos, L., Thirel, G. and Perrin, C. (2018).
Technical note: Pitfalls in using logtransformed flows within the KGE criterion.
Hydrol. Earth Syst. Sci., 22, 45834591, doi: 10.5194/hess2245832018.
RunModel
, CreateInputsModel
, CreateRunOptions
, CreateCalibOptions
, ErrorCrit
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48  library(airGR)
## loading catchment data
data(L0123001)
## preparation of the InputsModel object
InputsModel < CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR,
Precip = BasinObs$P, PotEvap = BasinObs$E)
## calibration period selection
Ind_Run < seq(which(format(BasinObs$DatesR, format = "%Y%m%d")=="19900101"),
which(format(BasinObs$DatesR, format = "%Y%m%d")=="19991231"))
## 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: NashSutcliffe Efficiency
InputsCritSingle < CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE,
InputsModel = InputsModel, RunOptions = RunOptions,
Obs = list(BasinObs$Qmm[Ind_Run]),
VarObs = "Q", transfo = "",
Weights = NULL)
str(InputsCritSingle)
invisible(ErrorCrit(InputsCrit = InputsCritSingle, OutputsModel = OutputsModel))
## 2 efficiency criteria: RMSE and NashSutcliffe Efficiency
InputsCritMulti < CreateInputsCrit(FUN_CRIT = list(ErrorCrit_RMSE, ErrorCrit_NSE),
InputsModel = InputsModel, RunOptions = RunOptions,
Obs = list(BasinObs$Qmm[Ind_Run], BasinObs$Qmm[Ind_Run]),
VarObs = list("Q", "Q"), transfo = list("", "sqrt"),
Weights = NULL)
str(InputsCritMulti)
invisible(ErrorCrit(InputsCrit = InputsCritMulti, OutputsModel = OutputsModel))
## efficiency composite criterion: NashSutcliffe Efficiency mixing
## both raw and logtransformed flows
InputsCritCompo < CreateInputsCrit(FUN_CRIT = list(ErrorCrit_NSE, ErrorCrit_NSE),
InputsModel = InputsModel, RunOptions = RunOptions,
Obs = list(BasinObs$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))

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