AbstractOne main problem with current research on spatio‐temporal modeling of ion fluxes in forest soils is the separation of space and time effects in the soil‐monitoring concept. This article describes an approach to overcome this weakness. Time trends of point information on soil‐solution data (base‐cation concentrations and fluxes) are scaled by linking them to soil‐chemical data which is available in higher spatial resolution and can be upscaled to an area base. This approach is based on a combined evaluation of bulk soil and soil‐solution data using both statistical and process‐oriented methods. Multiple‐linear‐regression analyses coupled with geostatistics were developed to predict spatial patterns of exchangeable cation percentages. In a second step, empirical ion‐distribution coefficients were adapted according to Gapon using data of suction‐cup plots and bulk‐soil samples. Seasonally adjusted time‐series data of soil‐solution chemistry were then connected with the maps of the predicted exchangeable‐cation percentages by means of the Gapon equations. This evaluation step provided both time‐ and space‐dependent maps of cation concentrations in the soil solution. Finally, using the results of a water‐budget model it was possible to derive spatio‐temporal patterns of soil cation fluxes. Methodological limitations and the results of verification processes are discussed. The methods described can only be used in acidic soils and should not be used in soil layers rich in humus, since adsorption to C compounds differs from adsorption to clay minerals. The time increments of the models should be not shorter than yearly in order to suppress annual periodicity. Although the Gapon equations were not based on laboratory‐determined exchange solutions at quasi‐equilibrium, but rather on field data from the suction‐cup technique, the exchangeable‐cation percentages showed steady functions of selectivity coefficients. The methods tested at a watershed scale may be flexible enough to be applied at other scales as well.