sara4r Vignette

Introduction

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.).

How to install

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 time

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(terra)
#> terra 1.7.83
#> 
#> Attaching package: 'terra'
#> The following objects are masked from 'package:tcltk2':
#> 
#>     size, values, values<-
library(sara4r)

Finally, to run our package, just type:

sara4r()
#> <Tcl>

Data preparation

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
  ...
  ...
  ...