Assessment of groundwater quality recovery strategies using nitrate transport modelling. Application to the Saône alluvial formations (Tournus, Saône-et-Loire)

To assess the efficiency of different agro-environmental strategies used to reduce groundwater pollution by nitrates, transport modelling in soils and groundwater has been carried out on two withdrawal areas in an alluvial plain. In a first time, the agro-environmental model AgriFlux allowed the simulation of water and nitrates fluxes flowing to groundwater. This model was calibrated for each agro-pedological unit of the studied territory. In a second time, the application of the hydrogeological model MODFLOW-MT3D allowed the simulation of nitrate transport in groundwater for the 1980-2004 period. This soil-groundwater coupled modelling has shown that soil nature is the first factor that conditions the vulnerability to nitrates. Thus, nitrate leaching occurs preferentially under sandy soils. Efficiency of different agro-environmental operations for groundwater quality recovery was quantified. The best results are obtained by combination of (1) grassland re-installation on sandy agricultural lots located in near well protection perimeter and (2) fertilization reduction on sandy agricultural lots located in the well alimentation area upstream the near protection perimeter. On other soils, the effect of grassland on groundwater quality improvement is more limited. Nevertheless, the control of nitrate fertilisation remains essential and is justified in both near and far well protection perimeters. Modelling thus allows optimising and priorizing agro-environmental actions in alluvial agricultural zones. [Comte J.-C., Banton O., Kockmann F., Villard A., Creuzot G. (2006), Assessment of groundwater quality recovery strategies using nitrate transport modelling. Application to the Saône alluvial formations (Tournus, Saône-et-Loire), Ingénieries Eau-Agriculture-Territoires, 45, 15-28]

ARE ARTIFICIAL NEURAL NETS AS SMART AS A RAT

The origins of artificial neural networks are related to animal conditioning theory: both are forms of connectionist theory, which in turn derives from the empiricist philosophers' principle of association. The parallel between animal learning and neural nets suggests that interaction between them should benefit both sides.

Determining propeller induced erosion alongside quay walls in harbours using Artificial Neural Networks

In shallow waters, such as those found close to berth structures, the wash from a manoeuvring ship’s propeller can cause erosion of the seabed. This erosion can be increased if the wash intersects a berth structure. A number of researchers have undertaken model studies and used regression analysis to develop predictive relationships for the scouring action. This paper presents an experimental investigation with Artificial Neural Networks (ANN’s), used to analyse the results. The purpose of using ANN’s was to examine the prediction accuracy of the Networks in comparison with previous regression analysis methods. ANN’s were found to provide a more accurate method of predicting propeller wash scour than the equations presented by previous investigators.

Degradation of carbon disulphide (CS2) in soils and groundwater from a CS2 -contaminated site

This study is the first investigation of biodegradation of carbon disulphide (CS₂) in soil that provides estimates of degradation rates and identifies intermediate degradation products and carbon isotope signatures of degradation. Microcosm studies were undertaken under anaerobic conditions using soil and groundwater recovered from CS₂-contaminated sites. Proposed degradation mechanisms were validated using equilibrium speciation modelling of concentrations and carbon isotope ratios. A first-order degradation rate constant of 1.25 × 10-2 h-1 was obtained for biological degradation with soil. Carbonyl sulphide (COS) and hydrogen sulphide (H₂S) were found to be intermediates of degradation, but did not accumulate in vials. A 13C/12C enrichment factor of -7.5 ± 0.8 ‰ was obtained for degradation within microcosms with both soil and groundwater whereas a 13C/12C enrichment factor of -23.0 ± 2.1 ‰ was obtained for degradation with site groundwater alone. It can be concluded that biological degradation of both CS2-contaminated soil and groundwater is likely to occur in the field suggesting that natural attenuation may be an appropriate remedial tool at some sites. The presence of biodegradation by-products including COS and H₂S indicates that biodegradation of CS₂ is occurring and stable carbon isotopes are a promising tool to quantify CS₂ degradation.

Demo: Have a Chat with Sensitive Artificial Listeners

Sensitive Artificial Listeners (SAL) are virtual dialogue partners based on audiovisual analysis and synthesis. Despite their very limited verbal understanding, they intend to engage the user in a conversation by paying attention to the user’s emotions and non- verbal expressions. The SAL characters have their own emotionally defined personality, and attempt to drag the user towards their dom- inant emotion through a combination of verbal and non-verbal ex- pression. The demonstrator shows the publicly available, fully au- tonomous SAL system.