Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model

Abstract

Abstract. Quantification of soil roughness, i.e. the irregularities of the soil surface due to soil texture, aggregates, rock fragments and land management, is important as it affects surface storage, infiltration, overland flow and ultimately sediment detachment and erosion. Roughness has been measured in the field using both contact methods, such as roller chain and pinboard, and sensor methods, such as stereophotogrammetry and terrestrial laser scanning (TLS). A novel depth sensing technique, originating in the gaming industry, has recently become available for earth sciences; the Xtion Pro method. Roughness data obtained using various methods are assumed to be similar; this assumption is tested in this study by comparing five different methods to measure roughness in the field on 1 m2 agricultural plots with different management (ploughing, harrowing, forest and direct seeding on stubble) in southern Norway. Subsequently, the values were used as input for the LISEM soil erosion model to test their effect on the simulated hydrograph on catchment scale. Results show that statistically significant differences between the methods were obtained only for the fields with direct drilling on stubble; for the other land management types the methods were in agreement. The spatial resolution of the contact methods was much lower than for the sensor methods (10 000 versus at least 57 000 points per m2 respectively). In terms of costs and ease of handling in the field, the Xtion Pro method is promising. Results from the LISEM model indicate that especially the roller chain underestimated the RR values and the model thereby calculated less surface runoff than measured. In conclusion: the choice of measurement method for roughness data matters and depends on the required accuracy, resolution, mobility in the field and available budget. It is recommended to use only one method within one study.

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

“…Regarding the roughness parameters values obtained with different techniques, the slight differences for parameter s observed in the presented work are in agreement with the harrowed and ploughed surfaces studied by Thomsen et al (). In this sense, for the harrowed field, they reported lower s values with stereo‐photogrammetry (‐16%) than with TLS.…”

“…Surface roughness measurement techniques can be classified according to various criteria: the dimensionality of measure (2D/3D), resolution (mm/cm), sensor type, and whether the measure is done with contact to the soil surface or not (Jester and Klik, ; Gilliot et al, ). However, most of the literature in the topic centered the classification into contact and non‐contact techniques (Govers et al, ; Verhoest et al, ; Aguilar et al, ; Thomsen et al, ; Nouwakpo et al, ). Regarding this, non‐contact devices are preferred because the physical contact between an instrument and the soil surface is associated with measurement biases and disturbances (Jester and Klik, ).…”

“…Many of these considered either one measurement technique, or just one single soil roughness condition (Taconet and Ciarletti, ; Heng et al, ; Mirzaei et al, ; Snapir et al, ; Milenković et al, ; Rodríguez‐Caballero et al, ; Nouwakpo et al, ). Other studies focused more on a comparison between old and new techniques (Jester and Klik, ; Thomsen et al, ), but over a rather small area (1 × 1 m), which does not allow analyzing the multiscale nature of SSR (Verhoest et al, ). Then, there are studies that applied one single technique, but considered different SSR conditions (Taconet and Ciarletti, ; Marzahn et al, ; Gilliot et al, ).…”

Quantifying the dynamics of microtopography during a snowmelt event

“…More recently, Thomsen et al. () provided a comparison of these methods with regard to their ability to quantify surface roughness. Photogrammetric methods, most notably structure‐from‐motion (SfM) techniques, are increasingly being used to quantify soil surface roughness on agricultural soils (Gilliot et al.…”

Addressing uncertainties in interpreting soil surface changes by multitemporal high‐resolution topography data across scales

“…Spatial resolution and data accuracy depend on the respective application, scale of and distance to the object of interest (Eltner, Kaiser, et al, ), potentially reaching submillimetre levels. Advancements were shown during the last decade demonstrating the potential of image‐based surface models for various applications: gully observations by Castillo et al (), Frankl et al (), and Gómez‐Gutiérrez, Schnabel, Berenguer‐Sempere, Lavado‐Contador, and Rubio‐Delgado (); watershed description by Ouédraogo, Degré, Debouche, and Lisein (); soil surface roughness measurements by Snapir, Hobbs, and Waine (), Nouwakpo et al (), Thomsen, Baartman, Barneveld, Starkloff, and Stolte (), and Kaiser et al (); badland analysis from Smith and Vericat (); and field plot investigations by Eltner, Maas, and Faust () and Hänsel, Schindewolf, Eltner, Kaiser, and Schmidt (). Also Bauer, Strauss, and Murer () and Bauer et al () show the potential of SfM for soil roughness, consolidation, and volumetric measurements (e.g., for bulk density) in close range applications.…”