title: Stochastic analysis to assess the spatial distribution of groundwater nitrate concentrations in the Po catchment (Italy).
abstract: A large database including temporal trends of physical, ecological and socio-economic data was developed within the EUROCAT project. The aim was to estimate the nutrient fluxes for different socio-economic scenarios at catchment and coastal zone level of the Po catchment (Northern Italy) with reference to the Water Quality Objectives reported in the Water Framework Directive (WFD 2000/60/CE) and also in Italian legislation. Emission data derived from different sources at national, regional and local levels are referred to point and non-point sources. While non-point (diffuse) sources are simply integrated into the nutrient flux model, point sources are irregularly distributed. Intensive farming activity in the Po valley is one of the main Pressure factors Driving groundwater pollution in the catchment, therefore understanding the spatial variability of groundwater nitrate concentrations is a critical issue to be considered in developing a Water Quality Management Plan. In order to use the scattered point source data as input in our biogeochemical and transport models, it was necessary to predict their values and associated uncertainty at unsampled locations. This study reports the spatial distribution and uncertainty of groundwater nitrate concentration at a test site of the Po watershed using a probabilistic approach. Our approach was based on geostatistical sequential Gaussian simulation used to yield a series of stochastic images characterized by equally probable spatial distributions of the nitrate concentration across the area. Post-processing of many simulations allowed the mapping of contaminated and uncontaminated areas and provided a model for the uncertainty in the spatial distribution of nitrate concentrations.
authors.affiliation: CNR-Institute for Atmospheric Pollution, Division of Rende, c/o UNICAL, 87036 Rende, Italy. s.cinnirella@cs.iia.cnr.it
authors.forename: Sergio
authors.initials: S
authors.lastname: Cinnirella
authors.forename: Gabriele
authors.initials: G
authors.lastname: Buttafuoco
authors.forename: Nicola
authors.initials: N
authors.lastname: Pirrone
mesh_terms: D000383:Agriculture; D000704:Analysis of Variance; D004784:Environmental Monitoring / Q000379:methods; D005618:Fresh Water / Q000737:chemistry*; D007220:Industrial Waste / Q000009:adverse effects; D007558:Italy; D008962:Models, Theoretical; D009566:Nitrates / Q000032:analysis*; D009584:Nitrogen / Q000032:analysis; D016011:Normal Distribution; D013269:Stochastic Processes; D035501:Uncertainty; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D007220:Industrial Waste; D009566:Nitrates; D014874:Water Pollutants, Chemical; D009584:Nitrogen