Wind Erosion in Western Queensland Australia

Chapter 5 – Land Erodibility Model Developmentwind erosion in marginal farming lands (Leys, 1999). Studies reporting the location of areassusceptible to wind erosion have foundations in land degradation surveys, analysis of duststorm frequencies and aerosol indices derived from satellite imagery, or present static erosionhazard maps based on soil texture or wind run. These methods have been applied extensivelyin Africa, North America, Europe, the Middle East and China (e.g. Lynch and Edwards,1980; Kalma et al., 1988; Mezösi and Szatmári, 1998; Prospero et al., 2002; Shi et al., 2004).An important limitation of these methods is that they have not provided a means for assessingdynamic changes in land susceptibility to wind erosion at scales between the field and coarserregional scales (10 4 km 2 ). In Australia reports of the extent of wind erosion have beenproduced from assessments of landscape condition during land degradation episodes (e.g.Ratcliffe, 1937, Carter, 1985). The survey methods tend to provide snapshots of erosionhazard which reflect the regional climate at the time of survey (i.e. drought), and may notaccount for spatial and temporal variability in erosion controls. While numerous wind erosionmodelling systems have been developed, rarely have the models been applied with theexpress purpose of monitoring spatio-temporal variability in areas susceptible to winderosion. This variability can be captured through modelling and is critical for identifyingwind erosion “hot spots” that are significant dust emitters (Gillette, 1999).The development of models to assess land susceptibility to wind erosion should be seen asbeing essential to supporting decisions about the management of dryland environments (e.g.Bhuyan et al., 2002; Bowker et al., 2006). This also applies to the development andapplication of models to assess water erosion (e.g. Berlekamp et al., 2007; Miller et al.,2007). Modelling provides the opportunity to examine spatial and temporal patterns inerosion dynamics within landscapes, at different spatial and temporal resolutions and acrossscales. Spatially distributed models can be used to establish benchmarks of historicalvariations in the landscape response to climate variability and land management pressures,and to provide measures of the sensitivity of landscapes and waterways to climate and landmanagement changes (Tegen and Fung, 1995; Baigorria and Romero, 2007). These are bothrequirements for enhancing land management policy. The need for research of this nature isgrowing, especially in sub-tropical environments in which rainfall amounts and variability,that control erosion processes, are expected to be affected by future climate change (Meehl etal., 2007).130