This paper presents the methodology applied and results obtained from testing the Decision Support System ‘mDSS’ developed by the MULINO Project (Multi-sectoral, integrated and operational decision support system for the sustainable use of water resources at the catchment scale), for assessing alternative measures for the reduction of nitrogen pressure from agriculture on water resources at European level. The European policy background is set by the EU Nitrates Directive (91/676/EEC) and the Water Framework Directive (2000/60/EC). The nature of the research is exploratory. It is aimed in particular at testing the usefulness of available official statistics for ex ante evaluations of alternative policy measures at the European scale, and the feasibility of such operations within the newly released mDSS software. Alternative measures for reducing N-pressure and spatial targets were designed and simulated in a GIS environment based on raster maps of 1 km resolution. The geographic extent of the present work is defined as the agricultural land of EU15. Data deriving from official statistics were used to calculate a simplified nitrogen balance, in which the sources of nitrogen are separated into organic (livestock manure) and mineral fertilisers, to distinguish the potential contribution of livestock and crop productions to water pollution at the river basin scale. Spatial indicators and evaluation indices were defined within a conceptual framework. For the study the DPSIR approach (Driving force, Pressure, State, Impact, Response), proposed by the European Environmental Agency, was adopted. The approach was subsequently elaborated by means of the multi-criteria functionality provided by mDSS. The results of this application test at the regional scale highlight the potential of the tool for evaluating the effects of policy measures targeted at different spatial implementation strategies through the application of simple screening models and using available data covering the EU15. The paper also contributes to identifying current strengths and weaknesses of available information, of the adopted methodology and the DSS tool.