• Volume
    2009
  • Year
    2009
  • Page
    214–227
  • Source
    Environmental Modelling & Software
  • Format Published
    PDF
  • Descriptors

    Wind erosion , Land erodibility , Dust , Erosion hazard , Monitoring , Model

  • Abstract
    This paper describes the development and validation of the Australian Land Erodibility Model (AUSLEM), designed to predict land susceptibility to wind erosion in western Queensland, Australia. The model operates at a 5 5 km spatial resolution on a daily time-step with inputs of grass and tree cover, soil moisture, soil texture and surficial stone cover. The system was implemented to predict land erodibility, i.e. susceptibility to wind erosion, for the period 1980–1990. Model performance was evaluated using cross-correlation analyses to compare trajectories of mean annual land erodibility at selected locations with trends in wind speed and observational records of dust events and a Dust Storm Index (DSI). The validation was conducted at four spatial length scales from 25 to 150 km using windows to represent potential dust source areas centered on and positioned around eight meteorological stations within the study area. The predicted land erodibility had strong correlations with dust-event frequencies at half of the stations. Poor correlations at the other stations were linked to the inability of the model to account for temporal changes in soil erodibility, and comparing trends in the land erodibility of regions with dust events whose source areas lie outside the regions of interest. The model agreement with dust-event frequency trends was found to vary across spatial scales and was highly dependent on land type characteristics around the stations and on the types of dust events used for validation.
  • Call. No.
    EA 57
  • IndexDate
    1397/10/17
  • Indexer
    Dashagha
  • Title of Article

    A model to predict land susceptibility to wind erosion in western Queensland, Australia

  • RecordNumber
    58
  • Issue/Number
    24
  • Author/Authors

    Nicholas P. Webb , Hamish A. McGowan , Stuart R. Phinn , John F. Leys , Grant H. McTainsh