Modelagem espacial de áreas de recarga subterrânea em região de afloramento do sistema aquífero guarani (sag), em Brotas/SP

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Paes, Claudiane Otilia [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/11449/123232
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.