Regional‐scale characterization of the geomorphic control of the spatial distribution of soil organic carbon in cropland

Abstract

SummaryThe heterogeneity of the spatial distribution of soil organic carbon (SOC) at the landscape scale is generally not considered in regional or national SOC dynamics models. In cropland this heterogeneity is controlled largely by topography, which influences the distribution of water, energy and sediments, and thus the SOC dynamics. Sediment redistribution rates have increased strongly since the mechanization of agriculture. The over‐simplification of landscape processes in regional models of C dynamics may add to the uncertainty in C balances. Therefore, a better characterization of the importance of landscape‐scale effects on the SOC distribution throughout a region is needed. This study characterized the relative importance of geomorphology in the SOC horizontal and vertical variability across croplands in the Belgian loess belt region. A large legacy dataset of soil horizons was exploited together with 147 recently sampled profiles. Mean SOC depth profiles for different soil types were compared. Various topographic attributes were computed from a digital elevation model, and their influence on SOC was quantified through simple linear models. Finally, SOC content was mapped at three depth layers through multiple linear models, and results were cross‐validated. The legacy dataset allowed identification of significant differences in the mean SOC profile according to texture, drainage or profile development classes. A clear relationship between SOC content and topographic attributes was demonstrated, but only for the recently sampled profiles. This may be explained by a substantial error in the location of the profiles of the legacy dataset. This study thus shows evidence that the major control of the vertical distribution of SOC is related to topography in a region where observed heterogeneities for other commonly involved factors are limited. However, the large amount of unexplained variability still limits the usefulness of the spatial prediction of SOC content, and suggests the importance of additional influencing factors.