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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

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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

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