From 1e29cf2c8813187fe461b426ea603b10c603ed86 Mon Sep 17 00:00:00 2001
From: unknown <olivier.delaigue@ANPI1430.antony.irstea.priv>
Date: Thu, 26 Oct 2017 10:17:31 +0200
Subject: [PATCH] v1.0.9.55 minor revision of Param_Sets_GR4J documentation
---
DESCRIPTION | 2 +-
NEWS.rmd | 2 +-
man/Param_Sets_GR4J.Rd | 7 +++----
3 files changed, 5 insertions(+), 6 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 7b68150d..34db3d73 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 c2690415..88c25f8d 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 2998a4fe..3c335d1a 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
--
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