title: A probabilistic methodology to assess the risk of groundwater quality degradation.
abstract: An approach to assess the risk of groundwater quality degradation with regard to fixed standards. based on Disjunctive Kriging (DK) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a considered groundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk. By repeating this analysis at different times, several spatial risk maps will be produced, one for each considered time. 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 of the trend values obtained as described above, can be superimposed on the most recent values of the spatial risk (i.e.: the most recent values of probability). 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 standard threshold. The methodology has been applied to values of nitrate concentration sampled in the monitoring well network of the Modena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along with industrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limits its use for potable purposes.
authors.affiliation: Water Research Institute, CNR, Bari, Italy. passarella@area.ba.cnr.it
authors.forename: G
authors.initials: G
authors.lastname: Passarella
authors.forename: M
authors.initials: M
authors.lastname: Vurro
authors.forename: V
authors.initials: V
authors.lastname: D'Agostino
authors.forename: G
authors.initials: G
authors.lastname: Giuliano
authors.forename: M J
authors.initials: MJ
authors.lastname: Barcelona
mesh_terms: D000383:Agriculture; D000818:Animals; D004784:Environmental Monitoring; D015233:Models, Statistical; D009566:Nitrates / Q000032:analysis; D018570:Risk Assessment; D012989:Soil Pollutants; D013552:Swine; D014873:Water Pollutants
chemical_list: D009566:Nitrates; D012989:Soil Pollutants; D014873:Water Pollutants