[1] The presence of nonerodible elements is well understood to be a reducing factor for soil erosion by wind, but the limits of its protection of the surface and erosion threshold prediction are complicated by the varying geometry, spatial organization, and density of the elements. The predictive capabilities of the most recent models for estimating wind driven particle fluxes are reduced because of the poor representation of the effectiveness of vegetation to reduce wind erosion. Two approaches have been taken to account for roughness effects on sediment transport thresholds. Marticorena and Bergametti (1995) in their dust emission model parameterize the effect of roughness on threshold with the assumption that there is a relationship between roughness density and the aerodynamic roughness length of a surface. Raupach et al. (1993) offer a different approach based on physical modeling of wake development behind individual roughness elements and the partition of the surface stress and the total stress over a roughened surface. A comparison between the models shows the partitioning approach to be a good framework to explain the effect of roughness on entrainment of sediment by wind. Both models provided very good agreement for wind tunnel experiments using solid objects on a nonerodible surface. However, the Marticorena and Bergametti (1995) approach displays a scaling dependency when the difference between the roughness length of the surface and the overall roughness length is too great, while the Raupach et al. (1993) model's predictions perform better owing to the incorporation of the roughness geometry and the alterations to the flow they can cause.Citation: King, J., W. G. Nickling, and J. A. Gillies (2005), Representation of vegetation and other nonerodible elements in aeolian shear stress partitioning models for predicting transport threshold,

[1] Roughness influences the flux of wind-driven sand transport. In this paper, we report on sediment transport measurements for four different surface roughness configurations composed of the same size (solid) roughness elements in the atmospheric inertial sublayer. Results of these tests indicate that sediment transport rates through patches of roughness in the atmospheric inertial sublayer are to a large extent controlled and scale proportionally with the roughness density (l = n b h/S, where n is number of elements of breadth b and height h in area S) of the surface. However, element size apparently increases the magnitude of the reduction beyond that attributable to l. A sediment transport model that incorporates the effect of shear stress partitioning appears to predict reasonably well the effect of roughness on sand transport in the cases where the roughness elements are 0.10 m in height. However, when the dimensions of the roughness itself are equivalent to or are greater than the range of saltation lengths (vertical and horizontal), additional interactions of the elements with the saltation cloud appear to reduce the transport efficiency.

[1] Whole-plant drag coefficients (C d ) for three plant species: Burning Bush (Euonymus alatus), Colorado Blue Spruce (Picea pungens glauca.), and Fountain Grass (Pennisetum setaceum) in five different porosity configurations were developed from force versus wind speed data collected with a force balance in a recirculating wind tunnel. The average C d for the Burning Bush, Colorado Spruce, and Fountain Grass in their untrimmed forms were 0.42 (±0.03), 0.39 (±0.04), and 0.34 (±0.06), respectively. Drag curves (C d versus flow Reynolds number (R e ) function) for the Burning Bush and Colorado Spruce were found to exhibit, for the lower porosity configurations, a rise to a maximum around flow Reynolds numbers (R e = ru h h/n) of 2 Â 10 5 . Fountain Grass C d was shown to be dependent upon R e to values >5 Â 10 5 . The Burning Bush and Colorado Spruce plants reduced their drag, upon reaching their maxima, by decreasing their frontal area and increasing their porosity. Maximum C d for these plants occurred at optical porosities of $0.20. The Fountain Grass reduced drag at high R e by decreasing frontal area and porosity. The mechanism of drag reduction in Fountain Grass was continual reconfiguration to a more aerodynamic form as evidenced by continual reduction of C d with R e .

Drag partition measurements were made in the atmospheric inertial sublayer for six roughness configurations made up of solid elements in staggered arrays of different roughness densities. The roughness was in the form of a patch within a large open area and in the shape of an equilateral triangle with 60 m long sides. Measurements were obtained of the total shear stress (τ ) acting on the surfaces, the surface shear stress on the ground between the elements (τ S ) and the drag force on the elements for each roughness array. The measurements indicated that τ S quickly reduced near the leading edge of the roughness compared with τ , and a τ S minimum occurs at a normalized distance (x/h, where h is element height) of ≈ −42 (downwind of the roughness leading edge is negative), then recovers to a relatively stable value. The location of the minimum appears to scale with element height and not roughness density. The force on the elements decreases exponentially with normalized downwind distance and this rate of change scales with the roughness density, with the rate of change increasing as roughness density increases. Average τ S : τ values for the six roughness surfaces scale predictably as a function of roughness density and in accordance with a shear stress partitioning model. The shear stress partitioning model performed very well in predicting the amount of surface shear stress, given knowledge of the stated input parameters for these patches of roughness. As the shear stress partitioning relationship within the roughness appears to come into equilibrium faster for smaller roughness element sizes it would also appear the Boundary-Layer Meteorol (2007) 122:367-396 shear stress partitioning model can be applied with confidence for smaller patches of smaller roughness elements than those used in this experiment. List of SymbolsA f frontal area of roughness elements (m 2 ) A u unit area over which surface shear stress associated with a roughness element is distributed (m 2 ) b element breadth (m) Cd surface drag coefficient Cd e roughness element drag coefficient Cd r rough surface drag coefficient Cd s smooth surface drag coefficient cv coefficient of variation d displacement height (m) F force on a roughness element (N) g acceleration due to gravity (m s −2 ) h element height (m) IBL internal boundary layer ISL inertial sublayer m empirical constant between 0 and 1 n number of roughness elements occupying the ground area of the roughness array NDD normalized downwind distance (x/h) NED normalized element drag R average friction velocity ratio R l local friction velocity ratio at different positions in a roughness array Re Reynolds number R t threshold wind friction velocity ratio SD standard deviation of a mean value u wind speed (m s −1 ) u * wind friction velocity (m s −1 ) u * tR threshold wind friction velocity with roughness elements (m s −1 ) u * tS threshold wind friction velocity of bare surface (m s −1 ) x downwind distance (m) z reference height above surface (m) z w roughness sublayer height (m) z o a...

[1] Surface roughness plays a key role in determining aerodynamic roughness length (z o ) and shear velocity, both of which are fundamental for determining wind erosion threshold and potential. While z o can be quantified from wind measurements, large proportions of wind erosion prone surfaces remain too remote for this to be a viable approach. Alternative approaches therefore seek to relate z o to morphological roughness metrics. However, dust-emitting landscapes typically consist of complex small-scale surface roughness patterns and few metrics exist for these surfaces which can be used to predict z o for modeling wind erosion potential. In this study terrestrial laser scanning was used to characterize the roughness of typical dust-emitting surfaces (playa and sandar) where element protrusion heights ranged from 1 to 199 mm, over which vertical wind velocity profiles were collected to enable estimation of z o . Our data suggest that, although a reasonable relationship (R 2 > 0.79) is apparent between 3-D roughness density and z o , the spacing of morphological elements is far less powerful in explaining variations in z o than metrics based on surface roughness height (R 2 > 0.92). This finding is in juxtaposition to wind erosion models that assume the spacing of larger-scale isolated roughness elements is most important in determining z o . Rather, our data show that any metric based on element protrusion height has a higher likelihood of successfully predicting z o . This finding has important implications for the development of wind erosion and dust emission models that seek to predict the efficiency of aeolian processes in remote terrestrial and planetary environments.