RunModel | R Documentation |
Function which performs a single model run with the provided function over the selected period.
RunModel(InputsModel, RunOptions, Param, FUN_MOD, ...)
InputsModel |
[object of class InputsModel] see |
RunOptions |
[object of class RunOptions] see |
Param |
[numeric] vector of model parameters (See details for SD lag model) |
FUN_MOD |
[function] hydrological model function (e.g. |
... |
(optional) arguments to pass to |
If InputsModel
parameter has been created for using a semi-distributed (SD) lag model (See CreateInputsModel
), the first item of Param
parameter should contain a constant lag parameter expressed as a velocity in m/s, parameters for the hydrological model are then shift one position to the right.
[list] see RunModel_GR4J
or RunModel_CemaNeigeGR4J
for details.
If InputsModel
parameter has been created for using a semi-distributed (SD) lag model (See CreateInputsModel
), the list value contains an extra item named QsimDown
which is a numeric series of simulated discharge [mm/time step] related to the run-off contribution of the downstream sub-catchment.
Laurent Coron, Olivier Delaigue
RunModel_GR4J
, RunModel_CemaNeigeGR4J
, CreateInputsModel
,
CreateRunOptions
, CreateIniStates
.
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$DatesR, format = "%Y-%m-%d")=="1999-12-31"))
## preparation of the RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J,
InputsModel = InputsModel, IndPeriod_Run = Ind_Run)
## simulation
Param <- c(X1 = 734.568, X2 = -0.840, X3 = 109.809, X4 = 1.971)
OutputsModel <- RunModel(InputsModel = InputsModel,
RunOptions = RunOptions, Param = Param,
FUN_MOD = RunModel_GR4J)
## results preview
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
## 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)
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