Spatial and statistical assessment of factors influencing nitrate contamination in groundwater.
The weights of evidence (WofE) modeling technique has been used to analyze both natural and anthropogenic factors influencing the occurrence of high nitrate concentrations in groundwater resources located in the central part of the Po Plain (Northern Italy). The proposed methodology applied in the Lodi District combines measurements of nitrate concentrations, carried out by means of a monitoring net of 69 wells, with spatial data representing both categorical and numerical variables. These variables describe either potential sources of nitrate and the relative ease with which it may migrate towards groundwater. They include population density, nitrogen fertilizer loading, groundwater recharge, soil protective capacity, vadose zone permeability, groundwater depth, and saturated zone permeability. Once conditional dependence problems among factors have been solved and validation tests performed, the statistical approach has highlighted negative and positive correlations between geoenvironmental factors and nitrate concentration in groundwater. These results have been achieved analysing the calculated statistical parameters (weights, contrasts, normalized contrasts) of each class by which each factor has been previously subdivided. This has permitted to outline: the overall influence each factor has on the presence/absence of nitrate; the range of their values mostly influencing this presence/absence; the most and least critical combination of factor classes existing in each specific zone; areas where the influence of impacting factor classes is reduced by the presence of not impacting factor classes. This last aspect could represent an important support for a correct land use management to preserve groundwater quality.
Masetti
Marco
M
Department of Earth Sciences, "Ardito Desio", University of Milan, Via Mangiagalli 34, 20133 Milan, Italy. marco.masetti@unimi.it
Poli
Simone
S
Sterlacchini
Simone
S
Beretta
Giovanni P
GP
Facchi
Arianna
A
D001499:Bayes Theorem; D004784:Environmental Monitoring / Q000706:statistics & numerical data; D007558:Italy; D008962:Models, Theoretical; D009566:Nitrates / Q000032:analysis*; D014874:Water Pollutants, Chemical / Q000032:analysis*; D014881:Water Supply / Q000032:analysis*
D009566:Nitrates; D014874:Water Pollutants, Chemical