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 RGtk2 and depends on other libraries to run (raster, sp, rgdal). Thus, to make available
sara4r in the R environment you must install
RGtk2 first, then the
The first time you execute our tool, you will be asked to install RGtk+.
# Load the RGtk2 library library(RGtk2)
Just type OK and wait until the program finished.
# Load the following libraries. library(raster) #> Loading required package: sp library(rgdal) #> rgdal: version: 1.3-2, (SVN revision 755) #> Geospatial Data Abstraction Library extensions to R successfully loaded #> Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20 #> Path to GDAL shared files: C:/Users/Veirus/Documents/R/win-library/3.4/rgdal/gdal #> GDAL binary built with GEOS: TRUE #> Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493] #> Path to PROJ.4 shared files: C:/Users/Veirus/Documents/R/win-library/3.4/rgdal/proj #> Linking to sp version: 1.3-1 library(sp) library(sara4r)
Finally, to run our software, 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
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 ... ... ...