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SOIL EROSION EVALUATION AND MAPPING USING
GIS
BY
1. JOHN NG’ANG’A GATHAGU
2. BRIAN OMONDI ODUOR
SUPERVISOR: PROF. ABDELKADER EL GAROUANI
Soil Erosion
• Process that invoves;
– Detachment
– Transportation and
– Deposition
2
Hydrological basis of Soil
Erosion
3
Global status of soil erosion
4
• 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.
5
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
6
– 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
7
8
Erosion evaluation in Taita
Hills, Kenya
9
10
Generation of LS factor from the
DEM
11
12
13
14
15
16
Amount of soil eroded in tons/ha/yr
17
Depth of soil eroded in mm/yr
18
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.
19
USLE predicted soil loss in ton/yr
20
Spatial variation vs Soil Erosion Risk in
Mara Catchment
21
22
• 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
Erosion Risk Mapping of Kartalkaya Dam Watershed, Turkey
24
Potential Vs Actual Soil Erosion Risk Maps of
Katalkaya Dam Water shed in Turkey
25
• 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
26
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
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
• 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
29
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
30
31

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Evaluating soil erosion 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 2
  • 3. Hydrological basis of Soil Erosion 3
  • 4. Global status of soil erosion 4
  • 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. 5
  • 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 6
  • 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 7
  • 8. 8
  • 9. Erosion evaluation in Taita Hills, Kenya 9
  • 10. 10
  • 11. Generation of LS factor from the DEM 11
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  • 17. Amount of soil eroded in tons/ha/yr 17
  • 18. Depth of soil eroded in mm/yr 18
  • 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. 19
  • 20. USLE predicted soil loss in ton/yr 20
  • 21. Spatial variation vs Soil Erosion Risk in Mara Catchment 21
  • 22. 22
  • 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 24
  • 25. Potential Vs Actual Soil Erosion Risk Maps of Katalkaya Dam Water shed in Turkey 25
  • 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 26
  • 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 29
  • 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 30
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