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The phenomenon of seawater intrusion is one of the major problems in Sardinian coastal aquifers (Italy). In particular, it has been detected in the reclamation area of Arborea plain (west Sardinia) where intensive agriculture and dairy farming are the mainstays of the local economy.In this research SINTACS and GALDIT vulnerability indexes and the numerical model for simulating groundwater flow have been applied for evaluating respectively the intrinsic vulnerability to pollution, seawater intrusion and groundwater flow for a typical Mediterranean phreatic sandy aquifer such as Arborea plain aquifer.This research may offer a valuable contribution to the team of existing tools in the field of seawater intrusion and groundwater quality modelling.

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.