Padrões espaciais da qualidade da água na Bacia do Rio Cuiabá e Rio São Lourenço – Mato Grosso

Detalhes bibliográficos
Ano de defesa: 2011
Autor(a) principal: Araújo, Gabriella Costa
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 Federal de Mato Grosso
Brasil
Faculdade de Arquitetura, Engenharia e Tecnologia (FAET)
UFMT CUC - Cuiabá
Programa de Pós-Graduação em Recursos Hídricos
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
GIS
Link de acesso: http://ri.ufmt.br/handle/1/1215
Resumo: Present study aimed the analysis of the spatio-temporal patterns of land use and occupation and its relationships with water quality in the Cuiabá e São Lourenço watersheds, the main affluents of the Pantanal wetland. The influences of farming, industries and other land use forms have been evaluated by a water quality monitoring between 2006 and 2007 of 12 stations of the Cuiaba River and five of the São Lourenço. Physiographic and socio- environmental characteristics of the stations contribution areas were elaborated by GIS and Remote Sensing techniques. The hypothesized relationships between water quality variables and land use were evaluated by using Polynomial Redundancy Analysis-RDA, a multivariate direct ordination method. Watersheds properties which most influenced water quality were soil types, urban population density, slope, watershed size and precipitation. Located in regions of intensive, the sub-watersheds Slo 245 and Slo 253 were found to suffer elevated impacts by Total Nitrogen, but without an expressive reduction in Dissoveld Oxygen concentrations. Sub-watersheds with high urban population density, such as Cba 437 e Cba 561 showed reduced water quality in all evaluated variables. We conclude that the utilization of GIS and Remote Sensing paired with RDA allows the analysis of complex land use - water quality relationships.