Our Digital, Data and Sensors webinar series is designed to take delegates on a journey of discovery into new and emerging technologies and how they can be applied to the water sector.
On Tuesday 29th September, join us to learn more about Data Management.
The Australian water sector is looking to data management to deal with challenges such as ageing infrastructure, asset maintenance and investment, climate change, water storage, and water supply.
In the face of these many challenges, water utilities also are expected to fulfil report requirements, which is increasingly demanding.
Data management and digital technologies are enabling utilities to obtain efficiencies from legacy infrastructure and assets, improving decision making and lifecycle management. This also provides utilities with a better understanding of their operations.
In the last of our webinar series, learn more about the benefits of data management and how big data is being used in the water sector to create valuable information about numerous parts of a business, allowing for more reliable assets and better customer relationships.
||Tuesday, 29 September 2020
||10:30am - 12:30pm (Sydney time - AEST)
||Online via Zoom
||Free for members, $30 for non-members
Full details including links to the webinar platform will be sent to registered attendees.
The webinar will be recorded and the recording will be provided to registered attendees within 7 business days after the event.
Our member rate is for WaterRA members only. Not sure if you're a member? Check our member listing here
MEET OUR PRESENTERS
Dr Lisa Blinco, Water Systems Optimisation Engineer, SA Water | Using real-time data
dashboards and machine learning forecasts to inform operational decisions
Operating major water systems while participating directly in the National Electricity Market requires
access to real-time information about the current and forecast state of water and energy systems.
SA Water uses several decision support tools and real-time information dashboards to assist the
operators in the 24/7 Operations Control Centre to run their systems efficiently. Lisa will discuss
how real-time data dashboards and machine learning forecasts inform operational decisions and
the future state of automated operations in SA Water.
Dr Lisa Blinco is a Water Systems Optimisation Engineer at SA Water and an Adjunct Lecturer at
the University of Adelaide. She studied Civil and Environmental Engineering at the University of
Adelaide, completing her bachelor’s degree in 2012. In her PhD research, she investigated the
optimisation of water systems operations, focussing on systems that utilised alternative water
sources such as harvested stormwater. In her current role at SA Water, she uses a specially
designed tool to plan the operation of South Australia’s bulk supply network including major pumped
pipelines from the River Murray, reservoirs in the Mt Lofty Ranges, the Adelaide Desalination Plant,
and major water treatment plants for the Adelaide Metropolitan region. Her work has assisted
projects such as dam upgrades for two major Adelaide reservoirs, the use of the Adelaide
Desalination Plant for drought relief in the Murray Darling Basin, and energy consumption budgets.
In her role, she provides support to the 24/7 Operations Control Centre including development and
maintenance of several decision support tools that integrate data and modelling from various sources
and display information for operators to make decisions.
Chris O'Neill, Director, Hydronumerics & Kathy Cinque, Principal Hydrodynamic Modeller,
Melbourne Water | Using water quality dashboards and models for rapid decision support
in receiving waters
Chris is a water resource engineer with over 15 years’ experience in hydrodynamic and water
quality modelling, design and testing of in-situ water quality interventions, and coupled water
quality and economic analysis for drinking and recreation water resources. Chris was the
program leader for the Ayeyarwady River Basin Pollution Assessment Program (Myanmar)
and is a 2016 Peter Cullen Fellow.
Kathy has worked at Melbourne Water for 20-years, initially in the drinking water planning
and research areas and now has an additional focus on receiving water modelling. She
completed her PhD in 2009, which investigated and quantified the effectiveness of buffer
strips for the protection of drinking water quality. This was followed by a secondment to a
modelling consultancy where she evaluated different hydrodynamic water quality receiving
models. Her current role has an emphasis on hydrodynamic, hydrologic and water quality
modelling in various environments including estuaries, bays, catchments and reservoirs.
Glenn Harris, Acting Manager Field Services & Network Operations, Western Water
Waternamics: Real Time Data Integration
Glenn Harris started his career at Western Water in 2009 as a Field Services operator and
then became a Team Leader in 2016 in charge of the Northern Region Maintenance Depot.
In 2017 an opportunity was offered to him to join the Operations Centre as the Team Leader
to deliver the Waternamics project for Field Services. Glenn is now Acting Manager Field
Services & Network Operations and one of his many responsibilities is to lead innovation
at Western Water including the development of Artificial Intelligence models for operations.
Jinhzu Wang, PhD Candidate, Deakin University
Monitoring long time built-up development at a large scale with consistently high accuracy
Jinzhu is a Ph.D. candidate in the Planet-A lab of Deakin Univerisity and working on a project
to track the built-up evolution and evaluate food security. Jinzhu will share his study of
manipulating large remote sensing data to monitor the development of built-up areas. The
built-up area is one of the highest levels of human activities, which directly links population
growth and economic development to food security, water circulation, and various
environmental challenges. Acquiring long time-series and high-accurate built-up data is the
premise to understanding this linkage. Jinzhu will present how to better use the Landsat
archive of the 1990s and achieve a ~95% accuracy in image classification throughout the
1990s~2010s. Jinzhu’s research method of temporal signature extraction could provide
references for water body monitoring; additionally, his built-up datasets could be used as a
reliable source for the research of water resource consumption.