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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Publications at this Location » Publication #114110
Title: SOIL EROSION PREDICTION USING RUSLE IN CENTRAL KENYA

Author
item ANGIMA, SAMSON - PURDUE UNIVERSITY
item Stott, Diane
item O'NEILL, M - NEW MEXICO STATE UNIV
item ONG, C - ICRAF
item WEESIES, GLENN - USDA-NRCS

Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 8/30/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Soil erosion by water is a serious global problem. Effective erosion control requires appropriate intervention techniques and a monitoring system to ensure continued success. This study was conducted at the Kianjuki catchment in Embu, Central Kenya, to estimate annual soil loss using the Revised Universal Soil Loss Equation (RUSLE) in comparison to actual erosion rates using runoff plots. All the RUSLE factors were determined for the area. Rainfall erosivity R-factor was 8527 MJ mm ha-1 h-1 yr-1 and a soil erodibility K-factor 0.17 Mg h MJ-1 mm-1. Slopes in the catchment varied between 0 and 53% with steeper slopes having overall LS-values of over 29. The C-factor values were computed from local cropping patterns that included corn-bean one-year rotation, coffee, and bananas. Support practice P-factors were determined for terraces that exist on slopes where coffee is grown. Total annual soil loss predicted varied from one overland flow segment to the next and ranged from 134 Mg ha-1 yr-1 for slopes with LS-factors of 0-10 to 549 Mg ha-1 yr-1 for slopes with LS-factors of 20-30. The RUSLE model under- predicted soil loss by about 50 Mg ha-1 for slopes with LS of 0-10 compared to erosion rates from runoff plots in the catchment. Using input parameters such as C and P-factors calculated for the local conditions. RUSLE can be used to estimate soil loss in similar ecological regions. This will allow the targeting of limited resources to the land areas that are most vulnerable to soil erosion and having the largest impact on the surrounding environment, especially water quality.