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 1 - Introduction• The ability of soils to sustain vegetation and livestock decreases;• Agricultural and pastoral productivity decreases;• Nutrient enrichment of streams occurs with the influx of wind blown sediments;• Spread of herbicides and pesticides off-farm; and• Damage to property (e.g. fences and roads) and farm infrastructure.Off-site effects of wind erosion are relevant across scales and relate to the transport anddeposition of mineral dust which (after Dentener et al., 1996; Prospero et al., 2002; Jickells etal., 2005 and others):• Alters the radiation balance in the atmosphere through scattering and absorption ofradiation;• Affects cloud nucleation and optical properties of the atmosphere;• Acts as a reactive mineral species in the atmosphere;• Moderates the photochemical oxidant cycle and biogeochemical processes;• Acts as a source of Fe that may be metabolised by cyanobacteria and may subsequentlymoderate the nitrogen chemistry of the ocean;• Acts as a source of Fe that may be a limiting nutrient for phytoplankton; and• Provides reaction sites for ozone and nitrogen molecules.Understanding spatial and temporal variations in wind erosion is required to develop methodsfor managing land degradation at the field (10 3 m 2 ) to landscape (10 3 km 2 ) scales, and forunderstanding the regional to global scale consequences of dust transport. Surprisingly littleattention has been given to the development of methods for assessing spatio-temporalpatterns in land areas susceptible to wind erosion.Existing maps of the location and extent of regions prone to wind erosion are based on: fieldassessments of affected areas (Carter, 1985; Mezösi and Szatmári, 1998); observational dataon dust-storm frequencies (Goudie and Middleton, 2006); analyses of satellite imagery(Prospero et al., 2002; Washington et al., 2003); and in a few cases spatial modelling (Böhneret al., 2003; Coen et al., 2004). However, these methods for assessing wind erosion have anumber of limitations. These include:2
Chapter 1 - Introduction1. Field surveys have historically been conducted as individual studies and have onlyprovided snapshots of the landscape condition relevant to the climatic conditions at thetime of survey (Leys, 1999).2. The analysis of dust-storm frequencies relies on the interpolation of data between distantlocations, e.g. meteorological stations in drylands are often >100 km apart, and so isgenerally unable to resolve dust source areas at scales less than ~10 5 km 2 (McTainsh andPitblado, 1987).3. The analysis of aerosol optical depth imagery (Prospero et al., 2002; Washington et al.,2003) and development of dust enhancing indices (Legrand et al., 1994; Miller, 2003) hasprovided a capability to detect point source and regional dust source areas using satelliteimagery. However, these methods cannot provide information on land erodibility unlessthe surface is eroding at the time of image acquisition.4. While numerous wind erosion models have been developed, few have been appliedspecifically to assess land susceptibility to wind erosion. Examples of this applicationhave been restricted to cultivated fields and over small geographic extents (e.g. Coen etal., 2004), or very coarse spatial resolutions (Ginoux et al., 2001).There remains a great deal of speculation about the location and strengths (erodibility) ofwind erosion prone areas (Grini et al., 2005). This is a global issue, relevant to ourunderstanding of the world’s major dust producing regions in Africa, the Middle East, Asia,North and South America, and Australia (Hermann et al., 1999). Quantitatively describingspatial and temporal patterns in land erodibility is essential for enhancing land managementstrategies to combat land degradation in dryland environments. Understanding landerodibility dynamics at the landscape scale (10 3 km 2 ) is also required to better understandregional scale dust emission and transport processes. Without a detailed knowledge of howthe erodibility of drylands responds to climate variability and land management, or of thefeedbacks between local wind erosion activity and regional climate, our capacity to mitigatepotential impacts of global climate change on this degradation process will be severelychallenged.This thesis develops a model to assess land susceptibility to wind erosion, i.e. landerodibility, in the rangelands of western Queensland, Australia. This chapter provides abackground to the research problem and synthesis of the research requirements. This isfollowed by a statement of the research aims and objectives, and research approach. The3
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Chapter 1 - Introduction1. Field surveys have historically been conducted as <strong>in</strong>dividual studies and have onlyprovided snapshots of the landscape condition relevant to the climatic conditions at thetime of survey (Leys, 1999).2. The analysis of dust-storm frequencies relies on the <strong>in</strong>terpolation of data between distantlocations, e.g. meteorological stations <strong>in</strong> drylands are often >100 km apart, and so isgenerally unable to resolve dust source areas at scales less than ~10 5 km 2 (McTa<strong>in</strong>sh andPitblado, 1987).3. The analysis of aerosol optical depth imagery (Prospero et al., 2002; Wash<strong>in</strong>gton et al.,2003) and development of dust enhanc<strong>in</strong>g <strong>in</strong>dices (Legrand et al., 1994; Miller, 2003) hasprovided a capability to detect po<strong>in</strong>t source and regional dust source areas us<strong>in</strong>g satelliteimagery. However, these methods cannot provide <strong>in</strong>formation on land erodibility unlessthe surface is erod<strong>in</strong>g at the time of image acquisition.4. While numerous w<strong>in</strong>d erosion models have been developed, few have been appliedspecifically to assess land susceptibility to w<strong>in</strong>d erosion. Examples of this applicationhave been restricted to cultivated fields and over small geographic extents (e.g. Coen etal., 2004), or very coarse spatial resolutions (G<strong>in</strong>oux et al., 2001).There rema<strong>in</strong>s a great deal of speculation about the location and strengths (erodibility) ofw<strong>in</strong>d erosion prone areas (Gr<strong>in</strong>i et al., 2005). This is a global issue, relevant to ourunderstand<strong>in</strong>g of the world’s major dust produc<strong>in</strong>g regions <strong>in</strong> Africa, the Middle East, Asia,North and South America, and <strong>Australia</strong> (Hermann et al., 1999). Quantitatively describ<strong>in</strong>gspatial and temporal patterns <strong>in</strong> land erodibility is essential for enhanc<strong>in</strong>g land managementstrategies to combat land degradation <strong>in</strong> dryland environments. Understand<strong>in</strong>g landerodibility dynamics at the landscape scale (10 3 km 2 ) is also required to better understandregional scale dust emission and transport processes. Without a detailed knowledge of howthe erodibility of drylands responds to climate variability and land management, or of thefeedbacks between local w<strong>in</strong>d erosion activity and regional climate, our capacity to mitigatepotential impacts of global climate change on this degradation process will be severelychallenged.This thesis develops a model to assess land susceptibility to w<strong>in</strong>d erosion, i.e. landerodibility, <strong>in</strong> the rangelands of western <strong>Queensland</strong>, <strong>Australia</strong>. This chapter provides abackground to the research problem and synthesis of the research requirements. This isfollowed by a statement of the research aims and objectives, and research approach. The3