A erosão hídrica é uma das maiores causas de depauperamento dos solos no mundo. No Brasil, a erosão causa a perda de produtividade, o avanço das fronteiras agrícolas, o assoreamento e a contaminação dos corpos d'água e a perda da biodiversidade. Neste cenário, para contribuir com o planejamento ambiental e a gestão territorial, foi avaliada a vulnerabilidade ambiental à erosão hídrica da sub-bacia hidrográfica do rio Mandu, sul de Minas Gerais, pela análise empírica da fragilidade dos ambientes naturais e antropizados. Para tanto, foram considerados os componentes da paisagem: uso do solo, relevo, solo, geologia e clima, em ordem decrescente de importância, pelo Processo Analítico Hierárquico. Foi verificado que os usos do solo estão adequados em 32,72% e inadequados em 67,28% da área. Mais especificamente, 17,68% apresentam forte propensão à erosão hídrica e 0,08% são locais em que os impactos diretos da erosão hídrica são irreversíveis. Portanto, a adoção de técnicas de manejo adequadas para as pastagens, a erradicação dos solos expostos e a redefinição dos locais de produção de café e da agricultura temporária atenuariam os impactos ambientais.

Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing techniques and statistical analyses. In the Potential Erosion Method, the coefficient indicating the mean erosion intensity was 0.37, which corresponded to erosion category IV and indicated weak laminar erosion processes, and the total soil loss was 649.31 Mg year -1 and the mean was 1.46 Mg ha -1 year -1 . These results were consistent in magnitude with those obtained in the Revised Universal Soil Loss Equation, which estimated a mean soil loss of 1.52 Mg ha -1 year -1 and a total soil loss of 668.26 Mg year -1 . The Potential Erosion Method suggests that 1.5% of the area presents potential soil losses above the soil loss tolerance limit, which ranged from 5.19 to 5.90 Mg ha -1 year -1 , while the Revised Universal Soil Loss Equation indicated that 7.3% of the area has potential soil losses above the limit. The maximum sediment discharge was 60 Mg year -1 , meaning that 9.3% of the total soil loss reached the depositional areas of the river plains or watercourses. The Potential Erosion Method was efficient in the evaluation of water erosion in tropical soils, and the results were consistent with models widely employed in the estimation of soil losses. Thus, the model can support the evaluation of soil losses in Brazil and is a robust tool for evaluating the sustainability of agricultural activities.

Water erosion is one of the most important soil degradation processes and it can be intensified by land use and vegetal covering changes. Thus, water erosion modeling studies associated to multi temporal analyses of land use are effective in assessing how changes in land cover affects sediment yield. Therefore, considering the modifications in the land use from 1986 to 2011, the aim of this study ranged to estimate water erosion rates and compare them to the soil loss tolerance (SLT) limit in the Latosols (Oxisols) at Ribeirão Caçús sub-basin, in the South of Minas Gerais State, Southeast Brazil, by means of the Revised Universal Soil Loss Equation (RUSLE) in association with the geographic information system (GIS), and geostatistical techniques. So, for each year mapped, soil loss averages were compared by t test at 5% significance to assess the soil degradation stage. The results indicated that, in the period, the soil loss average rate was from 2.4 to 2.6 Mg ha -1 year -1 and the areas with soil loss above the limit of SLT were around 8.0%. The t test demonstrated there was no considerable difference among the soil loss averages (p = 0.18). In consequence, the area of degraded soils did not increase. Thus, the RUSLE model in GIS is a simple and useful tool to estimate the soil loss and help define soil conservation and recovery measures.

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