4.7 Article

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

Journal

ENVIRONMENTAL MODELLING & SOFTWARE
Volume 22, Issue 8, Pages 1129-1139

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2006.03.003

Keywords

Bayesian network; sustainability; integrated assessment; coastal lakes; environmental management; pathogens; decision support

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Coastal takes 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 Bus 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. (c) 2006 Elsevier Ltd. All rights reserved.

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