Checking simulations of a geolithological model obtained by means of nested truncated bigaussian method

Characterizing the spatial distribution of major lithotypes and their relationships is a key aspect in the process of hydrogeological modeling of aquifers in that assignment of lithotypes-specific hydraulic and hydrochemical properties requires the knowledge of the layout of the lithotypes themselves. Truncated bigaussian simulation is a procedure derived from the truncated Gaussian model, used to simulate random sets, and, in particular, variable geological characteristics, expressed as categorical variables. Anyway, in cases of many lithotypes having not homogeneous spatial behaviors, this methodology might not explain at best the relations existing among the lithotypes themselves; a more general method is therefore required to represent this variability. In this paper, that concerns a site whose geologic asset has already been reconstructed, in order to better characterize the aquifer geolithological architecture, nested simulation for a macro-unit of the previously realized geolithologic model has been carried out, together with a check phase of the results obtained by the mentioned simulation. The proposed methodology can represent a useful instrument for the modeling of complex geological layouts other than in the detailed characterizations of hydrogeological studies, for a better interpretation of the complex phenomena that take place in groundwater circulation and contaminant propagation

Stochastic geolithological reconstruction coupled with artificial neural networks approach for hydrogeological modeling

When simulating fluid flow and solute transport a more accurate modeling of the lithologic, geological and structural characters of an aquifer is of extreme importance in order to improve the reliability of the numerical simulations. On the other hand the information available for the setting up of a hydrogeological model is subjected to ambiguities due to not univocal interpretations or to uncertainties linked to the methodologies of measurement of the variables of interest. Therefore, hydrogeological characterization of heterogeneous aquifers, if carried out up to a high degree of detail, should not identify a univocal model but a set of "equifinal" solutions. In the present paper the application of Artificial Neural Network approach coupled with a Nested Sequential Indicator simulation has allowed to obtain the distribution of hydrogeologic parameters that are not only conditioned by the in situ measured values but also by the soft information coming from geolithology. The results show a fairly good relationship between parameters such as Transmissivity and Storage coefficient and the geolithologic architecture of the examined aquifer

Methodological study on pesticides in Alsatian groundwater

The risk assessment conducted by many federal and state agencies have generally relied on deterministic approaches, that use single input/output values, generally selected to fulfill the goal of being health protective. But, the presence of uncertainty and variability within the parameters of the procedure of risk assessment let them assume different values within a range of possible values, each with different probability of occurrence. In particular, the case study deals with groundwater contamination by agrochemical substances occurring in the French aquifer of Alsace. The regional supply of drinking water, water for irrigation and industrial water depends mainly on this water resource. A proper management of this area must consider, thus, the sustainability of a landscape capable of multiple uses and the overwhelming presence of censored data. For this reason, particular attention is given to the characterization of the extent and the chemico-physical distribution of the pollutant source for what concern the delimitation of the hazardous areas, to the determination of the probability density functions of the concerned variables and of the representative concentrations

Modellizzazione dell'Attenuazione Naturale mediante tecniche geostatistiche multivariate

Up to the eighties, the chlorinated solvents have been considered recalcitrant to the common treatments and the attempts of remediation were limited to Pump&Treat technique. Modelling spatial variability of environmental parameters through the application of modern techniques of geostatistics has permitted to acquire elements apt to evaluate the possibility of using Natural Attenuation as a remediation technique for groundwater contaminated by chlorinated compounds. Moreover, a precise delineation of hazardous areas in a polluted site is strongly based on accurate predictions of contaminant concentrations, a task that is complicated by the presence of censored data and highly positively skewed distributions. The present paper proposes a geostatistical approach that includes different methods for the study and the control of the ongoing activity of Natural Attenuation in an abandoned industrial area