Dating of sediments in the Biscay bay: Implication for pollution chronology

Important historical informations on the temporal changes of anthropogenic pollution in marine environment can be assessed using sediment analysis. Dating is a crucial prerequisite to reconstruct pollution events, to calculate fluxes, and thus to allow comparison between different sites. This work presents estimates of accumulation rates of sediments in the Bay of Biscay. Fives cores were collected during RIKEAU 2002 cruise on board o/v Thalia in order to study temporal changes in PAH and organohalogens compounds content of sediment. We compare chronostratigraphic estimates on cores derived from the natural radionuclide 210Pb in excess with estimates from the known times of introduction of the artificial radionuclide 137Cs to the environment. 210Pb, 226Ra and 137Cs were measured directly by non-destructive gamma spectrometry using a well type γ-detector. Total 210Pb and 226Ra activities vary from 30 to 150 mBq g-1, and 20 to 36 mBq g-1 respectively; 137Cs presents lower levels (< 5 mBq g-1). Profiles of 210Pb in three cores present a well mixed layer, from 2-3 to 10 cm, in the uppermost sediments, followed by an exponential decrease of activities, suitable for the determination of sedimentation rates. Under constant flux and sedimentation rate assumptions, vertical accretion rates derived from 210Pb present a large range from nearly 0.1 cm yr-1 up to almost 0.3 cm yr-1. Differences are mainly due to relative position of studied cores regarding the muddy patch. Although the moderate level of 137Cs limits the accuracy of this dating method, profiles of 137Cs with depth strengthen mean rates derived from 210Pb data. The implication of this dating on pollutant inputs in sediments of the Bay of Biscay is briefly discussed.

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.