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 libraries to run (raster, sp, rgdal). Thus, to make available
sara4r in the R environment you must install
tcltk2 first, then the
First at all, ensure that you have intalled tcltk and tcltk2.
# Load the tcltk package library(tcltk)
Load required packages.
# Load the following packages. library(tcltk2) library(raster) #> Loading required package: sp library(rgdal) #> Please note that rgdal will be retired by the end of 2023, #> plan transition to sf/stars/terra functions using GDAL and PROJ #> at your earliest convenience. #> #> rgdal: version: 1.5-27, (SVN revision 1148) #> Geospatial Data Abstraction Library extensions to R successfully loaded #> Loaded GDAL runtime: GDAL 3.2.1, released 2020/12/29 #> Path to GDAL shared files: C:/Program Files/R/R-4.1.2/library/rgdal/gdal #> GDAL binary built with GEOS: TRUE #> Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721] #> Path to PROJ shared files: C:/Program Files/R/R-4.1.2/library/rgdal/proj #> PROJ CDN enabled: FALSE #> Linking to sp version:1.4-6 #> To mute warnings of possible GDAL/OSR exportToProj4() degradation, #> use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal. #> Overwritten PROJ_LIB was C:/Program Files/R/R-4.1.2/library/rgdal/proj library(sp) library(sara4r)
Finally, to run our package, just type:
sara4r() #> <Tcl>
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 ... ... ...