A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia

Jenifer L. Ticehurst, Lachlan T.H. Newham*, David Rissik, Rebecca A. Letcher, Anthony J. Jakeman

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    148 Citations (Scopus)

    Abstract

    Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.

    Original languageEnglish
    Pages (from-to)1129-1139
    Number of pages11
    JournalEnvironmental Modelling and Software
    Volume22
    Issue number8
    DOIs
    Publication statusPublished - Aug 2007

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