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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 5 – Land Erodibility Model DevelopmentA pattern was found <strong>in</strong> the years <strong>in</strong> which model output trends went aga<strong>in</strong>st those of dusteventfrequencies. For example, an <strong>in</strong>crease <strong>in</strong> dust events was l<strong>in</strong>ked to a decrease <strong>in</strong> landerodibility. This occurred at three and then four stations <strong>in</strong> 1981 and 1982, at three stations <strong>in</strong>both 1986 and 1987, and at five stations <strong>in</strong> 1990. The poor synchronisation of trends <strong>in</strong> theseyears was found to occur across each of the spatial scales from 25 to 150 km, and resulted <strong>in</strong>the weak correlations at Quilpie, Thargom<strong>in</strong>dah and Birdsville (Table 5.2). Thesynchronisation of trajectories <strong>in</strong> other years was found to be consistently good, except atLongreach where the trends did not match <strong>in</strong> any years.5.6 Discussion5.6.1 Model PerformanceCross-correlation results (Table 5.2) show that AUSLEM performs well at half of the stationsused for validation. The correlations between model output and dust-event frequencies werefound to vary with scale at all of the stations except Longreach, at which there was no matchbetween modelled land erodibility and dust-event frequencies. The differences <strong>in</strong> correlationswith scale <strong>in</strong>dicate that either: 1) the dust source areas responsible for the observed dustevents are located with<strong>in</strong> different areas and at different distances from the stations; 2) thatAUSLEM performs best at a particular scale depend<strong>in</strong>g on the land type characteristicsaround a station, or; 3) a comb<strong>in</strong>ation of these factors is responsible.Figure 5.5a <strong>in</strong>dicates that model output predictions can display similar temporal trends acrossspatial scales. Consistent model performance across scales (i.e. Urandangie) <strong>in</strong>dicates thatgrass cover and soil moisture conditions may be uniform around the station, and/or that thedust source areas were widespread. Variations <strong>in</strong> the trajectories at particular scales are<strong>in</strong>dicative of changes <strong>in</strong> land erodibility at a certa<strong>in</strong> distance from a station. An <strong>in</strong>crease <strong>in</strong>mean output values at larger scales, for example, suggests an <strong>in</strong>crease <strong>in</strong> land erodibilityfurther away from a station. By comparison, lower land erodibility values such as around<strong>W<strong>in</strong>d</strong>orah can be attributed to high vegetation cover on the Coopers’ Creek channels close tothe town. The strengthen<strong>in</strong>g of correlations between model output and dust-event frequenciesat Charleville and Quilpie can be expla<strong>in</strong>ed by local tree clear<strong>in</strong>g (Charleville) and the152

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