Wind Erosion in Western Queensland Australia

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Chapter 5 – Land Erodibility Model Developmenttree and stone cover effects on wind erosion, provide a more appropriate parameterisation ofthe erodibility continuum and further improve the model skill in assessing land susceptibilityto wind erosion.Vegetation EffectsVegetation effects on land erodibility are considered by separating the effects of woody(shrub/tree) and herbaceous (grass) cover. Herbaceous vegetation cover in arid and semi-aridenvironments tends to increase and decrease at rates faster than shrub- and tree cover inresponse to climate and management (Specht and Specht, 1999). While regional tree covercan be considered static over short periods, and its effect on wind erosion can be consideredby a simple threshold, the effects of temporally dynamic grass cover are better modelled by acontinuous function. The effects of grass cover (E gc ) on land erodibility are modelled by anegative exponential relationship:E gc(% gc)= exp(5.2)where α and β are regression coefficients (55.873; -0.0938) denoting the equation interceptand rate of change in erodibility given a change in percentage cover (Chapter 2, Figure 2.7).The relationship was determined by wind tunnel experimentation at wind speed 18 ms -1(Leys, 1991a) and is similar to that determined by Chepil (1944), and the Soil Loss Ratio(SLR) relating soil loss from a soil with cover to that of a bare soil (Fryrear, 1985; Findlateret al., 1990; Chapter 2, Section 2.2.8). While the expression was developed for prostrate (flatlying) wheat stubble, similar exponential relationships were determined by Siddoway et al.(1965) and Lyles and Allison (1981) for standing stubble. By increasing surface roughness,low cover levels of standing vegetation can reduce wind erosion to rates experienced athigher levels of prostrate cover. The mixture of prostrate and standing grass cover in thestudy region can be accounted for by adjusting the regression coefficients in Equation 5.2 toincrease or decrease the sensitivity of land erodibility to grass cover.Marshall (1972) determined a threshold for wind erosion control based on tree and shrubcover. The threshold exists where tree/shrub spacing is approximately 3.5 times the averagemaximum height of the vegetation, corresponding to roughly 20% lateral cover in the drylandshrub communities in Australia. Tree cover effects on land erodibility are modelled in138
Chapter 5 – Land Erodibility Model DevelopmentAUSLEM using a mask based on this cover threshold. The tree-cover mask (E tc ) assigns anerodibility rank of 0 (not erodible) to land areas with tree cover greater than 20%.Soil Moisture EffectsLand susceptibility to wind erosion may be significantly reduced by inter-particle cohesiveforces associated with soil moisture. The relationship between soil moisture and u *t has beendescribed by a number of authors, but empirical and theoretical models describing therelationship differ between studies due to differences in soil properties, experimental methodsand assumptions about the inter-particle contact geometries (Chepil, 1956; Belly, 1964;McKenna-Neuman and Nickling, 1989; Chen et al., 1996; Fécan et al., 1999, Cornelis andGabriels, 2003; Chapter 2, Section 2.2.5).An expression was sought that could be applied with the available input spatial datarepresenting soil moisture in the top 10 cm of profile (in mm of water per 10 cm). Ananalysis of dust-event frequencies was used to derive an appropriate function as wind tunnelexperimentation was not available for use in this study. Local dust-event (MeteorologicalCode 07) frequencies at 16 Australian Government Bureau of Meteorology stations inwestern Queensland, Australia, were related to event day soil moisture conditions within 25 x25 km windows representing potential dust source areas (PDSAs) surrounding the stations.The window size was selected based on the likely visible range within which blowing dustcould be seen from the stations. Soil moisture data for the PDSAs was extracted from theAussieGRASS pasture growth model (Rickert and McKeon, 1982; Littleboy and McKeon,1997). A database was then established listing the mean PDSA soil moisture conditions foreach dust event. Local dust-events were used as this is the only event type for which potentialsource areas can be defined with confidence; potential source areas for dust storms (Codes09, 30-35) and dust hazes (Codes 05, 06) could not be identified using the availableobservational data (code definitions in Goudie and Middleton, 2006). Local dust-eventfrequencies were plotted for 10 soil moisture classes defined by an arbitrary even breakdownof the distribution of 170 events, with soil moisture values from 0 to 36 mm per 10 cm,between 1991 and 2006. The data can be represented by a negative exponential relationshipof the form:wE w= exp (5.3)139
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Modelling Land Susceptibility toWin
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AUSLEM was developed as a Geographi
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who joined me on many trips, shared
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Conference Presentations by the Aut
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2.2.5 Soil Moisture Effects........
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Chapter 6: Assessing Land Susceptib
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List of FiguresChapter 1: Introduct
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Figure 2.11 Conceptual model of lan
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hand column) presents trajectories
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List of TablesChapter 1: Introducti
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Chapter 1 - Introduction• The abi
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Chapter 1 - Introductionchapter the
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Chapter 1 - IntroductionFigure 1.2
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Chapter 1 - Introductionsusceptibil
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Chapter 1 - Introductiontemporal pa
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Chapter 1 - Introduction1.5 Researc
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Chapter 1 - IntroductionFigure 1.3
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Chapter 1 - IntroductionSimpson-Str
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Chapter 1 - IntroductionDowns. Wind
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Chapter 8 - Conclusions• There is
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Chapter 8 - ConclusionsThe third ai
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Chapter 8 - Conclusionswas shown to
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Chapter 8 - Conclusionsland use cha
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Chapter 8 - Conclusionsmodels are n
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Chapter 8 - Conclusionsmultiple ass
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Chapter 8 - Conclusionsthe opportun
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Beadle, N.C.W., 1945. Dust storms.
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Bryan, R.B., Govers, G., Poesen, J.
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Chepil, W.S., 1965. Transport of so
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Fryrear, D.W., Sutherland, P.L., Da
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Gregory, J.M., 1984. Prediction of
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Hugenholtz, C.H., Wolfe, S.A., 2005
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Littleboy, M., McKeon, G.M., 1997.
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Marshall, J.K., 1973. Drought, land
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Assessment Report of the Intergover
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Penner, J.E., et al. , 2001. Climat
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Rickert, K.G., McKeon, G.M., 1982.
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Stokes, C., J., McAllister, R.R.J.,
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Williams, W.J., Eldridge, D.J., Alc
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Wind Erosion in Western Queensland Australia

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