Macropores have a great effect upon the overall saturated hydraulic conductivity (Ks) of soil samples. However, when using steel-cylinders for soil sampling, especially in stone-rich sites, soil core samples often bear sampling induced macropores due to improper sampling operation. The minimization of this macropore related bias of stone bearing soils‘ matrix Ks values is of high concern. To quantify the sampling induced error of Ks values of stony soils, Ks values were measured on a series of soil cores (n = 46) collected at 5 Bavarian sites under arable and grassland management. Based on texture-related tabulated Ks values, so-called Ks factors were extrapolated, which are related to the macropore fraction of the soil (RoGeR model). The overall Ks values of the soil cores were reduced by these Ks factors. The resulting matrix-related Ks values of the stone bearing soils were contrasted against the General Effective Medium (GEM) approach. Here, the shape of stones was parameterized as well as the critical stone fraction (fc). When applying sample specific fc values, the correlation between the RoGeR- and the GEM approach resulted in a good agreement (R² = 0.9) with an acceptable root mean square error (RMSE) of 4.6 cm/d. Ks reduction using the RoGeR approach seems to be a viable way to fit measured Ks values of stone bearing soil cores with sampling induced macropores to matrix conditions. Alternatively, GEM provides a way to calculate matrix Ks values of stone bearing soils based on tabulated Ks values and soil particle information.
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