KEY VARIABLES TO DETERMINATE THE WATER QUALITY IN WATERSHEDS WITH EUCALYPTUS PLANTATIONS

• Autor(a) principal: Gardiman Junior, Benvindo Sirtoli
• Data de Publicação: 2018
• Outros Autores: Garcia, Giovanni de Oliveira, Cecílio, Roberto Avelino, Loos, Rodolfo Araújo, Mafia, Reginaldo Gonçalves, Abad, Jupiter Israel Muro, Simão, João Batista Pavesi, Barbosa, Vitor Hugo Breda
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Ciência Florestal (Online)
• Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/31590
• topic: forest management; forest hydrology; water quality index; multivariate statistics.; manejo florestal; hidrologia florestal; índice de qualidade da água; estatística multivariada.

This work aimed to identify the main variables affected by natural factors and, or anthropic, which influence the quality of surface water in watersheds, managed for eucalyptus wood production. Water quality was monitored in four watersheds located in Aracruz, northern ES state, Brazil. The physical and chemical characteristics of the water and the potential presence of pesticides used in forest management were evaluated. Samples were collected after the silvicultural activities and, or, rainfall between the months of January to June 2012. Principal component and factor analysis techniques were used to determine the water variables most sensitive and correlated with forestry activities, soil and climatic conditions of the study watersheds. It was possible to obtain four components that explained 73.1% of the total variance. The components were correlated with the variables and defined as factors mineral, solid, acidity, and pedological. These factors explained 31.6; 18.5; 15.6; and 7.4% of the total variance of the data which are directly related to salinity, the presence of suspended solids, acidity and the inorganic carbon content of the soil, respectively. Sulfluramid (insecticide) and glyphosate (herbicide) were not found. In general, it is possible to reduce from 30 to 12 variables that should be monitored for prediction of water quality, maintaining at least 70% of the precision of the estimates. The evaluation of these key variables allows establishing an adequate monitoring system of water quality considering the eucalyptus forestry activities.