diff --git a/DESCRIPTION b/DESCRIPTION
index 3c2f142af4f66754938d3025a34746dc15a48aa3..8210df871cf4c2b06f0cd352d1bdbd1b2cc3ad41 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
-Version: 1.2.11.1
+Version: 1.2.11.2
Date: 2019-03-22
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
diff --git a/NEWS.rmd b/NEWS.rmd
index 23999779f1034f38e0bef48a9f5cdf19df572181..6db66a7fba8ac5ec1285d7f83bb225590264f61c 100644
--- a/NEWS.rmd
+++ b/NEWS.rmd
@@ -13,7 +13,7 @@ output:
-### 1.2.11.1 Release Notes (2019-03-22)
+### 1.2.11.2 Release Notes (2019-03-22)
@@ -33,8 +33,6 @@ output:
- Added <code>TransfoParam_CemaNeigeHyst()</code> function in order to take into account transformation of the parameters of the CemaNeige module when the hysteresis is used.
-- <code>RunModel_CemaNeige*()</code> functions now presents an <code>IsHyst</code> argument to give the possibility to use the hysteresis with CemaNeige.
-
- <code>CreateInputsCrit()</code> now can prepare an <code>InputsCrit</code> object in order to compute a single criterion (<code>Single</code> class), multiple criteria (<code>Multi</code> class) with the <code>ErrorCrit()</code> function. So it is now possible to set the following arguments as atomic (as before) or as list: <code>FUN_CRIT</code>, <code>obs</code>, <code>BoolCrit</code>, <code>transfo</code>, <code>weights</code>. If the list format is chosen, all the lists must have the same length.
- <code>CreateInputsCrit()</code> now presents a <code>varObs</code> argument in order to allow to prepare an <code>InputsCrit</code> object in order run a criterion on other variable than observed discharges with the <code>ErrorCrit()</code> function (e.g. SCA, SWE).
diff --git a/R/RunModel_CemaNeige.R b/R/RunModel_CemaNeige.R
index ba4d1192ef553f6d97eb33e154a21951af57b8fb..359f2259b588895afc8497499f1740f0f9e5e1ef 100644
--- a/R/RunModel_CemaNeige.R
+++ b/R/RunModel_CemaNeige.R
@@ -1,14 +1,9 @@
RunModel_CemaNeige <- function(InputsModel, RunOptions, Param, IsHyst = FALSE) {
-
- ## Arguments_check
- if (!is.logical(IsHyst) | length(IsHyst) != 1L) {
- stop("'IsHyst' must be a 'logical' of length 1")
- }
-
## Initialization of variables
- NParam <- ifelse(IsHyst, 4L, 2L)
+ IsHyst <- inherits(RunOptions, "hysteresis")
+ NParam <- ifelse(test = IsHyst, yes = 4L, no = 2L)
NStates <- 4L
FortranOutputsCemaNeige <- .FortranOutputs(GR = NULL, isCN = TRUE)$CN
diff --git a/R/RunModel_CemaNeigeGR4J.R b/R/RunModel_CemaNeigeGR4J.R
index 6d4d4e4129487f82ee946b705c106f8e6074c0f5..b943b340aa79fcd1ee27077e52775b2b8f06782f 100644
--- a/R/RunModel_CemaNeigeGR4J.R
+++ b/R/RunModel_CemaNeigeGR4J.R
@@ -1,12 +1,9 @@
-RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE){
+RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param){
- ## Arguments_check
- if (!is.logical(IsHyst) | length(IsHyst) != 1L) {
- stop("'IsHyst' must be a 'logical' of length 1")
- }
-
- NParam <- ifelse(IsHyst, 8L, 6L)
+ ## Initialization of variables
+ IsHyst <- inherits(RunOptions, "hysteresis")
+ NParam <- ifelse(test = IsHyst, yes = 8L, no = 6L)
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR4J", isCN = TRUE)
@@ -64,21 +61,21 @@ RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
StateStartCemaNeige <- RunOptions$IniStates[(7+20+40) + c(iLayer, iLayer+NLayers)]
RESULTS <- .Fortran("frun_CemaNeige",PACKAGE="airGR",
##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/d]
- InputsFracSolidPrecip=InputsModel$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(NParam), ### number of model parameter = 2
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
- 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
+ LInputs=LInputSeries, ### length of input and output series
+ InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/d]
+ InputsFracSolidPrecip=InputsModel$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(NParam), ### number of model parameter = 2
+ Param=as.double(ParamCemaNeige), ### parameter set
+ NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
+ 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 (reservoir levels [mm] and HU)
+ 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 (reservoir levels [mm] and HU)
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
@@ -113,18 +110,18 @@ RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
##Call_fortan
RESULTS <- .Fortran("frun_GR4J",PACKAGE="airGR",
##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
+ LInputs=LInputSeries, ### length of input and output series
+ InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
+ InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam=NParamMod, ### number of model parameter
+ Param=ParamMod, ### parameter set
+ NStates=NStatesMod, ### number of state variables used for model initialising
StateStart=RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
- IndOutputs=IndOutputsMod, ### indices of output series
+ NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
+ IndOutputs=IndOutputsMod, ### indices of output series
##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
+ Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
+ StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
@@ -170,6 +167,7 @@ RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
##End
rm(RESULTS);
+
class(OutputsModel) <- c("OutputsModel","daily","GR","CemaNeige");
if(IsHyst) {
class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
diff --git a/R/RunModel_CemaNeigeGR5J.R b/R/RunModel_CemaNeigeGR5J.R
index 92fe0f66faf2422e47969400cbc057bce3f6b375..70b254c128ad9a6a5e3a63bf7026cac6d97e71fb 100644
--- a/R/RunModel_CemaNeigeGR5J.R
+++ b/R/RunModel_CemaNeigeGR5J.R
@@ -1,12 +1,8 @@
-RunModel_CemaNeigeGR5J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE){
+RunModel_CemaNeigeGR5J <- function(InputsModel,RunOptions,Param){
- ## Arguments_check
- if (!is.logical(IsHyst) | length(IsHyst) != 1L) {
- stop("'IsHyst' must be a 'logical' of length 1")
- }
-
- NParam <- ifelse(IsHyst, 9L, 7L)
+ IsHyst <- inherits(RunOptions, "hysteresis")
+ NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L)
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR5J", isCN = TRUE)
@@ -63,21 +59,21 @@ RunModel_CemaNeigeGR5J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
StateStartCemaNeige <- RunOptions$IniStates[(7+20+40) + c(iLayer, iLayer+NLayers)]
RESULTS <- .Fortran("frun_CemaNeige",PACKAGE="airGR",
##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/d]
- InputsFracSolidPrecip=InputsModel$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(NParam), ### number of model parameter = 2
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
- 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
+ LInputs=LInputSeries, ### length of input and output series
+ InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/d]
+ InputsFracSolidPrecip=InputsModel$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(NParam), ### number of model parameter = 2
+ Param=as.double(ParamCemaNeige), ### parameter set
+ NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
+ 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 (reservoir levels [mm] and HU)
+ 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 (reservoir levels [mm] and HU)
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
@@ -112,18 +108,18 @@ RunModel_CemaNeigeGR5J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
##Call_fortan
RESULTS <- .Fortran("frun_GR5J",PACKAGE="airGR",
##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
+ LInputs=LInputSeries, ### length of input and output series
+ InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
+ InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam=NParamMod, ### number of model parameter
+ Param=ParamMod, ### parameter set
+ NStates=NStatesMod, ### number of state variables used for model initialising
StateStart=RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
- IndOutputs=IndOutputsMod, ### indices of output series
+ NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
+ IndOutputs=IndOutputsMod, ### indices of output series
##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
+ Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
+ StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
diff --git a/R/RunModel_CemaNeigeGR6J.R b/R/RunModel_CemaNeigeGR6J.R
index 2301c5ac37cfaf57cd31f43de4a5feb44e87a51a..7f1289ba400496a84dc77e3c41924c075d903006 100644
--- a/R/RunModel_CemaNeigeGR6J.R
+++ b/R/RunModel_CemaNeigeGR6J.R
@@ -1,12 +1,8 @@
-RunModel_CemaNeigeGR6J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE){
+RunModel_CemaNeigeGR6J <- function(InputsModel,RunOptions,Param){
- ## Arguments_check
- if (!is.logical(IsHyst) | length(IsHyst) != 1L) {
- stop("'IsHyst' must be a 'logical' of length 1")
- }
-
- NParam <- ifelse(IsHyst, 10L, 8L)
+ isHyst <- inherits(RunOptions, "hysteresis")
+ NParam <- ifelse(test = IsHyst, yes = 10L, no = 8L)
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR6J", isCN = TRUE)
@@ -72,16 +68,16 @@ RunModel_CemaNeigeGR6J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
InputsFracSolidPrecip=InputsModel$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(NParam), ### number of model parameter = 2
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
+ NParam=as.integer(NParam), ### number of model parameter = 2
+ Param=as.double(ParamCemaNeige), ### parameter set
+ NStates=as.integer(NStates), ### number of state variables used for model initialising = 2
StateStart=StateStartCemaNeige, ### state variables used when the model run starts
- IsHyst = as.integer(IsHyst), ### use of hysteresis
+ 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 (reservoir levels [mm] and HU)
+ StateEnd=rep(as.double(-999.999),as.integer(NStates)) ### state variables at the end of the model run (reservoir levels [mm] and HU)
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
@@ -117,18 +113,18 @@ RunModel_CemaNeigeGR6J <- function(InputsModel,RunOptions,Param, IsHyst = FALSE)
##Call_fortan
RESULTS <- .Fortran("frun_GR6J",PACKAGE="airGR",
##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
+ LInputs=LInputSeries, ### length of input and output series
+ InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
+ InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam=NParamMod, ### number of model parameter
+ Param=ParamMod, ### parameter set
+ NStates=NStatesMod, ### number of state variables used for model initialising
StateStart=RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
- IndOutputs=IndOutputsMod, ### indices of output series
+ NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
+ IndOutputs=IndOutputsMod, ### indices of output series
##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
+ Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
+ StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
)
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
diff --git a/man/RunModel_CemaNeige.Rd b/man/RunModel_CemaNeige.Rd
index 3b6f880124bba73ee97cdfbf4c4bf480d7fb511d..1f0de87d77244947f7f8d5bcf6e4141aa74822ff 100644
--- a/man/RunModel_CemaNeige.Rd
+++ b/man/RunModel_CemaNeige.Rd
@@ -9,7 +9,7 @@
\usage{
-RunModel_CemaNeige(InputsModel, RunOptions, Param, IsHyst = FALSE)
+RunModel_CemaNeige(InputsModel, RunOptions, Param)
}
@@ -25,8 +25,6 @@ CemaNeige X2 \tab degree-day melt coefficient [mm/°C/d]
CemaNeige X3 \tab (optional) accumulation threshold [mm] (needed if \code{IsHyst = TRUE}) \cr
CemaNeige X4 \tab (optional) percentage (between 0 and 1) of annual snowfall defining the melt threshold [-] (needed if \code{IsHyst = TRUE}) \cr
}}
-
-\item{IsHyst}{[boolean] boolean indicating if the hysteresis version of CemaNeige is used. See details}
}
@@ -58,7 +56,7 @@ Function which performs a single run for the CemaNeige daily snow module.
\details{
-The use of the \code{IsHyst} argument is explained in \code{\link{RunModel_CemaNeigeGR4J}}. \cr
+The choice of the CemaNeige version is explained in \code{\link{CreateRunOptions}}. \cr
For further details on the model, see the references section. \cr
For further details on the argument structures and initialisation options, see \code{\link{CreateRunOptions}}.
}
@@ -94,9 +92,12 @@ plot(OutputsModel)
## simulation with the Linear Hysteresis
+## preparation of the RunOptions object
+RunOptions <- CreateRunOptions(FUN_MOD = RunModel_CemaNeige, InputsModel = InputsModel,
+ IndPeriod_Run = Ind_Run, IsHyst = TRUE)
Param <- c(0.962, 2.249, 100, 0.4)
OutputsModel <- RunModel_CemaNeige(InputsModel = InputsModel,
- RunOptions = RunOptions, Param = Param, IsHyst = TRUE)
+ RunOptions = RunOptions, Param = Param)
## results preview
plot(OutputsModel)
diff --git a/man/RunModel_CemaNeigeGR4J.Rd b/man/RunModel_CemaNeigeGR4J.Rd
index 2904555657664e5624c4a53add1f19698817d93c..26756ffda8efced6ee679a32e5e536e050ae91a0 100644
--- a/man/RunModel_CemaNeigeGR4J.Rd
+++ b/man/RunModel_CemaNeigeGR4J.Rd
@@ -9,7 +9,7 @@
\usage{
-RunModel_CemaNeigeGR4J(InputsModel, RunOptions, Param, IsHyst = FALSE)
+RunModel_CemaNeigeGR4J(InputsModel, RunOptions, Param)
}
@@ -29,8 +29,6 @@ CemaNeige X2 \tab degree-day melt coefficient [mm/°C/d]
CemaNeige X3 \tab (optional) accumulation threshold [mm] (needed if \code{IsHyst = TRUE}) \cr
CemaNeige X4 \tab (optional) percentage (between 0 and 1) of annual snowfall defining the melt threshold [-] (needed if \code{IsHyst = TRUE}) \cr
}}
-
-\item{IsHyst}{[boolean] boolean indicating if the hysteresis version of CemaNeige is used. See details}
}
@@ -80,8 +78,7 @@ Function which performs a single run for the CemaNeige-GR4J daily lumped model o
\details{
-If \code{IsHyst = FALSE}, the original CemaNeige version from Valéry et al. (2014) is used. \cr
-If \code{IsHyst = TRUE}, the CemaNeige version from Riboust et al. (2019) is used. Compared to the original version, this version of CemaNeige needs two more parameters and it includes a representation of the hysteretic relationship between the Snow Cover Area (SCA) and the Snow Water Equivalent (SWE) in the catchment. The hysteresis included in airGR is the Modified Linear hysteresis (LH*); it is represented on panel b) of Fig. 3 in Riboust et al. (2019). Riboust et al. (2019) advise to use the LH* version of CemaNeige with parameters calibrated using an objective function combining 75 \% of KGE calculated on discharge simulated from a rainfall-runoff model compared to observed discharge and 5 \% of KGE calculated on SCA on 5 CemaNeige elevation bands compared to satellite (e.g. MODIS) SCA (see Eq. (18), Table 3 and Fig. 6). Riboust et al. (2019)'s tests were realized with GR4J as the chosen rainfall-runoff model. \cr \cr
+The choice of the CemaNeige version is explained in \code{\link{CreateRunOptions}}. \cr
For further details on the model, see the references section. \cr
For further details on the argument structures and initialisation options, see \code{\link{CreateRunOptions}}.
}
@@ -122,9 +119,12 @@ OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsMode
## simulation with the Linear Hysteresis
+## preparation of the RunOptions object
+RunOptions <- CreateRunOptions(FUN_MOD = RunModel_CemaNeigeGR4J, InputsModel = InputsModel,
+ IndPeriod_Run = Ind_Run, IsHyst = TRUE)
Param <- c(408.774, 2.646, 131.264, 1.174, 0.962, 2.249, 100, 0.4)
OutputsModel <- RunModel_CemaNeigeGR4J(InputsModel = InputsModel,
- RunOptions = RunOptions, Param = Param, IsHyst = TRUE)
+ RunOptions = RunOptions, Param = Param)
## results preview
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
diff --git a/man/RunModel_CemaNeigeGR5J.Rd b/man/RunModel_CemaNeigeGR5J.Rd
index c5fb85010081966b449f2e000af3d3148f594aff..e7bf524af2eaaca5da37ccdac50ab3c98bd30d1a 100644
--- a/man/RunModel_CemaNeigeGR5J.Rd
+++ b/man/RunModel_CemaNeigeGR5J.Rd
@@ -9,7 +9,7 @@
\usage{
-RunModel_CemaNeigeGR5J(InputsModel, RunOptions, Param, IsHyst = FALSE)
+RunModel_CemaNeigeGR5J(InputsModel, RunOptions, Param)
}
@@ -30,7 +30,6 @@ CemaNeige X2 \tab degree-day melt coefficient [mm/°C/d]
CemaNeige X3 \tab (optional) accumulation threshold [mm] (needed if \code{IsHyst = TRUE}) \cr
CemaNeige X4 \tab (optional) percentage (between 0 and 1) of annual snowfall defining the melt threshold [-] (needed if \code{IsHyst = TRUE}) \cr
}}
-\item{IsHyst}{[boolean] boolean indicating if the hysteresis version of CemaNeige is used. See details}
}
@@ -80,7 +79,7 @@ Function which performs a single run for the CemaNeige-GR5J daily lumped model.
\details{
-The use of the \code{IsHyst} argument is explained in \code{\link{RunModel_CemaNeigeGR4J}}. \cr
+The choice of the CemaNeige version is explained in \code{\link{CreateRunOptions}}. \cr
For further details on the model, see the references section. \cr
For further details on the argument structures and initialisation options, see \code{\link{CreateRunOptions}}.
}
@@ -121,9 +120,12 @@ OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsMode
## simulation with the Linear Hysteresis
+## preparation of the RunOptions object
+RunOptions <- CreateRunOptions(FUN_MOD = RunModel_CemaNeigeGR5J, InputsModel = InputsModel,
+ IndPeriod_Run = Ind_Run, IsHyst = TRUE)
Param <- c(179.139, -0.100, 203.815, 1.174, 2.478, 0.977, 2.774, 100, 0.4)
OutputsModel <- RunModel_CemaNeigeGR5J(InputsModel = InputsModel,
- RunOptions = RunOptions, Param = Param, IsHyst = TRUE)
+ RunOptions = RunOptions, Param = Param)
## results preview
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
diff --git a/man/RunModel_CemaNeigeGR6J.Rd b/man/RunModel_CemaNeigeGR6J.Rd
index d12514024a301463f805eb8683b81d87867e9e25..7a68a223da2996a52eacbda19b2ef50202f12d58 100644
--- a/man/RunModel_CemaNeigeGR6J.Rd
+++ b/man/RunModel_CemaNeigeGR6J.Rd
@@ -9,7 +9,7 @@
\usage{
-RunModel_CemaNeigeGR6J(InputsModel, RunOptions, Param, IsHyst = FALSE)
+RunModel_CemaNeigeGR6J(InputsModel, RunOptions, Param)
}
@@ -31,7 +31,6 @@ CemaNeige X2 \tab degree-day melt coefficient [mm/°C/d]
CemaNeige X3 \tab (optional) accumulation threshold [mm] (needed if \code{IsHyst = TRUE}) \cr
CemaNeige X4 \tab (optional) percentage (between 0 and 1) of annual snowfall defining the melt threshold [-] (needed if \code{IsHyst = TRUE})\cr
}}
-\item{IsHyst}{[boolean] boolean indicating if the hysteresis version of CemaNeige is used. See details}
}
@@ -83,7 +82,7 @@ Function which performs a single run for the CemaNeige-GR6J daily lumped model.
\details{
-The use of the \code{IsHyst} argument is explained in \code{\link{RunModel_CemaNeigeGR4J}}. \cr
+The choice of the CemaNeige version is explained in \code{\link{CreateRunOptions}}. \cr
For further details on the model, see the references section. \cr
For further details on the argument structures and initialisation options, see \code{\link{CreateRunOptions}}.
}
@@ -126,8 +125,11 @@ OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsMode
## simulation with the Linear Hysteresis
Param <- c(116.482, 0.500, 72.733, 1.224, 0.278, 30.333, 0.977, 2.774, 100, 0.4)
+## preparation of the RunOptions object
+RunOptions <- CreateRunOptions(FUN_MOD = RunModel_CemaNeigeGR6J, InputsModel = InputsModel,
+ IndPeriod_Run = Ind_Run, IsHyst = TRUE)
OutputsModel <- RunModel_CemaNeigeGR6J(InputsModel = InputsModel,
- RunOptions = RunOptions, Param = Param, IsHyst = TRUE)
+ RunOptions = RunOptions, Param = Param)
## results preview
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])