diff --git a/DESCRIPTION b/DESCRIPTION
index c1d7a41f7e8d05ce19b31250fc10283c8ea88408..1bcda4c133b40ec93ad45457502470ea38e157da 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
Package: airGR
Type: Package
Title: Suite of GR hydrological models for precipitation-runoff modelling
-Version: 1.0.5.2
+Version: 1.0.5.3
Date: 2017-01-19
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl")),
diff --git a/R/CreateInputsModel.R b/R/CreateInputsModel.R
index f11f160081a4295378fda04e39bcaba27a531f04..a83c0e663192373c9d800ebf20fe7c91556b7b4f 100644
--- a/R/CreateInputsModel.R
+++ b/R/CreateInputsModel.R
@@ -1,4 +1,4 @@
-CreateInputsModel <- function(FUN_MOD,DatesR,Precip,PotEvap=NULL,TempMean=NULL,TempMin=NULL,TempMax=NULL,ZInputs=NULL,HypsoData=NULL,NLayers=5, verbose = TRUE) {
+CreateInputsModel <- function(FUN_MOD, DatesR, Precip, PrecipScale = TRUE, PotEvap = NULL, TempMean = NULL, TempMin = NULL, TempMax = NULL, ZInputs = NULL, HypsoData = NULL, NLayers = 5, verbose = TRUE) {
ObjectClass <- NULL
@@ -126,7 +126,7 @@ CreateInputsModel <- function(FUN_MOD,DatesR,Precip,PotEvap=NULL,TempMean=NULL,T
##DataAltiExtrapolation_Valery
if("CemaNeige" %in% ObjectClass) {
- RESULT <- DataAltiExtrapolation_Valery(DatesR=DatesR,Precip=Precip,TempMean=TempMean,TempMin=TempMin,TempMax=TempMax,ZInputs=ZInputs,HypsoData=HypsoData,NLayers=NLayers, verbose = verbose);
+ RESULT <- DataAltiExtrapolation_Valery(DatesR = DatesR, Precip = Precip, PrecipScale = PrecipScale, TempMean = TempMean, TempMin = TempMin, TempMax = TempMax, ZInputs = ZInputs, HypsoData = HypsoData, NLayers = NLayers, verbose = verbose)
if(verbose) {
if(NLayers == 1) {
message("\t Input series were successfully created on 1 elevation layer for use by CemaNeige")
diff --git a/R/DataAltiExtrapolation_Valery.R b/R/DataAltiExtrapolation_Valery.R
index ff079ab23804344b5027af2704ffd2118a360d6a..fce85cb8128820e9bb903f6fab695728a26ff5f5 100644
--- a/R/DataAltiExtrapolation_Valery.R
+++ b/R/DataAltiExtrapolation_Valery.R
@@ -1,495 +1,503 @@
-DataAltiExtrapolation_Valery <- function(DatesR,Precip,TempMean,TempMin=NULL,TempMax=NULL,ZInputs,HypsoData,NLayers, verbose = TRUE){
-
-
- ##Altitudinal_gradient_functions_______________________________________________________________
- ##unique_gradient_for_precipitation
- GradP_Valery2010 <- function(){
- return(0.00041); ### value from Val? PhD thesis page 126
- }
- ##daily_gradients_for_mean_min_and_max_air_temperature
- GradT_Valery2010 <- function(){
- RESULT <- matrix(c(
- 1, 1, 0.434, 0.366, 0.498,
- 2, 1, 0.434, 0.366, 0.500,
- 3, 1, 0.435, 0.367, 0.501,
- 4, 1, 0.436, 0.367, 0.503,
- 5, 1, 0.437, 0.367, 0.504,
- 6, 1, 0.439, 0.367, 0.506,
- 7, 1, 0.440, 0.367, 0.508,
- 8, 1, 0.441, 0.368, 0.510,
- 9, 1, 0.442, 0.368, 0.512,
- 10, 1, 0.444, 0.368, 0.514,
- 11, 1, 0.445, 0.368, 0.517,
- 12, 1, 0.446, 0.368, 0.519,
- 13, 1, 0.448, 0.369, 0.522,
- 14, 1, 0.450, 0.369, 0.525,
- 15, 1, 0.451, 0.369, 0.527,
- 16, 1, 0.453, 0.370, 0.530,
- 17, 1, 0.455, 0.370, 0.533,
- 18, 1, 0.456, 0.370, 0.537,
- 19, 1, 0.458, 0.371, 0.540,
- 20, 1, 0.460, 0.371, 0.543,
- 21, 1, 0.462, 0.371, 0.547,
- 22, 1, 0.464, 0.372, 0.550,
- 23, 1, 0.466, 0.372, 0.554,
- 24, 1, 0.468, 0.373, 0.558,
- 25, 1, 0.470, 0.373, 0.561,
- 26, 1, 0.472, 0.374, 0.565,
- 27, 1, 0.474, 0.374, 0.569,
- 28, 1, 0.476, 0.375, 0.573,
- 29, 1, 0.478, 0.375, 0.577,
- 30, 1, 0.480, 0.376, 0.582,
- 31, 1, 0.483, 0.376, 0.586,
- 1, 2, 0.485, 0.377, 0.590,
- 2, 2, 0.487, 0.377, 0.594,
- 3, 2, 0.489, 0.378, 0.599,
- 4, 2, 0.492, 0.379, 0.603,
- 5, 2, 0.494, 0.379, 0.607,
- 6, 2, 0.496, 0.380, 0.612,
- 7, 2, 0.498, 0.381, 0.616,
- 8, 2, 0.501, 0.381, 0.621,
- 9, 2, 0.503, 0.382, 0.625,
- 10, 2, 0.505, 0.383, 0.630,
- 11, 2, 0.508, 0.384, 0.634,
- 12, 2, 0.510, 0.384, 0.639,
- 13, 2, 0.512, 0.385, 0.643,
- 14, 2, 0.515, 0.386, 0.648,
- 15, 2, 0.517, 0.387, 0.652,
- 16, 2, 0.519, 0.387, 0.657,
- 17, 2, 0.522, 0.388, 0.661,
- 18, 2, 0.524, 0.389, 0.666,
- 19, 2, 0.526, 0.390, 0.670,
- 20, 2, 0.528, 0.391, 0.674,
- 21, 2, 0.530, 0.392, 0.679,
- 22, 2, 0.533, 0.393, 0.683,
- 23, 2, 0.535, 0.393, 0.687,
- 24, 2, 0.537, 0.394, 0.691,
- 25, 2, 0.539, 0.395, 0.695,
- 26, 2, 0.541, 0.396, 0.699,
- 27, 2, 0.543, 0.397, 0.703,
- 28, 2, 0.545, 0.398, 0.707,
- 29, 2, 0.546, 0.399, 0.709,
- 1, 3, 0.547, 0.399, 0.711,
- 2, 3, 0.549, 0.400, 0.715,
- 3, 3, 0.551, 0.401, 0.718,
- 4, 3, 0.553, 0.402, 0.722,
- 5, 3, 0.555, 0.403, 0.726,
- 6, 3, 0.557, 0.404, 0.729,
- 7, 3, 0.559, 0.405, 0.732,
- 8, 3, 0.560, 0.406, 0.736,
- 9, 3, 0.562, 0.406, 0.739,
- 10, 3, 0.564, 0.407, 0.742,
- 11, 3, 0.566, 0.408, 0.745,
- 12, 3, 0.567, 0.409, 0.748,
- 13, 3, 0.569, 0.410, 0.750,
- 14, 3, 0.570, 0.411, 0.753,
- 15, 3, 0.572, 0.412, 0.756,
- 16, 3, 0.573, 0.413, 0.758,
- 17, 3, 0.575, 0.414, 0.761,
- 18, 3, 0.576, 0.415, 0.763,
- 19, 3, 0.577, 0.416, 0.765,
- 20, 3, 0.579, 0.417, 0.767,
- 21, 3, 0.580, 0.417, 0.769,
- 22, 3, 0.581, 0.418, 0.771,
- 23, 3, 0.582, 0.419, 0.773,
- 24, 3, 0.583, 0.420, 0.774,
- 25, 3, 0.584, 0.421, 0.776,
- 26, 3, 0.585, 0.422, 0.777,
- 27, 3, 0.586, 0.422, 0.779,
- 28, 3, 0.587, 0.423, 0.780,
- 29, 3, 0.588, 0.424, 0.781,
- 30, 3, 0.589, 0.425, 0.782,
- 31, 3, 0.590, 0.425, 0.783,
- 1, 4, 0.591, 0.426, 0.784,
- 2, 4, 0.591, 0.427, 0.785,
- 3, 4, 0.592, 0.427, 0.785,
- 4, 4, 0.593, 0.428, 0.786,
- 5, 4, 0.593, 0.429, 0.787,
- 6, 4, 0.594, 0.429, 0.787,
- 7, 4, 0.595, 0.430, 0.787,
- 8, 4, 0.595, 0.431, 0.788,
- 9, 4, 0.596, 0.431, 0.788,
- 10, 4, 0.596, 0.432, 0.788,
- 11, 4, 0.597, 0.432, 0.788,
- 12, 4, 0.597, 0.433, 0.788,
- 13, 4, 0.597, 0.433, 0.788,
- 14, 4, 0.598, 0.434, 0.788,
- 15, 4, 0.598, 0.434, 0.788,
- 16, 4, 0.598, 0.435, 0.787,
- 17, 4, 0.599, 0.435, 0.787,
- 18, 4, 0.599, 0.436, 0.787,
- 19, 4, 0.599, 0.436, 0.786,
- 20, 4, 0.599, 0.436, 0.786,
- 21, 4, 0.600, 0.437, 0.785,
- 22, 4, 0.600, 0.437, 0.785,
- 23, 4, 0.600, 0.437, 0.784,
- 24, 4, 0.600, 0.438, 0.784,
- 25, 4, 0.600, 0.438, 0.783,
- 26, 4, 0.601, 0.438, 0.783,
- 27, 4, 0.601, 0.438, 0.782,
- 28, 4, 0.601, 0.439, 0.781,
- 29, 4, 0.601, 0.439, 0.781,
- 30, 4, 0.601, 0.439, 0.780,
- 1, 5, 0.601, 0.439, 0.779,
- 2, 5, 0.601, 0.439, 0.778,
- 3, 5, 0.601, 0.439, 0.778,
- 4, 5, 0.601, 0.440, 0.777,
- 5, 5, 0.601, 0.440, 0.776,
- 6, 5, 0.601, 0.440, 0.775,
- 7, 5, 0.601, 0.440, 0.775,
- 8, 5, 0.601, 0.440, 0.774,
- 9, 5, 0.601, 0.440, 0.773,
- 10, 5, 0.602, 0.440, 0.772,
- 11, 5, 0.602, 0.440, 0.772,
- 12, 5, 0.602, 0.440, 0.771,
- 13, 5, 0.602, 0.440, 0.770,
- 14, 5, 0.602, 0.440, 0.770,
- 15, 5, 0.602, 0.440, 0.769,
- 16, 5, 0.602, 0.440, 0.768,
- 17, 5, 0.602, 0.440, 0.768,
- 18, 5, 0.602, 0.440, 0.767,
- 19, 5, 0.602, 0.440, 0.767,
- 20, 5, 0.602, 0.440, 0.766,
- 21, 5, 0.602, 0.440, 0.766,
- 22, 5, 0.602, 0.440, 0.765,
- 23, 5, 0.602, 0.440, 0.765,
- 24, 5, 0.602, 0.440, 0.764,
- 25, 5, 0.602, 0.440, 0.764,
- 26, 5, 0.602, 0.440, 0.764,
- 27, 5, 0.602, 0.439, 0.763,
- 28, 5, 0.602, 0.439, 0.763,
- 29, 5, 0.602, 0.439, 0.763,
- 30, 5, 0.602, 0.439, 0.762,
- 31, 5, 0.602, 0.439, 0.762,
- 1, 6, 0.602, 0.439, 0.762,
- 2, 6, 0.602, 0.439, 0.762,
- 3, 6, 0.602, 0.439, 0.762,
- 4, 6, 0.602, 0.439, 0.762,
- 5, 6, 0.602, 0.439, 0.762,
- 6, 6, 0.602, 0.438, 0.761,
- 7, 6, 0.602, 0.438, 0.761,
- 8, 6, 0.602, 0.438, 0.761,
- 9, 6, 0.602, 0.438, 0.761,
- 10, 6, 0.602, 0.438, 0.761,
- 11, 6, 0.602, 0.438, 0.762,
- 12, 6, 0.602, 0.438, 0.762,
- 13, 6, 0.602, 0.438, 0.762,
- 14, 6, 0.602, 0.438, 0.762,
- 15, 6, 0.602, 0.437, 0.762,
- 16, 6, 0.602, 0.437, 0.762,
- 17, 6, 0.602, 0.437, 0.762,
- 18, 6, 0.602, 0.437, 0.762,
- 19, 6, 0.602, 0.437, 0.763,
- 20, 6, 0.602, 0.437, 0.763,
- 21, 6, 0.602, 0.437, 0.763,
- 22, 6, 0.602, 0.436, 0.763,
- 23, 6, 0.602, 0.436, 0.763,
- 24, 6, 0.602, 0.436, 0.764,
- 25, 6, 0.602, 0.436, 0.764,
- 26, 6, 0.601, 0.436, 0.764,
- 27, 6, 0.601, 0.436, 0.764,
- 28, 6, 0.601, 0.436, 0.764,
- 29, 6, 0.601, 0.435, 0.765,
- 30, 6, 0.601, 0.435, 0.765,
- 1, 7, 0.601, 0.435, 0.765,
- 2, 7, 0.600, 0.435, 0.765,
- 3, 7, 0.600, 0.435, 0.765,
- 4, 7, 0.600, 0.434, 0.766,
- 5, 7, 0.600, 0.434, 0.766,
- 6, 7, 0.599, 0.434, 0.766,
- 7, 7, 0.599, 0.434, 0.766,
- 8, 7, 0.599, 0.434, 0.766,
- 9, 7, 0.598, 0.433, 0.766,
- 10, 7, 0.598, 0.433, 0.766,
- 11, 7, 0.598, 0.433, 0.766,
- 12, 7, 0.597, 0.433, 0.766,
- 13, 7, 0.597, 0.432, 0.767,
- 14, 7, 0.597, 0.432, 0.767,
- 15, 7, 0.596, 0.432, 0.767,
- 16, 7, 0.596, 0.432, 0.766,
- 17, 7, 0.595, 0.431, 0.766,
- 18, 7, 0.595, 0.431, 0.766,
- 19, 7, 0.594, 0.431, 0.766,
- 20, 7, 0.594, 0.430, 0.766,
- 21, 7, 0.593, 0.430, 0.766,
- 22, 7, 0.593, 0.430, 0.766,
- 23, 7, 0.592, 0.429, 0.765,
- 24, 7, 0.592, 0.429, 0.765,
- 25, 7, 0.591, 0.428, 0.765,
- 26, 7, 0.590, 0.428, 0.765,
- 27, 7, 0.590, 0.428, 0.764,
- 28, 7, 0.589, 0.427, 0.764,
- 29, 7, 0.588, 0.427, 0.764,
- 30, 7, 0.588, 0.426, 0.763,
- 31, 7, 0.587, 0.426, 0.763,
- 1, 8, 0.586, 0.425, 0.762,
- 2, 8, 0.586, 0.425, 0.762,
- 3, 8, 0.585, 0.424, 0.761,
- 4, 8, 0.584, 0.424, 0.761,
- 5, 8, 0.583, 0.423, 0.760,
- 6, 8, 0.583, 0.423, 0.760,
- 7, 8, 0.582, 0.422, 0.759,
- 8, 8, 0.581, 0.421, 0.758,
- 9, 8, 0.580, 0.421, 0.758,
- 10, 8, 0.579, 0.420, 0.757,
- 11, 8, 0.578, 0.420, 0.756,
- 12, 8, 0.578, 0.419, 0.755,
- 13, 8, 0.577, 0.418, 0.754,
- 14, 8, 0.576, 0.418, 0.754,
- 15, 8, 0.575, 0.417, 0.753,
- 16, 8, 0.574, 0.416, 0.752,
- 17, 8, 0.573, 0.415, 0.751,
- 18, 8, 0.572, 0.415, 0.750,
- 19, 8, 0.571, 0.414, 0.749,
- 20, 8, 0.570, 0.413, 0.748,
- 21, 8, 0.569, 0.413, 0.747,
- 22, 8, 0.569, 0.412, 0.746,
- 23, 8, 0.568, 0.411, 0.745,
- 24, 8, 0.567, 0.410, 0.744,
- 25, 8, 0.566, 0.409, 0.743,
- 26, 8, 0.565, 0.409, 0.742,
- 27, 8, 0.564, 0.408, 0.741,
- 28, 8, 0.563, 0.407, 0.740,
- 29, 8, 0.562, 0.406, 0.738,
- 30, 8, 0.561, 0.405, 0.737,
- 31, 8, 0.560, 0.405, 0.736,
- 1, 9, 0.558, 0.404, 0.735,
- 2, 9, 0.557, 0.403, 0.734,
- 3, 9, 0.556, 0.402, 0.732,
- 4, 9, 0.555, 0.401, 0.731,
- 5, 9, 0.554, 0.401, 0.730,
- 6, 9, 0.553, 0.400, 0.728,
- 7, 9, 0.552, 0.399, 0.727,
- 8, 9, 0.551, 0.398, 0.725,
- 9, 9, 0.550, 0.397, 0.724,
- 10, 9, 0.549, 0.396, 0.723,
- 11, 9, 0.548, 0.396, 0.721,
- 12, 9, 0.546, 0.395, 0.720,
- 13, 9, 0.545, 0.394, 0.718,
- 14, 9, 0.544, 0.393, 0.717,
- 15, 9, 0.543, 0.392, 0.715,
- 16, 9, 0.542, 0.391, 0.713,
- 17, 9, 0.541, 0.391, 0.712,
- 18, 9, 0.540, 0.390, 0.710,
- 19, 9, 0.538, 0.389, 0.709,
- 20, 9, 0.537, 0.388, 0.707,
- 21, 9, 0.536, 0.388, 0.705,
- 22, 9, 0.535, 0.387, 0.703,
- 23, 9, 0.533, 0.386, 0.702,
- 24, 9, 0.532, 0.385, 0.700,
- 25, 9, 0.531, 0.385, 0.698,
- 26, 9, 0.530, 0.384, 0.696,
- 27, 9, 0.528, 0.383, 0.694,
- 28, 9, 0.527, 0.383, 0.692,
- 29, 9, 0.526, 0.382, 0.690,
- 30, 9, 0.525, 0.381, 0.688,
- 1, 10, 0.523, 0.381, 0.686,
- 2, 10, 0.522, 0.380, 0.684,
- 3, 10, 0.521, 0.379, 0.682,
- 4, 10, 0.519, 0.379, 0.680,
- 5, 10, 0.518, 0.378, 0.678,
- 6, 10, 0.517, 0.377, 0.676,
- 7, 10, 0.515, 0.377, 0.674,
- 8, 10, 0.514, 0.376, 0.671,
- 9, 10, 0.512, 0.376, 0.669,
- 10, 10, 0.511, 0.375, 0.667,
- 11, 10, 0.510, 0.375, 0.664,
- 12, 10, 0.508, 0.374, 0.662,
- 13, 10, 0.507, 0.374, 0.659,
- 14, 10, 0.505, 0.373, 0.657,
- 15, 10, 0.504, 0.373, 0.654,
- 16, 10, 0.502, 0.372, 0.652,
- 17, 10, 0.501, 0.372, 0.649,
- 18, 10, 0.499, 0.372, 0.647,
- 19, 10, 0.498, 0.371, 0.644,
- 20, 10, 0.496, 0.371, 0.641,
- 21, 10, 0.495, 0.371, 0.639,
- 22, 10, 0.493, 0.370, 0.636,
- 23, 10, 0.492, 0.370, 0.633,
- 24, 10, 0.490, 0.370, 0.630,
- 25, 10, 0.489, 0.369, 0.628,
- 26, 10, 0.487, 0.369, 0.625,
- 27, 10, 0.485, 0.369, 0.622,
- 28, 10, 0.484, 0.368, 0.619,
- 29, 10, 0.482, 0.368, 0.616,
- 30, 10, 0.481, 0.368, 0.613,
- 31, 10, 0.479, 0.368, 0.610,
- 1, 11, 0.478, 0.368, 0.607,
- 2, 11, 0.476, 0.367, 0.604,
- 3, 11, 0.475, 0.367, 0.601,
- 4, 11, 0.473, 0.367, 0.598,
- 5, 11, 0.471, 0.367, 0.595,
- 6, 11, 0.470, 0.367, 0.592,
- 7, 11, 0.468, 0.367, 0.589,
- 8, 11, 0.467, 0.366, 0.586,
- 9, 11, 0.465, 0.366, 0.583,
- 10, 11, 0.464, 0.366, 0.580,
- 11, 11, 0.462, 0.366, 0.577,
- 12, 11, 0.461, 0.366, 0.574,
- 13, 11, 0.459, 0.366, 0.571,
- 14, 11, 0.458, 0.366, 0.568,
- 15, 11, 0.456, 0.366, 0.565,
- 16, 11, 0.455, 0.366, 0.562,
- 17, 11, 0.454, 0.366, 0.559,
- 18, 11, 0.452, 0.365, 0.556,
- 19, 11, 0.451, 0.365, 0.553,
- 20, 11, 0.450, 0.365, 0.550,
- 21, 11, 0.448, 0.365, 0.547,
- 22, 11, 0.447, 0.365, 0.544,
- 23, 11, 0.446, 0.365, 0.542,
- 24, 11, 0.445, 0.365, 0.539,
- 25, 11, 0.443, 0.365, 0.536,
- 26, 11, 0.442, 0.365, 0.533,
- 27, 11, 0.441, 0.365, 0.531,
- 28, 11, 0.440, 0.365, 0.528,
- 29, 11, 0.439, 0.365, 0.526,
- 30, 11, 0.438, 0.365, 0.523,
- 1, 12, 0.437, 0.365, 0.521,
- 2, 12, 0.436, 0.365, 0.519,
- 3, 12, 0.435, 0.365, 0.517,
- 4, 12, 0.434, 0.365, 0.515,
- 5, 12, 0.434, 0.365, 0.513,
- 6, 12, 0.433, 0.365, 0.511,
- 7, 12, 0.432, 0.365, 0.509,
- 8, 12, 0.431, 0.365, 0.507,
- 9, 12, 0.431, 0.365, 0.505,
- 10, 12, 0.430, 0.365, 0.504,
- 11, 12, 0.430, 0.365, 0.502,
- 12, 12, 0.429, 0.365, 0.501,
- 13, 12, 0.429, 0.365, 0.500,
- 14, 12, 0.429, 0.365, 0.498,
- 15, 12, 0.428, 0.365, 0.497,
- 16, 12, 0.428, 0.365, 0.496,
- 17, 12, 0.428, 0.365, 0.496,
- 18, 12, 0.428, 0.365, 0.495,
- 19, 12, 0.428, 0.365, 0.494,
- 20, 12, 0.428, 0.365, 0.494,
- 21, 12, 0.428, 0.365, 0.494,
- 22, 12, 0.428, 0.365, 0.493,
- 23, 12, 0.429, 0.365, 0.493,
- 24, 12, 0.429, 0.366, 0.493,
- 25, 12, 0.429, 0.366, 0.493,
- 26, 12, 0.430, 0.366, 0.494,
- 27, 12, 0.430, 0.366, 0.494,
- 28, 12, 0.431, 0.366, 0.495,
- 29, 12, 0.431, 0.366, 0.495,
- 30, 12, 0.432, 0.366, 0.496,
- 31, 12, 0.433, 0.366, 0.497),ncol=5,byrow=TRUE);
- dimnames(RESULT) <- list(1:366,c("day","month","grad_Tmean","grad_Tmin","grad_Tmax"));
- return(RESULT);
- }
-
-
-
- ##Format_______________________________________________________________________________________
- HypsoData <- as.double(HypsoData);
- ZInputs <- as.double(ZInputs);
-
-
- ##ElevationLayers_Creation_____________________________________________________________________
- ZLayers <- as.double(rep(NA,NLayers));
- if(!identical(HypsoData,as.double(rep(NA,101)))){
- nmoy <- 100 %/% NLayers;
- nreste <- 100 %% NLayers;
- ncont <- 0;
- for(iLayer in 1:NLayers){
- if(nreste > 0){ nn <- nmoy+1; nreste <- nreste-1; } else { nn <- nmoy; }
- if(nn==1){ ZLayers[iLayer] <- HypsoData[ncont+1]; }
- if(nn==2){ ZLayers[iLayer] <- 0.5 * (HypsoData[ncont+1] + HypsoData[ncont+2]); }
- if(nn>2 ){ ZLayers[iLayer] <- HypsoData[ncont+nn/2]; }
- ncont <- ncont+nn;
- }
- }
+DataAltiExtrapolation_Valery <- function(DatesR, Precip, PrecipScale = TRUE, TempMean, TempMin = NULL, TempMax = NULL, ZInputs, HypsoData, NLayers, verbose = TRUE){
-
- ##Precipitation_extrapolation__________________________________________________________________
- ##Initialisation
- LayerPrecip <- list();
- if(identical(ZInputs,HypsoData[51]) & NLayers==1){
- LayerPrecip[[1]] <- as.double(Precip);
- } else {
- ##Elevation_gradients_for_daily_mean_precipitation
- GradP <- GradP_Valery2010(); ### single value
- TabGradP <- rep(GradP,length(Precip));
- ##Extrapolation
- ##Thresold_of_inputs_median_elevation
- Zthreshold <- 4000;
- ##_On_each_elevation_layer...
- for(iLayer in 1:NLayers){
- ##If_layer_elevation_smaller_than_Zthreshold
- if(ZLayers[iLayer] <= Zthreshold){
- LayerPrecip[[iLayer]] <- as.double(Precip*exp(TabGradP*(ZLayers[iLayer]-ZInputs)));
- ##If_layer_elevation_greater_than_Zthreshold
- } else {
- ##If_inputs_median_elevation_smaller_than_Zthreshold
- if(ZInputs <= Zthreshold){ LayerPrecip[[iLayer]] <- as.double(Precip*exp(TabGradP*(Zthreshold-ZInputs)));
- ##If_inputs_median_elevation_greater_then_Zthreshold
- } else { LayerPrecip[[iLayer]] <- as.double(Precip); }
- }
- }
- }
-
-
-
- ##Temperature_extrapolation____________________________________________________________________
- ##Initialisation
- LayerTempMean <- list(); LayerTempMin <- list(); LayerTempMax <- list();
- if(identical(ZInputs,HypsoData[51]) & NLayers==1) {
- LayerTempMean[[1]] <- as.double(TempMean);
- if(!is.null(TempMin) & !is.null(TempMax)){ LayerTempMin[[1]] <- as.double(TempMin); LayerTempMax[[1]] <- as.double(TempMax); }
+
+ ##Altitudinal_gradient_functions_______________________________________________________________
+ ##unique_gradient_for_precipitation
+ GradP_Valery2010 <- function(){
+ return(0.00041); ### value from Val? PhD thesis page 126
+ }
+ ##daily_gradients_for_mean_min_and_max_air_temperature
+ GradT_Valery2010 <- function(){
+ RESULT <- matrix(c(
+ 01, 01, 0.434, 0.366, 0.498,
+ 02, 01, 0.434, 0.366, 0.500,
+ 03, 01, 0.435, 0.367, 0.501,
+ 04, 01, 0.436, 0.367, 0.503,
+ 05, 01, 0.437, 0.367, 0.504,
+ 06, 01, 0.439, 0.367, 0.506,
+ 07, 01, 0.440, 0.367, 0.508,
+ 08, 01, 0.441, 0.368, 0.510,
+ 09, 01, 0.442, 0.368, 0.512,
+ 10, 01, 0.444, 0.368, 0.514,
+ 11, 01, 0.445, 0.368, 0.517,
+ 12, 01, 0.446, 0.368, 0.519,
+ 13, 01, 0.448, 0.369, 0.522,
+ 14, 01, 0.450, 0.369, 0.525,
+ 15, 01, 0.451, 0.369, 0.527,
+ 16, 01, 0.453, 0.370, 0.530,
+ 17, 01, 0.455, 0.370, 0.533,
+ 18, 01, 0.456, 0.370, 0.537,
+ 19, 01, 0.458, 0.371, 0.540,
+ 20, 01, 0.460, 0.371, 0.543,
+ 21, 01, 0.462, 0.371, 0.547,
+ 22, 01, 0.464, 0.372, 0.550,
+ 23, 01, 0.466, 0.372, 0.554,
+ 24, 01, 0.468, 0.373, 0.558,
+ 25, 01, 0.470, 0.373, 0.561,
+ 26, 01, 0.472, 0.374, 0.565,
+ 27, 01, 0.474, 0.374, 0.569,
+ 28, 01, 0.476, 0.375, 0.573,
+ 29, 01, 0.478, 0.375, 0.577,
+ 30, 01, 0.480, 0.376, 0.582,
+ 31, 01, 0.483, 0.376, 0.586,
+ 01, 02, 0.485, 0.377, 0.590,
+ 02, 02, 0.487, 0.377, 0.594,
+ 03, 02, 0.489, 0.378, 0.599,
+ 04, 02, 0.492, 0.379, 0.603,
+ 05, 02, 0.494, 0.379, 0.607,
+ 06, 02, 0.496, 0.380, 0.612,
+ 07, 02, 0.498, 0.381, 0.616,
+ 08, 02, 0.501, 0.381, 0.621,
+ 09, 02, 0.503, 0.382, 0.625,
+ 10, 02, 0.505, 0.383, 0.630,
+ 11, 02, 0.508, 0.384, 0.634,
+ 12, 02, 0.510, 0.384, 0.639,
+ 13, 02, 0.512, 0.385, 0.643,
+ 14, 02, 0.515, 0.386, 0.648,
+ 15, 02, 0.517, 0.387, 0.652,
+ 16, 02, 0.519, 0.387, 0.657,
+ 17, 02, 0.522, 0.388, 0.661,
+ 18, 02, 0.524, 0.389, 0.666,
+ 19, 02, 0.526, 0.390, 0.670,
+ 20, 02, 0.528, 0.391, 0.674,
+ 21, 02, 0.530, 0.392, 0.679,
+ 22, 02, 0.533, 0.393, 0.683,
+ 23, 02, 0.535, 0.393, 0.687,
+ 24, 02, 0.537, 0.394, 0.691,
+ 25, 02, 0.539, 0.395, 0.695,
+ 26, 02, 0.541, 0.396, 0.699,
+ 27, 02, 0.543, 0.397, 0.703,
+ 28, 02, 0.545, 0.398, 0.707,
+ 29, 02, 0.546, 0.399, 0.709,
+ 01, 03, 0.547, 0.399, 0.711,
+ 02, 03, 0.549, 0.400, 0.715,
+ 03, 03, 0.551, 0.401, 0.718,
+ 04, 03, 0.553, 0.402, 0.722,
+ 05, 03, 0.555, 0.403, 0.726,
+ 06, 03, 0.557, 0.404, 0.729,
+ 07, 03, 0.559, 0.405, 0.732,
+ 08, 03, 0.560, 0.406, 0.736,
+ 09, 03, 0.562, 0.406, 0.739,
+ 10, 03, 0.564, 0.407, 0.742,
+ 11, 03, 0.566, 0.408, 0.745,
+ 12, 03, 0.567, 0.409, 0.748,
+ 13, 03, 0.569, 0.410, 0.750,
+ 14, 03, 0.570, 0.411, 0.753,
+ 15, 03, 0.572, 0.412, 0.756,
+ 16, 03, 0.573, 0.413, 0.758,
+ 17, 03, 0.575, 0.414, 0.761,
+ 18, 03, 0.576, 0.415, 0.763,
+ 19, 03, 0.577, 0.416, 0.765,
+ 20, 03, 0.579, 0.417, 0.767,
+ 21, 03, 0.580, 0.417, 0.769,
+ 22, 03, 0.581, 0.418, 0.771,
+ 23, 03, 0.582, 0.419, 0.773,
+ 24, 03, 0.583, 0.420, 0.774,
+ 25, 03, 0.584, 0.421, 0.776,
+ 26, 03, 0.585, 0.422, 0.777,
+ 27, 03, 0.586, 0.422, 0.779,
+ 28, 03, 0.587, 0.423, 0.780,
+ 29, 03, 0.588, 0.424, 0.781,
+ 30, 03, 0.589, 0.425, 0.782,
+ 31, 03, 0.590, 0.425, 0.783,
+ 01, 04, 0.591, 0.426, 0.784,
+ 02, 04, 0.591, 0.427, 0.785,
+ 03, 04, 0.592, 0.427, 0.785,
+ 04, 04, 0.593, 0.428, 0.786,
+ 05, 04, 0.593, 0.429, 0.787,
+ 06, 04, 0.594, 0.429, 0.787,
+ 07, 04, 0.595, 0.430, 0.787,
+ 08, 04, 0.595, 0.431, 0.788,
+ 09, 04, 0.596, 0.431, 0.788,
+ 10, 04, 0.596, 0.432, 0.788,
+ 11, 04, 0.597, 0.432, 0.788,
+ 12, 04, 0.597, 0.433, 0.788,
+ 13, 04, 0.597, 0.433, 0.788,
+ 14, 04, 0.598, 0.434, 0.788,
+ 15, 04, 0.598, 0.434, 0.788,
+ 16, 04, 0.598, 0.435, 0.787,
+ 17, 04, 0.599, 0.435, 0.787,
+ 18, 04, 0.599, 0.436, 0.787,
+ 19, 04, 0.599, 0.436, 0.786,
+ 20, 04, 0.599, 0.436, 0.786,
+ 21, 04, 0.600, 0.437, 0.785,
+ 22, 04, 0.600, 0.437, 0.785,
+ 23, 04, 0.600, 0.437, 0.784,
+ 24, 04, 0.600, 0.438, 0.784,
+ 25, 04, 0.600, 0.438, 0.783,
+ 26, 04, 0.601, 0.438, 0.783,
+ 27, 04, 0.601, 0.438, 0.782,
+ 28, 04, 0.601, 0.439, 0.781,
+ 29, 04, 0.601, 0.439, 0.781,
+ 30, 04, 0.601, 0.439, 0.780,
+ 01, 05, 0.601, 0.439, 0.779,
+ 02, 05, 0.601, 0.439, 0.778,
+ 03, 05, 0.601, 0.439, 0.778,
+ 04, 05, 0.601, 0.440, 0.777,
+ 05, 05, 0.601, 0.440, 0.776,
+ 06, 05, 0.601, 0.440, 0.775,
+ 07, 05, 0.601, 0.440, 0.775,
+ 08, 05, 0.601, 0.440, 0.774,
+ 09, 05, 0.601, 0.440, 0.773,
+ 10, 05, 0.602, 0.440, 0.772,
+ 11, 05, 0.602, 0.440, 0.772,
+ 12, 05, 0.602, 0.440, 0.771,
+ 13, 05, 0.602, 0.440, 0.770,
+ 14, 05, 0.602, 0.440, 0.770,
+ 15, 05, 0.602, 0.440, 0.769,
+ 16, 05, 0.602, 0.440, 0.768,
+ 17, 05, 0.602, 0.440, 0.768,
+ 18, 05, 0.602, 0.440, 0.767,
+ 19, 05, 0.602, 0.440, 0.767,
+ 20, 05, 0.602, 0.440, 0.766,
+ 21, 05, 0.602, 0.440, 0.766,
+ 22, 05, 0.602, 0.440, 0.765,
+ 23, 05, 0.602, 0.440, 0.765,
+ 24, 05, 0.602, 0.440, 0.764,
+ 25, 05, 0.602, 0.440, 0.764,
+ 26, 05, 0.602, 0.440, 0.764,
+ 27, 05, 0.602, 0.439, 0.763,
+ 28, 05, 0.602, 0.439, 0.763,
+ 29, 05, 0.602, 0.439, 0.763,
+ 30, 05, 0.602, 0.439, 0.762,
+ 31, 05, 0.602, 0.439, 0.762,
+ 01, 06, 0.602, 0.439, 0.762,
+ 02, 06, 0.602, 0.439, 0.762,
+ 03, 06, 0.602, 0.439, 0.762,
+ 04, 06, 0.602, 0.439, 0.762,
+ 05, 06, 0.602, 0.439, 0.762,
+ 06, 06, 0.602, 0.438, 0.761,
+ 07, 06, 0.602, 0.438, 0.761,
+ 08, 06, 0.602, 0.438, 0.761,
+ 09, 06, 0.602, 0.438, 0.761,
+ 10, 06, 0.602, 0.438, 0.761,
+ 11, 06, 0.602, 0.438, 0.762,
+ 12, 06, 0.602, 0.438, 0.762,
+ 13, 06, 0.602, 0.438, 0.762,
+ 14, 06, 0.602, 0.438, 0.762,
+ 15, 06, 0.602, 0.437, 0.762,
+ 16, 06, 0.602, 0.437, 0.762,
+ 17, 06, 0.602, 0.437, 0.762,
+ 18, 06, 0.602, 0.437, 0.762,
+ 19, 06, 0.602, 0.437, 0.763,
+ 20, 06, 0.602, 0.437, 0.763,
+ 21, 06, 0.602, 0.437, 0.763,
+ 22, 06, 0.602, 0.436, 0.763,
+ 23, 06, 0.602, 0.436, 0.763,
+ 24, 06, 0.602, 0.436, 0.764,
+ 25, 06, 0.602, 0.436, 0.764,
+ 26, 06, 0.601, 0.436, 0.764,
+ 27, 06, 0.601, 0.436, 0.764,
+ 28, 06, 0.601, 0.436, 0.764,
+ 29, 06, 0.601, 0.435, 0.765,
+ 30, 06, 0.601, 0.435, 0.765,
+ 01, 07, 0.601, 0.435, 0.765,
+ 02, 07, 0.600, 0.435, 0.765,
+ 03, 07, 0.600, 0.435, 0.765,
+ 04, 07, 0.600, 0.434, 0.766,
+ 05, 07, 0.600, 0.434, 0.766,
+ 06, 07, 0.599, 0.434, 0.766,
+ 07, 07, 0.599, 0.434, 0.766,
+ 08, 07, 0.599, 0.434, 0.766,
+ 09, 07, 0.598, 0.433, 0.766,
+ 10, 07, 0.598, 0.433, 0.766,
+ 11, 07, 0.598, 0.433, 0.766,
+ 12, 07, 0.597, 0.433, 0.766,
+ 13, 07, 0.597, 0.432, 0.767,
+ 14, 07, 0.597, 0.432, 0.767,
+ 15, 07, 0.596, 0.432, 0.767,
+ 16, 07, 0.596, 0.432, 0.766,
+ 17, 07, 0.595, 0.431, 0.766,
+ 18, 07, 0.595, 0.431, 0.766,
+ 19, 07, 0.594, 0.431, 0.766,
+ 20, 07, 0.594, 0.430, 0.766,
+ 21, 07, 0.593, 0.430, 0.766,
+ 22, 07, 0.593, 0.430, 0.766,
+ 23, 07, 0.592, 0.429, 0.765,
+ 24, 07, 0.592, 0.429, 0.765,
+ 25, 07, 0.591, 0.428, 0.765,
+ 26, 07, 0.590, 0.428, 0.765,
+ 27, 07, 0.590, 0.428, 0.764,
+ 28, 07, 0.589, 0.427, 0.764,
+ 29, 07, 0.588, 0.427, 0.764,
+ 30, 07, 0.588, 0.426, 0.763,
+ 31, 07, 0.587, 0.426, 0.763,
+ 01, 08, 0.586, 0.425, 0.762,
+ 02, 08, 0.586, 0.425, 0.762,
+ 03, 08, 0.585, 0.424, 0.761,
+ 04, 08, 0.584, 0.424, 0.761,
+ 05, 08, 0.583, 0.423, 0.760,
+ 06, 08, 0.583, 0.423, 0.760,
+ 07, 08, 0.582, 0.422, 0.759,
+ 08, 08, 0.581, 0.421, 0.758,
+ 09, 08, 0.580, 0.421, 0.758,
+ 10, 08, 0.579, 0.420, 0.757,
+ 11, 08, 0.578, 0.420, 0.756,
+ 12, 08, 0.578, 0.419, 0.755,
+ 13, 08, 0.577, 0.418, 0.754,
+ 14, 08, 0.576, 0.418, 0.754,
+ 15, 08, 0.575, 0.417, 0.753,
+ 16, 08, 0.574, 0.416, 0.752,
+ 17, 08, 0.573, 0.415, 0.751,
+ 18, 08, 0.572, 0.415, 0.750,
+ 19, 08, 0.571, 0.414, 0.749,
+ 20, 08, 0.570, 0.413, 0.748,
+ 21, 08, 0.569, 0.413, 0.747,
+ 22, 08, 0.569, 0.412, 0.746,
+ 23, 08, 0.568, 0.411, 0.745,
+ 24, 08, 0.567, 0.410, 0.744,
+ 25, 08, 0.566, 0.409, 0.743,
+ 26, 08, 0.565, 0.409, 0.742,
+ 27, 08, 0.564, 0.408, 0.741,
+ 28, 08, 0.563, 0.407, 0.740,
+ 29, 08, 0.562, 0.406, 0.738,
+ 30, 08, 0.561, 0.405, 0.737,
+ 31, 08, 0.560, 0.405, 0.736,
+ 01, 09, 0.558, 0.404, 0.735,
+ 02, 09, 0.557, 0.403, 0.734,
+ 03, 09, 0.556, 0.402, 0.732,
+ 04, 09, 0.555, 0.401, 0.731,
+ 05, 09, 0.554, 0.401, 0.730,
+ 06, 09, 0.553, 0.400, 0.728,
+ 07, 09, 0.552, 0.399, 0.727,
+ 08, 09, 0.551, 0.398, 0.725,
+ 09, 09, 0.550, 0.397, 0.724,
+ 10, 09, 0.549, 0.396, 0.723,
+ 11, 09, 0.548, 0.396, 0.721,
+ 12, 09, 0.546, 0.395, 0.720,
+ 13, 09, 0.545, 0.394, 0.718,
+ 14, 09, 0.544, 0.393, 0.717,
+ 15, 09, 0.543, 0.392, 0.715,
+ 16, 09, 0.542, 0.391, 0.713,
+ 17, 09, 0.541, 0.391, 0.712,
+ 18, 09, 0.540, 0.390, 0.710,
+ 19, 09, 0.538, 0.389, 0.709,
+ 20, 09, 0.537, 0.388, 0.707,
+ 21, 09, 0.536, 0.388, 0.705,
+ 22, 09, 0.535, 0.387, 0.703,
+ 23, 09, 0.533, 0.386, 0.702,
+ 24, 09, 0.532, 0.385, 0.700,
+ 25, 09, 0.531, 0.385, 0.698,
+ 26, 09, 0.530, 0.384, 0.696,
+ 27, 09, 0.528, 0.383, 0.694,
+ 28, 09, 0.527, 0.383, 0.692,
+ 29, 09, 0.526, 0.382, 0.690,
+ 30, 09, 0.525, 0.381, 0.688,
+ 01, 10, 0.523, 0.381, 0.686,
+ 02, 10, 0.522, 0.380, 0.684,
+ 03, 10, 0.521, 0.379, 0.682,
+ 04, 10, 0.519, 0.379, 0.680,
+ 05, 10, 0.518, 0.378, 0.678,
+ 06, 10, 0.517, 0.377, 0.676,
+ 07, 10, 0.515, 0.377, 0.674,
+ 08, 10, 0.514, 0.376, 0.671,
+ 09, 10, 0.512, 0.376, 0.669,
+ 10, 10, 0.511, 0.375, 0.667,
+ 11, 10, 0.510, 0.375, 0.664,
+ 12, 10, 0.508, 0.374, 0.662,
+ 13, 10, 0.507, 0.374, 0.659,
+ 14, 10, 0.505, 0.373, 0.657,
+ 15, 10, 0.504, 0.373, 0.654,
+ 16, 10, 0.502, 0.372, 0.652,
+ 17, 10, 0.501, 0.372, 0.649,
+ 18, 10, 0.499, 0.372, 0.647,
+ 19, 10, 0.498, 0.371, 0.644,
+ 20, 10, 0.496, 0.371, 0.641,
+ 21, 10, 0.495, 0.371, 0.639,
+ 22, 10, 0.493, 0.370, 0.636,
+ 23, 10, 0.492, 0.370, 0.633,
+ 24, 10, 0.490, 0.370, 0.630,
+ 25, 10, 0.489, 0.369, 0.628,
+ 26, 10, 0.487, 0.369, 0.625,
+ 27, 10, 0.485, 0.369, 0.622,
+ 28, 10, 0.484, 0.368, 0.619,
+ 29, 10, 0.482, 0.368, 0.616,
+ 30, 10, 0.481, 0.368, 0.613,
+ 31, 10, 0.479, 0.368, 0.610,
+ 01, 11, 0.478, 0.368, 0.607,
+ 02, 11, 0.476, 0.367, 0.604,
+ 03, 11, 0.475, 0.367, 0.601,
+ 04, 11, 0.473, 0.367, 0.598,
+ 05, 11, 0.471, 0.367, 0.595,
+ 06, 11, 0.470, 0.367, 0.592,
+ 07, 11, 0.468, 0.367, 0.589,
+ 08, 11, 0.467, 0.366, 0.586,
+ 09, 11, 0.465, 0.366, 0.583,
+ 10, 11, 0.464, 0.366, 0.580,
+ 11, 11, 0.462, 0.366, 0.577,
+ 12, 11, 0.461, 0.366, 0.574,
+ 13, 11, 0.459, 0.366, 0.571,
+ 14, 11, 0.458, 0.366, 0.568,
+ 15, 11, 0.456, 0.366, 0.565,
+ 16, 11, 0.455, 0.366, 0.562,
+ 17, 11, 0.454, 0.366, 0.559,
+ 18, 11, 0.452, 0.365, 0.556,
+ 19, 11, 0.451, 0.365, 0.553,
+ 20, 11, 0.450, 0.365, 0.550,
+ 21, 11, 0.448, 0.365, 0.547,
+ 22, 11, 0.447, 0.365, 0.544,
+ 23, 11, 0.446, 0.365, 0.542,
+ 24, 11, 0.445, 0.365, 0.539,
+ 25, 11, 0.443, 0.365, 0.536,
+ 26, 11, 0.442, 0.365, 0.533,
+ 27, 11, 0.441, 0.365, 0.531,
+ 28, 11, 0.440, 0.365, 0.528,
+ 29, 11, 0.439, 0.365, 0.526,
+ 30, 11, 0.438, 0.365, 0.523,
+ 01, 12, 0.437, 0.365, 0.521,
+ 02, 12, 0.436, 0.365, 0.519,
+ 03, 12, 0.435, 0.365, 0.517,
+ 04, 12, 0.434, 0.365, 0.515,
+ 05, 12, 0.434, 0.365, 0.513,
+ 06, 12, 0.433, 0.365, 0.511,
+ 07, 12, 0.432, 0.365, 0.509,
+ 08, 12, 0.431, 0.365, 0.507,
+ 09, 12, 0.431, 0.365, 0.505,
+ 10, 12, 0.430, 0.365, 0.504,
+ 11, 12, 0.430, 0.365, 0.502,
+ 12, 12, 0.429, 0.365, 0.501,
+ 13, 12, 0.429, 0.365, 0.500,
+ 14, 12, 0.429, 0.365, 0.498,
+ 15, 12, 0.428, 0.365, 0.497,
+ 16, 12, 0.428, 0.365, 0.496,
+ 17, 12, 0.428, 0.365, 0.496,
+ 18, 12, 0.428, 0.365, 0.495,
+ 19, 12, 0.428, 0.365, 0.494,
+ 20, 12, 0.428, 0.365, 0.494,
+ 21, 12, 0.428, 0.365, 0.494,
+ 22, 12, 0.428, 0.365, 0.493,
+ 23, 12, 0.429, 0.365, 0.493,
+ 24, 12, 0.429, 0.366, 0.493,
+ 25, 12, 0.429, 0.366, 0.493,
+ 26, 12, 0.430, 0.366, 0.494,
+ 27, 12, 0.430, 0.366, 0.494,
+ 28, 12, 0.431, 0.366, 0.495,
+ 29, 12, 0.431, 0.366, 0.495,
+ 30, 12, 0.432, 0.366, 0.496,
+ 31, 12, 0.433, 0.366, 0.497),ncol=5,byrow=TRUE);
+ dimnames(RESULT) <- list(1:366,c("day","month","grad_Tmean","grad_Tmin","grad_Tmax"));
+ return(RESULT);
+ }
+
+
+
+ ##Format_______________________________________________________________________________________
+ HypsoData <- as.double(HypsoData);
+ ZInputs <- as.double(ZInputs);
+
+
+ ##ElevationLayers_Creation_____________________________________________________________________
+ ZLayers <- as.double(rep(NA,NLayers));
+ if(!identical(HypsoData,as.double(rep(NA,101)))){
+ nmoy <- 100 %/% NLayers;
+ nreste <- 100 %% NLayers;
+ ncont <- 0;
+ for(iLayer in 1:NLayers){
+ if(nreste > 0){ nn <- nmoy+1; nreste <- nreste-1; } else { nn <- nmoy; }
+ if(nn==1){ ZLayers[iLayer] <- HypsoData[ncont+1]; }
+ if(nn==2){ ZLayers[iLayer] <- 0.5 * (HypsoData[ncont+1] + HypsoData[ncont+2]); }
+ if(nn>2 ){ ZLayers[iLayer] <- HypsoData[ncont+nn/2]; }
+ ncont <- ncont+nn;
+ }
+ }
+
+
+ ##Precipitation_extrapolation__________________________________________________________________
+ ##Initialisation
+ if (identical(ZInputs, HypsoData[51]) & NLayers == 1) {
+ LayerPrecip <- list(as.double(Precip))
+ } else {
+ ##Elevation_gradients_for_daily_mean_precipitation
+ GradP <- GradP_Valery2010() ### single value
+ TabGradP <- rep(GradP, length(Precip))
+ ##Extrapolation
+ ##Thresold_of_inputs_median_elevation
+ Zthreshold <- 4000
+ LayerPrecip_df <- sapply(1:NLayers, function(iLayer) {
+ ##If_layer_elevation_smaller_than_Zthreshold
+ if (ZLayers[iLayer] <= Zthreshold) {
+ prcp <- as.double(Precip * exp(TabGradP * (ZLayers[iLayer] - ZInputs)))
+ ##If_layer_elevation_greater_than_Zthreshold
} else {
- ##Elevation_gradients_for_daily_mean_min_and_max_temperature
- GradT <- as.data.frame(GradT_Valery2010())
- iday <- match(format(DatesR,format="%d%m"), sprintf("%02i%02i", GradT[, "day"], GradT[, "month"]))
- TabGradT <- GradT[iday, c("grad_Tmean", "grad_Tmin", "grad_Tmax")]
- ##Extrapolation
- ##On_each_elevation_layer...
- for(iLayer in 1:NLayers){
- LayerTempMean[[iLayer]] <- as.double(TempMean + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmean"])/100);
- if(!is.null(TempMin) & !is.null(TempMax)){
- LayerTempMin[[iLayer]] <- as.double(TempMin + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmin"])/100);
- LayerTempMax[[iLayer]] <- as.double(TempMax + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmax"])/100);
- }
+ ##If_inputs_median_elevation_smaller_than_Zthreshold
+ if (ZInputs <= Zthreshold) {
+ prcp <- as.double(Precip * exp(TabGradP*(Zthreshold - ZInputs)))
+ ##If_inputs_median_elevation_greater_then_Zthreshold
+ } else {
+ prcp <- as.double(Precip)
}
}
-
-
-
- ##Solid_Fraction_for_each_elevation_layer______________________________________________________
- LayerFracSolidPrecip <- list();
- ##Thresold_of_inputs_median_elevation
- Zthreshold <- 1500;
- ##On_each_elevation_layer...
- for(iLayer in 1:NLayers){
- Option <- "USACE";
- if(!is.na(ZInputs)){ if(ZInputs < Zthreshold & !is.null(TempMin) & !is.null(TempMax)){ Option <- "Hydrotel"; } }
- ##Turcotte_formula_from_Hydrotel
- if(Option=="Hydrotel"){
- TempMin <- LayerTempMin[[iLayer]];
- TempMax <- LayerTempMax[[iLayer]];
- SolidFraction <- 1 - TempMax/(TempMax - TempMin);
- SolidFraction[TempMin >= 0] <- 0;
- SolidFraction[TempMax <= 0] <- 1;
- }
- ##USACE_formula
- if(Option=="USACE"){
- USACE_Tmin <- -1.0;
- USACE_Tmax <- 3.0;
- TempMean <- LayerTempMean[[iLayer]];
- SolidFraction <- 1- (TempMean - USACE_Tmin)/(USACE_Tmax - USACE_Tmin);
- SolidFraction[TempMean > USACE_Tmax] <- 0;
- SolidFraction[TempMean < USACE_Tmin] <- 1;
- }
- LayerFracSolidPrecip[[iLayer]] <- as.double(SolidFraction);
+ return(prcp)
+ }
+ )
+ if (PrecipScale) {
+ LayerPrecip_df <- LayerPrecip_df / rowMeans(LayerPrecip_df) * Precip
+ LayerPrecip_df[is.nan(LayerPrecip_df)] <- 0
+ }
+ LayerPrecip <- lapply(seq_len(ncol(LayerPrecip_df)), function(x) LayerPrecip_df[, x])
+ }
+
+
+
+ ##Temperature_extrapolation____________________________________________________________________
+ ##Initialisation
+ LayerTempMean <- list(); LayerTempMin <- list(); LayerTempMax <- list();
+ if(identical(ZInputs,HypsoData[51]) & NLayers==1) {
+ LayerTempMean[[1]] <- as.double(TempMean);
+ if(!is.null(TempMin) & !is.null(TempMax)){ LayerTempMin[[1]] <- as.double(TempMin); LayerTempMax[[1]] <- as.double(TempMax); }
+ } else {
+ ##Elevation_gradients_for_daily_mean_min_and_max_temperature
+ GradT <- as.data.frame(GradT_Valery2010())
+ iday <- match(format(DatesR,format="%d%m"), sprintf("%02i%02i", GradT[, "day"], GradT[, "month"]))
+ TabGradT <- GradT[iday, c("grad_Tmean", "grad_Tmin", "grad_Tmax")]
+ ##Extrapolation
+ ##On_each_elevation_layer...
+ for(iLayer in 1:NLayers){
+ LayerTempMean[[iLayer]] <- as.double(TempMean + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmean"])/100);
+ if(!is.null(TempMin) & !is.null(TempMax)){
+ LayerTempMin[[iLayer]] <- as.double(TempMin + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmin"])/100);
+ LayerTempMax[[iLayer]] <- as.double(TempMax + (ZInputs-ZLayers[iLayer])*abs(TabGradT[, "grad_Tmax"])/100);
}
-
-
-
-
- ##END__________________________________________________________________________________________
- return(list(LayerPrecip=LayerPrecip,LayerTempMean=LayerTempMean,LayerTempMin=LayerTempMin,LayerTempMax=LayerTempMax,
- LayerFracSolidPrecip=LayerFracSolidPrecip,ZLayers=ZLayers));
-
+ }
+ }
+
+
+
+ ##Solid_Fraction_for_each_elevation_layer______________________________________________________
+ LayerFracSolidPrecip <- list();
+ ##Thresold_of_inputs_median_elevation
+ Zthreshold <- 1500;
+ ##On_each_elevation_layer...
+ for(iLayer in 1:NLayers){
+ Option <- "USACE";
+ if(!is.na(ZInputs)){ if(ZInputs < Zthreshold & !is.null(TempMin) & !is.null(TempMax)){ Option <- "Hydrotel"; } }
+ ##Turcotte_formula_from_Hydrotel
+ if(Option=="Hydrotel"){
+ TempMin <- LayerTempMin[[iLayer]];
+ TempMax <- LayerTempMax[[iLayer]];
+ SolidFraction <- 1 - TempMax/(TempMax - TempMin);
+ SolidFraction[TempMin >= 0] <- 0;
+ SolidFraction[TempMax <= 0] <- 1;
+ }
+ ##USACE_formula
+ if(Option=="USACE"){
+ USACE_Tmin <- -1.0;
+ USACE_Tmax <- 3.0;
+ TempMean <- LayerTempMean[[iLayer]];
+ SolidFraction <- 1- (TempMean - USACE_Tmin)/(USACE_Tmax - USACE_Tmin);
+ SolidFraction[TempMean > USACE_Tmax] <- 0;
+ SolidFraction[TempMean < USACE_Tmin] <- 1;
+ }
+ LayerFracSolidPrecip[[iLayer]] <- as.double(SolidFraction);
+ }
+
+
+
+
+ ##END__________________________________________________________________________________________
+ return(list(LayerPrecip=LayerPrecip,LayerTempMean=LayerTempMean,LayerTempMin=LayerTempMin,LayerTempMax=LayerTempMax,
+ LayerFracSolidPrecip=LayerFracSolidPrecip,ZLayers=ZLayers));
+
}
diff --git a/inst/CITATION b/inst/CITATION
index e909e2de5d4f134214b0c0fd55d7935e3d95d16e..bc2ca96af4f6ed8af511c1d58c5f8645c427e773 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -18,13 +18,13 @@ citEntry(entry="Manual",
author = personList(as.person("L. Coron"), as.person("C. Perrin"), as.person("C. Michel")),
journal = "R News",
year = "2017",
- note = "R package version 1.0.5.2",
+ note = "R package version 1.0.5.3",
url = "https://webgr.irstea.fr/airGR/?lang=en",
textVersion =
paste("Coron, L., Perrin, C. and Michel, C.",
"(2017).",
"airGR: Suite of GR hydrological models for precipitation-runoff modelling.",
- "R package version 1.0.5.2.",
+ "R package version 1.0.5.3.",
"https://webgr.irstea.fr/airGR/?lang=en.",
sep = " ")
)
diff --git a/man/CreateInputsModel.Rd b/man/CreateInputsModel.Rd
index cb668f1dc11c60ec0581975acdce301ca468ad10..ff37a4f87359027d94f40ff6f119d94dfde10b31 100644
--- a/man/CreateInputsModel.Rd
+++ b/man/CreateInputsModel.Rd
@@ -3,8 +3,8 @@
\alias{CreateInputsModel}
\title{Creation of the InputsModel object required to the RunModel functions}
\usage{
-CreateInputsModel(FUN_MOD, DatesR, Precip, PotEvap = NULL, TempMean = NULL,
- TempMin = NULL, TempMax = NULL, ZInputs = NULL, HypsoData = NULL,
+CreateInputsModel(FUN_MOD, DatesR, Precip, PrecipScale = TRUE, PotEvap = NULL,
+ TempMean = NULL, TempMin = NULL, TempMax = NULL, ZInputs = NULL, HypsoData = NULL,
NLayers = 5, verbose = TRUE)
}
\arguments{
@@ -14,6 +14,8 @@ CreateInputsModel(FUN_MOD, DatesR, Precip, PotEvap = NULL, TempMean = NULL,
\item{Precip}{[numeric] time series of total precipitation (catchment average) [mm], required to create the GR model and CemaNeige module inputs}
+\item{PrecipScale}{(optional) [boolean] indicating if the mean of the precipitation interpolated on the elevation layers must be kept or not, required to create CemaNeige module inputs, default = \code{TRUE} (the mean of the precipitation is kept to the original value)}
+
\item{PotEvap}{[numeric] time series of potential evapotranspiration (catchment average) [mm], required to create the GR model inputs}
\item{TempMean}{(optional) [numeric] time series of mean air temperature [°C], required to create the CemaNeige module inputs}
diff --git a/man/DataAltiExtrapolation_Valery.Rd b/man/DataAltiExtrapolation_Valery.Rd
index ed2966ce8dbe5db7a8e06dbc2ba34ceed4db9e17..c2988f54d2d54c736369c11764cf6a9daf0c11d9 100644
--- a/man/DataAltiExtrapolation_Valery.Rd
+++ b/man/DataAltiExtrapolation_Valery.Rd
@@ -3,14 +3,17 @@
\alias{DataAltiExtrapolation_Valery}
\title{Altitudinal extrapolation of precipitation and temperature series described by A. Valery}
\usage{
-DataAltiExtrapolation_Valery(DatesR, Precip, TempMean, TempMin = NULL,
- TempMax = NULL, ZInputs, HypsoData, NLayers, verbose = TRUE)
+DataAltiExtrapolation_Valery(DatesR, Precip, PrecipScale = TRUE,
+ TempMean, TempMin = NULL, TempMax = NULL,
+ ZInputs, HypsoData, NLayers, verbose = TRUE)
}
\arguments{
\item{DatesR}{[POSIXt] vector of dates}
\item{Precip}{[numeric] time series of daily total precipitation (catchment average) [mm]}
+\item{PrecipScale}{(optional) [boolean] indicating if the mean of the precipitation interpolated on the elevation layers must be kept or not, required to create CemaNeige module inputs, default = \code{TRUE} (the mean of the precipitation is kept to the original value)}
+
\item{TempMean}{[numeric] time series of daily mean air temperature [°C]}
\item{TempMin}{(optional) [numeric] time series of daily min air temperature [°C]}