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. / Plant Production and Soil Science / unrestricted

<p><a>Indiana is the leading state of cover crop adoption within the Upper Mississippi River Basin. However, since 2015 the cover crop adoption has slowed to a plateau. In order to regain the previous momentum, there must be an increased understanding of the spatiotemporal dynamics of cover crop adoption on the county and watershed scale. Currently, the cover crop adoption is monitored biannually through a driving transect survey method that investigates only 8.5% of the watershed and extrapolates to the entire county. However, the observations made by the driving transect survey can merely cover limited fields and is time-consuming. In addition, the driving transect survey did not provide comparative analysis among consecutive years. Therefore, we developed a rapid cover crop survey method by using remote sensing technology. The fundamental objectives of this research are: (1) evaluating the accuracy of the rapid cover crop survey method relative to the driving transect data and determining the best cut-off value (COV) of Normalized Difference Vegetation Index (NDVI); (2) performing a hindcasting analysis of cover crop adoption within the Big Pine Creek Watersheds within the period of 2014-2018 by employing a rapid cover crop survey remote sensing techniques; (3) accessing cover crop adoption management tendencies of farmers within the Big Pine Watersheds, and (4) determining the cover crop adoption tenure of farmers within the Big Pine Creek watersheds between 2014 and 2018. The cover crop management tendency represents the farmers’ preference on cash crop rotation method after harvesting cover crops, and the cover crop adoption tenure means that how often farmers adopt cover crops in a specific field in the research period.</a></p> <p>The results of this research demonstrated that relative to the conventional driving transect, remote sensing is a feasible method to successfully detect cover crop adoption on a county and watershed scale. Over a 4-year period (2015-2018), Producer’s Accuracy (PA) under the best COV, which represented how much vegetation-covered field recorded in transect data that can be captured in the processed NDVI map, was 89.02%. This PA value was relatively high compared with previous spatial crop classification research. The rapid remote sensing method also provided individual field locations of cover crop adoption over time within the entire watershed, compared to the driving transect that only gives extrapolated average of adoption. The hindcasting analysis of cover crop adoption revealed a 74% increase in cover crop acreage in the watershed from 2014 to 2018, which equated to a 0.71% increase in land receiving cover crops among all cultivated land annually. The evaluation of farmer cover crop adoption tendencies demonstrated that over a 4-year period, cover crop adoption going into corn was 19.7% greater on average relative to before soybean. Another key finding was that the level of cover crop adoption annually in the watershed was heavily influenced by the cash crop rotation. The cover crop tenure analysis demonstrated that agricultural fields of greater cover crop tenure represented the smallest portion of the cultivated land in the watershed, where 84.2% of the watershed was void of cover crop adoption and field that received cover crops for more than 4 consecutive years represented only 1% of cultivated land.</p> <p> To conclude, we are confident that the rapid cover crop survey method could replace the traditional driving transect survey. Our findings suggest that rapid assessment methods of cover crop adoption involving processed NDVI map could help advance the effectiveness, speed, and accuracy of cover crop adoption and assessment in the state of Indiana and the entire Mississippi River Basin region.</p>

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Costs and benefits associated with erosion reduction and adoption of soil conservation practices for a representative farm in a watershed in Honduras are examined in a linear programming framework. Special attention is paid to income-soil loss tradeoffs, income-risk tradeoffs, and on the effect of different farmers' planning horizons on net farm income. A representative farm model for the area was constructed to achieve the objectives of the study. Twelve farmers in the region were surveyed, crop budgets were prepared, and soil loss values were calculated to provide the information required to construct this representative farm. A linear programming model that maximizes net farm income is used to examine the effect of different soil loss levels on farm income. A MOTAD model that minimizes deviation in income (risk) is used to determine risk levels while income and/or soil loss levels restrictions are imposed. Results indicate that considerable reductions in the amount of soil loss can be achieved in the study area. Erosion is reduced from 328.24 ton./mn./year to 6.56 ton./mn./year1 when constraints are imposed on the model. The reduced erosion lowers income from L.5929.24/year for high erosion rates to L.2825.8l/year for low erosion rates. Low levels of soil erosion are achieved at the expense of higher levels of risk. High levels of income are associated with high levels of risk regardless of whether soil loss constraints exist or not. Small differences in income exist among the four planning horizons analyzed. The best soil conservation practices for this region turned out to be the cultivation of coffee on the highest slopes, the use of live barriers and terraces, and the use of conventional and minimum tillage. / Master of Science

M.S.

The purpose of this study is to secure and organize materials on non-engineering phases or Soil Conservation, to be used by teachers and students in Vocational Agricultural Classes. The first part of each unit is designed for use as reference study by students of Vocational Agriculture and the second part consists of a job analysis intended primarily for the use of the teacher. (The Job analysis form is that used by the U.S. Office of Education.) Available information on Soil Conservation was secured by interviewing representatives of agencies engaged in this field of work, namely; Soil Conservation Service, Agricultural Adjustment Agency, the State Experiment Station and the Virginia Polytechnic Agronomy Department. All available literature and illustrative material were reviewing and made personal visits to farmers. The most important phases of study in the field of non-engineering soil conservation were selected, made a job analysis of each phase, and arranged in a form suitable for use by teachers in Vocational Agriculture. The most up-to-date practices in non-engineering soil conservation were selected and organized, and designed especially as a reference for use by boys in vocational agriculture classes. / M.S.