Adaptation of RUSLE to Model Erosion Risk in a Watershed with Terrain Heterogeneity

is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract The modeling capability of the Revised Universal Soil Loss Equation (RUSLE) on a heterogeneous landscape is usually limited due to computational challenges of slope length and slope steepness (LS) factor. RUSLE can be adapted to Arc-Macro (C++) executable programs to obtain LS values even for highly variable landscapes based on Digital Elevation Models (DEMs); and then predict erosion risk. The objective of this study was to compute LS factor from DEM using C++; and predict soil erosion risk in a banana-coffee watershed of the Lake Victoria Basin (LVB) of Uganda. DEM data of Nabajuzi watershed were used as an input file for running the (C++) executable program to obtain LS factor. The predicted LS values were calibrated against tabulated LS values; and a strong linear relationship (R = 0.998) was observed between them. The LS factor increased with slope length and slope gradient. Erosion risk across landuse were predicted as follows: small scale farmland (38 t ha-1 yr-1), built up area (35 t ha-1 yr-1), grassland (25 t ha-1 yr-1), woodland (11 t ha 1 y