sara4r
is an easy way to calculate the rainfall-runoff relation using the
Natural Resources Conservation Service - Curve Number method (NRCS-CN
method) but includes modifications by Hawkins et al., (2002) about the
Initial Abstraction. This graphical user interface follows the
programming logic of a previously published software CN-Idris,
Hernández-Guzmán et al., 2011 - CN-Idris: An Idrisi tool for generating
curve number maps and estimating direct runoff. Environmental Modelling
& Software, 26(12), 1764-1766, a raster-based GIS tool that
outputs runoff estimates from Land use/land cover and hydrologic soil
group maps. This package is under development at the Institute about
Natural Resources Research (INIRENA) from the Universidad Michoacana de
San Nicolás de Hidalgo and represents a collaborative effort between the
Hydro-Geomatic Lab
(INIRENA) with the Environmental Management Lab (CIAD, A.C.).
sara4r
package is a Graphical User Interface developed
in tcltk and depends on other packages to run (terra). Thus, to make
available sara4r
in the R environment you must install
tcltk2
first, then the terra
package.
First at all, ensure that you have intalled tcltk and tcltk2.
Load required packages.
# Load the following packages.
library(tcltk2)
library(terra)
#> terra 1.7.46
#>
#> Attaching package: 'terra'
#> The following objects are masked from 'package:tcltk2':
#>
#> size, values, values<-
library(sara4r)
Finally, to run our package, just type:
As you can see in the Menu - Help, there are the instructions to make
all required files to use sara4r
. If you go to the
installed folder (sara4r), you will find the
HowtoMake_CNindexFile.xlsx
with all the instructions. In
overall terms:
Land use and land cover map should be reclassified as follow:
LULC in the first place should be reclassified as 10
LULC in second place should be reclassified as 20
... and so on.
As an example, Landuse file would be:
10 Tropical dry forest
20 Agriculture
30 Mangrove
40 Grassland
50 Evergreen forest
...
While the Hydrologic Soil Group map should be reclassified as follow:
HSG A should be reclassified as 1
HSG B should be reclassified as 2
HSG C should be reclassified as 3
HSG D should be reclassified as 4
Thus, GSH map would be:
1 A
2 B
3 C
4 D
Finally,
The logic behind the method is:"
Landsoil is produced as the sum of LANDUSE and HSG maps. Thus, the possible values it can take are:"
11 = Landuse 1 (reclassified as 10) with HSG A (reclassified as 1)
12 = Landuse 1 (reclassified as 10) with HSG B (reclassified as 2)
13 = Landuse 1 (reclassified as 10) with HSG C (reclassified as 3)
14 = Landuse 1 (reclassified as 10) with HSG D (reclassified as 4)
21 = Landuse 2 (reclassified as 20) with HSG A (reclassified as 1)
22 = Landuse 2 (reclassified as 20) with HSG B (reclassified as 2)
23 = Landuse 2 (reclassified as 20) with HSG C (reclassified as 3)
24 = Landuse 2 (reclassified as 20) with HSG D (reclassified as 4)
31 = Landuse 3 (reclassified as 30) with HSG A (reclassified as 1)
...
Thus, the CN index file would be (csv file):"
11,12,CNvalue1
12,13,CNvalue2
13,14,CNvalue3
14,15,CNvalue4
21,22,CNvalue5
22,23,CNvalue6
23,24,CNvalue7
24,25,CNvalue8
31,32,CNvalue9
...
...
...