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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 3 – Modell<strong>in</strong>g Land Erodibility Reviewscales, and <strong>in</strong> particular there is a significant lack of modell<strong>in</strong>g research at the landscape scale(i.e. ~10 3 km 2 ).A number of common challenges and limitations have emerged <strong>in</strong> represent<strong>in</strong>g landerodibility <strong>in</strong> w<strong>in</strong>d erosion models. The first of these represents arguably the greatestchallenge <strong>in</strong> w<strong>in</strong>d erosion modell<strong>in</strong>g, and affects the accuracy of model representations ofland susceptibility to w<strong>in</strong>d erosion. They <strong>in</strong>clude (after Raupach and Lu, 2004):• Reliability of control representations and ability to account for soil erodibility dynamics;• The availability of suitable <strong>in</strong>put data;• Up-scal<strong>in</strong>g models and account<strong>in</strong>g for sub-grid scale heterogeneity; and• Validation of regional to global scale models.3.5.1 Reliability of Control RepresentationsThe reliability of how controls are represented <strong>in</strong> w<strong>in</strong>d erosion models has been affected by:1) a lack of research <strong>in</strong>to the temporal dynamics of soil erodibility, and 2) our ability toaccount for sub-grid scale variations <strong>in</strong> soil and land surface conditions, <strong>in</strong> particular theheterogeneous distribution of surface roughness. The effects of sub-grid scale heterogeneityon model performance are described <strong>in</strong> Section 3.5.3.Raupach and Lu (2004) note that deficiencies <strong>in</strong> dust source parameterisations account for alarge part of the observed discrepancies <strong>in</strong> model estimations of dust emissions. The accuraterepresentation of spatial and temporal patterns <strong>in</strong> land erodibility is therefore essential forgood model performance. While field scale models, for example WEQ, RWEQ, WEPS,conta<strong>in</strong> factors to account for and simulate changes <strong>in</strong> soil erodibility, such factors have notbeen <strong>in</strong>tegrated <strong>in</strong>to the regional to global scale models (Zobeck et al., 2003). These modelsaccount for spatial variations <strong>in</strong> soil erodibility by estimat<strong>in</strong>g u *t as a function of the soilparticle size distribution (e.g. Marticorena and Bergametti, 1995) and/or by designat<strong>in</strong>gregional dust source areas us<strong>in</strong>g topographic, geomorphic or remote sens<strong>in</strong>g based <strong>in</strong>dicators(e.g. G<strong>in</strong>oux et al., 2001; Gr<strong>in</strong>i et al., 2005). The rationale for omitt<strong>in</strong>g soil erodibility factorsfrom these broad-scale models is that robust models to simulate temporal changes <strong>in</strong> soilaggregation and crust<strong>in</strong>g simply do not exist (Shao, 2000). Empirical models, like that used93

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