Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter

Abstract

Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5 m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and

Evaluation of Terrestrial Laser Scanner and Structure from Motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils

“…Also, the only analysis comparing laser profilometer with stereo‐photogrammetry showed higher s values (~50%) and l values (~20%) for the laser profilometer (Blaes and Defourny, ). On the other hand, differences between roughness classes were clear with parameter s , which confirmed the results of the different studies where s has been proposed for distinguishing different roughness classes (Helming et al, ; Magunda et al, ; Kamphorst et al, ; Vermang et al, ; Bauer et al, ; Martinez‐Agirre et al, ). For the horizontal parameter l , there is no agreement in the literature.…”

“…In agricultural soils, SSR is a property with a high spatial variability, since the same type of tillage can result in surfaces with different SSRs depending on the physical characteristics of the soil. In addition, SSR is more or less susceptible to change through time due to the action of meteorological agents (e.g., precipitation, wind and temperature changes) in the low atmosphere or even animal activity (Martinez‐Agirre et al, ).…”

“…Many different parameters and indices have been proposed for quantifying SSR (e.g., Helming et al, 1993;Magunda et al, 1997;Kamphorst et al, 2000;Taconet and Ciarletti, 2007;Vermang et al, 2013). These can be divided into four groups (Martinez-Agirre et al, 2016), following a criterion similar to that of Smith (2014): (1) parameters measuring the vertical dimension of roughness, (2) parameters measuring the horizontal dimension of roughness, (3) parameters combining both dimensions, and (4) parameters based on fractal theory. The first parameters measure the magnitude of elevation differences along a transect or area.…”

Quantifying the dynamics of microtopography during a snowmelt event

“…One‐dimensional laser scanners have been in use for almost 30 years (Huang and Bradford, ), and continue to be employed (Martinez‐Agirre et al. ), but their frame mounting limits the spatial extent of the measurable object. Most other methods to obtain three‐dimensional datasets are either intrusive or can only cover limited surface areas.…”

“…Photogrammetric methods, most notably structure-from-motion (SfM) techniques, are increasingly being used to quantify soil surface roughness on agricultural soils (Gilliot et al, 2017) and its development over time (Snapir et al, 2014;Bauer et al, 2015;Hänsel et al, 2016). One-dimensional laser scanners have been in use for almost 30 years (Huang and Bradford, 1992), and continue to be employed (Martinez-Agirre et al, 2016), but their frame mounting limits the spatial extent of the measurable object.…”