Temporal and spatial evolution of soil surface roughness on stony plots

Authors: LI, LI - University Of Arizona; Nearing, Mark; Nichols, Mary; Polyakov, Viktor; WINTER, C.L. - University Of Arizona; Cavanaugh, Michelle

Submitted to: Soil & Tillage Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/28/2019
Publication Date: 9/9/2020
Publication URL: https://handle.nal.usda.gov/10113/6775208
Citation: Li, L., Nearing, M.A., Nichols, M.H., Polyakov, V.O., Winter, C., Cavanaugh, M.L. 2020. Temporal and spatial evolution of soil surface roughness on stony plots. Soil & Tillage Research. 200. https://doi.org/10.1016/j.still.2019.104526.
DOI: https://doi.org/10.1016/j.still.2019.104526

Interpretive Summary: Scientists often measure the roughness of soil surfaces for a variety of reasons, including when attempting to understand how water moves over a soil surface and how much soil is eroded during a rainstorm. On rocky soils, such as we find in the Southwestern part of the United States, when soils erode the fine soil particles tend to be eroded first, often leaving a lot of rocks on the soil surface. These rocks are a big part of what constitutes the roughness of those surfaces. In this experiment we applied artificial rainfall to a 6 by 20-foot soil plot and measured how the surface roughness and rock cover changed over time. The measurements were made with a Terrestrial LiDAR scanner, which is a very accurate instrument for measuring surface elevations utilizing a laser. We found that steeper slopes evolved to a greater roughness than did the less steep slopes. We also found that the surfaces were fractal in nature, and the characteristics of the fractals that we measured told us a lot about the geometry of those surfaces and how they changed at different scales. For example, we found that the parameter called the fractal dimension told us a lot about the complexity of the surface, including large scale features such as eroded rills. Other numbers calculated from the fractal analysis, such as the scaling parameter crossover length, told us more about the smaller scale roughness that would influence surface water runoff velocities on hillslopes.

Technical Abstract: Soil surface roughness (SSR) is widely recognized as an important factor influencing water erosion processes. On semiarid hillslopes with stony soils, rock fragments accumulate as the result of preferential erosion of fine materials, often creating a rough, rocky surface. A series of rainfall events were simulated on a stony plot (2 × 6.1 m) at three slope gradients (5%, 12%, and 20%) and rock cover was measured. Surface elevations were sampled by terrestrial LiDAR at high resolutions. Calculated roughness indices included random roughness (RR), fractal dimension and generalized fractal dimension. Results showed: 1) SSR displayed an increasing trend as the rainfall simulation proceeded for all three slope treatments; 2) the steeper slope developed greater surface roughness; and 3) both the increase of surficially exposed rocks and the formation of erosional features, e.g., rills and depressions, contributed to the spatiotemporal variations of SSR. Results showed that fractal dimension was not a good indicator of surface roughness, but rather was an index of the form of the surface. Random roughness and crossover length were indicators of surface roughness, the difference being that crossover length was a measure of roughness at a scale of a few millimeters, while random roughness was a measure of elevation variation on the scale of the length of the transect measured, and thus encompassed larger morphological features including rills. We also established a new method for analyzing multiple fractals that characterized the heterogeneity. These results improve our understanding of the evolution of semiarid stony hillslopes