|Title||Parameterizing an aeolian erosion model for rangelands|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Authors||Edwards, BL, Webb, NP, Galloza, M, Van Zee, JW, Courtright, EM, Cooper, BF, Metz, LJ, Herrick, JE, Okin, GS, Duniway, MC, Tatarko, J, Tedela, NH, Moriasi, DN, Newingham, BA, Pierson, FB, Toledo, D, Van Pelt, RS|
|Keywords||aeolian, Assessment, Dust emission, Indicators, Land management, monitoring, Wind erosion|
Aeolian processes are fundamental to arid and semi-arid ecosystems, but modeling approaches are poorly developed for assessing impacts of management and environmental change on sediment transport rates over meaningful spatial and temporal scales. For model estimates to provide value, estimates of sediment flux that encapsulate intra- and inter-annual and spatial variability are needed. Further, it is important to quantify and communicate transparent estimates of model uncertainty to users. Here, we present a wind erosion and dust emission model parameterized for rangelands using a Generalized Likelihood Uncertainty Estimation framework. Modeled horizontal sediment flux was calibrated using data from five diverse grassland and shrubland sites from the USDA National Wind Erosion Research Network. Observations of wind speed, vegetation height, length of gaps between vegetation, and percent bare ground were used as model inputs. Horizontal sediment flux estimates from 10,000 independently selected parameter sets were compared to flux observations from 44 ∼ month-long collection periods to calculate a likelihood measure for each model. Results show good agreement for individual sampling periods across sites with few observations falling outside prediction bounds and a one-to-one relationship between median predictions and observations. Additionally, combined distributions of sediment flux estimates from all sample periods for a given site closely approximated the probability of observing a given flux at that site. These results suggest AERO effectively represents temporal variability in aeolian transport rates at rangeland sites and provides robust assessments suitable for assessing land health and better predicting changes in air quality and the impacts of land management activities.