Core Ideas The volume ratio of large to small particles controls intact sand hydraulic properties. Simple model explained sand saturated hydraulic conductivity within a factor of two. The new concept was also related to effective porosity and water retention points. Soil mineral particles larger than 0.1 mm and organic matter need to be considered. The volume ratio concepts seem promising for developing pedotransfer functions. Hydraulic conductivity (Ks) and effective porosity (ϕeff) for saturated water flow are essential hydraulic properties for describing fluid and chemical transport in soil and groundwater systems. Typically, Ks is predicted by pedotransfer functions of soil texture and total porosity or ϕeff. This study shows that a more conceptual approach that uses a volume‐weighted ratio of coarser (part of the sand fraction) to finer (clay and organic matter) particles alongside total porosity could explain variations in both Ks and φeff in intact 100‐cm3 samples of 20 sandy surface and subsurface soils with <10% fines (clay + organic matter). The Ks function used was a simple power‐law function of the volume‐weighted coarse/fine particle ratio with two calibration parameters [A and pore network connectivity (PNC)]. The value of the power‐law exponent (PNC) in the calibrated function was 1.8, similar to power‐law exponents for gas diffusivity and air permeability in unsaturated soil (1.5–2). The second calibration parameter (A) probably depends on the soil classes under consideration, the Ks measurement method, and the sample scale. A sensitivity analyses showed that both Ks and ϕeff (taken as the volume content of pores larger than 30 μm, that is, drained at –10 kPa of soil water matric potential) are especially sensitive to organic matter content. Besides the water transport parameters, water retention under dry conditions was also closely correlated with the volume‐weighted fines content. Therefore, the volume ratio concept seems to be a promising platform for the development of simple, accurate functions for the hydraulic properties of coarse‐textured soils.

The particle-size curve (PSC) defines the continuous size distribution of mineral particles <2 mm. It is used for soil classification and to derive functional soil parameters such as the soil-water characteristic (SWC) curve, soil hydraulic properties, and gas transport properties. Conventional methods for measuring texture are time-consuming and most methods only provide discrete particle-size intervals. The Rosin-Rammler and Fredlund functions enable a continuous description of the size distribution of mineral particles using two and three fitting parameters, respectively. Visible near-infrared diffuse reflectance spectroscopy (vis-NIRS) is a time-saving and well-known alternative soil analysis method. In this study vis-NIRS was used to indirectly obtain PSCs by predicting the fitting parameters of the Rosin-Rammler (alpha(R), beta(R)) and Fredlund (alpha(F), n(F), and m(F)) functions. A total of 431 soil samples from 7 agricultural fields in Denmark and Greenland were analyzed for soil texture (clay: 0.028-0.426 kg kg(-1)) and organic matter (OM) content (0.018-0.143 kg kg(-1)). The Rosin-Rammler and Fredlund functions were fitted to the PSCs. Soil diffuse reflectance was measured from 400 to 2500 nm with a spectrometer. The important spectral regions for correlating alpha(R), beta(R), alpha(F), n(F), m(F), and OM to spectra were selected using forward interval partial least squares (iPLS) regression on a calibration set. The soil spectra showed high correlation to PSC function parameters and OM content for the validation set. Further, vis-NIRS cross-validation models for the fitting parameters of the Rosin-Rammler and Fredlund functions were built on all samples and used as input for the PSCs, generating RMSE values of 4.2 and 3.5%, respectively. Both PSC functions convincingly covered the PSC variation within fields, although the Fredlund function performed slightly better. From one vis-NIRS scanning the complete texture comprising the PSC and the OM content was successfully characterized.

The soil water retention curve (SWRC) is the most fundamental soil hydraulic function required for modelling soil–plant–atmospheric water flow and transport processes. The SWRC is intimately linked to the distribution of the size of pores, the composition of the solid phase and the soil specific surface area. Detailed measurement of the SWRC is impractical in many cases because of the excessively long equilibration times inherent to most standard methods, especially for fine textured soil. Consequently, it is more efficient to predict the SWRC based on easy‐to‐measure basic soil properties. In this research we evaluated a new two‐stage approach developed recently to predict the SWRC based on measurements for disturbed repacked soil samples. Our study involved undisturbed structured soil and took into account the effects of bulk density, organic matter content and particle‐size distribution. Independently measured SWRCs for 171 undisturbed soil samples with organic matter contents that ranged from 3 to 14% were used for model validation. The results indicate that consideration of the silt and organic matter fractions, in addition to the clay fraction, improved predictions for the dry‐end SWRC. The dry‐end results revealed that the smallest matric potential at hypothetical ‘zero‐water‐content’ varies between −45 000 and −125 000 m (pF 6.65–7.1) even for soils with similar clay mineralogy. The sensitivity analysis of the two‐stage approach indicated that predicted SWRC results are more sensitive to bulk density than to organic matter content or soil texture. For the soils studied, the two‐stage approach showed reasonable agreement with measured data, with a root mean square error of 0.04 cm3 cm−3 for the matric potential range from pF 1 to pF 6.6.HighlightsIs a new approach to modelling the soil water retention (SWR) curve applicable to structured soil? The model accurately predicts the full SWR curve with an RMSE of 0.04 cm3 cm−3. Prediction accuracy of the wet part of the SWR curve was sensitive to variation in bulk density. The pF at zero water content, which affects the prediction of dry SWR, ranged from 6.65 to 7.10.

Solute transport through the soil matrix is non-uniform and greatly affected by soil texture, soil structure, and macropore networks. Attempts have been made in previous studies to use infiltration experiments to identify the degree of preferential flow, but these attempts have often been based on small datasets or data collected from literature with differing initial and boundary conditions. This study examined the relationship between tracer breakthrough characteristics, soil hydraulic properties, and basic soil properties. From six agricultural fields in Denmark, 193 intact surface soil columns 20 cm in height and 20 cm in diameter were collected. The soils exhibited a wide range in texture, with clay and organic carbon (OC) contents ranging from 0.03 to 0.41 and 0.01 to 0.08 kg kg− 1, respectively. All experiments were carried out under the same initial and boundary conditions using tritium as a conservative tracer. The breakthrough characteristics ranged from being near normally distributed to gradually skewed to the right along with an increase in the content of the mineral fines (particles ≤ 50 μm). The results showed that the mineral fines content was strongly correlated to functional soil structure and the derived tracer breakthrough curves (BTCs), whereas the OC content appeared less important for the shape of the BTC. Organic carbon was believed to support the stability of the soil structure rather than the actual formation of macropores causing preferential flow. The arrival times of 5% and up to 50% of the tracer mass were found to be strongly correlated with volumetric fines content. Predicted tracer concentration breakthrough points as a function of time up to 50% of applied tracer mass could be well fitted to an analytical solution to the classical advection-dispersion equation. Both cumulative tracer mass and concentration as a function of time were well predicted from the simple inputs of bulk density, clay and silt contents, and applied tracer mass. The new concept seems promising as a platform towards more accurate proxy functions for dissolved contaminant transport in intact soil.