Estimativa da erosão na microbacia do Córrego do Gambá no município de Monte Alto, SP

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Damasceno, Gabriel Ferreira [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/121990
Resumo: The process of occupying space in a disorderly way, the need to increase agricultural and new areas for the expansion of urban centers areas, result in environmental damage, such as erosion caused by water, which are aggravated due to the lack of use of appropriate practices to each unique terrain and the lack of urban planning management, resulting in exacerbated soil loss and compromised quality of water bodies. This work aimed to use remote sensing and Geographic Information Systems (GIS), supported by the predictive model Revised Universal Soil Loss Equation (RUSLE) in environmental analysis to quantify soil loss contributions in the areas of the springs the Gambá stream in the county of Monte Alto/SP. This work presents the factors recommended by RUSLE, as erosivity (R), erodibility (K), use and soil management (C), conservation practices (P), topographic factor (LS), obtained in a GIS environment, allowing to obtain these parameters for the preparation of final maps. Soil loss in 65.7% of the watershed studied, shows lower than 10 Mg ha-1 year-1. Regarding the importance of planning of land use, most of the study area is considered by the estimated values as high susceptibility to soil erodibility, with values between 0.03 to 0.04 Mg h MJ-1 mm-1. In estimating the erosion potential, the total area, 47.3% is classified as very high, with high correlation to the topographic factor. The use of integrated GIS and RUSLE allowed a detailed analysis, allowing pinpoint areas of greatest vulnerability to the process of soil loss in the study area.