Evaluating soil erosion and mapping using GIS

1. SOIL EROSION EVALUATION AND MAPPING USING
GIS
BY
1. JOHN NG’ANG’A GATHAGU
2. BRIAN OMONDI ODUOR
SUPERVISOR: PROF. ABDELKADER EL GAROUANI

2. Soil Erosion
• Process that invoves;
– Detachment
– Transportation and
– Deposition
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3. Hydrological basis of Soil
Erosion
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4. Global status of soil erosion
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5. • There are several GIS-Based models used to estimate soil loss.
The models include;
– Distributed soil erosion model
– Modified USLE
– Gully Surface Growth
– Gully Head Advance.
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6. Soil erosion evaluation
• Integration of RUSLE and GIS has been used for soil loss
estimation.
• To run the model, five input raster files are needed as data files;
– Rainfall erosivity factor, R
• Related to rainfall through the detaching power of
raindrops
– Soil erodibility factor, K
• Inherent susceptibility of soil to erosion; depends on
mineralogical, chemical, physical and morphological
attributes of the soil
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7. – Topographic factor, LS
• Slope length and slope steepness influence surface
runoff speed
– Crop management factor, C
• Ratio of soil under a given crop to that of the base soil
(Morgan, 1994)
– Practice factor, P, of the map area
• Erosion management practice; varies from 0-1
depending on the soil management activities in a given
plot
Average annual soil loss per unit area (tons/ha)
A = R*K*LS*C*P
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9. Erosion evaluation in Taita
Hills, Kenya
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11. Generation of LS factor from the
DEM
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17. Amount of soil eroded in tons/ha/yr
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18. Depth of soil eroded in mm/yr
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19. Soil Erosion mapping using
GIS
• In soil and water conservation, the objective of GIS application
is to capture soil erosion data, set up database and model for
soil erosion evaluation and management.
• GIS will INCREASE efficiency and accuracy of data capturing;
massive data accessing efficiency and forecasting.
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20. USLE predicted soil loss in ton/yr
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21. Spatial variation vs Soil Erosion Risk in
Mara Catchment
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23. • Eroded area DECREASED from 32.1% in 2004 to 25.43% in 2010.
• REDUCTION in Erosion risk was mainly observed in remote mountains
with high vegetation coverage, where human activities were
infrequent and vegetation coverage was high.
• INCREASE in Erosion risk was observed in barren mountains, open
forest land, young plantation land, and bare soil caused by
development projects in the construction stage at which vegetation
coverage was low.
• The decrease in soil erosion risk and the reduction of eroded area from
2004–2010 show that soil erosion risk can be reduced by increased
vegetation cover or the conversion of slope farmland to terraced field23

24. Erosion Risk Mapping of Kartalkaya Dam Watershed, Turkey
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25. Potential Vs Actual Soil Erosion Risk Maps of
Katalkaya Dam Water shed in Turkey
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26. • Potential erosion risk map generated by overlapping soil
erodibility, erosivity, and slope layers
• Actual soil erosion risk map = Land cover map + potential
erosion risk map
• The difference between the areas of potential and actual erosion
risk indicates the effects of vegetation cover on soil erosion
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27. Soil Mapping unit of Manjunto Island
Eroded area INCREASED in 2009 compared to 2000 due to
Dryland Farming in the lower areas of the basin 27

28. Annual soil erosion in Mae Ao, Thailand
Average annual rate of erosion in 1992 Average annual rate of erosion in 1996
Average annual erosion rate REDUCED in 1996 compared to 1992 due to
the conservation measures and plantation program taken up in the area28

29. • Evaluation of soil erosion risk
vulnerability is essential for;
– sustainable land-use planning and
comprehensive local and regional
development.
– plan the future land-use
alternatives and to apply specific
soil conservation practices at the
identified high-risk areas
– solid base to create a Decision
Support System (DSS)
CONCLUSION
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30. References
 Morgan, R.P.C. 1994. Soil Erosion and Conservation. Silsoe College, Cranfield
University.
 Bizuwerk, A., Taddese, G., & Getahun, Y. 2008.Application of GIS for Modeling Soil
Loss Rate in Awash Basin, Ethiopia. International Livestock Research Institute (ILRI).
 Biswas Sumantra & Pani Padmini. 2015. Estimation of soil erosion using RUSLE and
GIS techniques: a case study of Barakar River basin, Jharkhand, India.
 Shi, Z. H., Cai, C. F., Ding, S. W. 2004. Soil Conservation Planning at the Small
Watershed Level Using RUSLE with GIS: A Case Study in the Three Gorge Area of
China. Catena, 55(1): 33–48.
 Mwawasi, Nellly. 2013. Risk assessment analyses of soil erosion using GIS: A case
study of Taita Hills, Kenya. University of Nairobi
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