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Elsevier, Science of the Total Environment, 1-3(359), p. 57-75

DOI: 10.1016/j.scitotenv.2005.07.013

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Ag-PIE: A GIS-based screening model for assessing agricultural pressures and impacts on water quality on a European scale

Journal article published in 2006 by Carlo Giupponi ORCID, Irena Vladimirova
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Diffuse pollution of water resources from agricultural sources is a major environmental issue in the European Union, and has been dealt with by specific legislation: the Nitrate Directive of 1991 and the Water Framework Directive of 2000. These attempts to provide a coordinated approach to solving environmental problems require methods and tools for spatial analysis and modelling on a continental scale, with river basins being used as spatial units. This paper presents a screening model (Ag-PIE), developed in a GIS environment, for the assessment of pressures from agricultural land use and the consequent impacts on surface and groundwater. Ag-PIE has been applied at the European scale (EU15), with focus on nitrogen pollution from chemical fertilisers and manure. The model adopts a multi-criteria evaluation procedure applied to spatial data layers which represent the variety of factors affecting the pollution process. The DPSIR (Driving forces, Pressures, State, Impact, Responses) approach is applied to provide the modelling approach with a conceptual framework and to further analyse and communicate results. Ag-PIE is ultimately aimed at providing a tool making use of state-of-the-art geographical databases to support policy-makers at the European level. The scale of reference adopted is the river basin, in particular those that extend across national boundaries. The quality of the results obtained has been assessed against existing related studies and monitoring reports and by means of sensitivity analysis. Conclusions are driven by considering the potential of Ag-PIE in devising policy support and its strengths and weaknesses in view of identifying future research needs.