Bayesian Network and System Thinking Modelling to Manage Water-Related Health Risks from Extreme Events

Abstract

A combination of Bayesian Network (BN), System Dynamics (SD) and participatory modelling to develop a risk assessment tool for managing water-related health risks associated with extreme events has been developed. The risk assessment tool is applied to the Prospect water filtration plant system, main source of potable water for the Sydney metropolitan region. Conceptual models were developed by the stakeholders around the key indicator parameters of turbidity, water colour and cryptosporidium. These three conceptual models were and used for developing separate BN and SD models. Here we present the development of a BN designed to understand the risk of extreme events on the ability to provide drinking water of a desired quality. The model has undergone development and preliminary parameterization via two participatory workshops. However, its development is an ongoing process with the next stage involving supplementing the `expert opinion' used to parameterize the model so far with `hard' data.