Análises das variações dos níveis freáticos em uma área de afloramento do sistema aquífero guarani em BROTAS/SP-Brasil - Manzione, Rodrigo Lilla [UNESP]; Soldera, Bruna Camargo [UNESP]; Paes, Claudiane Otilia [UNESP]; Wendland, Edson (Brazilian Journal of Irrigation and Drainage - IRRIGA, 2015)
Several factors may influence variations in ground water levels. Some of these factors present static behavior while others present dynamic changes over time. The differences in management operations in agricultural sites, plant development and agricultural practices have direct impact on the unsaturated zone, as the levels of recharge and water tables can respond differently due to local conditions. Different information sources may be used and integrated in a statistical model to reveal the responses of ground water levels under certain conditions. Understanding these processes involves meeting a way of representing correlated variables together to form a new and smaller set of derived variables with minimum loss of information, removing redundancy or duplication. The objective of this study was to analyze the variations in water table depths using information from a groundwater monitoring network in an outcrop area of the Guarani Aquifer System (GAS) in Brotas, São Paulo, Brazil, associated with soil, vegetation and terrain variables, which possibly influence the groundwater dynamics. A factorial analysis was applied to identify the underlying factors which would explain this pattern of correlation within these sets of study variables. The main factors influencing the variations in water table over the monitoring period were as follows: sand particle size, terrain attributes, soil texture, soil and crop management and vegetation. This methodology can be useful for groundwater management, policy making and regulation of soil use in watersheds, and regional studies, for example, maximizing information in data analysis.
Analyses of water table depths variations in an outcrop area of the guarani aquifer system in BROTAS/SP-Brazil
Keywords: Brazil; Factorial analysis; Recharge; Statistical modeling