Commit 1e29cf2c authored by unknown's avatar unknown
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v1.0.9.55 minor revision of Param_Sets_GR4J documentation

parent ead17ece
Package: airGR Package: airGR
Type: Package Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.0.9.54 Version: 1.0.9.55
Date: 2017-10-26 Date: 2017-10-26
Authors@R: c( Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl")), person("Laurent", "Coron", role = c("aut", "trl")),
......
...@@ -14,7 +14,7 @@ output: ...@@ -14,7 +14,7 @@ output:
### 1.0.9.54 Release Notes (2017-10-26) ### 1.0.9.55 Release Notes (2017-10-26)
#### New features #### New features
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...@@ -20,8 +20,7 @@ ...@@ -20,8 +20,7 @@
\description{ \description{
These parameter sets can be used as an alternative for the grid-screening calibration procedure (i.e. first step in \code{\link{Calibration_Michel}}). These parameter sets can be used as an alternative for the grid-screening calibration procedure (i.e. first step in \code{\link{Calibration_Michel}}).
Please note that the given GR4J X4u variable does not correspond to the actual GR4J X4 parameter. As explained in Andréassian et al. (2014; section 2.1), the given GR4J X4u value has to be adjusted (rescaled) using catchment area (S) [km2] as follows: {X4 = X4u / 5.995 * S^0.3}. Please note that the given GR4J X4u variable does not correspond to the actual GR4J X4 parameter. As explained in Andréassian et al. (2014; section 2.1), the given GR4J X4u value has to be adjusted (rescaled) using catchment area (S) [km2] as follows: {X4 = X4u / 5.995 * S^0.3} (please note that the formula is erroneous in the publication). Please, see the example below. \cr
3 (please note that the formula is erroneous in the publication). Please, see the example below. \cr
As shown in Andréassian et al. (2014; figure 4), only using these parameters sets as the tested values for calibration is more efficient than a classical calibration when the amount of data is low (6 months or less). As shown in Andréassian et al. (2014; figure 4), only using these parameters sets as the tested values for calibration is more efficient than a classical calibration when the amount of data is low (6 months or less).
} }
...@@ -61,7 +60,7 @@ InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$Date ...@@ -61,7 +60,7 @@ InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$Date
## short calibration period selection (< 6 months) ## short calibration period selection (< 6 months)
Ind_Cal <- seq(which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/01/1990 00:00"), Ind_Cal <- seq(which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/01/1990 00:00"),
which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/03/1990 00:00")) which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="28/02/1990 00:00"))
## preparation of the RunOptions object for the calibration period ## preparation of the RunOptions object for the calibration period
RunOptions_Cal <- CreateRunOptions(FUN_MOD = RunModel_GR4J, RunOptions_Cal <- CreateRunOptions(FUN_MOD = RunModel_GR4J,
...@@ -86,7 +85,7 @@ Param_Best <- unlist(Param_Sets_GR4J[which.max(OutputsCrit_Loop), ]) ...@@ -86,7 +85,7 @@ Param_Best <- unlist(Param_Sets_GR4J[which.max(OutputsCrit_Loop), ])
## ---- validation step ## ---- validation step
## validation period selection ## validation period selection
Ind_Val <- seq(which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/01/1991 00:00"), Ind_Val <- seq(which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/03/1990 00:00"),
which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="31/12/1999 00:00")) which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="31/12/1999 00:00"))
## preparation of the RunOptions object for the validation period ## preparation of the RunOptions object for the validation period
......
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