A hybrid-DSS for the groundwater pollution risk assessment

In most of the Mediterranean countries, groundwater is the primary resource for irrigation and drinking purposes. Water resources availability significantly affects a sustainable growth, and informative tools for managing and preserving such a resource represent a key issue. In this paper, a hybrid Decision Support System able to provide information about the impact of human activities on groundwater quality is proposed. In order to assess the risk of groundwater quality degradation with regard to fixed standards, the system uses a methodology based on geostatistical simulations. Simulations allow one to evaluate the Conditional Probability (CP) of overriding a given threshold of a pollutant concentration at different times, and at a generic point in a considered groundwater system. By means of non-parametric statistics, the temporal trend of the CPs can be evaluated at every point of the considered area. The trend index, assessed by means of a sort of classification, can be superimposed on the most recent values of the spatial risk. Consequently, a classification of the risk of groundwater quality degradation results with which to weigh both the spatial distribution and the temporal behaviour of the probability to exceed a given threshold. Sometimes incompleteness of monitoring information can reduce the reliability of geostatistical simulations. To overcome the limits imposed by the lack of available information, the system integrates such a methodology with a more qualitative approach obtained interacting with expert people. In fact, the experts seem to be able to formulate judgement regarding the risk of groundwater pollution having recourse to approximate reasoning based on their own expertise. Capturing that expertise, turning it into knowledge, using that knowledge and integrating it with the information coming from the geostatistical module, the proposed system becomes able to assess the risk of groundwater quality degradation also in cases characterized by lack of information.