Application of three different methods to evaluate the nitrate pollution of groundwater in the Arborea plain (Sardinia – Italy)

Maria Laura Foddis (a), Anna Matzeu (a), Augusto Montisci (b) & Gabriele Uras (a)
(a) Department of Civil, Environmental Engineering and ARchitectural - Section of applied Geology and applied geophysics, University of Cagliari, via Marengo 3, 09123, Cagliari, Italy. E-mail: ing.foddis@gmail.com (b) Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, via Marengo 3, 09123, Cagliari, Italy.

This paper describes three different methods used to evaluate the nitrate contamination from agricultural practices in a study area located in the Nitrate Vulnerable Zone (NVZ) of the Arborea plain (Sardinia - Italy). Potential risk of contamination and concentration of nitrate pollution in groundwater has been estimated by using Parametric, Numerical and Artificial Neural Networks methods. Parametric methods consider the combination of intrinsic aquifer vulnerability to contamination index (SINTACS) and agricultural nitrates hazard index (IPNOA). The transport numerical model is based on flow model, obtained with modular three dimensional finite difference groundwater flow model (MODFLOW), and it is made applying 3-D Multi-Species Transport Model (MT3D). Artificial Neural Networks (ANNs) are used for the estimation of the nitrate concentration in monitoring well.

Artificial Neural Networks, IPNOA, nitrate contamination, numerical model, SINTACS.