IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring", Hyderabad, India, 2002 
  
potatoes, cabbage, cauliflower and tomatoes. Under this, dried 
twigs, branches of natural forest spread over the raised bed 
which are covered with thin layer of soil burnt as such before 
raising the crops in the buns. These lands are highly prone to 
severe erosion. 
Pine (Pines khasiana) is major forest species at the higher 
elevation of mountains of major hills. The lower elevations of 
hills are covered by tree species viz., Schima vallichi, 
Phyllanthus emblica etc. Vast areas of grassland with scrubs or 
without scrubs are present in few places. Barren, stony 
wastelands were also lying in the area. 
3. METHODOLOGY 
Universal Soil Loss Equation (USLE) and Sediment Yield 
Index (SYI) (AIS & LUS) models were employed in a GIS 
(Geographic Information System) environment to predict 
erosion hazards and for prioritization of sub-watersheds for 
conservation planning for sustainable management of natural 
resources. Individual spatial layers in raster based GIS (ILWIS 
version 3.0) software were prepared for each factor pertaining 
to the models and integrated in raster based spatial domain to 
predict soil and sediment yield for each pixel, represented by 
235x23.5m. 
3.1 USLE model 
The Universal Soil Loss Equation (USLE) (Wischmeier & 
Smith, 1978) predicts the average annual soil loss based on 
rainfall pattern, soil type, topography, crop system and 
management practices. The USLE model calculate the soil 
erosion as follows : 
A = RK ES CP (1) 
Where A = annual soil loss in t ha! yr! 
R = Rainfall erosivity factor (J mm. m? h^!) 
K = Soil erodibility factor (t J! mm!) 
L z Slope length factor 
S = Slope steepness factor 
C = Crop/Vegetation and management factor 
P = Support practice factor 
USLE factor values are explained as: 
3.1.1 Rainfall erosivity (R) factor was calculated using the 
equation 2 (Bhattacharya, 1993). - 
Rainfall erosivity = E," p* >1omm /P (2) 
Where p? >i0mm = average monthly rainfall of the months 
having at least 10mm of rain 
P = average annual rainfall in mm 
m = months having >10 mm rainfall 
The rainfall erosivity factor was determined to be 864.25. 
3.1.2 Soil Erodibility (K) factor is measure of the 
susceptibility of soil particles to detachment and transport by 
rainfall and runoff. Soil texture, structure, organic matter and 
permeability influence of the soil erodibility. It was computed 
by using the Equation 3. 
K = 2.8*10" M! (12-a)+ 4.3*10* (b-2) + 3.3*10*%(c-3) (3) 
Where K = Soil erodibility factor 
a = Organic matter content 
b = Structure of soil 
¢ = Permeability 
M = (% Silt + % Very fine sand) * (100-% clay) 
Representative soil samples from each physiographic unit were 
collected during the field survey. The soil samples were taken 
to the laboratory and analyzed for percentage of fine sand, silt, 
clay and organic matter. These values were used to estimate 
the erodibility (K) factor. The K —factor map was prepared by 
digitizing the physiographic-soil map on scale 1:50,000. 
3.1.3 Topograpahic factor (L and S) 
The contour and drainage were digitized separately from the 
topographic map of scale 1:50,000. The slope length for each 
physiographic / land use unit was measured during field survey, 
as well as computed by overlying contour map over drainage 
map. The contour map was used to build up DEM (Digital 
Elevation Model) to determine slope steepness (S) using GIS. 
The slope steepness (S) and length (L) factors are computed 
using Equation 4, 5 and 6 , respectively. 
L3(1/22.13)" (4) 
S = 10.8 sin0 + 0.03 for slopes < 9% (5) 
S = 16.8 sin0 - 0.50 for slopes » 996 (6) 
Where m = an exponent that depends on slope steepness, 
being 0.5 for slopes exceeding 5 percent, 0.4 for 4 
percent slopes and 0.3 for slopes less than 3 percent. 
A = Slope length 
0 = Slope angle 
The LS - factor was determined by multiplying the L and S — 
factor by map cross analysis in GIS. 
3.1.4 Crop and management (C ) and conservation practice 
* (P) factors were based on land use / land cover map prepared 
by visual analysis of IRS IC LISS III + PAN merged false 
colour composite on scale 1:25,000 acquired on dated 07" 
January 2000. Field survey was conducted for ground truth of 
various land use / land cover and to determine various soil 
conservation practices in the area. The USLE cover and 
management factor ( C-factors) and conservation practices (P- 
factors) corresponding to each land use types were determined 
from USLE guide tables (Wischmeier & Smith, 1978). These 
values were used to reclassify the land use / land cover map to 
obtain the CP- factor map. 
3.1.5 Soil Erosion Hazard was estimated by multiplying the 
USLE factors map using equation 1. The soil loss values 
obtained were classified into five classes to generate erosion 
hazard map shown in Figure 2. The soil loss map was 
intersected with sub-watershed map and weighted average soil 
loss of each sub-watershed was computed from attribute table 
and priority of sub-watershed assigned for conservation 
planning. 
    
3.2 
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Figur