RunModel_CemaNeigeGR4H: Run with the CemaNeigeGR4H hydrological model

View source: R/RunModel_CemaNeigeGR4H.R

RunModel_CemaNeigeGR4HR Documentation

Run with the CemaNeigeGR4H hydrological model


Function which performs a single run for the CemaNeige-GR4H hourly lumped model over the test period.


RunModel_CemaNeigeGR4H(InputsModel, RunOptions, Param)



[object of class InputsModel] see CreateInputsModel for details


[object of class RunOptions] see CreateRunOptions for details


[numeric] vector of 6 (or 8 parameters if IsHyst = TRUE, see CreateRunOptions for details)

GR4H X1 production store capacity [mm]
GR4H X2 intercatchment exchange coefficient [mm/h]
GR4H X3 routing store capacity [mm]
GR4H X4 unit hydrograph time constant [h]
CemaNeige X1 weighting coefficient for snow pack thermal state [-]
CemaNeige X2 degree-hour melt coefficient [mm/°C/h]
CemaNeige X3 (optional) accumulation threshold [mm] (needed if IsHyst = TRUE)
CemaNeige X4 (optional) percentage (between 0 and 1) of annual snowfall defining the melt threshold [-] (needed if IsHyst = TRUE)


It is advised to run the GR5H model with an interception store (see Ficchi et al. (2019)) as it improves the consistency of the model fluxes and provides better performance. To do so, the Imax functions allows to estimates the maximal capacity of the interception store, which can then be given to CreateRunOptions.

The choice of the CemaNeige version is explained in CreateRunOptions.
For further details on the model, see the references section.
For further details on the argument structures and initialisation options, see CreateRunOptions.

See RunModel_GR4J to look at the diagram of the hydrological model.


[list] containing the function outputs organised as follows:

$DatesR [POSIXlt] series of dates
$PotEvap [numeric] series of input potential evapotranspiration (E) [mm/h]
$Precip [numeric] series of input total precipitation (P) [mm/h]
$Prod [numeric] series of production store level (S) [mm]
$Pn [numeric] series of net rainfall (Pn) [mm/h]
$Ps [numeric] series of the part of Pn filling the production store (Ps) [mm/h]
$AE [numeric] series of actual evapotranspiration [mm/h]
$Perc [numeric] series of percolation (Perc) [mm/h]
$PR [numeric] series of Pr=Pn-Ps+Perc (Pr) [mm/h]
$Q9 [numeric] series of UH1 outflow (Q9) [mm/h]
$Q1 [numeric] series of UH2 outflow (Q1) [mm/h]
$Rout [numeric] series of routing store level (R1) [mm]
$Exch [numeric] series of potential semi-exchange between catchments [mm/h]
$AExch1 [numeric] series of actual exchange between catchments for branch 1 [mm/h]
$AExch2 [numeric] series of actual exchange between catchments for branch 2 [mm/h]
$AExch [numeric] series of actual exchange between catchments (AExch1+AExch2) [mm/h]
$QR [numeric] series of routing store outflow (Qr) [mm/h]
$QD [numeric] series of direct flow from UH2 after exchange (Qd) [mm/h]
$Qsim [numeric] series of simulated discharge (Q) [mm/h]
$CemaNeigeLayers [list] CemaNeige outputs (1 element per layer)
$CemaNeigeLayers[[iLayer]]$Pliq [numeric] series of liquid precip. [mm/h]
$CemaNeigeLayers[[iLayer]]$Psol [numeric] series of solid precip. [mm/h]
$CemaNeigeLayers[[iLayer]]$SnowPack [numeric] series of snow pack (snow water equivalent)[mm]
$CemaNeigeLayers[[iLayer]]$ThermalState [numeric] series of snow pack thermal state [°C]
$CemaNeigeLayers[[iLayer]]$Gratio [numeric] series of Gratio [0-1]
$CemaNeigeLayers[[iLayer]]$PotMelt [numeric] series of potential snow melt [mm/h]
$CemaNeigeLayers[[iLayer]]$Melt [numeric] series of actual snow melt [mm/h]
$CemaNeigeLayers[[iLayer]]$PliqAndMelt [numeric] series of liquid precip. + actual snow melt [mm/h]
$CemaNeigeLayers[[iLayer]]$Temp [numeric] series of air temperature [°C]
$CemaNeigeLayers[[iLayer]]$Gthreshold [numeric] series of melt threshold [mm]
$CemaNeigeLayers[[iLayer]]$Glocalmax [numeric] series of local melt threshold for hysteresis [mm]
RunOptions$WarmUpQsim [numeric] series of simulated discharge (Q) on the warm-up period [mm/h]
RunOptions$Param [numeric] parameter set parameter set used by the model
$StateEnd [numeric] states at the end of the run: store & unit hydrographs levels [mm], CemaNeige states [mm & °C]. See CreateIniStates for more details

Refer to the provided references or to the package source code for further details on these model outputs.


Laurent Coron, Claude Michel, Charles Perrin, Thibault Mathevet, Audrey Valéry, Vazken Andréassian, Olivier Delaigue, Guillaume Thirel


Mathevet, T. (2005). Quels modèles pluie-débit globaux pour le pas de temps horaire ? Développement empirique et comparaison de modèles sur un large échantillon de bassins versants. PhD thesis (in French), ENGREF - Cemagref Antony, Paris, France.

Le Moine, N. (2008). Le bassin versant de surface vu par le souterrain : une voie d'amélioration des performances et du réalisme des modèles pluie-débit ? PhD thesis (in French), UPMC - Cemagref Antony, Paris, France.

Riboust, P., Thirel, G., Le Moine, N. and Ribstein, P. (2019). Revisiting a simple degree-day model for integrating satellite data: Implementation of SWE-SCA hystereses. Journal of Hydrology and Hydromechanics, 67(1), 70–81, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2478/johh-2018-0004")}.

Valéry, A., Andréassian, V. and Perrin, C. (2014). "As simple as possible but not simpler": What is useful in a temperature-based snow-accounting routine? Part 1 - Comparison of six snow accounting routines on 380 catchments. Journal of Hydrology, 517(0), 1166-1175, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jhydrol.2014.04.059")}.

Valéry, A., Andréassian, V. and Perrin, C. (2014). "As simple as possible but not simpler": What is useful in a temperature-based snow-accounting routine? Part 2 - Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments. Journal of Hydrology, 517(0), 1176-1187, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jhydrol.2014.04.058")}.

See Also

RunModel_CemaNeige, RunModel_CemaNeigeGR4J, RunModel_CemaNeigeGR5J, RunModel_CemaNeigeGR6J, RunModel_GR4H, CreateInputsModel, CreateRunOptions, CreateIniStates.


## Not run: 

## loading catchment data

## preparation of the InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_CemaNeigeGR4H, DatesR = BasinObs$DatesR,
                                 Precip = BasinObs$P, PotEvap = BasinObs$E, TempMean = BasinObs$T,
                                 ZInputs = BasinInfo$ZInputs,
                                 HypsoData = BasinInfo$HypsoData, NLayers = 5)

## run period selection
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d %H")=="2004-03-01 00"),
               which(format(BasinObs$DatesR, format = "%Y-%m-%d %H")=="2008-12-31 23"))

## --- original version of CemaNeige

## preparation of the RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_CemaNeigeGR4H, InputsModel = InputsModel,
                               IndPeriod_Run = Ind_Run)

## simulation
Param <- c(X1 = 149.905, X2 = -0.487, X3 = 391.506, X4 = 9.620,
           CNX1 = 0.520, CNX2 = 0.133)
OutputsModel <- RunModel_CemaNeigeGR4H(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)

## End(Not run)

airGR documentation built on Oct. 26, 2023, 9:07 a.m.