Combining transient micro-reflections and multi-sensor arrays for condition assessment of buried pipes. This project will develop an accurate and reliable approach for assessing the condition of pipelines. This new approach will reduce costs and save considerable amounts of water each year, as it will assist utilities in preventing major failures such as pipe bursts, and performing strategically targeted maintenance, replacement and rehabilitation.
Cost Effective Pipeline Condition Assessment Using Paired Pressure Sensor Arrays. Water distribution networks represent society's most important infrastructure asset. They are buried pipes and are often old and deteriorating. Cost-effective methods to assess their physical condition are urgently needed. This research will develop a novel and advanced approach to determine the interior condition of pipes quickly and effectively using small water hammer pulses or waves. Paired pressure sensor arra ....Cost Effective Pipeline Condition Assessment Using Paired Pressure Sensor Arrays. Water distribution networks represent society's most important infrastructure asset. They are buried pipes and are often old and deteriorating. Cost-effective methods to assess their physical condition are urgently needed. This research will develop a novel and advanced approach to determine the interior condition of pipes quickly and effectively using small water hammer pulses or waves. Paired pressure sensor arrays will be used to measure reflections of the waves in pipes and these methods will enable finer resolution and identification of pipeline faults, such as wall thickness loss and leakage while at the same time allowing operational continuity. The outcome will be powerful tools to more cost effectively manage these crucial assets.Read moreRead less
High-resolution pipeline condition assessment using hydraulic transients. This project aims to develop urgently needed non-invasive methods to assess fine detail of a pipe’s condition and allow ‘just in time’ predictive repair. Water distribution networks are society's most important infrastructure asset. They consist of buried pipes that are often old and deteriorating, and annual maintenance overhead exceeds $1 billion per year in Australia alone. The project will develop cost-effective powerf ....High-resolution pipeline condition assessment using hydraulic transients. This project aims to develop urgently needed non-invasive methods to assess fine detail of a pipe’s condition and allow ‘just in time’ predictive repair. Water distribution networks are society's most important infrastructure asset. They consist of buried pipes that are often old and deteriorating, and annual maintenance overhead exceeds $1 billion per year in Australia alone. The project will develop cost-effective powerful tools to identify faults, such as pipe wall corrosion and blockages, while allowing operational continuity. The expected outcome is high-resolution images of wall condition of pipes using high-frequency pressure transients and sophisticated fibre optic sensor arrays.Read moreRead less
A unified approach for estimating coastal flood risk. The project aims to develop a unified approach to quantifying flood risk. Because flooding is caused by multiple mechanisms such as extreme rainfall, storm surge and astronomical tide, accurately estimating flood levels in the Australian coastal zone is challenging. By quantifying flood risk in terms of these mechanisms, the project is expected to provide reliable flood risk estimates for both historical settings and future climate scenarios. ....A unified approach for estimating coastal flood risk. The project aims to develop a unified approach to quantifying flood risk. Because flooding is caused by multiple mechanisms such as extreme rainfall, storm surge and astronomical tide, accurately estimating flood levels in the Australian coastal zone is challenging. By quantifying flood risk in terms of these mechanisms, the project is expected to provide reliable flood risk estimates for both historical settings and future climate scenarios. The improved estimation should enable Australian water agencies and policy-makers to effectively design defence infrastructure (e.g. drainage systems) and urban planning policies to adapt to future flood risk.Read moreRead less
A spatial extremes framework for predicting subdaily rainfall intensity. Climate change is causing extreme rainfall intensity to increase globally. The greatest increases occur for short-duration storms lasting up to several hours, bringing a heightened risk of flash-floods that are often extremely hazardous due to their rapid onset. The project aims to develop a new spatial extreme value framework to predict extreme rainfall patterns, using insights on future changes to rainfall triggering mech ....A spatial extremes framework for predicting subdaily rainfall intensity. Climate change is causing extreme rainfall intensity to increase globally. The greatest increases occur for short-duration storms lasting up to several hours, bringing a heightened risk of flash-floods that are often extremely hazardous due to their rapid onset. The project aims to develop a new spatial extreme value framework to predict extreme rainfall patterns, using insights on future changes to rainfall triggering mechanisms (e.g. convective, frontal or orographic). The research aims to provide projections in the form of intensity-frequency-duration curves, areal reduction factors and antecedent rainfall depths. Engineers are expected to use this information to design infrastructure and urban planning policies to adapt to future flood risk.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Robust streamflow predictions by improving the identification of hydrological model structure. This project aims to provide Australian environmental agencies, design engineers and policy-makers with robust methods that better utilise observed environmental data and process understanding to produce hydrological models with stronger scientific basis and improved operational predictive ability in gauged and ungauged catchments.
A new strategy for design flood estimation in a nonstationary climate. Evidence suggests that global warming will result in an increase in the frequency and/or magnitude of heavy rainfall, leading to flooding with potentially devastating consequences. This study provides a renewed focus on design flood estimation that takes into account a changing climate where assumptions of stationarity are no longer tenable.