EI, which 
imum 30 
f silt, and 
entage of 
s from a 
22.13 m) 
loss from 
effect of 
ing and 
ical and 
inder six 
>xpressed 
) prepare 
, ILWIS 
d for the 
ours and 
and soil 
ire 2 and 
\rea 
IAPRS & SIS, Vol.34. Part 7, "Resource and Environmental Monitoring”, Hyderabad, India,2002 
For the preparation of soil texture map and other details like 
soil depth, soil structure, permeability, percent organic matter 
etc, the field surveys were carried out to collect the soil 
samples from various locations (26 stations). The samples were 
analysed for its textural characteristics in the laboratory. The 
digitised contour and spot height information from toposheet 
were used to obtain Digital Elevation Model (DEM), which is 
further used for the calculation of LS factor. 
Calculation of USLE Parameters 
R-Factor: The R-factor was calculated using the average annual 
and seasonal rainfall of three raingauge stations. The following 
equations were used to estimate annual and seasonal R-factor 
(Singh et. al, 1981). 
Ra = 79 - 0.363 * P (2) 
Where, Pisrainfall in mm 
Ra is annual R factor 
  
In ILWIS environment, a rainfall distribution map was created 
using the interpretation technique. Rain erosivity map was then 
developed by applying the above equations through map 
calculation function. 
K-Factor: Soil erodibility nomograph (USDA, 1978) was used 
for determining K-factor based on the particle size, the organic 
matter present, and the permeability class. An attribute table 
was prepared using these values for different soil types. The 
soil erodibilty map was prepared using the soil map and K- 
factor table. 
LS-Factor: For slope steepness upto 2196, the original USLE 
formula (USDA, 1978) for estimating the slope length and 
slope steepness was used: 
LS= (L/72.6) * (65.4 * sin (S) + 4.56 * sin (S) + 0.065) -—--(3) 
Where, L is slope length in m 
S is slope steepness in per centage 
For slope steepness of 21 % and more, the Gaudasamita 
equation (USDA, 1978) was used: 
LS = (L/22.1°7 * (6.432 * sin (S7) * cos (S)) — 4) 
The slope map was generated from the DEM in ILWIS 
environment by applying the gradient filters dfdx and dfdy. The 
relationship between the slope steepness in percentage (S) and 
slope length in metres (L) for the study area was estimated as; 
L = 0.4*S + 40 (5) 
  
From the slope map, using the above equation in map 
calculation function, slope length map was created. By 
combining the slope steepness and slope length map, LS- factor 
map was created. 
CP-Factor: The calculation of CP factor for each land cover 
unit was made on the basis of management practices, physical 
conditions and characteristics of cover units. CP factor for 
various cropping and management practices for the study area 
are given in table 4. The CP factor map for the USLE was created by 
linking the attribute table of CP factor with the land use map. 
3. RESULTS AND DISCUSSION 
Land Use/Cover 
Land use is an important aspect for determining the various 
phenomena like infiltration, overland flow, evaporation and 
interception etc. It has significant influence on the soil erosion 
process. The four major land use/cover classes i.e. forest, shrubs, 
agriculture, and barren land were identified in the study area. The 
spatial distribution of these land use/cover classes is described in 
Table 2. 
  
  
  
SI. Land type Area in Area in 
No. Sq.km. ( 96) 
1 Forest 338.04 62.60 
2 Shrubs 107.09 19.85 
3 Agriculture 88.56 16.40 
4 Barren 6.21 1.15 
  
  
  
  
  
Table 2. Land Use/Cover Classification in Malaprabha sub basin 
Soil Texture 
Two major soil groups were identified in the study area after the 
laboratory analysis of the collected soil samples. Their spatial 
distribution is given in Table 3. 
  
  
  
  
  
  
  
SI. Land type Area in Area in 
No. Sq.km. ( 96 ) 
1 Red Loamy Soil 432.00 80.00 
2 Medium Black Soil 108.00 20.00 
  
Table 3. Soil Groups identified in Malaprabha sub basin 
Soil Loss 
The average annual soil loss was estimated by using USLE model 
with the conventional method and GIS technique. Its shows a 
considerable match with the one determined by using GIS technique 
(Table 4). 
  
  
  
  
Si. Land use | Average Soil Loss in 
No. | type tons/ha/year 
USLE GIS Technique 
estimated 
1 Forest 1.27 0.86 
2 Shrubs 3.27 2.89 
3 Agriculture 12.32 11.07 
4 Barren 3.57 5.41 
  
  
  
  
  
Table 4. Average Annual Soil Loss estimated by USLE method and 
GIS technique 
697