RunModel_GR5H: Run with the GR5H hydrological model

In airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling

Run with the GR5H hydrological model

Description

Function which performs a single run for the GR5H hourly lumped model.

Usage

RunModel_GR5H(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 5 parameters GR5H X1 production store capacity [mm] GR5H X2 intercatchment exchange coefficient [mm/h] GR5H X3 routing store capacity [mm] GR5H X4 unit hydrograph time constant [h] GR5H X5 intercatchment exchange threshold [-]

Details

It is advised to run the GR5H model with an interception store (see Ficchi (2017) and Ficchi et al. (2019)) as it improves the consistency of the model fluxes and provides better performance. To do so, the Imax function allows to estimate the maximal capacity of the interception store, which can then be given to 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_GR5J to look at the diagram of the hydrological model when no interception store is used.

Value

[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]
$Interc	[numeric] series of interception store level (I) [mm]
$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 (Ei+Es) [mm/h]
$EI	[numeric] series of evapotranspiration from rainfall neutralisation or interception store (Ei) [mm/h]
$ES	[numeric] series of evapotranspiration from production store (Es) [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 UH outflow going into branch 9 (Q9) [mm/h]
$Q1	[numeric] series of UH outflow going into branch 1 (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 UH after exchange (Qd) [mm/h]
$Qsim	[numeric] series of simulated discharge (Q) [mm/h]
RunOptions$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 (res. levels, UH 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, Guillaume Thirel, Olivier Delaigue

References

Ficchi, A. (2017). An adaptive hydrological model for multiple time-steps: Diagnostics and improvements based on fluxes consistency. PhD thesis, UPMC - Irstea Antony, Paris, France.

Ficchi, A., Perrin, C. and Andréassian, V. (2019). Hydrological modelling at multiple sub-daily time steps: model improvement via flux-matching. Journal of Hydrology, 575, 1308-1327, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jhydrol.2019.05.084")}.

See Also

RunModel_GR4H, RunModel_CemaNeigeGR5H, Imax, CreateInputsModel, CreateRunOptions, CreateIniStates.

Examples

library(airGR)

## load of catchment data
data(L0123003)

## preparation of the InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR5H, DatesR = BasinObs$DatesR,
                                 Precip = BasinObs$P, PotEvap = BasinObs$E)

## run period selection
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d %H")=="2006-01-01 00"),
               which(format(BasinObs$DatesR, format = "%Y-%m-%d %H")=="2006-12-31 23"))

## Imax computation
Imax <- Imax(InputsModel = InputsModel, IndPeriod_Run = Ind_Run,
             TestedValues = seq(from = 0, to = 3, by = 0.2))

## preparation of the RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR5H, Imax = Imax,
                               InputsModel = InputsModel, IndPeriod_Run = Ind_Run)

## simulation
Param <- c(X1 = 706.912, X2 = -0.163, X3 = 188.880, X4 = 2.575, X5 = 0.104)
OutputsModel <- RunModel_GR5H(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)

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