Parameterization of a drag partition scheme using field measurements of surface shear stress distribution

Authors: ZIEGLER, NANACY - Us Army Engineer Research And Dvelopment Center; WEBB, NICHOLAS - New Mexico State University; GILLIES, JACK - Desert Research Institute; NIKOLICH, GEORGE - Desert Research Institute; Van Zee, Justin; EDWARDS, BRANDON - New Mexico State University; OKIN, GREGORY - University Of California (UCLA); LEGRAND, SANDRA - Us Army Engineer Research And Dvelopment Center

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 7/28/2020
Publication Date: N/A
Citation: N/A

Interpretive Summary: Here, we present a field test of a model to estimate effects of vegetation on wind erosion over a National Wind Erosion Research Network site with mixed grasses and shrubs at the Jornada Experimental Range in New Mexico. We compare measurements of wind-blown sediment flux from 27 Modified Wilson and Cook (MWAC) sediment collectors and surface wind firction velocity (us*) from an array of 27 Irwin pressure sensors installed in the soil surface with estimates of the distribution of wind shear stress at the surface and resultant flux estimates calculated by applying the model to on-site vegetation and meteorological observations over the same measurement period. Results confirm the model accuracy to predict effects of vegetation on wind erosivity and sediment mass flux The results of this research confirm the findings of earlier wind tunnel studies of the need to represent the spatial distribution of wind erosivity over the soil surface to accurately estimate wind erosion.

Technical Abstract: Inherent biases in sediment transport and dust emission models present a problem for understanding the frequency and magnitude of dust emitted from landscapes and how the overall dust cycle responds to environmental change. Specifically, the insensitivity of dust models to surface roughness, particularly vegetation, leads to inaccurate—often by orders of magnitude—predictions of horizontal sediment transport, Q, with poorly defined or unknown uncertainties, limiting our ability to forecast large-scale dust events. Since dust emission schemes are largely driven by Q, it is critical to improve predictive modeling capabilities and reduce uncertainty by more fully representing the effects of surface roughness on sediment transport processes.  Dust emission models that incorporate the effects of vegetation generally employ drag partition schemes that quantify surface roughness using look-up tables generalized by land cover classes. Consequently, they do not capture spatial and temporal variability in vegetation structure, distribution, and configuration. Okin (2008) developed a drag partition scheme to more accurately represent the dynamic effect of vegetation on the momentum partition. The Okin scheme uses the size distribution of gaps between roughness elements to characterize the surface shear stress (us*). To date, however, validation and parameterization of this scheme have been limited due to cost of data collection, instrument maintenance, and the lack of high-quality, high-frequency data required to do so.  Here, we present a field test of the Okin (2008) drag partition scheme using measurements of us* collected over a 1 ha site with heterogeneous surface roughness at the Jornada Experimental Range in New Mexico. We compare measurements of sediment flux from 27 MWAC sediment collectors and us* from an array of 27 Irwin pressure sensors installed in the sediment bed with estimates of the distribution of stress at the surface and resultant flux estimates calculated by applying the Okin drag partition to on-site vegetation and meteorological observations over the same measurement period. Results confirm the efficacy of the Okin scheme to predict the drag partition and sediment mass flux and enable local parameterization of the shear stress ratio (us*/u*) and e-folding distance that describe shear stress recovery downwind of vegetation. The results of this research confirm the findings of earlier wind tunnel studies of the need to represent the spatial distribution of us* to accurately estimate aeolian sediment transport.