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ADDIS ABABA UNIVERSITY
SCHOOL OF GRADUATE STUDIES
FACULITY OF NATURAL SCIENCE

DEPARTMENT OF EARTH SCIENCES



ASSESSMENT OF LAND DEGRADATION USING GIS BASED MODEL AND

REMOTE SENSING IN BISHAN GURACHA-ADILO SUBCATCHMENTS,

SOUTHERN ETHIOPIA





BY

TSEGAYE BIRKNEH




ADDIS ABABA
JULY, 2007

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4.4.4 USLE Model Parameters Estimation

The Universal Soil Loss Equation (USLE) is accentuated as one of the most significant

developments in soil and water conservation in the 20th century. It is an empirical

technology that has been applied around the world to estimate soil erosion by raindrop

impact and surface runoff. As already stated in literature reviews, this model is selected

and applied in estimating soil loss has been attributed to its clear and relatively

computational simple inputs compared to others conceptual and possessed based models.

Parameterization of each variable has been performed just as follows.


Rainfall Erosivity (R)

The ability of erosion agents to cause soil detachment and transport is erosivity. It is an

index that represents the energy that initiates the sheet and rill erosion. The erosivity of

rain fall is due to partly to direct raindrop impact and partly to the run off that rainfall

generates. The ability of erosion agents to cause soil erosion is attributed to its rate and

drop size distribution, both of which affect the energy load of a rainstorm. The erosivity

of a rainstorm is caused by its kinetic energy. In simple way, rainfall erosivity is a term

used to describe the degree of soil loss from cultivated fields due to rainfall effect when

other factors of erosion are held constant.


Even though there are different computational techniques to compute erosivity factor

across the globe depending on the use of various inputs, estimating rainfall erosivity in

here is based on the calculation of R generated by Hurni (1985), derived from a spatial

analysis regression (Hellden, 1987) adapted for Ethiopia on the basis of annual

precipitation

R= -8.12 +0.562*P
Where p is mean annual rainfall in mm

In order to compute R factor using such formula five stations with mean annual rainfall

of 18 years were used. After having averaged 18 years (1987-2004) for each station,

interpolation was made to make the points distribution into surface. When performing

this spatial analyst of IDW (Inverse Distance weighted) with the principle of things found

to be close to one another are more alike than those that are farther apart has been used by

specifying the cell size (grid) into 30m.

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When applied the formula to generate rainfall erosivity factor from the values of long

year mean rainfall, R factor seen in Table 4.3 and its converted grid raster in Fig 4.3 was

obtained.


Table 4.3 Erosivity Factor (R) Estimation


Station’s name Mean annual rainfall(mm) R_factor
Kulito 1152 639
Shone 1375 887
Durame 1593 764
Boditi 1220 599
Angacha 1081 677




Fig. 4.3 Raster format of Rainfall Factor

Soil Erodibility Factor (K)

Soil erodibility factor denoted by letter “K” in the USLE reflects the liability of a soil

type to erosion, the unit depending upon the amount of soil occurring per unit of erosivity

and under specified conditions. The inherent properties of the soil would have more

influence for being liable to erosion than other factors. However, some soils erode more

readily than others even when all other factors are the same.

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1995 7.9 63.4 106.8 264.1 105.6 122.8 107.1 115.0 111.3 52.0 4.0 26.9 1086.9
1996 72.0 28.9 101.9 196.7 121.3 245.1 168.4 218.4 149.2 15.7 20.5 1.0 1339.1
1997 3.5 10.0 84.1 247.6 206.4 101.8 120.8 128.3 41.2 227.5 265.3 13.4 1449.9
1998 79.3 109.8 133.1 230.3 290.4 160.9 150.9 145.8 67.5 131.8 20.2 6.0 1526.0
1999 32.3 35.7 42.7 105.9 98.5 94.3 200.7 180.5 40.1 174.4 17.9 15.2 1038.2
2000 13.0 23.6 26.4 92.6 202.8 96.9 83.1 142.1 69.8 130.5 81.7 22.5 985.0
2001 10.1 67.2 100.2 123.0 245.7 134.2 212.4 209.5 141.6 106.4 33.1 28.6 1412.0
2002 58.8 10.9 147.7 113.6 119.8 59.6 137.1 160.6 130.5 52.2 1.5 113.3 1105.6
2003 59.1 20.3 85.6 182.4 64.1 143.1 200.9 159.1 108.3 69.4 36.6 34.0 1162.9
2004 78.3 41.1 43.0 154.5 85.3 71.3 217.4 76.1 173.1 69.8 24.1 50.7 1084.7

Total 21954.8


ANNEX 3
Population Number at Woreda Level


Woreda 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Kedida
Gamela 124,497 128,945 133,408 137,902 142,423 147,004 151,635 156,294 161,000 165,783 170,638 175,591

Badawacho 180,156 186,377 192,634 198,914 205,223 211,602 218,037 224,520 231,036 237,646 244,345 251,159

Alaba 153,070 158,580 164,105 169,672 175,275 180,953 186,697 192,474 198,315 204,254 210,283 216,439

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