Imax | R Documentation |
Function which calculates the maximal capacity of the GR5H interception store. This function compares the interception evapotranspiration from the GR5H interception store for different maximal capacity values with the interception evapotranspiration classically used in the daily GR models (e.g. GR4J). Among all the TestedValues
, the value that gives the closest interception evapotranspiration flux over the whole period is kept.
Imax(InputsModel, IndPeriod_Run, TestedValues = seq(from = 0.1, to = 3, by = 0.1))
InputsModel |
[object of class InputsModel] see |
IndPeriod_Run |
[numeric] index of period to be used for the model run [-] |
TestedValues |
[numeric] vector of tested Imax values [mm] |
Optimal Imax value [mm].
Guillaume Thirel, Olivier Delaigue
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, doi: 10.1016/j.jhydrol.2019.05.084.
RunModel_GR5H
,
CreateInputsModel
, CreateRunOptions
.
library(airGR) ## loading 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:%M")=="2006-01-01 00:00"), which(format(BasinObs$DatesR, format = "%Y-%m-%d %H:%M")=="2006-12-31 23:00")) ## Imax computation Imax <- Imax(InputsModel = InputsModel, IndPeriod_Run = Ind_Run, TestedValues = seq(from = 0, to = 3, by = 0.2)) ## preparation of the RunOptions object RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR5H, Imax = Imax, InputsModel = InputsModel, IndPeriod_Run = Ind_Run) ## simulation Param <- c(X1 = 706.912, X2 = -0.163, X3 = 188.880, X4 = 2.575, X5 = 0.104) OutputsModel <- RunModel_GR5H(InputsModel = InputsModel, RunOptions = RunOptions, Param = Param) ## results preview plot(OutputsModel, Qobs = BasinObs$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)
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