Wind Erosion in Western Queensland Australia

Chapter 5 – Land Erodibility Model Developmentdetect erodible regions in arid and semi-arid Australia that are consistent with satellite andobservational records of wind erosion activity. However, the model accuracy was affected byits rule-based structure which biased the output toward particular soil texture groups. It didnot account for the dynamic nature of soil surface conditions. In addition to this, the modelformulation was restrictive such that AUSLEM could not capture the full range of theerodibility continuum (Figure 2.11). The monthly temporal resolution of inputs confoundedthis issue and suppressed the model sensitivity to short-term (e.g. daily) rainfall events thatare an important driver of land erodibility dynamics. A new scheme is therefore requiredwhich can capture high temporal resolution changes in land erodibility and through the fullrange of the land erodibility continuum described in Chapter 2.Computation of u *t forms the basis of the particle emission schemes in many process basedwind erosion models (Hagen, 1991; Marticorena and Bergametti, 1995; Shao et al., 1996;Gregory et al., 2004). As u *t is independent of but determines the wind velocity at whichparticle entrainment occurs it can be physically related to erosion controls. However,modelling land susceptibility to wind erosion using a physical parameterisation of u *t iscomputationally intensive and requires continual measurement of variables that are difficultto quantify, e.g. frontal area effects of vegetation and soil particle size distribution (Shao,2000). The lack of suitable spatial data required as input to the models has also been alimiting factor to their application (Raupach and Lu, 2004).Land erodibility to wind is a concept and cannot be directly measured in the field. It can,however, be inferred through either u *t , or measurements of wind erosion rates under avariety of conditions for some reference wind velocity. Empirical functions relating erosionrates (i.e. streamwise sediment flux in gm -1 s -1 ) to surface conditions have been used in thedevelopment of field scale wind erosion models with applications in North America andAfrica (Woodruff and Siddoway, 1965; Fryrear et al., 1998; Visser et al., 2005; Chapter 3). Ifderived under standard measurement conditions (i.e. wind tunnel dimensions, wind speeds,etc.) simple empirical expressions can be combined to model the land erodibility continuum.A benefit of this approach is that a model can be developed using functions for which spatialdata tend to be readily available as inputs. Further, calibration of the models to improveperformance can be achieved without violating assumptions inherent to physicalparameterisations of u *t . Caveats of using empirical soil loss functions to define wind erosionrates and land erodibility are that they must exist relative to some reference wind speed at135