WIT Press

Modelling long-term mean hillslope erosion at a large catchment scale


Free (open access)


Volume 1 (2006), Issue 1



Page Range

72 - 89

Paper DOI



WIT Press


B.M. Mutua, A. Klik


To better understand the relative impact of land use and management practices on hillslope erosion, modelling of spatial interrill and rill erosion needs to be undertaken at a catchment scale. This paper describes a spatial modelling procedure and presents the results of the predicted mean annual soil erosion over the Masinga catchment in Kenya. The model used is the Revised Universal Soil Loss Equation (RUSLE) integrated within a Geographical Information System environment. The spatial data layers for RUSLE were generated from the digital elevation model, soil property maps, remotely sensed images and climatic data. The current land use and management practices within the catchment were evaluated to determine their effects on mean annual soil loss. The results show that the present land utilization with lack of soil conservation measures, a rather low standard of husbandry on arable land, gross overstocking and lack of management on range land is resulting in high soil erosion. With the current land use and management practices, only 9.3% of the total catchment area is experiencing soil loss within the allowable tolerable rates of 2.2&#x2013;10.0 ton ha<sup>&#x2212;1</sup> year<sup>&#x2212;1</sup> recommended for the Masinga area. Other feasible alternative land management practices were also modelled. The results from these simulation scenarios were used to assess the effect of implementing best management practices. The integrated approach allows for relatively easy, fast and cost-effective prediction of spatially distributed soil erosion. It thus provides a useful and efficient tool for predicting long-term soil erosion potential and assessing the erosion impacts of alternative land use/cover and conservation support practices.


ArcView GIS, catchment management, conservation tool, hillslope, Masinga, RUSLE, soil erosion modelling