5 minute read
Sensing the future of data technology in water networks
By Stephanie Nestor, Journalist, Utility Magazine
A new report suggests that setting up and monitoring future water assets will require a clearer understanding of the complexities of natural water systems, which can only be achieved with advanced sensors.
With many water assets located in remote areas, and unprecedented rainfall and floods compromising natural water processes, it is difficult to understand the full extent of Australia’s hydrology.
In an effort to fill knowledge gaps, the New South Wales Smart Sensing Network (NSSN) has published a report to investigate the potential of adopting both physical and remote sensors alongside probabilistic modelling for monitoring water resources.
For New South Wales in particular, NSSN’s report endeavoured to reduce unaccounted for differences in knowledge, by employing various methods to measure and model natural water processes, as well as bring together organisations and researchers.
According to the report, collecting data from multiple types of sensors as well as predictive modelling can reduce uncertainty and inform decision-making. The future of data technology in water utilities will combine various sensors and modelling to understand what is really happening to water in New South Wales.
COLLABORATION TO FILL IN THE GAPS
This report is the culmination of NSSN’s “Where is All the Water?” Project, which aimed to help New South Wales Government agencies and organisations monitor water assets. The project intended to create a technological framework for managing water resources in New South Wales.
NSSN turned to a number of academic and scientific partners to conduct research and tests, showcasing the possibilities that come with collaboration between agencies and universities.
Partners included: • The Australian National University (ANU), which led two sub-projects – a local gravity sensing trial and an investigation into satellite gravity measurements for water • Macquarie University, which offered expertise in low-cost monitoring • The University of Sydney, which provided probabilistic modelling with its ARC Training Centre in Data Analytics for Resources and Environments (DARE) • The University of New South Wales (UNSW), which offered background knowledge regarding hydrology and led an investigation into aquifer recharge mechanisms
NSSN Industrial Futures Theme Leader, Dr Don McCallum, said the project aimed to overcome the imbalances in data across New South Wales through collaboration.
“Given Australia’s immense size and the remoteness of many of our rural areas, there are often gaps in water data, often with government reports simply stating imbalances in the water equation as ‘unaccounted for differences’,” Dr McCallum said.
“The NSSN is an expert in multiparty projects, collaboration and stakeholder engagement. The NSSN works with clients,
to help nurture, simplify and guide complex projects to make them crisp and straightforward, yet with often advanced and complex underlying science and engineering.”
NEW METHODS OFFERING NEW INSIGHTS
The project combined existing data with innovative lowcost sensing technology and analytical modelling, bringing together different methods that could provide a clearer picture of New South Wales’ water.
Despite using complicated science, the report was created to be understood and applied by network operators, agencies, and other organisations.
“The report contained some very complex science: quantum physics, satellite gravitational measurements and Bayesian probabilistic modelling,” Dr McCallum said.
“The report worked hard to make this work accessible to the broadest readership, without ‘dumbing it down’.”
Following these research projects, the report outlines five new ways for network operators and agencies to understand water in catchments: 1. Bayesian modelling 2. Low-cost telemetry sensors 3. Quantum sensors 4. Satellites 5. Groundwater recharge
Bayesian modelling uses probability to represent all uncertainty within the model, including any uncertainty regarding both the output and input data. This type of modelling is ideal when data is limited.
As part of the project, the University of Sydney's DARE Centre formulated a prototype framework using Bayesian modelling to quantify losses and uncertainties in New South Wales river systems. This framework could offer organisations a tool to explain unaccounted for differences.
Additionally, UNSW conducted an investigation into aquifer recharge mechanisms and determined that direct rainfall on fields may not be a considerable factor for groundwater recharge. Instead, focussed recharge, from sources such as inflows from surface water, is the predominant recharge mechanism in areas near intermittent streams.
This offers a mechanism to explain surface water transmission losses in dry streams since UNSW identified that flow is mostly generated by rainfall further upstream for New South Wales water catchments.
COMBINING PHYSICAL AND REMOTE SENSORS
The report recommended that in order to better understand water resources in New South Wales, organisations should use a combination of low-cost physical sensors and remote sensors.
Macquarie University tested telemetry sensors in the Namoi catchment. This trial proved that these sensors are able to gather data at a lower cost and are easy to install. Paired with remote sensors, strategically placed telemetry sensors across the state could provide better insight into state water catchments and supplies.
In another part of the project, ANU investigated how using quantum sensors can accurately measure gravitational signals from near surface groundwater. This method avoids digging, tunnelling, boreholes or any other contact. Not to mention, a gravity signal cannot be shielded or blocked by anything.
Using these sensors, ANU could detect a leaking pipe underground in an urban environment and measure total water mass changes in a catchment.
The project also tested how satellites can be used to show the movement of groundwater, surface water and soil moisture by measuring changes in the gravitational pull of water. This could provide global communities with early warnings of floods or detect water deposits.
WHAT THIS MEANS FOR UTILITIES
Following the report, the NSSN recommends continuing collaboration between agencies and researchers to switch efforts from a researcher-push to industry-pull when it comes to understanding water. Utilising the report’s five innovative sensing and modelling methods will offer the right tools to tackle future problems.
Dr McCallum said that data will be key to monitoring networks, as better analytics can help to predict and prevent the problems that come with floods, droughts and unprecedented rainfall.
“To help improve monitoring networks, the adoption of low-cost sensing, use of quantum sensors, satellite gravity measurements, better knowledge of groundwater-surface water interactions, and use of advanced data analytics techniques can all be used,” Dr McCallum said.
Particularly for New South Wales utilities, embracing low-cost sensing can help with all forms of monitoring water networks, including asset management, quality control, and safety.
“Australian utilities are welcome to work with the findings as they see fit. In many cases, further implementation work is required. Utilities wanting to adopt the work should contact the NSSN to see how this work can be applied to their particular situation,” Dr McCallum said.
By collaborating with researchers and deploying sensors, water utilities will be able to reduce uncertainty and gain a greater understanding of New South Wales’ hydrology to better prepare for what the future has in store.
