diff --git a/DESCRIPTION b/DESCRIPTION
index 7b68150df9cd5b1d9e9bda463c44089386879517..34db3d73d1780c61f6106a7a2972482316b8f99e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: airGR
 Type: Package
 Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
-Version: 1.0.9.54
+Version: 1.0.9.55
 Date: 2017-10-26
 Authors@R: c(
   person("Laurent", "Coron", role = c("aut", "trl")),
diff --git a/NEWS.rmd b/NEWS.rmd
index c26904158cb416c3314deca160cbd597e973fb2e..88c25f8d08f4998c1f279e04b7710aee0eb81d7f 100644
--- a/NEWS.rmd
+++ b/NEWS.rmd
@@ -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
 
diff --git a/man/Param_Sets_GR4J.Rd b/man/Param_Sets_GR4J.Rd
index 2998a4fe1e191828ec02d276a33c465c2dce259c..3c335d1a0f1380f8fd634f5e497e55c5123b20f9 100644
--- a/man/Param_Sets_GR4J.Rd
+++ b/man/Param_Sets_GR4J.Rd
@@ -20,8 +20,7 @@
 
 \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}}).
-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}.
-3 (please note that the formula is erroneous in the publication). Please, see the example below. \cr
+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
 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
 
 ## short calibration period selection (< 6 months)
 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
 RunOptions_Cal <- CreateRunOptions(FUN_MOD = RunModel_GR4J,
@@ -86,7 +85,7 @@ Param_Best <- unlist(Param_Sets_GR4J[which.max(OutputsCrit_Loop), ])
 ## ---- validation step
 
 ## 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"))
 
 ## preparation of the RunOptions object for the validation period