Land and water degradations are serious environmental concerns facing South Africa. One of the major causes is human-induced soil erosion due to intensified land uses and environmental degradation caused by bad agricultural practices and inappropriate land uses. Soil erosion is a typical and important example of land degradation that the LandCare program intends to address. In order to evaluate the success of LandCare project in addressing soil erosion evaluation tools which can be applied during the project monitoring and evaluation process. Several soil loss models and field assessment methods were theoretically evaluated on criteria such as the scientific principles, availability and the impact of data requirements of the models. Soil loss models, SLEMSA (Soil Loss Estimation for Southern Africa) and RUSLE (Revised Universal Soil Loss Estimation) and the ACED (Assessment of Current Erosion Damage) method were selected to be tested in a study area that is naturally susceptible to erosion. The soil loss as predicted by RUSLE and SLEMSA and that resulting from visible damage as accounted by ACED method is not comparable. The SLEMSA and RUSLE models vary considerably in extent and approach compared with the field assessment method, ACED. ACED can be used as a participatory learning erosion tool and to identify critical areas on hillslopes. SLEMSA and RUSLE had predictive advantage over ACED and could predict soil loss before and after the LandCare project. Therefore, the models were considered valuable tools to guide decision-making based on the management and use of the natural resources on farmland or by the community. Soil loss models that require readily available input data, such as RUSLE and SLEMSA, are suitable evaluation tools for monitoring and evaluation of soil erosion in LandCare project. Based on the results of the scenario prediction study, it was found that RUSLE could simulate the impact of different agricultural practices much better than SLEMSA. However, the reliability of SLEMSA and RUSLE should be verified with measured data from erosion plots as RUSLE also underestimate the erodibility of the Escourt soil.
Dissertation (MSc (Agriculture))--University of Pretoria, 2006.