Wind Erosion in Western Queensland Australia

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Chapter 5 – Land Erodibility Model DevelopmentAUSLEM was run to predict land erodibility on a daily time-step for the period 1980 to 1990.Output was then aggregated into monthly and annual means to match the temporal resolutionof dust-event frequencies. A caveat of using observational dust-event data is the inherentdifficulty in identifying source areas of non-local dust events (i.e. dust hazes, and duststorms). AUSLEM output was compared with the station data at multiple spatial scales todetermine if an optimal scale exists for this validation approach. Firstly, circular source areasof interest (AOIs) were delineated around each of the eight stations to act as potential dustsource regions with radii of 25 km, 50 km, 100 km, and 150 km. The AOI size range wasdetermined based on the ranges of maximum visibility around the stations within which dustevents could be observed, and the requirement to test AUSLEM performance across multiplescales. A second half-circle AOI from (25 to 150 km radii) was then used, with AOIs alignedto the north, south, east and west around the stations. The purpose of this second directionaltest was to determine whether a better comparison between model output and dust-eventfrequencies could be made if only dominant dust sources upwind of the stations wereconsidered. Summary statistics (mean, min, max, standard deviation, mode) of mean annualAUSLEM output were computed for each AOI at each station. Cross-correlation analysis wasthen used to compare temporal trends in model output statistics with the measures of dusteventfrequencies.5.5.2 Results - Annual Land Erodibility PredictionsFigure 5.4 presents mean annual land erodibility predictions for western Queensland from1980 to 1990. Results show that regions experiencing high susceptibility to wind erosionoccur in the south-western corners of the state in the Mulga Lands, Simpson DesertDunefields, and western Channel Country. The Mitchell Grass Downs in the north-east of thestudy region tend to have consistently low land erodibility. The regions of high landerodibility in the south-west lie in the most arid section of the study area (< 250 mm rainfallper annum), while the low erodibility lands to the north-east are consistent with that areareceiving higher mean annual rainfall (~450 mm). The distribution of modelled landerodibility is in agreement with the general spatial pattern of wind erosion activity acrosswestern Queensland (Middleton, 1984; Burgess et al., 1989; McTainsh et al., 1990).144
Chapter 5 – Land Erodibility Model DevelopmentFigure 5.4 Mean annual land erodibility predictions from AUSLEM for the period 1980-1990. Whiteareas are not erodible due to tree and stone cover being above the model thresholds.5.5.3 Results - Station ComparisonsAnnual dust-event frequencies and DSI values for the eight BoM stations are listed in Table5.1. The spatial distribution of stations allows for analysis of model performance in each ofthe four study area bioregions (Figure 5.1).145
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Modelling Land Susceptibility toWin
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AUSLEM was developed as a Geographi
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who joined me on many trips, shared
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Conference Presentations by the Aut
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2.2.5 Soil Moisture Effects........
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Chapter 6: Assessing Land Susceptib
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List of FiguresChapter 1: Introduct
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Figure 2.11 Conceptual model of lan
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Beadle, N.C.W., 1945. Dust storms.
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Bryan, R.B., Govers, G., Poesen, J.
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Chepil, W.S., 1965. Transport of so
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Fryrear, D.W., Sutherland, P.L., Da
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Gregory, J.M., 1984. Prediction of
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Hugenholtz, C.H., Wolfe, S.A., 2005
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Littleboy, M., McKeon, G.M., 1997.
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Marshall, J.K., 1973. Drought, land
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Assessment Report of the Intergover
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Penner, J.E., et al. , 2001. Climat
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Rickert, K.G., McKeon, G.M., 1982.
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Stokes, C., J., McAllister, R.R.J.,
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Williams, W.J., Eldridge, D.J., Alc
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Wind Erosion in Western Queensland Australia

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