Modelagem temporal e espacial da erosão hídrica na sub-bacia hidrográfica do Ribeirão Caçús, Alfenas, MG

• Ano de defesa: 2014
• Autor(a) principal: Olivetti, Diogo
• Orientador(a): Mincato, Ronaldo Luiz
• Banca de defesa: Landgraf, Paulo Roberto Corrêa, Polo, Marcelo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Alfenas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ecologia e Tecnologia Ambiental
• Departamento: Instituto de Ciências da Natureza
• País: Brasil
• Palavras-chave em Português: Ciências do solo; Conservacao do Solo; Uso do solo; Erosão do solo; Solo - Degradação
• Área do conhecimento CNPq: CIENCIA DO SOLO::MANEJO E CONSERVACAO DO SOLO
• Link de acesso: https://repositorio.unifal-mg.edu.br/handle/123456789/569

Water erosion is one of the main soil degradation processes and land cover changes can intensify it. Thus, modeling soil erosion studies associated with the multitemporal analysis of land use are important to assess the effects of such changes in sediment production. Therefore, according with the land use changes from 1986 to 2011, the objective of this work was to estimate the water erosion in Latosols of Ribeirão Caçús watershed, southern Minas Gerais State, southeastern Brazil, by the Revised Universal Soil Loss Equation (RUSLE) and to compare with the soil loss tolerance (SLT). The RUSLE, created in the end of the twentieth century, is an adaptation of the Universal Soil Loss Equation (USLE), because its parameters are calculated with adjustments in seasonal variations and the geographic information system (GIS) techniques. These models are more applied in water erosion estimate due to availability and simplicity of information. Both are based on the formula: A = R*K*LS*C*P, where: A is the soil loss; R is the rainfall erosivity; K is the soil erodibility; LS is the topographic factor; C is the soil management and use factor and P is the support practice factor. In this work the R factor was obtained from literature; the K factor was obtained by application of estimating indirect model; the LS factor was obtained from digital elevation model (DEM); the C factor was obtained by soil use multitemporal mapping using GIS and remote sensing techniques from satellite images, and the C values were obtained from literature. The P factor is the poorest in literature and was not considered. Results indicate that changes in land use intensified the erosive process. In terms of area, soil loss values above of the SLT increased from 7.9% in 1986 to 8.4% in 2011. This growth was due to the decrease of pasture lands and native forest and increase of bare soil and sugarcane, corn and coffee crops areas. The RUSLE model associated with GIS is one simple and useful tool that allows identifying areas of soil degraded and to auxiliary in definition of soil recovery and conservation measures.