Wind Erosion in Western Queensland Australia
Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One
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
Chapter 5 – Land Erodibility Model DevelopmentThe development of models provides a means for assessing and extending our understandingof wind erosion processes across multiple spatial and temporal scales. There are fewaccessible methods for modelling or mapping spatio-temporal patterns of wind erosionhazard in Australia at moderate to high spatio-temporal resolutions (< 10 3 km 2 ; daily –monthly). The development of the Integrated Wind Erosion Modelling System (IWEMS) hasprovided a resource for addressing this deficiency, but the model is currently only applicableat a moderate (5 x 5 km) spatial resolution within south-eastern Australia (Lu and Shao,2001). Webb et al. (2006) presented a spatially explicit Australian Land Erodibility Model(AUSLEM) for predicting land susceptibility to wind erosion. The model was applied at a 5 x5 km spatial resolution on a monthly time-step across Australia. Qualitative comparisons ofmodel output with an index of wind erosion activity indicated that the model could hind-casterosion hazard with a reasonable level of success. However, the model used a thresholdbasedrule-set which tended to bias output predictions toward areas situated in a small rangeof soil textures.This chapter addresses the limitations of the AUSLEM rule-based modelling system byderiving a new scheme to predict land erodibility. The chapter presents a description of therevised land erodibility model and evaluates model performance through a comparison ofoutput and observational records of wind erosion activity. The focus of this research was todevelop AUSLEM to predict land susceptibility to wind erosion in western Queensland,Australia.5.2 Study AreaAnalyses of long term dust-event frequencies in Australia indicate that the eastern half of thecontinent is the most active wind erosion region (McTainsh et al. 1990). Model developmentand validation were carried out for the northern part of this region, in western Queensland.Figure 5.1 provides a map of the study area, as described in Chapter 1, Section 1.6. The mapshows the extent of the four bioregions covering the western Queensland rangelands and thelocation of meteorological stations from which observational records of dust events, used inthis chapter, were acquired. Wind erosion is infrequently observed to the east of the studyarea due to higher annual rainfall and vegetation cover, so that area is not considered here.131
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Chapter 5 – Land Erodibility Model DevelopmentThe development of models provides a means for assess<strong>in</strong>g and extend<strong>in</strong>g our understand<strong>in</strong>gof w<strong>in</strong>d erosion processes across multiple spatial and temporal scales. There are fewaccessible methods for modell<strong>in</strong>g or mapp<strong>in</strong>g spatio-temporal patterns of w<strong>in</strong>d erosionhazard <strong>in</strong> <strong>Australia</strong> at moderate to high spatio-temporal resolutions (< 10 3 km 2 ; daily –monthly). The development of the Integrated <strong>W<strong>in</strong>d</strong> <strong>Erosion</strong> Modell<strong>in</strong>g System (IWEMS) hasprovided a resource for address<strong>in</strong>g this deficiency, but the model is currently only applicableat a moderate (5 x 5 km) spatial resolution with<strong>in</strong> south-eastern <strong>Australia</strong> (Lu and Shao,2001). Webb et al. (2006) presented a spatially explicit <strong>Australia</strong>n Land Erodibility Model(AUSLEM) for predict<strong>in</strong>g land susceptibility to w<strong>in</strong>d erosion. The model was applied at a 5 x5 km spatial resolution on a monthly time-step across <strong>Australia</strong>. Qualitative comparisons ofmodel output with an <strong>in</strong>dex of w<strong>in</strong>d erosion activity <strong>in</strong>dicated that the model could h<strong>in</strong>d-casterosion hazard with a reasonable level of success. However, the model used a thresholdbasedrule-set which tended to bias output predictions toward areas situated <strong>in</strong> a small rangeof soil textures.This chapter addresses the limitations of the AUSLEM rule-based modell<strong>in</strong>g system byderiv<strong>in</strong>g a new scheme to predict land erodibility. The chapter presents a description of therevised land erodibility model and evaluates model performance through a comparison ofoutput and observational records of w<strong>in</strong>d erosion activity. The focus of this research was todevelop AUSLEM to predict land susceptibility to w<strong>in</strong>d erosion <strong>in</strong> western <strong>Queensland</strong>,<strong>Australia</strong>.5.2 Study AreaAnalyses of long term dust-event frequencies <strong>in</strong> <strong>Australia</strong> <strong>in</strong>dicate that the eastern half of thecont<strong>in</strong>ent is the most active w<strong>in</strong>d erosion region (McTa<strong>in</strong>sh et al. 1990). Model developmentand validation were carried out for the northern part of this region, <strong>in</strong> western <strong>Queensland</strong>.Figure 5.1 provides a map of the study area, as described <strong>in</strong> Chapter 1, Section 1.6. The mapshows the extent of the four bioregions cover<strong>in</strong>g the western <strong>Queensland</strong> rangelands and thelocation of meteorological stations from which observational records of dust events, used <strong>in</strong>this chapter, were acquired. <strong>W<strong>in</strong>d</strong> erosion is <strong>in</strong>frequently observed to the east of the studyarea due to higher annual ra<strong>in</strong>fall and vegetation cover, so that area is not considered here.131