RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
  
  IsHyst <- inherits(RunOptions, "hysteresis")
  NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L)
  NParamCN <- NParam - 5L
  NStates <- 4L
  FortranOutputs <- .FortranOutputs(GR = "GR5H", isCN = TRUE)
  IsIntStore <- inherits(RunOptions, "interception")
  if(IsIntStore) {
    Imax <- RunOptions$Imax
  } else {
    Imax <- -99
  }
  
  ##Arguments_check
  if(!inherits(InputsModel,"InputsModel")){ stop("'InputsModel' must be of class 'InputsModel'") }  
  if(!inherits(InputsModel,"hourly"     )){ stop("'InputsModel' must be of class 'hourly'     ") }  
  if(!inherits(InputsModel,"GR"         )){ stop("'InputsModel' must be of class 'GR'         ") }  
  if(!inherits(InputsModel,"CemaNeige"  )){ stop("'InputsModel' must be of class 'CemaNeige'  ") }  
  if(!inherits(RunOptions,"RunOptions"  )){ stop("'RunOptions' must be of class 'RunOptions'  ") }  
  if(!inherits(RunOptions,"GR"          )){ stop("'RunOptions' must be of class 'GR'          ") }  
  if(!inherits(RunOptions,"CemaNeige"   )){ stop("'RunOptions' must be of class 'CemaNeige'   ") }  
  if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
  if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
  Param <- as.double(Param);
  
  Param_X1X3_threshold <- 1e-2
  Param_X4_threshold   <- 0.5
  if (Param[1L] < Param_X1X3_threshold) {
    warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
    Param[1L] <- Param_X1X3_threshold
  }
  if (Param[3L] < Param_X1X3_threshold) {
    warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
    Param[3L] <- Param_X1X3_threshold
  }
  if (Param[4L] < Param_X4_threshold) {
    warning(sprintf("Param[4] (X4: unit hydrograph time constant [h]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
    Param[4L] <- Param_X4_threshold
  }     
  
  ##Input_data_preparation
  if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
  IndPeriod1   <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
  LInputSeries <- as.integer(length(IndPeriod1))
  if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs)); 
  } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim);  }
  
  ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
  NParamMod      <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
  ParamMod       <- Param[1:NParamMod];
  NLayers        <- length(InputsModel$LayerPrecip);
  NStatesMod     <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
  
  ##Output_data_preparation
  IndPeriod2     <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
  ExportDatesR   <- "DatesR"   %in% RunOptions$Outputs_Sim;
  ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
  
  ##SNOW_MODULE________________________________________________________________________________##
  if(inherits(RunOptions,"CemaNeige")){
    if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN)); 
    } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim);  }
    CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
    
    
    ##Call_DLL_CemaNeige_________________________
    for(iLayer in 1:NLayers){
      if (!IsHyst) {
        StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)]
      } else {
        StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
      }
      RESULTS <- .Fortran("frun_cemaneige",PACKAGE="airGR",
                          ##inputs
                          LInputs=LInputSeries,                                                         ### length of input and output series
                          InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1],                   ### input series of total precipitation [mm/h]
                          InputsFracSolidPrecip=InputsModel$LayerFracSolidPrecip[[iLayer]][IndPeriod1], ### input series of fraction of solid precipitation [0-1]
                          InputsTemp=InputsModel$LayerTemp[[iLayer]][IndPeriod1],                       ### input series of air mean temperature [degC]
                          MeanAnSolidPrecip=RunOptions$MeanAnSolidPrecip[iLayer],                       ### value of annual mean solid precip [mm/y]
                          NParam=as.integer(NParamCN),                                                  ### number of model parameters = 2 or 4
                          Param=as.double(ParamCemaNeige),                                              ### parameter set
                          NStates=as.integer(NStates),                                                  ### number of state variables used for model initialisation = 4
                          StateStart=StateStartCemaNeige,                                               ### state variables used when the model run starts
                          IsHyst = as.integer(IsHyst),                                                  ### use of hysteresis
                          NOutputs=as.integer(length(IndOutputsCemaNeige)),                             ### number of output series
                          IndOutputs=IndOutputsCemaNeige,                                               ### indices of output series
                          ##outputs                                                               
                          Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsCemaNeige)), ### output series [mm]
                          StateEnd=rep(as.double(-999.999),as.integer(NStates))                                   ### state variables at the end of the model run
      )
      RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
      RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
      
      ##Data_storage
      CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
      names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
      IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
      if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
      if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
      if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
      rm(RESULTS); 
    } ###ENDFOR_iLayer
    names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
  } ###ENDIF_RunSnowModule
  if(!inherits(RunOptions,"CemaNeige")){
    CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
    CatchMeltAndPliq  <- InputsModel$Precip[IndPeriod1]; }
  
  
  ##MODEL______________________________________________________________________________________##
  
  ##Use_of_IniResLevels
  if(!is.null(RunOptions$IniResLevels)){
    RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1];  ### production store level (mm)
    RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3];  ### routing store level (mm)
    if(IsIntStore) {
      RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax;  ### interception store level (mm)
    }
  }
  
  ##Call_fortan
  RESULTS <- .Fortran("frun_gr5h",PACKAGE="airGR",
                      ##inputs
                      LInputs=LInputSeries,                             ### length of input and output series
                      InputsPrecip=InputsModel$Precip[IndPeriod1],      ### input series of total precipitation [mm/h]
                      InputsPE=InputsModel$PotEvap[IndPeriod1],         ### input series potential evapotranspiration [mm/h]
                      NParam=as.integer(length(Param)),                 ### number of model parameter
                      Param=Param,                                      ### parameter set
                      NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
                      StateStart=RunOptions$IniStates,                  ### state variables used when the model run starts
                      Imax=Imax,                                        ### maximal capacity of interception store
                      NOutputs=as.integer(length(IndOutputs)),          ### number of output series
                      IndOutputs=IndOutputs,                            ### indices of output series
                      ##outputs
                      Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)),  ### output series [mm or mm/h]
                      StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates))                  ### state variables at the end of the model run
  )
  RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
  RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
  if (ExportStateEnd) {
    RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
    RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR5H, InputsModel = InputsModel, IsHyst = IsHyst,
                                        ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
                                        IntStore = RESULTS$StateEnd[4L],
                                        UH1 = NULL, UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
                                        GCemaNeigeLayers       = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
                                        eTGCemaNeigeLayers     = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
                                        GthrCemaNeigeLayers    = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]], 
                                        GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
                                        verbose = FALSE)
  }
  
  if(inherits(RunOptions,"CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
  
  ##Output_data_preparation
  ##OutputsModel_only
  ##OutputsModel_only
  if(!ExportDatesR & !ExportStateEnd){
    OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
                       list(CemaNeigeLayers) );
    names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
  ##DatesR_and_OutputsModel_only
  if( ExportDatesR & !ExportStateEnd){
    OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
                       lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
                       list(CemaNeigeLayers) );
    names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers);      }
  ##OutputsModel_and_SateEnd_only
  if(!ExportDatesR & ExportStateEnd){
    OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
                       list(CemaNeigeLayers),
                       list(RESULTS$StateEnd) );
    names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd");      }
  ##DatesR_and_OutputsModel_and_SateEnd
  if( ExportDatesR & ExportStateEnd){
    OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
                       lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
                       list(CemaNeigeLayers),
                       list(RESULTS$StateEnd) );
    names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd");      }
  
  ##End
  rm(RESULTS); 
  class(OutputsModel) <- c("OutputsModel","hourly","GR","CemaNeige");
  if(IsHyst) {
    class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
  }
  if(IsIntStore) {
    class(OutputsModel) <- c(class(OutputsModel), "interception")
  }
  return(OutputsModel);
  
}