Wind Erosion in Western Queensland Australia

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Chapter 3 – Modelling Land Erodibility Reviewwhere SA is the sand content (%), Si is the silt content (%), CL is the clay content (%), OM isthe organic matter content (%), and CaCO 3 is the calcium carbonate content (%). The soilcrust factor (CF) is computed using the equation:CF1= (3.4)1+0.0066( CL) 2 + 0. 021( OM ) 2The model weather factor (WF) combines measures of wind erosivity and a wind erodibilityfactor based on soil water content. The weather data is simulated and draws on an historicalweather database (Fryrear et al., 1998). As for WEQ, the model K’ factor describes the soilridge roughness and COG (Equation 3.2) defines the percentage cover of dead, flat andstanding plant material. Both the K’ and COG factors can be either measured in situ, orderived from a series of empirical relationships (Merrill et al., 1999). Importantly, the factorsin RWEQ reflect current field conditions for particular events, rather than annual averageconditions (as for WEQ).RWEQ can be applied to predict soil loss from multiple individual fields. However, themodel inputs represent single value average conditions for the fields, and so the modelassumes spatial homogeneity in the soil management, surface crusting, and vegetation coverconditions. The implication of this is that the model cannot be applied to accurately simulatesoil loss in rangeland environments where field conditions are highly non-uniform(heterogeneous). The expressions used to compute the soil surface conditions are based onregression equations and data collected on soils in the United States (US). While RWEQ hasbeen applied successfully outside the US (Van Pelt et al., 2004), this application is still relianton experimental data to support model predictions of soil erodibility on soils different tothose in the US (Leys, 1999).3.2.3 Wind Erosion Prediction System (WEPS)The Wind Erosion Prediction System (WEPS) was developed to advance wind erosionprediction through process-based modelling. While WEQ and RWEQ rely on empiricalrelationships and field-measured inputs, WEPS was developed as a process based,continuous, daily time-step wind erosion model that simulates weather, field conditions,74
Chapter 3 – Modelling Land Erodibility Reviewmanagement, and erosion (Hagen, 1991). WEPS can be run to simulate single erosion eventsor soil loss over multiple years.WEPS uses a database of inputs to define land surface characteristics. The inputs areprocessed by sub-models to compute soil and land erodibility components that are used bythe erosion scheme. Inputs include data on climate, soils, management, and crop conditions.Table 3.2 provides a description of the WEPS sub-models.Table 3.2 Definitions of the WEPS sub-models used to simulate soil loss due to wind erosion (afterHagen, 1991).Sub-Model DescriptionWeatherContains programs that simulate wind speeds, air temperature,precipitation, solar radiation and dew point temperature. These are used asinput to the remaining sub-models.HydrologySimulates soil water content in the various layers of the soil profile and atthe soil-atmosphere interface.Management Accounts for soil, surface and biomass manipulations that could affect theerosion process. These include timing and method of cultivation andirrigation.SoilSimulates random and oriented roughness, crust generation, coverfraction, density, stability and thickness, and loose erodible material oncrusted surfaces. These temporal properties are simulated in response toweather processes like wetting/drying, freeze/thaw, precipitation amountand intensity, and time.CropSimulates the amount of live biomass growth on the surface bycalculating daily production of roots, stems and leaves. The growth modelaccounts for variations in biomass cover in response to climate andmanagement decisions.Decomposition Simulates the decrease in crop residue biomass due to microbial activity.The biomass is partitioned into dead standing, surface, buried, and root.May be modified by management conditions.ErosionUses input parameters supplied by the other sub-models that describe thesoil surface, flat biomass cover, standing biomass leaf and stem areas, andweather to calculate threshold friction velocities and particle entrainment.The sub-models operate at different temporal resolutions depending on the availability ofinput data and variability in input conditions. These temporal resolutions range from hourlyto sub-hourly for the hydrology and erosion models, to daily changes in soil surfaceconditions that drive the erosion model (Hagen, 1991). Unlike the majority of wind erosionmodels, WEPS contains schemes to predict spatial and temporal variability in soil erodibility.This is in contrast to earlier models like RWEQ which rely on single value inputs toapproximate soil erodibility within fields.75
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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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hand column) presents trajectories
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Chapter 1 - IntroductionDowns. Wind
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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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Wind Erosion in Western Queensland Australia

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