The Distribution of Redox Sensitive Elements (U, As, Sb, V and Mo) along a River-Wetland-Lake System (Balaton Region, Hungary)

The distribution of redox sensitive elements (U, As,Sb, Mo and V) has been investigated in Lake Balatonand two man-made reservoirs (Lake Kis-Balaton-1 andKis-Balaton-2) built along the River Zala, the mainriver discharging into it. These elements underwentremoval in Lake Kis Balaton-2 (KB-2) during anoxicconditions (May and September).Similarities were found between the distributions ofdissolved As and Sb. Both elements had elevateddissolved concentrations in Lake Kis-Balaton-1 (KB-1)and in Lake Balaton in September. This increasedmobility could be due to a change of speciation (viareduction and the formation of methylated species).Such changes in speciation are well documented in theliterature and are generally enhanced during periodsof warmth and high primary productivity.Dissolved V and Mo distributions also showedsimilarities with higher concentrations in LakeBalaton than in other parts of the system.Although removal is not clearly detected from thedissolved concentrations, U, As, Sb and Mo aresignificantly enriched in the organic-rich sedimentsof Lake KB-1, while V is mainly associated with thealumino-silicate fraction. In Lake KB-1, theconcentrations of all elements in SPM (suspendedparticulate matter) are lower than in the depositedsediments (except for As) suggesting that enrichmentprocesses are occuring in the deposited sediments.Additionnally the cycling of As and Mo can be alsopartly controlled by uptake and scavenging processesin the water column, as suggested by the elevated Asand Mo concentrations observed in SPM seasonnally forAs in Lake KB-1 and at Z.mouth-1 station and for Mo atZ.mouth-1 station and Lake Balaton.     

Dérive à la surface de l'océan sous l'effet des vagues

We model the drift velocity near the ocean surface separating the motion induced by the local current, itself influenced by winds and waves, and the motion induced by the waves, which are generated by local and remote winds. Application to the drift of ‘tar balls’, following the sinking of the oil tanker Prestige-Nassau in November 2002, shows that waves contribute at least one third of the drift for pollutants floating 1 m below the surface, with a mean direction about 30° to the right of the wind-sea direction. Although not new, this result was previously obtained with specific models, whereas the formalism used here combines classical wave and circulation forecasting models. To cite this article: F. Ardhuin et al., C. R. Geoscience 336 (2004).     

Apports de la méthode sismique réflexion haute résolution à l'identification des structures profondes des formations tertiaires en Médoc (Gironde,France) : implications hydrogéologiques

Near Bordeaux (France), the Oligocene aquifer is a potential target for drinking water supply. A high-resolution seismic campaign and several exploration wells helped to clarify the geometry of this formation and, as a consequence, the Medoc Tertiary aquifers. The major information extracted from these new data is the existence of a soft deformation inducing two different deposit areas, showing different hydrogeological characteristics (thickness, type, hydraulic properties, etc.). The presence of an erosional gap area affecting the Oligocene formations lead us to propose a new image of groundwater flow in the area, in the context of a predicted intensive exploitation of this resource. To cite this article: F. Larroque, A. Dupuy, C. R. Geoscience 336 (2004).     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Assessing regression‐based statistical approaches for downscaling precipitation over North America

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.