Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A Bayesian decision network approach for assessing the ecological impacts of salinity management
Mathematics and Computers in Simulation - Special issue: Second special issue: Selected papers of the MSSANZ/IMACS 15th biennial conference on modelling and simulation
Bayesian Networks and participatory modelling in water resource management
Environmental Modelling & Software
Bayesian networks in planning a large aquifer in Eastern Mancha, Spain
Environmental Modelling & Software
Coupling real-time control and socio-economic issues in participatory river basin planning
Environmental Modelling & Software
Public participation modelling using Bayesian networks in management of groundwater contamination
Environmental Modelling & Software
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
Editorial: Bayesian networks in water resource modelling and management
Environmental Modelling & Software
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
Mathematics and Computers in Simulation
A framework for linking advanced simulation models with interactive cognitive maps
Environmental Modelling & Software
Environmental Modelling & Software
Analysing complex behaviour of hydrological systems through a system dynamics approach
Environmental Modelling & Software
Modelling sustainable international tourism demand to the Brazilian Amazon
Environmental Modelling & Software
Environmental Modelling & Software
A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Position Paper: Modelling with stakeholders
Environmental Modelling & Software
An integrated approach to linking economic valuation and catchment modelling
Environmental Modelling & Software
Environmental Modelling & Software
A methodology for the design and development of integrated models for policy support
Environmental Modelling & Software
Analysis of facility location model using Bayesian Networks
Expert Systems with Applications: An International Journal
Review: Bayesian networks in environmental modelling
Environmental Modelling & Software
Assessing the likelihood of realizing idealized goals: The case of urban water strategies
Environmental Modelling & Software
Position Paper: The role of expert opinion in environmental modelling
Environmental Modelling & Software
Good practice in Bayesian network modelling
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Hi-index | 0.00 |
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.