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Mapping Soil Erosion using USLE

by Tejaswi Bhardwaj
Due to inappropriate land use, erosion has become one of the most dangerous forms of soil degradation leading to significant reduction of soil fertility and crop yields. The implementation of appropriate measures is strongly needed in order to prevent further degradation of soil. For this reason, GIS and Remote Sensing have been used extensively for mapping soil erosion risk. 
 
The Universal Soil Loss Equation (USLE) has been the most widely used model in predicting soil erosion loss. USLE is an empirical equation that estimates the average annual soil loss caused by sheet and rill erosion. More recently, the Revised Universal Soil Loss Equation (RUSLE) has been developed. RUSLE has the basic structure of the USLE but several improvements in the determining factors. Despite USLE's limitations, it is still widely used because of its simplicity. Various studies for erosion risk assessment around the world can be found in the literature, but there is no user-friendly automated tool for easy estimation. The aim of this study was to develop and implement an automatic procedure in ArcGIS Model Builder for soil erosion risk assessment using the Universal Soil Loss Equation (USLE).
 
Fig 1  Methodology Flow Chart of USLE for soil erosion mapping
Universal Soil Loss Equation (USLE) is implemented using GIS, to assess erosion risk on agricultural land. USLE is programmed in ModelBuilder - an ArcGIS application that creates, edits, and manages mathematical models. The USLE soil loss equation is: 
 

A = R x K x LS x C x P

 
Where, ‘A’ is the average annual soil loss; R is Rainfall-runoff erosivity factor; K is Soil- erodibility factor; L is Slope-length factor; S is the slope-gradient factor; C is the cropping-management factor and P is support practice factor.
 
GIS for soil erosion
 
Each of the USLE factors with associated attribute data is digitally encoded in a GIS database to eventually produce five thematic layers. These are then spatially overlaid to produce a resultant polygonal layer. Application of the USLE model to the resultant layer yields a soil erosion map with 3 classes of soil loss.
 
Fig 2  Use of GIS & Image Processing in Risk Assessment of Soil Erosion
USLE Factors : The Universal Soil Loss Equation (USLE) is used to create soil erosion map from the DEM data derived from three different data sources at the resolution of 90m, 150m, 210m and 270m.
 
  • •R factor : This stands for Rainfall erosivity factor containing the analysis of daily rainfall of past few years 
  • K factor : This stands for Soil Erodibility factor which represents both susceptibility of soil to erosion and the rate of runoff. Soil structures affects both susceptibility to detachment and infiltration. Permeability of the soil profile affects K because it affects runoff. 
  • LS factor : This stands for slope and slope length factor. The slope length factor (L) and slope steepness factor (S) mainly reflect the effect of topography on erosion. Slope steepness reflects the influence of slope gradient on erosion.
  • C factor : This stands for cover management factor which was calculated from the Landsat 7 satellite image through the Normalized Difference Vegetation Index (NDVI). 
  • P factor : This stands for support practice factor (P). Due to the lack of spatial distribution data, it is set to 1 assuming that no protection measure is taken.
Fig 3  Open Source DEMs to create maps for R factor, C factor & K factor
 
 
The use of different types of open source DEMs (SRTM, ASTER and CARTOSAT) with the original resolution (30 m) and aggregated resolution has a scope to identify the uncertainty of soil erosion modelling considering the changes in relation to the elevation accuracy. The results show significant variation in the rate of soil erosion only by using different DEMs of the same resolution and then by aggregating the resolution of all DEMs.
 
Soil Erosion Maps
 
Rainfalls of eight rain gauge stations are taken to calculate the rainfall erosivity (R) and are interpolated by Inverse Distance Weighting (IDW) method to show spatial distribution. Data processing and analysis of USLE factors is performed in the form of raster layers. The R factor (rainfall-runoff factor) is calculated from monthly and annual precipitation data of two meteorological stations in the area. 
 
Calculation of K factor ( soil erodibility factor) is based on soils properties measured in-situ from past surveys. The LS factor (topographic factor) was derived from the digital elevation model of the area. The C factor (cover and management factor) is extracted using the Normalized Difference Vegetation Index (NDVI) and remote sensing techniques. The P factor (support practice factor) is set to 1 due to lack of data. 
 
Fig 4  Soil Erosion Maps 
 
 
Four major types of soils are clay, clay loam, sandy clay loam and sandy loam, where clay soil is covering a maximum area (72.72%) (Fig 4a). Soil erodibility (K) values are varying from 0.0198 to 0.0894 t ha h ha−1 MJ−1 mm−1 (Fig 4b). The cover management factor (C) is generated using NDVI (Normalized Difference Vegetation Index) prepared from the satellite imagery. Ranges of C factor vary from 0 to 0.87 in the study area (Fig 4c). The R or rainfall erosivity value is higher in the eastern part where rainfall is high and it is gradually decreasing from east to west. Range of R values is 996 to 1529 MJ mm ha−1 h−1 yr−1 ( Fig 4d). Topographic factor (LS) is prepared using slopes (degree and percentage), which are generated from DEMs. The LS factor is the only changeable parameter in the calculation of soil erosion. Variation in grid spaces of DEMs is used for identifying the changes in the accuracy of soil erosion. 
 
Summary
 
The assessment of soil erosion is of great significance for land use planning and watershed management in hilly region. The use of the USLE model integrated to GIS and RS is an effective tool than the time consuming conventional methods for assessing the soil loss vulnerability. The factor maps from R factor, K factor, C factor along with LS factor with the P factor set to 1 are overlayed to create the annual average soil loss map of a region using the Universal Soil Loss Equation ( USLE).

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