Many landscape models have been developed over the past decades; however, relatively little is known about handling the effects of changing spatial and temporal resolutions. Therefore, resolution effects remain a factor of uncertainty in many hydrological and geomorphological modelling approaches. In this paper we present an experimental multi-scale study of landscape process modelling. Emphasis was laid on quantifying the effect of changing the spatial resolution upon modelling the processes of erosion and sedimentation. A simple single process model was constructed and equal boundary conditions were created. Using artificial digital elevation models (DEMs) eliminated effects of landscape representation. The only variable factors were DEM resolution and the method of flow routing, both steepest descent and multiple flow directions. Our experiments revealed an important dependency of modelled erosion and sedimentation rates on these main variables. The general trend is an increase of erosion predictions with coarser resolutions. An artificial mathematical overestimation of erosion and a realistic natural modelling effect of underestimating resedimentation cause this. Increasing the spatial extent eliminates the artificial effect while at the same time the realistic effect is enhanced. Both effects can be quantified and are expected to increase within natural landscapes. The modelling of landscape processes will benefit from integrating these types of results at different resolutions.

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Abstract. Differences in land‐use history within soil series, although not influencing soil classification, lead to variability of non‐diagnostic soil properties in soil databases. Regional studies that use soil databases are confronted with this considerable variability. This has, for example, been reported in regional studies focused on nitrate leaching from agricultural land. Such findings have a direct impact on regional assessments of nitrate leaching from dairy farms on sandy soils, a major environmental issue in the Netherlands. There is thus a need to deal with this variability in soil properties. We were able to relate soil organic nitrogen, soil organic carbon and its dynamics to land use history for a Dutch sandy soil series. Within one soil series, three different land use histories were identified: old grassland, reseeded grassland and grassland converted from continuous cropping with silage maize. The addition of landscape characteristics significantly improved the regression models based on land‐use only. Once established for any given soil series, such relationships can significantly improve soil survey input into dynamic models of soil behaviour such as regional nitrate leaching studies.