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Wind Erosion in Western Queensland Australia

Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One

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Chapter 4 –Modell<strong>in</strong>g Soil Erodibility Dynamicsand management factors, the slope gradient or rate of change <strong>in</strong> erodibility, and therefore them<strong>in</strong>imum period of time a soil may spend <strong>in</strong> this phase mov<strong>in</strong>g toward Q max .Gillette (1978) reported on the dependence of soils on drought to experience an <strong>in</strong>crease <strong>in</strong>erodibility to w<strong>in</strong>d (Chapter 2, Figure 2.5). His results show that the erodibility of sandy soilswith 40% clay are highly dependent ondrought to experience an <strong>in</strong>crease <strong>in</strong> erodibility. This time dependence is driven by the soilparticle size distributions and particle shapes which affect the strength of <strong>in</strong>ter-particle bonds.The f<strong>in</strong>al phase <strong>in</strong> the cont<strong>in</strong>uum, (iii) def<strong>in</strong>es the condition of maximum erodibility (Q max ).In order for a soil to reach this condition moisture content (antecedent ra<strong>in</strong>fall) must be at am<strong>in</strong>imum and disturbance to the soil surface at a maximum. Soils at Q max can be consideredto have an effective gra<strong>in</strong> diameter d of 0.08 mm to position the soil at the u *t m<strong>in</strong>ima(Chapter 2, Figure 2.3) reported by Bagnold (1941).Mathematically the phase shifts through the soil erodibility cont<strong>in</strong>uum, from i to iii (Figure4.4), can be def<strong>in</strong>ed by a logistic (sigmoid) curve. Numerous expressions are available thatcan be used to del<strong>in</strong>eate the shape of this curve (e.g. Richards, 1959; Turner et al., 1976). Thelogistic curve form can be approximated with few parameters, mak<strong>in</strong>g it a good start<strong>in</strong>g po<strong>in</strong>tfor modell<strong>in</strong>g temporal changes <strong>in</strong> soil erodibility to w<strong>in</strong>d. The model framework presentedhere uses the Richard’s equation (Richards, 1959), selected for its wide application <strong>in</strong>modell<strong>in</strong>g vegetation growth dynamics (Tsoularis and Wallace, 2002) and more recentlydunefield activation and stabilisation (Hugenholtz and Wolfe, 2005). In differential form theRichard’s equation is expressed as:dNdt N = rN 1 (4.7) K where N is the population size, r is the growth rate, β is a positive real number and K is thepopulation carry<strong>in</strong>g capacity reached as lim t→∞ N(t) = K. The <strong>in</strong>tegral of Equation (4.7) isthen:113

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