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Abstract: Soil is one of the most important and most complex natural resources, but current developments (urbanisation, erosion and climate change) increasingly threaten this valuable resource in Europe and worldwide. The main objective of this paper is to introduce how changes in soil quality were modelled in the SENSOR project through two indicators: soil carbon content and soil water erosion. Indicators were calculated using state variables and model variables that were mainly derived from the CLUE model which predicts land use change in response to policy scenarios. In the case of erosion, accuracy of the calculations was evaluated by comparing GIS data with the results of the PESERA project. The PESERA and SENSOR models predicted comparable soil loss for the first year in the NUTS-X regions of Europe that were analysed. The higher resolution national soil-loss prediction USLE map largely overestimated the amount of soil loss compared to the PESERA and the SENSOR models in the NUTS-X regions of Hungary. This discrepancy may result from technical or methodological differences such as the spatial reference framework (NUTS-X regions), spatial resolution or levels of data aggregation. The soil organic carbon loss predictions for the NUTS-X regions of Europe are displayed on maps and background data are given in tables. The greatest decreases in soil carbon content may be expected in some regions of Poland, Latvia, Lithuania, south-eastern UK and eastern Germany. The greatest increases in soil carbon content may be expected in central and eastern parts of the UK, in Ireland, in northern and central Sweden and Estonia, in Greece, in central and southern Italy, in the island of Sardinia and in some regions of Spain. As erosion strongly reduces soil productivity these predictions have not only environmental but also socio-economic implications. The results presented in this paper could be used at EU level to locate regions where negative changes in soil quality can be expected. [Copyright &y& Elsevier]