There is increasing recognition that 137Cs data remain one of the few sources of spatially distributed information concerning soil erosion. However, many of the conversion models that have been used to convert 137Cs data into soil redistribution rates failed to account for some of the key factors affecting the redistribution of 137Cs in agricultural landscapes. The conversion model presented in this paper aims to overcome some of the limitations associated with existing models and therefore to provide more realistic estimates of soil erosion rates on agricultural land. The conversion model aims at coupling soil redistribution processes directly with 137Cs redistribution. Emphasis is placed on the spatial representation of soil redistribution processes and the adequate simulation of tillage processes. The benefits of the presented model arise from the two-dimensional spatial integration of mass balance models with soil erosion models. No a priori assumptions about the intensity of any soil redistribution process are necessary and the level of agreement between observed and simulated 137Cs inventories enables us to evaluate the performance of the model. The spatial implementation and the use of fuzzy parameter sets also allow us to assess the uncertainties associated with soil erosion estimates. It was shown that an adequate simulation of tillage processes is necessary and that simplified tillage models may lead to erroneous estimates of soil redistribution. The model was successfully applied to a study site in the Belgian Loam Belt and the results indicated that tillage is the dominant process. Furthermore, the uncertainties associated with the estimation of water erosion rates were much higher than those associated with tillage, especially for depositional areas. Copyright © 2003 John Wiley & Sons, Ltd.