A Bayesian decision network approach for assessing the ecological impacts of salinity management

  • Authors:

  • A. Sadoddin;R. A. Letcher;A. J. Jakeman;L. T. H. Newham

  • Affiliations:

  • Centre for Resource and Environmental Studies, The Australian National University, Building 48A, Linnaeus Way, Canberra, ACT 0200, Australia and Gorgan University of Agricultural Sciences and Natu ...;Integrated Catchment Assessment and Management Centre, The Australian National University, Canberra, ACT 0200, Australia;Centre for Resource and Environmental Studies, The Australian National University, Building 48A, Linnaeus Way, Canberra, ACT 0200, Australia and Integrated Catchment Assessment and Management Cent ...;Integrated Catchment Assessment and Management Centre, The Australian National University, Canberra, ACT 0200, Australia

  • Venue:
  • Mathematics and Computers in Simulation - Special issue: Second special issue: Selected papers of the MSSANZ/IMACS 15th biennial conference on modelling and simulation
  • Year:
  • 2005

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Abstract

This paper outlines one component of a study being undertaken to provide a new tool for integrated management of dryland salinity, a major environmental problem in Australia. The Little River Catchment in the upper Macquarie River basin of New South Wales (NSW) is used as a case study. A Bayesian decision network (BDN) approach integrates the various system components - biophysical, social, ecological, and economic. The method of integration of the system components is demonstrated through an example application showing the impacts of various management scenarios on terrestrial and riparian ecology. The ecological impacts of management scenarios are assessed using a probabilistic approach to evaluate ecological criteria which are compared with those for the present situation. In considering different ecological indices, the direction and magnitude of change under different management scenarios varies because of the diverse influence of habitat fragmentation.