TL dating of pottery fragments from four archaeological sites in Taquari Valley, Brazil

Sixty-three pottery fragments from four archaeological sites, numbered RST110, RST101, RST114 and RST114, in the Taquari Valley, vicinity of the city of Lajeado, Rio Grande do Sul state, southern Brazil, have been dated by the thermoluminescence method. Some of them from RST110 and RST101 are as old as 1400-1200 years, whereas those from RST114 and RST107 are younger than 800 years. This result indicates that RST101 and RST110 were peopled earlier than RST114 and RST107. The recent dates found are 302, 295 and 146 years and they are possible, since the first German immigrants who arrived in this region encountered Tupi-Guarani Indians still living there. One interesting result refers to the glow curves of quartz grains RST110, RST101 and RST114 that differ from the glow curves of RST107 quartz grains.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.