Wind Erosion in Western Queensland Australia
Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One Modelling Land Susceptibility to Wind Erosion in Western ... - Ninti One
Chapter 3 – Modelling Land Erodibility Reviewwhere I’ is the soil and knoll erodibility; C’ is the local wind erosion climatic factor; K’ is thesoil ridge roughness factor; L’ is the field length; and V is the equivalent quantity ofvegetation cover. Table 3.1 provides a description of each of the WEQ model input factors.Table 3.1 Components of the Wind Erosion Equation (after Woodruff and Siddoway, 1965).ControlDescriptionSoil Erodibility, I The potential soil loss (t/acre/annum) from a wide, unsheltered, isolatedKnoll Erodibility, I s field with a bare, smooth, un-crusted surface. Developed from wind tunneland field measures. I s is used to compute erodibility of windward slopes lessSurface CrustStability F sSoil RidgeRoughness K rVelocity of ErosiveWind vSoil SurfaceMoisture MDistance AcrossField D rSheltered DistanceD bQuantity ofVegetative Cover R’Kind of VegetativeCover SOrientation ofVegetative CoverVariable K othan 500 ft long – varies with slope.Considered insignificant as crust breakdown occurs due to aeolian abrasiononce wind erosion has started. This factor is also transitionary and is onlyconsidered significant where the erodibility of a field is to be computed fora given moment in time. Is is usually disregarded.Measure of soil surface roughness (other than clods or vegetation).Mean annual wind velocity corrected to a standard height (30 ft).Moisture is assumed to be proportional to the Thornthwaite P-E Index(Thornthwaite, 1931).Total distance across a given field measured along the prevailing winddirection.Distance along the prevailing wind erosion direction that is sheltered by abarrier, if any, adjoining the field.Surface residue amounts determined by sampling.Factor denoting the cross-sectional area of the cover.A roughness variable. Values vary to describe prostrate to standing cover.Following publication of WEQ, a number of modifications to the model were made byWoodruff and Armbrust (1968), Skidmore and Woodruff (1968), Skidmore et al., (1970),Bondy et al., (1980), Lyles (1988), and Skidmore and Nelson (1992). Bondy et al. (1980)modified WEQ such that the model could provide estimates of erosion rates for periods lessthan one year. While the foundation of WEQ is its soil erodibility factor, defined from fieldmeasured conditions, application of the model outside North America has been limited by itsdependence on the availability of field-measured input conditions, which are expensive toacquire, and the coarse (annual) temporal resolution of its output. The model was designedfor operation in cultivated lands and does not predict short-term or seasonal variations inwind erosion. This means that it does not accurately simulate wind erosion in rangelands, soits application in countries like Australia is further restricted.72
Chapter 3 – Modelling Land Erodibility Review3.2.2 Revised Wind Erosion Equation (RWEQ)The Revised Wind Erosion Equation (RWEQ) was designed to predict soil loss due to winderosion at sub-annual time scales. RWEQ combines empirical and process-based modelcomponents that became available following the development of WEQ. While WEQ providesestimates of annual soil loss, RWEQ can be applied to calculate the sediment transport massat specific field lengths, as well as average and maximum soil loss within a field. A majordevelopment in RWEQ was the incorporation of management factors to describe soil surfaceconditions, vegetation state, and soil moisture changes due to irrigation (Fryrear et al., 1998;Fryrear et al., 2000).The general input structure of RWEQ is similar to WEQ; however, the integration of modelcomponents reflects developments in field and wind tunnel studies that allowed for inputconditions to be modelled (Fryrear et al., 1998). The inclusion of a scheme to compute soilsurface conditions reflects these developments. Input variables of RWEQ include ER, the soilerodible fraction computed from soil properties; SCF, a soil crust factor computed from soilclay and organic matter content; WF, a weather factor; field size; COG, the crop type andorientation; and Hills, a factor used to modify wind speeds depending on field slope andheight. The model computes soil loss by the expression:( WF.EF.SCF.K COG)Qmax p= 109.8'.(3.2)where Q maxp is the maximum amount of soil that can be transported downwind in an event.While RWEQ can be run at variable temporal resolutions, the model computes soil loss on anevent basis. The input variables are computed by empirical relationships derived from fieldstudies on agricultural soils, but also still rely on the measurement of field conditions prior tomodel application. The model requires inputs of soil conditions, as well as land type and landuse, tillage/crop information, crop type, type of tillage tool, and amount and date of irrigation(Fryrear et al., 2001). The soil erodibile fraction EF (%DA
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Chapter 3 – Modell<strong>in</strong>g Land Erodibility Review3.2.2 Revised <strong>W<strong>in</strong>d</strong> <strong>Erosion</strong> Equation (RWEQ)The Revised <strong>W<strong>in</strong>d</strong> <strong>Erosion</strong> Equation (RWEQ) was designed to predict soil loss due to w<strong>in</strong>derosion at sub-annual time scales. RWEQ comb<strong>in</strong>es empirical and process-based modelcomponents that became available follow<strong>in</strong>g the development of WEQ. While WEQ providesestimates of annual soil loss, RWEQ can be applied to calculate the sediment transport massat specific field lengths, as well as average and maximum soil loss with<strong>in</strong> a field. A majordevelopment <strong>in</strong> RWEQ was the <strong>in</strong>corporation of management factors to describe soil surfaceconditions, vegetation state, and soil moisture changes due to irrigation (Fryrear et al., 1998;Fryrear et al., 2000).The general <strong>in</strong>put structure of RWEQ is similar to WEQ; however, the <strong>in</strong>tegration of modelcomponents reflects developments <strong>in</strong> field and w<strong>in</strong>d tunnel studies that allowed for <strong>in</strong>putconditions to be modelled (Fryrear et al., 1998). The <strong>in</strong>clusion of a scheme to compute soilsurface conditions reflects these developments. Input variables of RWEQ <strong>in</strong>clude ER, the soilerodible fraction computed from soil properties; SCF, a soil crust factor computed from soilclay and organic matter content; WF, a weather factor; field size; COG, the crop type andorientation; and Hills, a factor used to modify w<strong>in</strong>d speeds depend<strong>in</strong>g on field slope andheight. The model computes soil loss by the expression:( WF.EF.SCF.K COG)Qmax p= 109.8'.(3.2)where Q maxp is the maximum amount of soil that can be transported downw<strong>in</strong>d <strong>in</strong> an event.While RWEQ can be run at variable temporal resolutions, the model computes soil loss on anevent basis. The <strong>in</strong>put variables are computed by empirical relationships derived from fieldstudies on agricultural soils, but also still rely on the measurement of field conditions prior tomodel application. The model requires <strong>in</strong>puts of soil conditions, as well as land type and landuse, tillage/crop <strong>in</strong>formation, crop type, type of tillage tool, and amount and date of irrigation(Fryrear et al., 2001). The soil erodibile fraction EF (%DA