Vis-NIR spectroscopic assessment of soil aggregate stability and aggregate size distribution in the Belgian Loam Belt

Soil aggregate stability (AS) reflects a soil's resistance to external erosive forces and is an indicator that varies with changing elementary soil properties across space and time. However, the quantification of AS via conventional wet-sieving is too resource-demanding a task to be carried out at large scales. We explored the possibility of using laboratory Visible-Near infrared (Vis-NIR) spectroscopy to predict aggregate mean weight diameter (MWD), and three aggregate size fractions (i.e. clay + silt, microaggregate (63–250 μm) and macroaggregate (>250 μm)) resulting from wet-sieving. Two spectra-based approaches, one (SPF approach) that built direct linkage between soil spectra and four AS indexes via partial least squares regression and the other (SPF + PTF approach) that established pedotransfer functions based on spectroscopically predicted elementary soil properties, were developed on a total of 83 topsoil samples collected in the Belgian Loam Belt. These two approaches were later compared to a third approach (PTF approach) that built pedotransfer functions using measured elementary soil properties. Results show that, with the PTF approach consistently giving the best performance, all three approaches produced good prediction models (R2: 0.62–0.85; RPD: 1.59–2.46) for MWD, microaggregate and macroaggregate fractions, while no correct model was developed for the clay + silt fraction using the two spectra-based approaches, due to the rather homogenous soil texture in the study area. Soil organic carbon was a major factor that controlled the variations in AS, and a critical threshold of 2% SOC content was found to be the level that separated the “stable” and “unstable” AS classes. This study demonstrated that Vis-NIR spectroscopy is a promising technique that enables large-scale assessment of AS and aggregate size fractions, especially considering that future space-borne hyperspectral imagers will provide high-resolution Vis-NIR spectral data at unprecedented scales.