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Selection of a Parameter Describing Soil Surface Roughness
Author(s) -
Lehrsch G. A.,
Whisler F. D.,
Römkens M. J. M.
Publication year - 1988
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1988.03615995005200050044x
Subject(s) - transect , seedbed , surface roughness , soil science , surface finish , environmental science , roughness length , hydrology (agriculture) , materials science , geology , seedling , geotechnical engineering , agronomy , composite material , wind profile power law , wind speed , oceanography , biology
The microrelief of the soil surface, termed soil surface roughness, affects water movement into a soil profile as well as seedling germination in the seedbed. When analyzing surface roughness, the selection of a measurable, physically significant parameter describing roughness is critical. An evaluation was conducted on eight roughness parameters, including maximum peak height, a microrelief index (the area per unit transect length between the measured surface profile and the least‐squares regression line through all measured positions of the transect), peak frequency, and MIF (the product of the microrelief index and peak frequency). The objective of the study was to select the parameter being the best descriptor of soil surface roughness. An automated, noncontact profiler was used to obtain surface profiles along transects, 5‐cm apart, of 1‐m by 1‐m plots after a cultivation and a simulated rainfall application at each of three different stages of soybean [ Glycine max (L.)] development. For each cultivation, surface profiles were obtained on bare plots before rainfall and on adjacent vegetated plots after rainfall. The common logarithm of the MIF parameter was selected as the best descriptor of surface roughness because of its sensitivity to simulated rainfall as a source of variation, and its consistent response to such rainfall. MIF can also account for spatial dependency and can be measured relatively precisely.