airGR (version 1.7.6)

RunModel_GR6J: 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)

Value

[list] containing the function outputs organised as follows:

$DatesR	[POSIXlt] series of dates
$PotEvap	[numeric] series of input potential evapotranspiration (E) [mm/d]
$Precip	[numeric] series of input total precipitation (P) [mm/d]
$Prod	[numeric] series of production store level (S) [mm]
$Pn	[numeric] series of net rainfall (Pn) [mm/d]
$Ps	[numeric] series of the part of Pn filling the production store (Ps) [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 (Pr) [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 (R1) [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 (AExch1+AExch2) [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) (R2) [mm]
$QD	[numeric] series of direct flow from UH2 after exchange (Qd) [mm/d]
$Qsim	[numeric] series of simulated discharge (Q) [mm/d]
RunOptions$WarmUpQsim	[numeric] series of simulated discharge (Q) on the warm-up period [mm/d]
RunOptions$Param	[numeric] parameter set parameter set used by the model
$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.

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	exponential store depletion coefficient [mm]

Author

Laurent Coron, Claude Michel, Charles Perrin, Raji Pushpalatha, Nicolas Le Moine, Olivier Delaigue, Guillaume Thirel

Details

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

References

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