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 3 – Modelling Land Erodibility Review10 to 31 vertical layers, and a horizontal resolution ranging from 5 x 5 km to 75 x 75 km. Theatmospheric model provides forcing for both the dust emission and transport models (Lu andShao, 2001).In addition to the spatial expansion of model application, and input upgrades, the modelestimation of u *t was also revised. The revisions built upon the model presented by Shao et al.(1996) and Shao and Leslie (1997), with the inclusion of factors to account for multiple nonerodibleroughness element layers, and the erodible fraction of the exposed surface (Lu andShao, 2001). In a development from the drag partitioning scheme used in WEAM, IWEMSuses a double drag partitioning approach that allows for the independent (and combined)effects of large roughness elements (e.g. trees) and also small roughness elements to bemodelled (Shao, 2000).Lu and Shao (1999) developed a soil classification map to account for spatial differences insoil erodibility. In using this the model groups soil inputs into erodible and non-erodibleclasses, with the erodible soils being assigned particle size distributions based on fieldsamples from the soil type classes (Lu and Shao, 1999). This is similar to the methodologyemployed by Marticorena and Bergametti (1995) to account for spatial variability in desertdust source areas (Section 3.4.1). Due to a lack of quantitative research on the temporalevolution of surface crusts in Australia, the surface crust/mobility factor remained set to aconstant (1) for all soils. The model therefore still lacks a dynamic component to define soilerodibility (Lu and Shao, 2001). This means that temporal changes in u *t in IWEMS aredriven by variations in surface roughness and soil moisture conditions.3.4 Continental to Global Scale ModelsThis section describes the prediction of land erodibility in continental and global scale dustemission and transport models. The section includes reviews of the Dust Production Model(DPM) and Dust Entrainment and Deposition Model (DEAD), and notes characteristics of theCommunity Aerosol and Radiation Model (CARMA), and the Global Ozone ChemistryAerosol Radiation and Transport (GOCART) model. In general these models use erosionschemes developed for smaller scale models, with adaptations to suit their applicationenvironments.86
Chapter 3 – Modelling Land Erodibility Review3.4.1 Dust Production Model (DPM)Marticorena and Bergametti (1995) developed the Dust Production Model (DPM). The modelwas designed with a dust emission scheme that accounts for spatial variations in dust sourceerodibility. Early regional to global scale models (e.g. Tegen and Fung, 1995) compute dustemission as a function of wind velocity. The DPM computes emissions in a similar way toWEAM and IWEMS, using a relationship between soil particle size distribution, surfaceroughness and u *t . Importantly, the approach allows for the direct and relative contributionsof various source areas to global dust emissions to be quantified (Marticorena andBergametti, 1995).The basis of the dust emission scheme is that land erodibility is strongly dependent on soiltexture and surface roughness characteristics. Values for u *t are assigned to soil input mapsbased on the size distribution of particles in different textured soils (Marticorena andBergametti, 1995). Semi-empirical equations of Iversen and White (1982) were thenmodified to obtain a relationship between particle or aggregate diameter and u *t . Therelationship was developed as a piecewise function dependent on the Reynolds number (heredenoted B):( D )0.129Ku*t p=for 0.03 < B < 10 (3.25)x 0.092( 1.928( aD + b)1) 0. 5px( D ) = 0.129K[ 10.0858exp( 0.0617( aD + b)10)]u* t pp for B > 10where D p is the size of the soil surface aggregates (cm),. The Reynolds number (B) isdescribed by the term:xB = aD b(3.26)p+where a = 1331, b = 0.38, and x = 1.56. The influence of surface roughness on the loss ofwind momentum is accounted for using a scheme developed by Marticorena and Bergametti(1995) and Marticorena et al. (1997). The drag partitioning scheme of Raupach et al. (1993)requires a measure of the frontal area and estimation of the m parameter, so an alternatespecification of drag was included in DPM and is based on the roughness length z 0 :87
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Chapter 3 – Modell<strong>in</strong>g Land Erodibility Review10 to 31 vertical layers, and a horizontal resolution rang<strong>in</strong>g from 5 x 5 km to 75 x 75 km. Theatmospheric model provides forc<strong>in</strong>g for both the dust emission and transport models (Lu andShao, 2001).In addition to the spatial expansion of model application, and <strong>in</strong>put upgrades, the modelestimation of u *t was also revised. The revisions built upon the model presented by Shao et al.(1996) and Shao and Leslie (1997), with the <strong>in</strong>clusion of factors to account for multiple nonerodibleroughness element layers, and the erodible fraction of the exposed surface (Lu andShao, 2001). In a development from the drag partition<strong>in</strong>g scheme used <strong>in</strong> WEAM, IWEMSuses a double drag partition<strong>in</strong>g approach that allows for the <strong>in</strong>dependent (and comb<strong>in</strong>ed)effects of large roughness elements (e.g. trees) and also small roughness elements to bemodelled (Shao, 2000).Lu and Shao (1999) developed a soil classification map to account for spatial differences <strong>in</strong>soil erodibility. In us<strong>in</strong>g this the model groups soil <strong>in</strong>puts <strong>in</strong>to erodible and non-erodibleclasses, with the erodible soils be<strong>in</strong>g assigned particle size distributions based on fieldsamples from the soil type classes (Lu and Shao, 1999). This is similar to the methodologyemployed by Marticorena and Bergametti (1995) to account for spatial variability <strong>in</strong> desertdust source areas (Section 3.4.1). Due to a lack of quantitative research on the temporalevolution of surface crusts <strong>in</strong> <strong>Australia</strong>, the surface crust/mobility factor rema<strong>in</strong>ed set to aconstant (1) for all soils. The model therefore still lacks a dynamic component to def<strong>in</strong>e soilerodibility (Lu and Shao, 2001). This means that temporal changes <strong>in</strong> u *t <strong>in</strong> IWEMS aredriven by variations <strong>in</strong> surface roughness and soil moisture conditions.3.4 Cont<strong>in</strong>ental to Global Scale ModelsThis section describes the prediction of land erodibility <strong>in</strong> cont<strong>in</strong>ental and global scale dustemission and transport models. The section <strong>in</strong>cludes reviews of the Dust Production Model(DPM) and Dust Entra<strong>in</strong>ment and Deposition Model (DEAD), and notes characteristics of theCommunity Aerosol and Radiation Model (CARMA), and the Global Ozone ChemistryAerosol Radiation and Transport (GOCART) model. In general these models use erosionschemes developed for smaller scale models, with adaptations to suit their applicationenvironments.86