Modelagem espacial de áreas de recarga subterrânea em região de afloramento do sistema aquífero guarani (sag), em Brotas/SP
Ano de defesa: | 2014 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Estadual Paulista (Unesp)
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Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11449/123232 http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/13-04-2015/000819924.pdf |
Resumo: | In areas of groundwater recharge water infiltration into the soil at depth is critical to that demand does not exceed supply of water. Different methods of handling the soil due to its occupation will put pressure on this resource, and generate different responses in their ability to recharge. Modeling the spatial variability of physical, and hydraulic properties of the soil is a key issue for the success of management systems of land use that allow recharging of groundwater. Through interpolation methods you can access this information, and map more favorable or unfavorable to the recharge areas within a spatial prediction model that many different variables that explain the variation in groundwater levels. Thus, the aim of this work was to model the different levels of response Guarani Aquifer System (SAG) as a function of land use and hydro-physical soil properties, at Ribeirão da Onça basin in Brotas / SP. Through a survey of variables such as texture, grain size, hydraulic conductivity, and penetration resistance, associated with a collection of temporal groundwater levels and classified satellite images of the basin and using regression methods series, we created a model capable of predicting spatial to generate maps representing the areas with higher, and lower levels of interference in the rebound. From the description of these phenomena it is intended that this prediction model assists in decision making in the management plan of the watershed and sustainable, use and protection of groundwater resources in vulnerable areas such as outcrops SAG. |