Wind Erosion in Western Queensland Australia

Chapter 6 – Field Assessments and Model Validation6.3 Field Data and Model Simulations6.3.1 Field Data CollectionThree trips were conducted to collect land erodibility assessments across the westernQueensland study area: September 2006 (1171 observations); November 2006 (962observations); May 2007 (1521 observations). Routes were surveyed based on therequirement to assess the condition of all of the major land types within the study area oneach trip. This included surveying country in the Mulga Lands, Channel Country, MitchellGrass Downs, and along the eastern margins of the Simpson Desert (described in Chapter 1,Section 1.6). The routes were also selected so that a range of land types within the bioregionswere surveyed. This meant that the transects traversed river channel systems, floodplains,gibber plains, dunefields, open downs, woodlands and escarpments. Routes were revisited toprovide multi-date samples of the same areas to build a database of spatial and temporalchange in the erodibility of the landscape.6.3.2 Model SimulationsThe Australian Land Erodibility Model (AUSLEM) was used to simulate land erodibilityacross the study area of western Queensland. The model operates at a 5 x 5 km spatialresolution on a daily time step with inputs of grass and tree cover, soil moisture, soil textureand surficial stone cover (Webb et al., 2009). Previous validation of the model (in Chapter 5)was conducted by comparison of time-series predictions with point observational records ofwind erosion activity (Webb et al., 2009). Attempts to validate the model at the 5 x 5 kmresolution using visual assessments of land erodibility were restricted by vegetationheterogeneity in the study area which compounded scale differences between the validationdata (~100 x 100 m) and model output (5 x 5 km). There is therefore a requirement to test themodel performance using higher spatial resolution inputs.In the current study AUSLEM was run at a 200 x 200 m resolution. Landsat ETM+ derivedbare ground (%) and foliage projective cover (%) data were used for the grass (inverse ofbare ground) and tree cover model inputs (after Danaher et al., 2004; Scarth et al., 2006). Thedata were rescaled from 30 x 30 m to the 200 x 200 m spatial resolution to minimise datascale differences and ensure that the validation data points would correspond to individual162