A large set of sediment samples from a 1600 m2 experimental plot within a 2.2 km2 vadose zone and groundwater uranium (VI) plume was subject to physical, chemical, and mineralogic characterization.
One-quarter to one-half of sampling sites had concentrations of PAHs, Cu, Pb, or Zn above the probable effects concentration, a set of sediment quality guidelines for adverse effects to aquatic biota, and sediments were predicted to be toxic, on average, when CIT land use exceeded about 10%.
In order to obtain the highest quality of information contained in a set of sediment samples, one has to follow an approach called operationalism, i.e. a set of recipe-like sequential operations by which a scientific proposition can be verified or rejected.
The sediment PNEC can be estimated from the limited set of sediment toxicity data described previously and would be close to 0.035 mg/L using an AF of 10 applied to the lowest chronic toxicity end point.
Due to the few experimental data sets on sediment transport inside of rock layers, a sediment transport formulation has been proposed based on a matching between the numerical model and experimental data on the profile deformation inside an open filter.
We then applied this method to a set of sediments collected in a river along a gradient of anthropogenic pressure and compared their isotopic signatures with those from samples that are representative of the potential P-PO4 inputs to the river system (soils and riverbank material).
A set of Pliocene sediment samples is organized according to grain size distribution, geochemistry, and mineralogy, and their chemical composition is compared with the composition of possible source rocks.
To this end, four data sets including wide ranges of sediment size and concentration, deposit thickness, and pipe size are used.
The boundaries of model estimations were assessed by retaining predictions of behavioural parameter sets, defined as parameter sets that resulted in efficiencies of sediment load and specific sediment yield estimations not more than 5% lower than the efficiency of the optimal parameter set.
Future steps will include the incorporation of sets of environmental data-like sediment texture, eutrophication (dissolved nutrients) and pollutant (heavy metals, hydrocarbons) variables to permit pairwise analysis.
