RunModel_GR6J {airGR} | R Documentation

## Run with the GR6J hydrological model

### Description

Function which performs a single run for the GR6J daily lumped model over the test period.

### Usage

    RunModel_GR6J(InputsModel, RunOptions, Param)

### Arguments

`InputsModel` | [object of class InputsModel] see `CreateInputsModel` for details
`RunOptions` | [object of class RunOptions] see `CreateRunOptions` for details

`Param`

[numeric] vector of 6 parameters

GR6J X1 | production store capacity [mm]
GR6J X2 | intercatchment exchange coefficient [mm/d]
GR6J X3 | routing store capacity [mm]
GR6J X4 | unit hydrograph time constant [d]
GR6J X5 | intercatchment exchange threshold [-]
GR6J X6 | coefficient for emptying exponential store [mm]

### Details

For further details on the model, see the references section. For further details on the argument structures and initialisation options, see `CreateRunOptions`.

### Value

[list] list containing the function outputs organised as follows:

$DatesR | [POSIXlt] series of dates
$PotEvap | [numeric] series of input potential evapotranspiration [mm/d]
$Precip | [numeric] series of input total precipitation [mm/d]
$Prod | [numeric] series of production store level [mm]
$Pn | [numeric] series of net rainfall [mm/d]
$Ps | [numeric] series of the part of Pn filling the production store [mm/d]
$AE | [numeric] series of actual evapotranspiration [mm/d]
$Perc | [numeric] series of percolation (PERC) [mm/d]
$PR | [numeric] series of PR=Pn-Ps+Perc [mm/d]
$Q9 | [numeric] series of UH1 outflow (Q9) [mm/d]
$Q1 | [numeric] series of UH2 outflow (Q1) [mm/d]
$Rout | [numeric] series of routing store level [mm]
$Exch | [numeric] series of potential semi-exchange between catchments [mm/d]
$AExch1 | [numeric] series of actual exchange between catchments for branch 1 [mm/d]
$AExch2 | [numeric] series of actual exchange between catchments for branch 2 [mm/d]
$AExch | [numeric] series of actual exchange between catchments (1+2) [mm/d]
$QR | [numeric] series of routing store outflow (QR) [mm/d]
$QRExp | [numeric] series of exponential store outflow (QRExp) [mm/d]
$Exp | [numeric] series of exponential store level (negative) [mm]
$QD | [numeric] series of direct flow from UH2 after exchange (QD) [mm/d]
$Qsim | [numeric] series of Qsim [mm/d]
$StateEnd | [numeric] states at the end of the run (res. levels, UH1 levels, UH2 levels) [mm],
| see `CreateIniStates` for more details

(refer to the provided references or to the package source code for further details on these model outputs)

### Author(s)

Laurent Coron, Claude Michel, Charles Perrin, Raji Pushpalatha, Nicolas Le Moine

### References

Pushpalatha, R., C. Perrin, N. Le Moine, T. Mathevet and V. Andréassian (2011). A downward structural sensitivity analysis of hydrological models to improve low-flow simulation. Journal of Hydrology, 411(1-2), 66-76. doi:10.1016/j.jhydrol.2011.09.034.

### See Also

`RunModel_GR4J`, `RunModel_GR5J`, `RunModel_CemaNeigeGR6J`, `CreateInputsModel`, `CreateRunOptions`, `CreateIniStates`.

### Examples

    library(airGR)

    ## loading catchment data
    data(L0123001)

    ## preparation of the InputsModel object
    InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR6J, 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_GR6J,
                                   InputsModel = InputsModel, IndPeriod_Run = Ind_Run)

    ## simulation
    Param <- c(X1 = 242.257, X2 = 0.637, X3 = 53.517, X4 = 2.218, X5 = 0.424, X6 = 4.759)
    OutputsModel <- RunModel_GR6J(InputsModel = InputsModel,
                                 RunOptions = RunOptions, Param = Param)

    ## 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)

[Package airGR version 1.3.2.23 Index]