Asset management plays a significant role in modern industries, particularly in water utilities, in providing available and reliable service at an optimised asset Life Cycle Cost (LCC). Asset owners require an optimal life cycle decision support model for the longer-term asset strategy, planning and budgeting. There are numerous asset life models to predict physical, economic, and technological aspect of asset life, individually; however, there is currently no such model that combines all aspects. The aim of this project is to develop asset life cycle decision support model explicitly joint three aspects of asset lives and their determinants (i.e. physical age and degradation, operating, maintenance costs and technology changes). To this purpose, multi-objective optimisation method and stochastic dynamic programming would be applied to model an optimised asset renewal decision support. This model is expected to determine an optimal asset renewal and replacement decision support model at the lowest LCC in water industry, providing a stable and reliable service and having an optimised investment plan.

Thesis underway.

Water Footprinting provides a different approach to understanding the role of water than traditional water resources planning and management. Water Footprinting tools can be applied in the Urban Water Sector to investigate:

• The amount of fresh water that must be withdrawn from the environment to deliver a specified volume of water to a customer;
• The amount of fresh water consumed (i.e. no longer available for other purposes) when delivering urban water services; or
• The impact (from a water resource perspective) that the delivery of urban water services has on the environment.

The approaches consider both Direct and Indirect Fresh Water Flows.

This project developed an understanding of the Water Footprinting concept; investigated the applicability of Water Footprinting tools to the Urban Water Sector and how they combine with or complement other sustainability related tools, and determined further development and application of the tools.

The ADWG explains policies but does not provide the specific steps and actions needed to apply risk management principles within a water treatment plant (WTP). The original ‘Guide to Drinking Water Supply Systems for the Management of Microbial Risk’ (WaterRA Project 1074) filled this gap by providing Australian-specific advice about managing and optimising common water treatment processes to achieve microbial health-based targets. Since its publication in 2015 it has become a popular reference document, and its widespread acceptance and use has prompted the production of this second edition. Included are updated technologies and regulations, and a series of auditing tools and templates for application in a variety of situations, including the identification and quantification of risk.

Click here to download the Good Practice Guide.

A survey of water utilities identified the top five challenges faced in daily operations, and technical, economic and literature reviews identified remote sensing strategies and technologies to address these five operational issues. The need for, and benefits of real-time monitoring which facilitates cost-effective and efficient responses to rapidly changing conditions, were common to all five challenges, which were: monitoring cyanobacteria and their metabolites, the effects of contamination and extreme climate-change driven events on water quality, the variation in climatological data over relatively small distances (need to increase focus, precision and produce ‘finer’ datasets for reservoir management), asset inspection and management and monitoring catchments for a variety of factors. This research evaluated and explained the solutions, strengths, weaknesses, and costs of products best suited for addressing each challenge.

Water utilities lack the information they need to implement risk-based adaptation and planning strategies that incorporate climate change. This research addresses this problem by modelling the effects of climate change on reservoirs in three climate zones: temperate, humid tropical and Mediterranean. By integrating different modelling approaches it was concluded that increased temperatures will increase water stratification; the differences in water temperature that occur with depth. This is important because the duration and type of stratification affects the storage and release of substances from reservoir floors and this in turn affects blue-green algal blooms and water quality. The integrated modelling approach developed in this project can be applied to the management of contaminants running off the catchments and for future risk assessment. This information will also support the development of business cases for targeted catchment interventions.