diff --git a/DESCRIPTION b/DESCRIPTION index 2d371b6684133ad2346aace5338cc7b98ab42cfa..a6ceb5eb4245b0f6fcbb6b627bb43c3e27ff7d73 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: airGR Type: Package Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling -Version: 1.6.8.18 +Version: 1.6.8.19 Date: 2020-12-01 Authors@R: c( person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")), diff --git a/man/RunModel_GR2M.Rd b/man/RunModel_GR2M.Rd index b491a99c0feb476e1ad2806ea0b2149e1c83d4c1..ccfd7ee83684268d90f55295afdfde06fe4ee30b 100644 --- a/man/RunModel_GR2M.Rd +++ b/man/RunModel_GR2M.Rd @@ -68,22 +68,16 @@ library(airGR) ## loading catchment data data(L0123001) -## conversion of example data from daily to monthly time step -TabSeries <- data.frame(DatesR = BasinObs$DatesR, - P = BasinObs$P, - E = BasinObs$E, - Qmm = BasinObs$Qmm) -TimeFormat <- "\%Y\%m" -ConvertFun <- c("sum", "sum", "sum") -BasinObs <- SeriesAggreg(TabSeries = TabSeries, Format = TimeFormat, ConvertFun = ConvertFun) - -## preparation of the InputsModel object -InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR2M, DatesR = BasinObs$DatesR, +## preparation of the InputsModel object with daily time step data +InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR, Precip = BasinObs$P, PotEvap = BasinObs$E) +## conversion of InputsModel to monthly time step +InputsModel <- SeriesAggreg(InputsModel, Format = "\%Y\%m") + ## run period selection -Ind_Run <- seq(which(format(BasinObs$DatesR, format = "\%Y-\%m")=="1990-01"), - which(format(BasinObs$DatesR, format = "\%Y-\%m")=="1999-12")) +Ind_Run <- seq(which(format(InputsModel$DatesR, format = "\%Y-\%m")=="1990-01"), + which(format(InputsModel$DatesR, format = "\%Y-\%m")=="1999-12")) ## preparation of the RunOptions object RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR2M, @@ -93,12 +87,18 @@ RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR2M, Param <- c(X1 = 265.072, X2 = 1.040) OutputsModel <- RunModel_GR2M(InputsModel = InputsModel, RunOptions = RunOptions, Param = Param) +## conversion of observed discharge to monthly time step +Qobs <- SeriesAggreg(data.frame(BasinObs$DatesR, BasinObs$Qmm), + Format = "\%Y\%m", + ConvertFun = "sum") +Qobs <- Qobs[Ind_Run, 2] + ## results preview -plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run]) +plot(OutputsModel, Qobs = Qobs) ## efficiency criterion: Nash-Sutcliffe Efficiency InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel, - RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run]) + RunOptions = RunOptions, Obs = Qobs) OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel) } diff --git a/man/SeriesAggreg.Rd b/man/SeriesAggreg.Rd index 8e8d0949594312a692a5a9a406324410c8a97615..156677816f5aece3523554bffe631d1ac7b20b7e 100644 --- a/man/SeriesAggreg.Rd +++ b/man/SeriesAggreg.Rd @@ -102,6 +102,14 @@ NewTabSeries <- SeriesAggreg(TabSeries = TabSeries, Format = "\%m", ConvertFun = c("sum", "sum", "mean", "sum")) str(NewTabSeries) + +# Conversion of InputsModel +example("RunModel_GR2M") + +# Monthly regime on OutputsModel object +SimulatedMonthlyRegime <- SeriesAggreg(OutputsModel, Format = "\%m") +str(SimulatedMonthlyRegime) + }