# NOT RUN {
library(airGR)
## loading catchment data
data(L0123001)
## conversion of example data from daily to yearly time step
TabSeries <- data.frame(BasinObs$DatesR, BasinObs$P, BasinObs$E, BasinObs$T, BasinObs$Qmm)
TimeFormat <- "daily"
NewTimeFormat <- "yearly"
ConvertFun <- c("sum", "sum", "mean", "sum")
YearFirstMonth <- 09;
NewTabSeries <- SeriesAggreg(TabSeries = TabSeries, TimeFormat = TimeFormat,
NewTimeFormat = NewTimeFormat, ConvertFun = ConvertFun,
YearFirstMonth = YearFirstMonth)
BasinObs <- NewTabSeries
names(BasinObs) <- c("DatesR", "P", "E", "T", "Qmm")
## preparation of the InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR1A, DatesR = BasinObs$DatesR,
Precip = BasinObs$P, PotEvap = BasinObs$E)
## run period selection
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y")=="1990"),
which(format(BasinObs$DatesR, format = "%Y")=="1999"))
## preparation of the RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR1A,
InputsModel = InputsModel, IndPeriod_Run = Ind_Run)
## simulation
Param <- c(X1 = 0.840)
OutputsModel <- RunModel_GR1A(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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