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Spatial distribution of surface rock fragments along catenas in semiarid Arizona and Nevada, USA

Simanton, J.R., Renard, K.G., Christiansen, C.M., Lane, L.J.
Catena 1994 v.23 no.1-2 pp. 29
rocks, spatial distribution, catenas, soil, surfaces, surface layers, slope, vegetation, vegetation cover, equations, semiarid zones, semiarid soils, soil erosion, prediction, soil erosion models, Arizona, Nevada
Improved techniques for estimating soil erosion by water have shown that soil surface cover is a major component in the estimate of soil loss. Erosion prediction models require the user to input slope gradient and soil profile descriptions. If equations expressing the relations between slope gradient, soil profile rock fragment content, and surface rock fragment cover were embedded in these models, then direct user input could be reduced. Field measurements of slope gradient, soil profile rock fragment content, surface rock fragment cover, and vegetation type and cover were made on 12 soil-slope complexes on catenas in southeastern Arizona, USA. Correlation analysis showed that both slope gradient and soil profile rock fragment content were significantly (p < 0.01) correlated to surface rock fragment cover. Additional analysis indicated that the combined effects of slope gradient and soil profile rock content were better defined by a soil-slope factor (SSF). Two equations were developed to estimate surface rock fragment cover; a logarithmic relation using slope gradient as the independent variable and a hyperbolic equation using the SSF as the independent variable. These equations were used to estimate surface rock fragment cover from a soil-slope complex in southern Nevada. The SSFRFc equation gave better estimates of the measured surface rock fragment cover. These relations developed for catenas in southeastern Arizona may be site specific but they do show that a relation exists for this semiarid area and suggest that similar relations may exist in areas with similar geology and climate such as parts of Africa, Asia, Australia, and South America. Development of simple relations describing important erosion processes will improve erosion estimates while simultaneously decreasing time and costs associated with using erosion prediction models.