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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Publications at this Location » Publication #118898

Title: SOIL EROSION PREDICTION USING RUSLE FOR CENTRAL KENYAN HIGHLAND CONDITIONS

Author
item ANGIMA, S - PURDUE UNIVERSITY
item Stott, Diane
item O'NEILL, M - ICRAF, KENYA
item ONG, C - ICRAF, KENYA
item WEESIES, G - USDA-NRCS

Submitted to: Agriculture Ecosystems and the Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/7/2003
Publication Date: N/A
Citation: N/A

Interpretive Summary: Soil erosion by water is a serious global problem, including Africa. There are many methods to control soil erosion, but due to economic considerations, intervention erosion control techniques must be targeted to areas that will most benefit. Use of erosion models can aid in selecting the these areas. We conducted a study at the Kianjuki catchment in Central Kenya to determine if the RUSLE Model (Revised Universal Soil Loss Equation, Ver. 1.06) would adequately predict the annual soil loss from this area, and use the model to determine the erosion hazards and target areas for initiating conservation measures. All RUSLE parameters were determined using local soil and climatic information. Crop databases were determined for the dominant cropping patterns in the catchment, including corn-soybean double cropping, coffee, and banana. Conservation practices included existing terraces where coffee is grown. Total annual soil loss predictions varied from one slope segment to the next and ranged from 60 to 245 tons of topsoil per acre/year for unprotected slopes ranging up to 53%. The model pinpointed site-specific erosion hazards associated with each slope segment in the catchment for different management practices. Tests showed that proposed mixed grass-shrub hedges markedly reduced erosion, and compared well with local erosion experiments that included 3 years of field data. Developing databases of local crop, soil and climatic conditions will allow this model to be used throughout the region for planning and resource allocation.

Technical Abstract: Soil erosion by water is a serious global problem. In Africa, about 5 Mg ha-1 of productive topsoil is lost to lakes and oceans each year. Effective erosion control requires appropriate intervention techniques after meaningful and accurate estimation of soil loss by water has been undertaken. This study was conducted at the Kianjuki catchment in Central Kenya to predict annual soil loss using the Revised Universal Soil Loss Equation (V1.06) to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures. The factors for use in RUSLE were calculated for the catchment. Rainfall erosivity R-factor was 8527 MJ mm ha- h-1 yr-1 and the annual average soil erodibility K-factor was 0.016 Mg h MJ-1 mm-1. Slopes in the catchment varied between 0 and 53% with steeper slopes having overall LS-values of over 17. The C-factor values were computed from existing cropping patterns in the catchment, including corn-bean 1- year rotation, coffee, and banana. Support practice P-factors were from terraces that exist on slopes where coffee is grown. Total annual soil loss predictions varied from one overland flow segment to the next and ranged from 134 Mg ha-1 yr-1 for slopes with average LS-factors of 0-10 to 549 Mg ha-1 yr-1 for slopes with average LS-factors of 20-30, which is more than the estimated soil loss tolerance (T) for the area of 2.2- 10 Mg ha-1 yr-1. Using 3 years of field data, the RUSLE model was able to pinpoint site specific erosion hazards associated with each overland flow segment in the catchment for different cropping patterns and management practices. Developing a database of local agro-ecological conditions will allow this model to be used throughout the region.