The Use of the Weights-of-Evidence Modeling Technique to Estimate the Vulnerability of Groundwater to Nitrate Contamination
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The occurrence of elevated nitrate (NO 3 − ) concentration in the aquifer of the Province of Milan (northern Italy) is related to both natural and anthropogenic variables. Using the weights-of-evidence modeling technique a specific vulnerability assessment has been performed. This study presents an evolution of previous applications of the proposed methodology as a consequence of an updating of the available database, in terms of data type, quality, and accuracy, and of a more specific and enhanced statistical controls onto the final results.
A comparison between the spatial distribution of vulnerability classes and the frequency of occurrences of nitrate in wells shows a high degree of correlation, both for low and high nitrate concentration. Similar results may be evidenced considering the correlation between posterior probability classes and mean nitrate concentrations in wells located in each of these classes: a high R 2 value (0.99) and the agreement with the threshold concentration value used to define prior probability testifies a general good quality of results. Groundwater-specific vulnerability has been classified in terms of vulnerability classes and, according to the outcomes of the model, the density of population can be considered the most impacting source of nitrate. Mean annual irrigation and groundwater depth can be identified as influencing factors in the distribution of nitrate, while agricultural practice appears a negligible factor.
KeywordsAquifer vulnerability nitrate weights-of-evidence
The authors would like to thank Jonathan Arthur from Florida Geological Survey and Gary Lee Raines from United States Geological Survey for comments and suggestions on the manuscript.
- Acutis, M., and Provolo, M., 2003, Stime dei carichi diffusi di Azoto, Fosforo e Fitofarmaci da agricoltura nelle acque di superficie della Lombardia: IReR, Piano di Tutela delle Acque della regione Lombardia, Allegato 7, 53 pGoogle Scholar
- Agterberg, F. P., Bonham-Carter, G. F., and Wright D. F., 1989, Weights of Evidence modelling: a new approach to mapping mineral potential, in Agterberg, F. P., and Bonham-Carter, G. F., eds., Statistical Applications in the Earth Sciences: Geol. Survey Canada, Paper 89-9, p. 171–183Google Scholar
- Alberti, L., Francani, V., Masetti, M., and Parri, A., 2000, Valutazione del livello massimo raggiungibile dalla falda nel Comune di Milano: Quaderni di Geologia Applicata, Pitagora Editrice, Bologna, no. 7-4, p. 13–28Google Scholar
- Bonham-Carter G. F., Agterberg F. P., Wright D. F., 1988, Integration of geological datasets for gold exploration in Nova Scotia: Photogrammetric Engineering and Remote Sensing, 54, 11, 1585–1592Google Scholar
- Calabrese E. J., Kostecki P.T. 1988, Soils contaminated by petroleum: Environmental and public health effects John Wiley & Sons, New York, 458Google Scholar
- Chung C. F., Fabbri A. G., 1999, Probabilistic prediction models for landslide hazard zonation, Photogrammetric Engineering & Remote Sensing 65, 12, 1389–1399Google Scholar
- Cohen, S., Creeger, S., Carsel, R., and Enfield, C., 1984, Potential for pesticide contamination of groundwater resulting from agriculture uses, in Krueger, R. R., and Seiber, J. N., eds., Treatement and Disposals of Pesticides Wastes: Am. Chemical Soc. Symp. Ser. No. 259 ACS, Washington, DC., p. 297–325Google Scholar
- European Community, 1991, Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources, (Nitrate Directive) OJ L 375, 31.12.1991: p. 1–8Google Scholar
- ERSAF (Ente di Ricerca per lo Sviluppo Agricolo e Forestale), 2004, Strumenti ed indirizzi per la gestione multifunzionale dei suoli agricoli (SIGMA), Piano di Tutela delle Acque della regione Lombardia, Allegato 10, 102 pGoogle Scholar
- Fetter C. W. 1999. Contaminant hydrogeology: Prentice-Hall, Englewood Cliffs, New Jersey, 500 pGoogle Scholar
- Harrison, R. M., ed., 1992, Pollution: causes, effect and control: The Royal Society of Chemistry, London, Spec. Publ. No. 44, 322 pGoogle Scholar
- ISTAT (Istituto di STatistica Applicata al Territorio), 2001, General Population and Housing Census. http://dawinci.istat.it/pop/Google Scholar
- Kemp, L. D., Bonham-Carter, G. F., Raines, G. L., and Looney, C. G., 2001, Arc-SDM: Arcview extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neural network analysis. http://www.ige.unicamp.br/sdm/default_e.htmGoogle Scholar
- Masetti M., Poli S., Sterlacchini S. 2005 Aquifer vulnerability assessment using weights of evidence modelling technique: application to the Province of Milan, northern Italy. Proc. of IAMG 2005: GIS and Spatial Analysis l, 499–504Google Scholar
- Sawatzky, D. L., Raines, G. L., Bonham-Carter, G. F., and Looney, C. G., 2004, ARCSDM3.1: ArcMAP extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neural network analysis. http://www.ige.unicamp.br/sdm/default_e.htmGoogle Scholar
- Schwab G. O., Fangmeier D. D., Elliot W.J., Freveret R. K. 1993, Soil and water conservation engineering: John Wiley & Sons, New York 507 pGoogle Scholar
- U.S. Soil Conservation Service, 1964, Hydrology. Section 4, SCS National Engineering Handbook: Washington, D.C., 30 pGoogle Scholar