Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface

• Published in: Nonlinear processes in geophysics Vol. 24; no. 3; pp. 569 - 579
• Main Authors: Abban, Benjamin K. B., Papanicolaou, A. N. (Thanos), Giannopoulos, Christos P., Dermisis, Dimitrios C., Wacha, Kenneth M., Wilson, Christopher G., Elhakeem, Mohamed
• Format: Journal Article
• Language: English
• Published: Gottingen Copernicus GmbH 28.09.2017; Copernicus Publications
• Subjects: Agricultural land; Cameras; Climate change; Computer simulation; Environmental aspects; Environmental impact; Experiments; Laboratories; Landscape; Lasers; Length; Markov chains; Observations; Rain; Rainfall; Rainfall impact; Rainfall intensity; Rainfall simulators; Scanners; Simulators; Soil; Soil conditions; Soil erosion; Soil mechanics; Soil moisture; Soil surfaces; Soils; Studies; Surface chemistry; Surface roughness; United States > US
• ISSN: 1607-7946; 1023-5809; 1607-7946
• DOI: 10.5194/npg-24-569-2017

This study examines the rainfall-induced change in soil microroughness of a bare smooth soil surface in an agricultural field. The majority of soil microroughness studies have focused on surface roughness on the order of ∼ 5–50 mm and have reported a decay of soil surface roughness with rainfall. However, there is quantitative evidence from a few studies suggesting that surfaces with microroughness less than 5 mm may undergo an increase in roughness when subject to rainfall action. The focus herein is on initial microroughness length scales on the order of 2 mm, a low roughness condition observed seasonally in some landscapes under bare conditions and chosen to systematically examine the increasing roughness phenomenon. Three rainfall intensities of 30, 60, and 75 mm h−1 are applied to a smoothened bed surface in a field plot via a rainfall simulator. Soil surface microroughness is recorded via a surface-profile laser scanner. Several indices are utilized to quantify the soil surface microroughness, namely the random roughness (RR) index, the crossover length, the variance scale from the Markov–Gaussian model, and the limiting difference. Findings show a consistent increase in roughness under the action of rainfall, with an overall agreement between all indices in terms of trend and magnitude. Although this study is limited to a narrow range of rainfall and soil conditions, the results suggest that the outcome of the interaction between rainfall and a soil surface can be different for smooth and rough surfaces and thus warrant the need for a better understanding of this interaction.