diff --git a/DESCRIPTION b/DESCRIPTION
index d2c09b8ba612cbc11ee595a1e200a0f7ad59173f..bae6fed2f86d812bcff869984b75b4eb1dc62164 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
-Version: 1.6.3.42
-Date: 2020-11-09
+Version: 1.6.3.65
+Date: 2020-11-17
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
person("Olivier", "Delaigue", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7668-8468"), email = "airGR@inrae.fr"),
diff --git a/NEWS.md b/NEWS.md
index c25fb352eff9cd956add529b9c2e2ceb9d115d22..29cfe222b7368dc08d361050d11a9742a795c113 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -4,7 +4,7 @@
-### 1.6.3.42 Release Notes (2020-11-09)
+### 1.6.3.65 Release Notes (2020-11-17)
#### New features
diff --git a/R/RunModel_CemaNeige.R b/R/RunModel_CemaNeige.R
index e1dbbf659969732b8fbeca38246e7db2d8aa8bf2..a9f35e0e189465dd24e23bb0b4904216e98b6766 100644
--- a/R/RunModel_CemaNeige.R
+++ b/R/RunModel_CemaNeige.R
@@ -8,7 +8,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
FortranOutputsCemaNeige <- .FortranOutputs(GR = NULL, isCN = TRUE)$CN
- ## Arguments_check
+ ## Arguments check
if (!inherits(InputsModel, "InputsModel")) {
stop("'InputsModel' must be of class 'InputsModel'")
}
@@ -39,7 +39,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
time_mult <- 24
}
- ## Input_data_preparation
+ ## Input data preparation
if (identical(RunOptions$IndPeriod_WarmUp, as.integer(0))) {
RunOptions$IndPeriod_WarmUp <- NULL
}
@@ -52,7 +52,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
- ## SNOW_MODULE________________________________________________________________________________
+ ## CemaNeige________________________________________________________________________________
ParamCemaNeige <- Param
NLayers <- length(InputsModel$LayerPrecip)
@@ -71,7 +71,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
NameCemaNeigeLayers <- "CemaNeigeLayers"
- ## Call_DLL_CemaNeige_________________________
+ ## Call CemaNeige Fortran_________________________
for (iLayer in 1:NLayers) {
if (!IsHyst) {
@@ -105,7 +105,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
- ## Data_storage
+ ## Data storage
CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
names(CemaNeigeLayers[[iLayer]]) <- FortranOutputsCemaNeige[IndOutputsCemaNeige]
if (ExportStateEnd) {
@@ -113,7 +113,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
}
rm(RESULTS)
- } ### ENDFOR_iLayer
+ } ### ENDFOR iLayer
names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
@@ -129,7 +129,7 @@ RunModel_CemaNeige <- function(InputsModel, RunOptions, Param) {
verbose = FALSE)
}
- ## Output_data_preparation
+ ## Output data preparation
if (!ExportDatesR & !ExportStateEnd) {
OutputsModel <- list(CemaNeigeLayers)
names(OutputsModel) <- NameCemaNeigeLayers
diff --git a/R/RunModel_CemaNeigeGR4H.R b/R/RunModel_CemaNeigeGR4H.R
index 7aecbaf11c5f7e0e7b701069f7f618ca5119a4a1..fe29e9096e863e14283b54635006c341d13ab9dd 100644
--- a/R/RunModel_CemaNeigeGR4H.R
+++ b/R/RunModel_CemaNeigeGR4H.R
@@ -1,5 +1,5 @@
-RunModel_CemaNeigeGR4H <- function(InputsModel,RunOptions,Param){
-
+RunModel_CemaNeigeGR4H <- function(InputsModel, RunOptions, Param) {
+
## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis")
@@ -7,177 +7,221 @@ RunModel_CemaNeigeGR4H <- function(InputsModel,RunOptions,Param){
NParamCN <- NParam - 4L
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR4H", isCN = TRUE)
-
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "hourly")) {
+ stop("'InputsModel' must be of class 'hourly'")
+ }
+ if (!inherits(InputsModel, "GR")) {
+ stop("'InputsModel' must be of class 'GR'")
+ }
+ if (!inherits(InputsModel, "CemaNeige")) {
+ stop("'InputsModel' must be of class 'CemaNeige'")
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("'RunOptions' must be of class 'RunOptions'")
+ }
+ if (!inherits(RunOptions, "GR")) {
+ stop("'RunOptions' must be of class 'GR'")
+ }
+ if (!inherits(RunOptions, "CemaNeige")) {
+ stop("'RunOptions' must be of class 'CemaNeige'")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
+ }
+ Param <- as.double(Param)
+
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [hour]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp) + 1):LInputSeries
+ ParamCemaNeige <- Param[(length(Param)-1 - 2 * as.integer(IsHyst)):length(Param)]
+ NParamMod <- as.integer(length(Param) - (2 + 2 * as.integer(IsHyst)))
+ ParamMod <- Param[1:NParamMod]
+ NLayers <- length(InputsModel$LayerPrecip)
+ NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+
+ ## CemaNeige________________________________________________________________________________
+ if (inherits(RunOptions, "CemaNeige")) {
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
+ } else {
+ IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
+ }
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- "CemaNeigeLayers"
- ##Arguments_check
- if(!inherits(InputsModel,"InputsModel")){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(!inherits(InputsModel,"hourly" )){ stop("'InputsModel' must be of class 'hourly' ") }
- if(!inherits(InputsModel,"GR" )){ stop("'InputsModel' must be of class 'GR' ") }
- if(!inherits(InputsModel,"CemaNeige" )){ stop("'InputsModel' must be of class 'CemaNeige' ") }
- if(!inherits(RunOptions,"RunOptions" )){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(!inherits(RunOptions,"GR" )){ stop("'RunOptions' must be of class 'GR' ") }
- if(!inherits(RunOptions,"CemaNeige" )){ stop("'RunOptions' must be of class 'CemaNeige' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [hour]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
+
+ ## Call CemaNeige Fortran_________________________
+ for (iLayer in 1:NLayers) {
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
- NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
- ParamMod <- Param[1:NParamMod];
- NLayers <- length(InputsModel$LayerPrecip);
- NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
+ if (!IsHyst) {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)]
+ } else {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
+ }
+ RESULTS <- .Fortran("frun_cemaneige", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h]
+ InputsFracSolidPrecip = InputsModel$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(NParamCN), ### number of model parameters = 2 or 4
+ Param = as.double(ParamCemaNeige), ### parameter set
+ NStates = as.integer(NStates), ### number of state variables used for model initialisation = 4
+ 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
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
- ##SNOW_MODULE________________________________________________________________________________##
- if(inherits(RunOptions,"CemaNeige")){
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN));
- } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
-
-
- ##Call_DLL_CemaNeige_________________________
- for(iLayer in 1:NLayers){
- if (!IsHyst) {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)]
- } else {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
- }
- RESULTS <- .Fortran("frun_cemaneige",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h]
- InputsFracSolidPrecip=InputsModel$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(NParamCN), ### number of model parameters = 2 or 4
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialisation = 4
- 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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
-
- ##Data_storage
- CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
- IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
- if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
- rm(RESULTS);
- } ###ENDFOR_iLayer
- names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
- } ###ENDIF_RunSnowModule
- if(!inherits(RunOptions,"CemaNeige")){
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
- CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; }
-
-
-
- ##MODEL______________________________________________________________________________________##
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR));
- } else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); }
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*ParamMod[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*ParamMod[3]; ### routing store level (mm)
+ ## Data storage
+ CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
+ IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
+ if (iLayer == 1) {
+ CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr4h",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/h]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
- StateStart=RunOptions$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
- ##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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- idNStates <- seq_len(NStates*NLayers) %% NStates
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR4H, InputsModel = InputsModel, IsHyst = IsHyst,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = RESULTS$StateEnd[(1:(20*24))+7], UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
- GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
- eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
- GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
- GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
- verbose = FALSE)
+ if (iLayer > 1) {
+ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- if(inherits(RunOptions,"CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(!ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##DatesR_and_OutputsModel_only
- if( ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##OutputsModel_and_SateEnd_only
- if(!ExportDatesR & ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if( ExportDatesR & ExportStateEnd){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
-
- ##End
- rm(RESULTS);
-
- class(OutputsModel) <- c("OutputsModel","hourly","GR","CemaNeige");
- if(IsHyst) {
- class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ if (ExportStateEnd) {
+ CemaNeigeStateEnd <- c(CemaNeigeStateEnd, RESULTS$StateEnd)
}
- return(OutputsModel);
-
+ rm(RESULTS)
+ } ### ENDFOR iLayer
+ names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
+ } ### ENDIF RunSnowModule
+ if (!inherits(RunOptions, "CemaNeige")) {
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- NULL
+ CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
+ }
+
+
+
+ ## GR model
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
+ } else {
+ IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * ParamMod[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * ParamMod[3] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr4h", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = CatchMeltAndPliq, ### input series of total precipitation [mm/h]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
+ NParam = NParamMod, ### number of model parameter
+ Param = ParamMod, ### parameter set
+ NStates = NStatesMod, ### number of state variables used for model initialising
+ StateStart = RunOptions$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
+ ## 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
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ idNStates <- seq_len(NStates*NLayers) %% NStates
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR4H, InputsModel = InputsModel, IsHyst = IsHyst,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = RESULTS$StateEnd[(1:(20*24))+7], UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
+ GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
+ eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
+ GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
+ GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
+ verbose = FALSE)
+ }
+
+ if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
+ RESULTS$Outputs[, which(FortranOutputs$GR[IndOutputsMod] == "Precip")] <- InputsModel$Precip[IndPeriod1]
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## DatesR and OutputsModel only
+ if ( ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ( ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "hourly", "GR", "CemaNeige")
+ if (IsHyst) {
+ class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ }
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_CemaNeigeGR4J.R b/R/RunModel_CemaNeigeGR4J.R
index f3a7f8226511264f189df5346a32e29b8a8528d7..9156165856ae34a26358c231d9466c8174823bee 100644
--- a/R/RunModel_CemaNeigeGR4J.R
+++ b/R/RunModel_CemaNeigeGR4J.R
@@ -1,5 +1,5 @@
-RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param){
-
+RunModel_CemaNeigeGR4J <- function(InputsModel, RunOptions, Param) {
+
## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis")
@@ -7,177 +7,219 @@ RunModel_CemaNeigeGR4J <- function(InputsModel,RunOptions,Param){
NParamCN <- NParam - 4L
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR4J", isCN = TRUE)
-
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily")) {
+ stop("'InputsModel' must be of class 'daily'")
+ }
+ if (!inherits(InputsModel, "GR")) {
+ stop("'InputsModel' must be of class 'GR'")
+ }
+ if (!inherits(InputsModel, "CemaNeige")) {
+ stop("'InputsModel' must be of class 'CemaNeige'")
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("'RunOptions' must be of class 'RunOptions'")
+ }
+ if (!inherits(RunOptions, "GR")) {
+ stop("'RunOptions' must be of class 'GR'")
+ }
+ if (!inherits(RunOptions, "CemaNeige")) {
+ stop("'RunOptions' must be of class 'CemaNeige'")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp) + 1):LInputSeries
+ ParamCemaNeige <- Param[(length(Param)- 1 - 2 * as.integer(IsHyst)):length(Param)]
+ NParamMod <- as.integer(length(Param) - (2 + 2*as.integer(IsHyst)))
+ ParamMod <- Param[1:NParamMod]
+ NLayers <- length(InputsModel$LayerPrecip)
+ NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+
+ ## CemaNeige________________________________________________________________________________
+ if (inherits(RunOptions, "CemaNeige")) {
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
+ } else {
+ IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
+ }
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- "CemaNeigeLayers"
- ##Arguments_check
- if(!inherits(InputsModel,"InputsModel")){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(!inherits(InputsModel,"daily" )){ stop("'InputsModel' must be of class 'daily' ") }
- if(!inherits(InputsModel,"GR" )){ stop("'InputsModel' must be of class 'GR' ") }
- if(!inherits(InputsModel,"CemaNeige" )){ stop("'InputsModel' must be of class 'CemaNeige' ") }
- if(!inherits(RunOptions,"RunOptions" )){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(!inherits(RunOptions,"GR" )){ stop("'RunOptions' must be of class 'GR' ") }
- if(!inherits(RunOptions,"CemaNeige" )){ stop("'RunOptions' must be of class 'CemaNeige' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
+
+ ## Call CemaNeige Fortran_________________________
+ for(iLayer in 1:NLayers) {
+ if (!IsHyst) {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
+ } else {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
}
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
+ RESULTS <- .Fortran("frun_cemaneige", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$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$MeanAnSolidPrecip[iLayer], ### value of annual mean solid precip [mm/y]
+ NParam = as.integer(NParamCN), ### number of model parameters = 2 or 4
+ Param = as.double(ParamCemaNeige), ### parameter set
+ NStates = as.integer(NStates), ### number of state variables used for model initialising = 4
+ StateStart = StateStartCemaNeige, ### state variables used when the model run starts
+ IsHyst = as.integer(IsHyst), ### use of hysteresis
+ NOutputs = as.integer(length(IndOutputsCemaNeige)), ### number of output series
+ IndOutputs = IndOutputsCemaNeige, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputsCemaNeige)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), as.integer(NStates)) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
- NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
- ParamMod <- Param[1:NParamMod];
- NLayers <- length(InputsModel$LayerPrecip);
- NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
-
- ##SNOW_MODULE________________________________________________________________________________##
- if(inherits(RunOptions,"CemaNeige")){
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN));
- } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
-
-
- ##Call_DLL_CemaNeige_________________________
- for(iLayer in 1:NLayers){
- if (!IsHyst) {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
- } else {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*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(NParamCN), ### number of model parameters = 2 or 4
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 4
- 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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
-
- ##Data_storage
- CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
- IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
- if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
- rm(RESULTS);
- } ###ENDFOR_iLayer
- names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
- } ###ENDIF_RunSnowModule
- if(!inherits(RunOptions,"CemaNeige")){
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
- CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; }
-
-
-
- ##MODEL______________________________________________________________________________________##
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR));
- } else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); }
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*ParamMod[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*ParamMod[3]; ### routing store level (mm)
+ ## Data storage
+ CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
+ IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
+ if (iLayer == 1) {
+ CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- ##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$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
- StateStart=RunOptions$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
- ##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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- idNStates <- seq_len(NStates*NLayers) %% NStates
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR4J, InputsModel = InputsModel, IsHyst = IsHyst,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
- eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
- GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
- GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
- verbose = FALSE)
+ if (iLayer >1) {
+ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- if(inherits(RunOptions,"CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(!ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##DatesR_and_OutputsModel_only
- if( ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##OutputsModel_and_SateEnd_only
- if(!ExportDatesR & ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if( ExportDatesR & ExportStateEnd){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
-
- ##End
- rm(RESULTS);
-
- class(OutputsModel) <- c("OutputsModel","daily","GR","CemaNeige");
- if(IsHyst) {
- class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ if (ExportStateEnd) {
+ CemaNeigeStateEnd <- c(CemaNeigeStateEnd, RESULTS$StateEnd)
}
- return(OutputsModel);
-
+ rm(RESULTS)
+ } ### ENDFOR iLayer
+ names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
+ } ### ENDIF RunSnowModule
+ if (!inherits(RunOptions, "CemaNeige")) {
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- NULL
+ CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
+ }
+
+
+
+ ## GR model______________________________________________________________________________________
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
+ } else {
+ IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * ParamMod[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * ParamMod[3] ### routing store level (mm)
+ }
+
+ ## Call GR model 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$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam = NParamMod, ### number of model parameter
+ Param = ParamMod, ### parameter set
+ NStates = NStatesMod, ### number of state variables used for model initialising
+ StateStart = RunOptions$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
+ ## 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
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ idNStates <- seq_len(NStates*NLayers) %% NStates
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR4J, InputsModel = InputsModel, IsHyst = IsHyst,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
+ eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
+ GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
+ GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
+ verbose = FALSE)
+ }
+
+ if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
+ RESULTS$Outputs[, which(FortranOutputs$GR[IndOutputsMod] == "Precip")] <- InputsModel$Precip[IndPeriod1]
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## DatesR and OutputsModel only
+ if ( ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+ ## DatesR and OutputsModel and Sate
+ if ( ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR", "CemaNeige")
+ if (IsHyst) {
+ class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ }
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_CemaNeigeGR5H.R b/R/RunModel_CemaNeigeGR5H.R
index c8639d71338d8bd5ef4d204959258c2098160236..6cfcc4180c93eb3fa361830d55b0f382df949b57 100644
--- a/R/RunModel_CemaNeigeGR5H.R
+++ b/R/RunModel_CemaNeigeGR5H.R
@@ -1,28 +1,50 @@
-RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
+RunModel_CemaNeigeGR5H <- function(InputsModel, RunOptions, Param) {
+
+ ## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis")
NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L)
NParamCN <- NParam - 5L
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR5H", isCN = TRUE)
IsIntStore <- inherits(RunOptions, "interception")
- if(IsIntStore) {
+ if (IsIntStore) {
Imax <- RunOptions$Imax
} else {
Imax <- -99
}
- ##Arguments_check
- if(!inherits(InputsModel,"InputsModel")){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(!inherits(InputsModel,"hourly" )){ stop("'InputsModel' must be of class 'hourly' ") }
- if(!inherits(InputsModel,"GR" )){ stop("'InputsModel' must be of class 'GR' ") }
- if(!inherits(InputsModel,"CemaNeige" )){ stop("'InputsModel' must be of class 'CemaNeige' ") }
- if(!inherits(RunOptions,"RunOptions" )){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(!inherits(RunOptions,"GR" )){ stop("'RunOptions' must be of class 'GR' ") }
- if(!inherits(RunOptions,"CemaNeige" )){ stop("'RunOptions' must be of class 'CemaNeige' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "hourly")) {
+ stop("'InputsModel' must be of class 'hourly'")
+ }
+ if (!inherits(InputsModel, "GR")) {
+ stop("'InputsModel' must be of class 'GR'")
+ }
+ if (!inherits(InputsModel, "CemaNeige")) {
+ stop("'InputsModel' must be of class 'CemaNeige'")
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("'RunOptions' must be of class 'RunOptions'")
+ }
+ if (!inherits(RunOptions, "GR")) {
+ stop("'RunOptions' must be of class 'GR'")
+ }
+ if (!inherits(RunOptions, "CemaNeige")) {
+ stop("'RunOptions' must be of class 'CemaNeige'")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
+ }
+ Param <- as.double(Param)
+
Param_X1X3_threshold <- 1e-2
Param_X4_threshold <- 0.5
@@ -39,108 +61,132 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
Param[4L] <- Param_X4_threshold
}
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+
LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs));
- } else { IndOutputsMod <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
- NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
- ParamMod <- Param[1:NParamMod];
- NLayers <- length(InputsModel$LayerPrecip);
- NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##SNOW_MODULE________________________________________________________________________________##
- if(inherits(RunOptions,"CemaNeige")){
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN));
- } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputsMod <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ParamCemaNeige <- Param[(length(Param) - 1 - 2 * as.integer(IsHyst)):length(Param)]
+ NParamMod <- as.integer(length(Param) - (2 + 2 * as.integer(IsHyst)))
+ ParamMod <- Param[1:NParamMod]
+ NLayers <- length(InputsModel$LayerPrecip)
+ NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
+
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## CemaNeige________________________________________________________________________________
+ if (inherits(RunOptions, "CemaNeige")) {
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
+ } else {
+ IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
+ }
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- "CemaNeigeLayers"
- ##Call_DLL_CemaNeige_________________________
- for(iLayer in 1:NLayers){
+ ## Call CemaNeige Fortran_________________________
+ for(iLayer in 1:NLayers) {
if (!IsHyst) {
StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)]
} else {
StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
}
RESULTS <- .Fortran("frun_cemaneige",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h]
- 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$MeanAnSolidPrecip[iLayer], ### value of annual mean solid precip [mm/y]
- NParam=as.integer(NParamCN), ### number of model parameters = 2 or 4
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialisation = 4
- StateStart=StateStartCemaNeige, ### state variables used when the model run starts
- IsHyst = as.integer(IsHyst), ### use of hysteresis
- NOutputs=as.integer(length(IndOutputsCemaNeige)), ### number of output series
- IndOutputs=IndOutputsCemaNeige, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsCemaNeige)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),as.integer(NStates)) ### state variables at the end of the model run
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h]
+ 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$MeanAnSolidPrecip[iLayer], ### value of annual mean solid precip [mm/y]
+ NParam = as.integer(NParamCN), ### number of model parameters = 2 or 4
+ Param = as.double(ParamCemaNeige), ### parameter set
+ NStates = as.integer(NStates), ### number of state variables used for model initialisation = 4
+ StateStart = StateStartCemaNeige, ### state variables used when the model run starts
+ IsHyst = as.integer(IsHyst), ### use of hysteresis
+ NOutputs = as.integer(length(IndOutputsCemaNeige)), ### number of output series
+ IndOutputs = IndOutputsCemaNeige, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputsCemaNeige)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), as.integer(NStates)) ### state variables at the end of the model run
)
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
- ##Data_storage
- CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
- IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
- if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
- rm(RESULTS);
- } ###ENDFOR_iLayer
+ ## Data storage
+ CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
+ IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
+ if (iLayer == 1) {
+ CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / NLayers
+ }
+ if (iLayer > 1) {
+ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
+ }
+ if (ExportStateEnd) {
+ CemaNeigeStateEnd <- c(CemaNeigeStateEnd, RESULTS$StateEnd)
+ }
+ rm(RESULTS)
+ } ### ENDFOR iLayer
names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
- } ###ENDIF_RunSnowModule
- if(!inherits(RunOptions,"CemaNeige")){
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
- CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; }
+ } ### ENDIF RunSnowModule
+ if (!inherits(RunOptions, "CemaNeige")) {
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- NULL
+ CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
+ }
- ##MODEL______________________________________________________________________________________##
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR));
- } else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); }
+ ## GR model______________________________________________________________________________________
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
+ } else {
+ IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
+ }
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- if(IsIntStore) {
- RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax; ### interception store level (mm)
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * Param[3] ### routing store level (mm)
+ if (IsIntStore) {
+ RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax ### interception store level (mm)
}
}
- ##Call_fortan
+ ## Call GR model Fortan
RESULTS <- .Fortran("frun_gr5h",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- Imax=Imax, ### maximal capacity of interception store
- NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
- IndOutputs=IndOutputsMod, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm or mm/h]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ Imax = Imax, ### maximal capacity of interception store
+ 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 or mm/h]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### state variables at the end of the model run
)
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
if (ExportStateEnd) {
RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
idNStates <- seq_len(NStates*NLayers) %% NStates
@@ -154,45 +200,51 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
verbose = FALSE)
}
-
- if(inherits(RunOptions,"CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
-
- ##Output_data_preparation
- ##OutputsModel_only
- ##OutputsModel_only
- if(!ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##DatesR_and_OutputsModel_only
- if( ExportDatesR & !ExportStateEnd){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##OutputsModel_and_SateEnd_only
- if(!ExportDatesR & ExportStateEnd){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if( ExportDatesR & ExportStateEnd){
+
+ if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
+ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## DatesR and OutputsModel only
+ if ( ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ( ExportDatesR & ExportStateEnd) {
OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","hourly","GR","CemaNeige");
- if(IsHyst) {
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "hourly", "GR", "CemaNeige")
+ if (IsHyst) {
class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
}
- if(IsIntStore) {
+ if (IsIntStore) {
class(OutputsModel) <- c(class(OutputsModel), "interception")
}
- return(OutputsModel);
+ return(OutputsModel)
}
diff --git a/R/RunModel_CemaNeigeGR5J.R b/R/RunModel_CemaNeigeGR5J.R
index 2d41be506a20dd5cebe5ef3e0ca5006aa5ada343..3e3344d5e3b589bb310d15e075a528e86a2b91b2 100644
--- a/R/RunModel_CemaNeigeGR5J.R
+++ b/R/RunModel_CemaNeigeGR5J.R
@@ -1,180 +1,226 @@
-RunModel_CemaNeigeGR5J <- function(InputsModel,RunOptions,Param){
-
+RunModel_CemaNeigeGR5J <- function(InputsModel, RunOptions, Param) {
+
+ ## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis")
NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L)
NParamCN <- NParam - 5L
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR5J", isCN = TRUE)
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"daily" )==FALSE){ stop("'InputsModel' must be of class 'daily' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(InputsModel,"CemaNeige" )==FALSE){ stop("'InputsModel' must be of class 'CemaNeige' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(inherits(RunOptions,"CemaNeige" )==FALSE){ stop("'RunOptions' must be of class 'CemaNeige' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily")) {
+ stop("'InputsModel' must be of class 'daily'")
+ }
+ if (!inherits(InputsModel, "GR")) {
+ stop("'InputsModel' must be of class 'GR'")
+ }
+ if (!inherits(InputsModel, "CemaNeige")) {
+ stop("'InputsModel' must be of class 'CemaNeige'")
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("'RunOptions' must be of class 'RunOptions'")
+ }
+ if (!inherits(RunOptions, "GR")) {
+ stop("'RunOptions' must be of class 'GR'")
+ }
+ if (!inherits(RunOptions, "CemaNeige")) {
+ stop("'RunOptions' must be of class 'CemaNeige'")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
+ }
+ Param <- as.double(Param)
+
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp) + 1):LInputSeries
+ ParamCemaNeige <- Param[(length(Param) - 1 - 2 * as.integer(IsHyst)):length(Param)]
+ NParamMod <- as.integer(length(Param) - (2 + 2 * as.integer(IsHyst)))
+ ParamMod <- Param[1:NParamMod]
+ NLayers <- length(InputsModel$LayerPrecip)
+ NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+
+ ## CemaNeige________________________________________________________________________________
+ if (inherits(RunOptions, "CemaNeige")) {
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
+ } else {
+ IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
+ }
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- "CemaNeigeLayers"
+
+
+ ## Call CemaNeige Fortran_________________________
+ for(iLayer in 1:NLayers) {
+ if (!IsHyst) {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
+ } else {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
}
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
- NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
- ParamMod <- Param[1:NParamMod];
- NLayers <- length(InputsModel$LayerPrecip);
- NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
-
- ##SNOW_MODULE________________________________________________________________________________##
- if(inherits(RunOptions,"CemaNeige")==TRUE){
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN));
- } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
-
+ 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(NParamCN), ### number of model parameters = 2 or 4
+ Param = as.double(ParamCemaNeige), ### parameter set
+ NStates = as.integer(NStates), ### number of state variables used for model initialising = 4
+ 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
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
- ##Call_DLL_CemaNeige_________________________
- for(iLayer in 1:NLayers){
- if (!IsHyst) {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
- } else {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
+ ## Data storage
+ CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
+ IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
+ if (iLayer == 1) {
+ CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / 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(NParamCN), ### number of model parameters = 2 or 4
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 4
- 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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
-
- ##Data_storage
- CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
- IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
- if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
- rm(RESULTS);
- } ###ENDFOR_iLayer
- names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
- } ###ENDIF_RunSnowModule
- if(inherits(RunOptions,"CemaNeige")==FALSE){
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
- CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; }
-
-
-
- ##MODEL______________________________________________________________________________________##
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR));
- } else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); }
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*ParamMod[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*ParamMod[3]; ### routing store level (mm)
+ if (iLayer > 1) {
+ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr5j",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=CatchMeltAndPliq, ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$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
- StateStart=RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputsMod)), ### number of output series
- IndOutputs=IndOutputsMod, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),NStatesMod) ### state variables at the end of the model run
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- idNStates <- seq_len(NStates*NLayers) %% NStates
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR5J, InputsModel = InputsModel, IsHyst = IsHyst,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = NULL, UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
- eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
- GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
- GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
- verbose = FALSE)
+ CemaNeigeStateEnd <- c(CemaNeigeStateEnd, RESULTS$StateEnd)
}
-
- if(inherits(RunOptions,"CemaNeige")==TRUE & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if(ExportDatesR==TRUE & ExportStateEnd==TRUE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","daily","GR","CemaNeige");
- if(IsHyst) {
- class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
- }
- return(OutputsModel);
-
+ rm(RESULTS)
+ } ### ENDFOR iLayer
+ names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
+ } ### ENDIF RunSnowModule
+ if (!inherits(RunOptions, "CemaNeige")) {
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- NULL
+ CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
+ }
+
+
+
+ ## GR model______________________________________________________________________________________
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
+ } else {
+ IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * ParamMod[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * ParamMod[3] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr5j", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = CatchMeltAndPliq, ### input series of total precipitation [mm/d]
+ InputsPE = InputsModel$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
+ StateStart = RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputsMod)), ### number of output series
+ IndOutputs = IndOutputsMod, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputsMod)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), NStatesMod) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ idNStates <- seq_len(NStates*NLayers) %% NStates
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR5J, InputsModel = InputsModel, IsHyst = IsHyst,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = NULL, UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
+ eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
+ GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
+ GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
+ verbose = FALSE)
+ }
+
+ if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
+ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod] == "Precip")] <- InputsModel$Precip[IndPeriod1]
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if (ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR", "CemaNeige")
+ if (IsHyst) {
+ class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ }
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_CemaNeigeGR6J.R b/R/RunModel_CemaNeigeGR6J.R
index 54b4497f6f6a989952eb6978d37f9bc1e46af026..d82a0241ec42abb8a607d291d60f588885f8defb 100644
--- a/R/RunModel_CemaNeigeGR6J.R
+++ b/R/RunModel_CemaNeigeGR6J.R
@@ -1,186 +1,232 @@
-RunModel_CemaNeigeGR6J <- function(InputsModel,RunOptions,Param){
-
+RunModel_CemaNeigeGR6J <- function(InputsModel, RunOptions, Param) {
+
+ ## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis")
NParam <- ifelse(test = IsHyst, yes = 10L, no = 8L)
NParamCN <- NParam - 6L
NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR6J", isCN = TRUE)
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"daily" )==FALSE){ stop("'InputsModel' must be of class 'daily' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(InputsModel,"CemaNeige" )==FALSE){ stop("'InputsModel' must be of class 'CemaNeige' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(inherits(RunOptions,"CemaNeige" )==FALSE){ stop("'RunOptions' must be of class 'CemaNeige' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3X6_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[1L] <- Param_X1X3X6_threshold
- }
- if (Param[3L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[3L] <- Param_X1X3X6_threshold
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily")) {
+ stop("'InputsModel' must be of class 'daily'")
+ }
+ if (!inherits(InputsModel, "GR")) {
+ stop("'InputsModel' must be of class 'GR'")
+ }
+ if (!inherits(InputsModel, "CemaNeige")) {
+ stop("'InputsModel' must be of class 'CemaNeige'")
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("'RunOptions' must be of class 'RunOptions'")
+ }
+ if (!inherits(RunOptions, "GR")) {
+ stop("'RunOptions' must be of class 'GR'")
+ }
+ if (!inherits(RunOptions, "CemaNeige")) {
+ stop("'RunOptions' must be of class 'CemaNeige'")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
+ }
+ Param <- as.double(Param)
+
+
+ Param_X1X3X6_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[1L] <- Param_X1X3X6_threshold
+ }
+ if (Param[3L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[3L] <- Param_X1X3X6_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+ if (Param[6L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[6] (X6: coefficient for emptying exponential store [mm]) < %.2f\n X6 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[6L] <- Param_X1X3X6_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp) + 1):LInputSeries
+ ParamCemaNeige <- Param[(length(Param) - 1 - 2 * as.integer(IsHyst)):length(Param)]
+ NParamMod <- as.integer(length(Param) - (2 + 2 * as.integer(IsHyst)))
+ ParamMod <- Param[1:NParamMod]
+ NLayers <- length(InputsModel$LayerPrecip)
+ NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+
+ ## CemaNeige________________________________________________________________________________
+ if (inherits(RunOptions, "CemaNeige")) {
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
+ } else {
+ IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
+ }
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- "CemaNeigeLayers"
+
+
+ ## Call CemaNeige Fortran_________________________
+ for(iLayer in 1:NLayers) {
+ if (!IsHyst) {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
+ } else {
+ StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
}
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
- if (Param[6L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[6] (X6: coefficient for emptying exponential store [mm]) < %.2f\n X6 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[6L] <- Param_X1X3X6_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)];
- NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst)));
- ParamMod <- Param[1:NParamMod];
- NLayers <- length(InputsModel$LayerPrecip);
- NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers);
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
-
- ##SNOW_MODULE________________________________________________________________________________##
- if(inherits(RunOptions,"CemaNeige")==TRUE){
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN));
- } else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers";
-
+ 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(NParamCN), ### number of model parameters = 2 or 4
+ Param = as.double(ParamCemaNeige), ### parameter set
+ NStates = as.integer(NStates), ### number of state variables used for model initialising = 4
+ 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
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
- ##Call_DLL_CemaNeige_________________________
- for(iLayer in 1:NLayers){
- if (!IsHyst) {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers)]
- } else {
- StateStartCemaNeige <- RunOptions$IniStates[(7 + 20 + 40) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*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(NParamCN), ### number of model parameters = 2 or 4
- Param=as.double(ParamCemaNeige), ### parameter set
- NStates=as.integer(NStates), ### number of state variables used for model initialising = 4
- 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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
-
- ##Data_storage
- CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige];
- IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt");
- if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; }
- if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); }
- rm(RESULTS);
- } ###ENDFOR_iLayer
- names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
- } ###ENDIF_RunSnowModule
- if(inherits(RunOptions,"CemaNeige")==FALSE){
- CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL;
- CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; }
-
-
-
- ##MODEL______________________________________________________________________________________##
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR));
- } else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); }
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * ParamMod[1] ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * ParamMod[3] ### routing store level (mm)
- RunOptions$IniStates[3] <- RunOptions$IniResLevels[3] ### exponential store level (mm)
+ ## Data storage
+ CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
+ IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
+ if (iLayer == 1) {
+ CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- ##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$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=NParamMod, ### number of model parameter
- Param=ParamMod, ### parameter set
- NStates=NStatesMod, ### number of state variables used for model initialising
- StateStart=RunOptions$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
- ##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
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- idNStates <- seq_len(NStates*NLayers) %% NStates
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR6J, InputsModel = InputsModel, IsHyst = IsHyst,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = RESULTS$StateEnd[3L],
- UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
- eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
- GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
- GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
- verbose = FALSE)
+ if (iLayer >1 ) {
+ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
-
- if(inherits(RunOptions,"CemaNeige")==TRUE & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if(ExportDatesR==TRUE & ExportStateEnd==TRUE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(CemaNeigeLayers),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","daily","GR","CemaNeige");
- if(IsHyst) {
- class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ if (ExportStateEnd) {
+ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd)
}
- return(OutputsModel);
-
+ rm(RESULTS)
+ } ### ENDFOR iLayer
+ names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
+ } ### ENDIF RunSnowModule
+ if (!inherits(RunOptions, "CemaNeige")) {
+ CemaNeigeLayers <- list()
+ CemaNeigeStateEnd <- NULL
+ NameCemaNeigeLayers <- NULL
+ CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
+ }
+
+
+
+ ## GR model______________________________________________________________________________________
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
+ } else {
+ IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * ParamMod[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * ParamMod[3] ### routing store level (mm)
+ RunOptions$IniStates[3] <- RunOptions$IniResLevels[3] ### exponential store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr6j", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = CatchMeltAndPliq, ### input series of total precipitation [mm/d]
+ InputsPE = InputsModel$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
+ StateStart = RunOptions$IniStates[1:NStatesMod], ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputsMod)), ### number of output series
+ IndOutputs = IndOutputsMod, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries,ncol = length(IndOutputsMod)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), NStatesMod) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ## remove negative values except for the ExpStore location
+ idNStates <- seq_len(NStates*NLayers) %% NStates
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_CemaNeigeGR6J, InputsModel = InputsModel, IsHyst = IsHyst,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = RESULTS$StateEnd[3L],
+ UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 1]],
+ eTGCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 2]],
+ GthrCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 3]],
+ GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
+ verbose = FALSE)
+ }
+
+ if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
+ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod] == "Precip")] <- InputsModel$Precip[IndPeriod1]
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR== FALSE & !ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## DatesR and OutputsModel only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if (ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(CemaNeigeLayers),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR", "CemaNeige")
+ if (IsHyst) {
+ class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
+ }
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR1A.R b/R/RunModel_GR1A.R
index 432a1eaa9e22c1a51ef9c97faffd7e82298c6730..58bca283713067eb4ebc0547671b0fc61303b790 100644
--- a/R/RunModel_GR1A.R
+++ b/R/RunModel_GR1A.R
@@ -1,10 +1,12 @@
RunModel_GR1A <- function(InputsModel, RunOptions, Param) {
+
+ ## Initialization of variables
NParam <- 1
FortranOutputs <- .FortranOutputs(GR = "GR1A")$GR
- ## Arguments_check
+ ## Arguments check
if (!inherits(InputsModel, "InputsModel")) {
stop("'InputsModel' must be of class 'InputsModel'")
}
@@ -48,8 +50,8 @@ RunModel_GR1A <- function(InputsModel, RunOptions, Param) {
ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
- ## Call_fortan
- RESULTS <- .Fortran("frun_gr1a", PACKAGE = "airGR",
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr1a", PACKAGE = "airGR",
## inputs
LInputs = LInputSeries, ### length of input and output series
InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/y]
@@ -61,11 +63,11 @@ RunModel_GR1A <- function(InputsModel, RunOptions, Param) {
NOutputs = as.integer(length(IndOutputs)), ### number of output series
IndOutputs = IndOutputs, ### indices of output series
## outputs
- Outputs = matrix(as.double(-999.999), nrow = LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol=length(IndOutputs)), ### output series [mm]
StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### 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
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
## Output data preparation
@@ -76,20 +78,20 @@ RunModel_GR1A <- function(InputsModel, RunOptions, Param) {
}
## DatesR and OutputsModel only
if (ExportDatesR & !ExportStateEnd) {
- OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
}
## OutputsModel and SateEnd only
if (!ExportDatesR & ExportStateEnd) {
- OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
list(RESULTS$StateEnd))
names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
}
## DatesR and OutputsModel and SateEnd
if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
- OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
list(RESULTS$StateEnd))
names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
}
diff --git a/R/RunModel_GR2M.R b/R/RunModel_GR2M.R
index 59c3e9d414e0692c91384e676e3f0671c1cce20b..385c5f1a798de5ea4ac460fd3fb0d516c7c6430b 100644
--- a/R/RunModel_GR2M.R
+++ b/R/RunModel_GR2M.R
@@ -1,98 +1,124 @@
-RunModel_GR2M <- function(InputsModel,RunOptions,Param){
-
- NParam <- 2;
- FortranOutputs <- .FortranOutputs(GR = "GR2M")$GR
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"monthly" )==FALSE){ stop("'InputsModel' must be of class 'monthly' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X2_threshold <- 1e-2
- if (Param[1L] < Param_X1X2_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X2_threshold, Param_X1X2_threshold))
- Param[1L] <- Param_X1X2_threshold
- }
- if (Param[2L] < Param_X1X2_threshold) {
- warning(sprintf("Param[2] (X2: routing store capacity [mm]) < %.2f\n X2 set to %.2f", Param_X1X2_threshold, Param_X1X2_threshold))
- Param[2L] <- Param_X1X2_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[2]; ### routing store level (mm)
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr2M",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/month]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/month]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
- )
- RESULTS$Outputs [round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR2M, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = NULL, UH2 = NULL,
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","monthly","GR");
- return(OutputsModel);
-
+RunModel_GR2M <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 2
+ FortranOutputs <- .FortranOutputs(GR = "GR2M")$GR
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "monthly" )) {
+ stop("'InputsModel' must be of class 'monthly' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X2_threshold <- 1e-2
+ if (Param[1L] < Param_X1X2_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X2_threshold, Param_X1X2_threshold))
+ Param[1L] <- Param_X1X2_threshold
+ }
+ if (Param[2L] < Param_X1X2_threshold) {
+ warning(sprintf("Param[2] (X2: routing store capacity [mm]) < %.2f\n X2 set to %.2f", Param_X1X2_threshold, Param_X1X2_threshold))
+ Param[2L] <- Param_X1X2_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[2] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr2M", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/month]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/month]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs [round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR2M, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = NULL, UH2 = NULL,
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "monthly", "GR")
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR4H.R b/R/RunModel_GR4H.R
index 71ecde1d427433921c2ef3c5ce42d0fca660303c..47c26ff968cce41eb982f897604c7d4b843d0162 100644
--- a/R/RunModel_GR4H.R
+++ b/R/RunModel_GR4H.R
@@ -1,103 +1,129 @@
-RunModel_GR4H <- function(InputsModel,RunOptions,Param){
-
- NParam <- 4;
- FortranOutputs <- .FortranOutputs(GR = "GR4H")$GR
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"hourly" )==FALSE){ stop("'InputsModel' must be of class 'hourly' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [h]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr4h",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR4H, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = RESULTS$StateEnd[(1:(20*24))+7], UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","hourly","GR");
- return(OutputsModel);
-
+RunModel_GR4H <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 4
+ FortranOutputs <- .FortranOutputs(GR = "GR4H")$GR
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "hourly" )) {
+ stop("'InputsModel' must be of class 'hourly' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [h]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr4h", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### 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
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR4H, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = RESULTS$StateEnd[(1:(20*24))+7], UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "hourly", "GR")
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR4J.R b/R/RunModel_GR4J.R
index 8d383a18a17e16f0ee3aac77e952ebc96727b47f..fc647035051dc0f05fb741f0f43ae1f1945ded08 100644
--- a/R/RunModel_GR4J.R
+++ b/R/RunModel_GR4J.R
@@ -1,102 +1,128 @@
-RunModel_GR4J <- function(InputsModel,RunOptions,Param){
-
- NParam <- 4;
- FortranOutputs <- .FortranOutputs(GR = "GR4J")$GR
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"daily" )==FALSE){ stop("'InputsModel' must be of class 'daily' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
- ##Input_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr4j",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR4J, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_StateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_StateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","daily","GR");
- return(OutputsModel);
-
+RunModel_GR4J <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 4
+ FortranOutputs <- .FortranOutputs(GR = "GR4J")$GR
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily" )) {
+ stop("'InputsModel' must be of class 'daily' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+ ## Input data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr4j", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### 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
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR4J, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and StateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and StateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR")
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR5H.R b/R/RunModel_GR5H.R
index a36613d6aad5038fe134199a4a36fe85df3e382f..590a103291d3ea8e99f26681cd3eb1774ef05edb 100644
--- a/R/RunModel_GR5H.R
+++ b/R/RunModel_GR5H.R
@@ -1,117 +1,142 @@
-RunModel_GR5H <- function(InputsModel,RunOptions,Param){
-
- NParam <- 5;
- FortranOutputs <- .FortranOutputs(GR = "GR5H")$GR
- IsIntStore <- inherits(RunOptions, "interception")
- if(IsIntStore) {
- Imax <- RunOptions$Imax
- } else {
- Imax <- -99
+RunModel_GR5H <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 5
+ FortranOutputs <- .FortranOutputs(GR = "GR5H")$GR
+ IsIntStore <- inherits(RunOptions, "interception")
+ if (IsIntStore) {
+ Imax <- RunOptions$Imax
+ } else {
+ Imax <- -99
+ }
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "hourly" )) {
+ stop("'InputsModel' must be of class 'hourly' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [h]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) { IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3] ### routing store level (mm)
+ if (IsIntStore) {
+ RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax ### interception store level (mm)
}
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"hourly" )==FALSE){ stop("'InputsModel' must be of class 'hourly' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [h]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- if(IsIntStore) {
- RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax; ### interception store level (mm)
- }
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr5h",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- Imax=Imax, ### maximal capacity of interception store
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm or mm/h]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### 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;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR5H, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- IntStore = RESULTS$StateEnd[4L],
- UH1 = NULL, UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_StateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_StateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","hourly","GR");
- if(IsIntStore) {
- class(OutputsModel) <- c(class(OutputsModel), "interception")
- }
- return(OutputsModel);
-
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr5h", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ Imax = Imax, ### maximal capacity of interception store
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm or mm/h]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### 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
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR5H, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ IntStore = RESULTS$StateEnd[4L],
+ UH1 = NULL, UH2 = RESULTS$StateEnd[(1:(40*24))+(7+20*24)],
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and StateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and StateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "hourly", "GR")
+ if (IsIntStore) {
+ class(OutputsModel) <- c(class(OutputsModel), "interception")
+ }
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR5J.R b/R/RunModel_GR5J.R
index 56e750ae73aef1affd9762460837d445f3dc1b5a..33210729deffa802b0e51732e0659e27ee7802be 100644
--- a/R/RunModel_GR5J.R
+++ b/R/RunModel_GR5J.R
@@ -1,103 +1,129 @@
-RunModel_GR5J <- function(InputsModel,RunOptions,Param){
-
- NParam <- 5;
- FortranOutputs <- .FortranOutputs(GR = "GR5J")$GR
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"daily" )==FALSE){ stop("'InputsModel' must be of class 'daily' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[1L] <- Param_X1X3_threshold
- }
- if (Param[3L] < Param_X1X3_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
- Param[3L] <- Param_X1X3_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr5j",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR5J, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
- UH1 = NULL, UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","daily","GR");
- return(OutputsModel);
-
+RunModel_GR5J <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 5
+ FortranOutputs <- .FortranOutputs(GR = "GR5J")$GR
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily" )) {
+ stop("'InputsModel' must be of class 'daily' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[1L] <- Param_X1X3_threshold
+ }
+ if (Param[3L] < Param_X1X3_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3_threshold, Param_X1X3_threshold))
+ Param[3L] <- Param_X1X3_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3] ### routing store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr5j", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR5J, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = NULL,
+ UH1 = NULL, UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR")
+ return(OutputsModel)
+
}
diff --git a/R/RunModel_GR6J.R b/R/RunModel_GR6J.R
index 15bd28423f7efa46e2962b9aa47dea9fddce0813..c971056fbd21f4fd423a0b98abe0065d62c5090b 100644
--- a/R/RunModel_GR6J.R
+++ b/R/RunModel_GR6J.R
@@ -1,109 +1,134 @@
-RunModel_GR6J <- function(InputsModel,RunOptions,Param){
-
- NParam <- 6;
- FortranOutputs <- .FortranOutputs(GR = "GR6J")$GR
-
- ##Arguments_check
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("'InputsModel' must be of class 'InputsModel'") }
- if(inherits(InputsModel,"daily" )==FALSE){ stop("'InputsModel' must be of class 'daily' ") }
- if(inherits(InputsModel,"GR" )==FALSE){ stop("'InputsModel' must be of class 'GR' ") }
- if(inherits(RunOptions,"RunOptions" )==FALSE){ stop("'RunOptions' must be of class 'RunOptions' ") }
- if(inherits(RunOptions,"GR" )==FALSE){ stop("'RunOptions' must be of class 'GR' ") }
- if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") }
- if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) }
- Param <- as.double(Param);
-
- Param_X1X3X6_threshold <- 1e-2
- Param_X4_threshold <- 0.5
- if (Param[1L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[1L] <- Param_X1X3X6_threshold
- }
- if (Param[3L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[3L] <- Param_X1X3X6_threshold
- }
- if (Param[4L] < Param_X4_threshold) {
- warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
- Param[4L] <- Param_X4_threshold
- }
- if (Param[6L] < Param_X1X3X6_threshold) {
- warning(sprintf("Param[6] (X6: coefficient for emptying exponential store [mm]) < %.2f\n X6 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
- Param[6L] <- Param_X1X3X6_threshold
- }
-
- ##Input_data_preparation
- if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; }
- IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run);
- LInputSeries <- as.integer(length(IndPeriod1))
- if("all" %in% RunOptions$Outputs_Sim){ IndOutputs <- as.integer(1:length(FortranOutputs));
- } else { IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim); }
-
- ##Output_data_preparation
- IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries;
- ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
- ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
-
- ##Use_of_IniResLevels
- if(!is.null(RunOptions$IniResLevels)){
- RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm)
- RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm)
- RunOptions$IniStates[3] <- RunOptions$IniResLevels[3] ### exponential store level (mm)
- }
-
- ##Call_fortan
- RESULTS <- .Fortran("frun_gr6j",PACKAGE="airGR",
- ##inputs
- LInputs=LInputSeries, ### length of input and output series
- InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
- InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
- NParam=as.integer(length(Param)), ### number of model parameter
- Param=Param, ### parameter set
- NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
- StateStart=RunOptions$IniStates, ### state variables used when the model run starts
- NOutputs=as.integer(length(IndOutputs)), ### number of output series
- IndOutputs=IndOutputs, ### indices of output series
- ##outputs
- Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputs)), ### output series [mm]
- StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run
- )
- RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA;
- RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA;
- if (ExportStateEnd) {
- RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
- RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR6J, InputsModel = InputsModel,
- ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = RESULTS$StateEnd[3L],
- UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
- GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
- verbose = FALSE)
- }
-
- ##Output_data_preparation
- ##OutputsModel_only
- if(ExportDatesR==FALSE & ExportStateEnd==FALSE){
- OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]);
- names(OutputsModel) <- FortranOutputs[IndOutputs]; }
- ##DatesR_and_OutputsModel_only
- if(ExportDatesR==TRUE & ExportStateEnd==FALSE){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs]); }
- ##OutputsModel_and_SateEnd_only
- if(ExportDatesR==FALSE & ExportStateEnd==TRUE){
- OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c(FortranOutputs[IndOutputs],"StateEnd"); }
- ##DatesR_and_OutputsModel_and_SateEnd
- if((ExportDatesR==TRUE & ExportStateEnd==TRUE) | "all" %in% RunOptions$Outputs_Sim){
- OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]),
- list(RESULTS$StateEnd) );
- names(OutputsModel) <- c("DatesR",FortranOutputs[IndOutputs],"StateEnd"); }
-
- ##End
- rm(RESULTS);
- class(OutputsModel) <- c("OutputsModel","daily","GR");
- return(OutputsModel);
-
+RunModel_GR6J <- function(InputsModel, RunOptions, Param) {
+
+
+ ## Initialization of variables
+ NParam <- 6
+ FortranOutputs <- .FortranOutputs(GR = "GR6J")$GR
+
+
+ ## Arguments check
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("'InputsModel' must be of class 'InputsModel'")
+ }
+ if (!inherits(InputsModel, "daily" )) {
+ stop("'InputsModel' must be of class 'daily' ")
+ }
+ if (!inherits(InputsModel, "GR" )) {
+ stop("'InputsModel' must be of class 'GR' ")
+ }
+ if (!inherits(RunOptions, "RunOptions" )) {
+ stop("'RunOptions' must be of class 'RunOptions' ")
+ }
+ if (!inherits(RunOptions, "GR" )) {
+ stop("'RunOptions' must be of class 'GR' ")
+ }
+ if (!is.vector(Param) | !is.numeric(Param)) {
+ stop("'Param' must be a numeric vector")
+ }
+ if (sum(!is.na(Param)) != NParam) {
+ stop(paste("'Param' must be a vector of length ", NParam, " and contain no NA", sep = ""))
+ }
+ Param <- as.double(Param)
+
+ Param_X1X3X6_threshold <- 1e-2
+ Param_X4_threshold <- 0.5
+ if (Param[1L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[1] (X1: production store capacity [mm]) < %.2f\n X1 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[1L] <- Param_X1X3X6_threshold
+ }
+ if (Param[3L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[3] (X3: routing store capacity [mm]) < %.2f\n X3 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[3L] <- Param_X1X3X6_threshold
+ }
+ if (Param[4L] < Param_X4_threshold) {
+ warning(sprintf("Param[4] (X4: unit hydrograph time constant [d]) < %.2f\n X4 set to %.2f", Param_X4_threshold, Param_X4_threshold))
+ Param[4L] <- Param_X4_threshold
+ }
+ if (Param[6L] < Param_X1X3X6_threshold) {
+ warning(sprintf("Param[6] (X6: coefficient for emptying exponential store [mm]) < %.2f\n X6 set to %.2f", Param_X1X3X6_threshold, Param_X1X3X6_threshold))
+ Param[6L] <- Param_X1X3X6_threshold
+ }
+
+ ## Input data preparation
+ if (identical(RunOptions$IndPeriod_WarmUp, 0L)) {
+ RunOptions$IndPeriod_WarmUp <- NULL
+ }
+ IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
+ LInputSeries <- as.integer(length(IndPeriod1))
+ if ("all" %in% RunOptions$Outputs_Sim) {
+ IndOutputs <- as.integer(1:length(FortranOutputs))
+ } else {
+ IndOutputs <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
+ }
+
+ ## Output data preparation
+ IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
+ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
+ ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
+
+ ## Use of IniResLevels
+ if (!is.null(RunOptions$IniResLevels)) {
+ RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1] ### production store level (mm)
+ RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3] ### routing store level (mm)
+ RunOptions$IniStates[3] <- RunOptions$IniResLevels[3] ### exponential store level (mm)
+ }
+
+ ## Call GR model Fortan
+ RESULTS <- .Fortran("frun_gr6j", PACKAGE = "airGR",
+ ## inputs
+ LInputs = LInputSeries, ### length of input and output series
+ InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/d]
+ InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/d]
+ NParam = as.integer(length(Param)), ### number of model parameter
+ Param = Param, ### parameter set
+ NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
+ StateStart = RunOptions$IniStates, ### state variables used when the model run starts
+ NOutputs = as.integer(length(IndOutputs)), ### number of output series
+ IndOutputs = IndOutputs, ### indices of output series
+ ## outputs
+ Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputs)), ### output series [mm]
+ StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### state variables at the end of the model run
+ )
+ RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
+ RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
+ if (ExportStateEnd) {
+ RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
+ RESULTS$StateEnd <- CreateIniStates(FUN_MOD = RunModel_GR6J, InputsModel = InputsModel,
+ ProdStore = RESULTS$StateEnd[1L], RoutStore = RESULTS$StateEnd[2L], ExpStore = RESULTS$StateEnd[3L],
+ UH1 = RESULTS$StateEnd[(1:20)+7], UH2 = RESULTS$StateEnd[(1:40)+(7+20)],
+ GCemaNeigeLayers = NULL, eTGCemaNeigeLayers = NULL,
+ verbose = FALSE)
+ }
+
+ ## Output data preparation
+ ## OutputsModel only
+ if (!ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
+ names(OutputsModel) <- FortranOutputs[IndOutputs]
+ }
+ ## DatesR and OutputsModel only
+ if (ExportDatesR & !ExportStateEnd) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs])
+ }
+ ## OutputsModel and SateEnd only
+ if (!ExportDatesR & ExportStateEnd) {
+ OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c(FortranOutputs[IndOutputs], "StateEnd")
+ }
+ ## DatesR and OutputsModel and SateEnd
+ if ((ExportDatesR & ExportStateEnd) | "all" %in% RunOptions$Outputs_Sim) {
+ OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
+ lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
+ list(RESULTS$StateEnd))
+ names(OutputsModel) <- c("DatesR", FortranOutputs[IndOutputs], "StateEnd")
+ }
+
+ ## End
+ rm(RESULTS)
+ class(OutputsModel) <- c("OutputsModel", "daily", "GR")
+ return(OutputsModel)
+
}
-
\ No newline at end of file