Modeling clod evolution under rainfall according to clod size.

Determing soil spatial variability is a key point in soil sciences either for soil preparation in precision agriculture, or because of influence on overland flow and erosion. Soil Surface Roughness (SSR) represents the undulation of the surface at small scale, due to the presence of small elevations and depressions. It results from tillage operations and changes over time due to weathering. SSR can be related to clod-size distribution. So, many research has been conducted on monitoring the size and number of clods using photogrammetry method. Nowadays, it is possible to acquire high resolution Digital Elevation Models (DEMs). This study seeks to model the evolution of clod size under rainfall impact with modeling and data processing tools.

Seedbed-like soil surface was made in the laboratory by filling a tray with loose soil of silt loam and setting upon pre-sieved clods. It was eroded by controlled laboratory rainfalls. A millimeter DEM was recorded at each stage of the surface with laser-scanner. Wavelet-based clod segmentation leaded to measurement of the volume of individual clods. Clod subsets were formed according to clod size. Normalized mean volume decrease was modelled by exponential function.

Greater clods showed swelling (volume increase) and erosion (volume decrease), with cumulated rainfall. These two phenomena being size dependent. Amplitude and slope parameters of the exponential decrease of clod volume could be modelled as a function of mean volume of the clod subset at initial stage. Results obtained with this surface strengthen those previously obtained with less data and basic segmentation. A power law is confirmed for amplitude parameter and a sigmoïd function is highlighted for slope parameter.

Modelling and data processing tools are efficient to differentiate and estimate the dynamics of clods depending on their size. Usually, clod size distribution is addressed with statistics of clod diameters obtained by real or numerical sieving. Working on 2.5 D DEMs gives also an acces to the vertical dimension of clods, which is included in their volume. This technique completes the usual roughness description and is promissing for use in precision agriculture or numerical surface generation.