Fast Digital Twin of Water Systems for City of Toronto and York Region

Much of the water infrastructure in our urban environments is aging rapidly, and water systems require proactive management, preventative maintenance and a future-ready mitigation approach. Understanding that ageing infrastructure is prone to a higher frequency of leaks and breaks, the City of Toronto and the York Region recognized the need to heed close attention to hydraulic transients. At scale, a type of hydraulic shock called “water hammer” causes either catastrophic failures or continuous and significant deterioration of infrastructure, reducing its life expectancy and driving up staff and repair costs.

Retained as the Lead Consultant by the Toronto Water with HydraTek as sub-consultant, WSP predicted long-term, cumulative wear-and-tear using digital twin systems to monitor day-to-day operations and emergency water management. Toronto Water is a division of the City of Toronto that operates a water supply system from Lake Ontario northward to supply the York Region. The system includes numerous pump stations and large transmission networks that serve 7.3 million residents. WSP studied systems that serve about 4 million residents across 2,400 km².

1  WSP was the lead consultant, with HydraTek as sub-consultant.

It costs less to be proactive with managing infrastructure degradation than reacting to an event after it occurs, such a pipe break. Digital twins support better decision-making and allocation of scarce public resources to deliver water more reliably and improve systems over the years by making them Future Ready® in terms of resiliency and ability to support change and population redistribution and growth.

To enable effective risk management across Toronto Water’s systems, WSP deployed “faster” digital twin (transient) models and 128Hz pressure sensors, as interactions caused by pressure waves travelling at the speed of sound can be accurately measured, simulated and therefore controlled. Over 300 transient scenarios were simulated to quantify and reduce risks arising from emergency conditions, such as power failures, control valve mishaps, or hydrant flow starts/stops during fires. Subsequently, the resulting extremely high and low transient pressures simulated across the system were correlated to pipe-break data and mapped to highlight areas with the highest risk. 

WSP also updated the water systems’ hydraulic models and related pressure measurements to match 24/7 performance. The tests used existing SCADA (Supervisory Control and Data Acquisition) system sensors supplemented with transient pressure sensors that recorded data at 1/100s intervals to collect real-world dynamic responses to power failures. These IoT (Internet of Things) and web interfaces help calibrate the models operationally, to support preventative maintenance and reduce the frequency of pipe breaks and the extent of emergency road closures for repairs.

Using digital twins enables operators to look beyond asset snapshots frozen in time and receive timely data that communicates real-time updates. Having immediate access to this data helps operators and engineers make more timely and better-informed decisions when it comes to maintenance, optimizing operations, conducting repairs and responding to issues. It also allows experts to consider the entire water supply system when planning upgrades, assessing the best way to repair or improve the system and responding to unusual situations. Without such tools, simpler and conservative predictions drive up capital and operating costs as they limit engineers from quantifying the extent to which the network is its own protection, as loops can split and dissipate transient energy.

To develop such a model, it is essential to have the right platform and solver capable of carrying out millions of calculations in a matter of seconds accurately. Bentley HAMMER, developed by EHG (now WSP-Hydraulics), used a Method of Characteristic (MOC) solver that calculated the transient pressure/HGL at the nodes and along with the intermediate points.

The enhanced models are now information assets that the in-house hydraulic engineers will maintain at Toronto Water and York Region and used to answer operational questions such as how to grow the system. Over the next few years, the models will also ‘grow’ and connect, forming a single model representing the large-scale system at the highest accuracy to pinpoint problem areas.

A digital twin is a virtual replica of an asset that includes real-time operational data of an asset. It provides an immersive and integrate visualization of previously siloed information and enables the use of modern digital analysis techniques, such as condition-based monitoring and predictive analysis, to plan for the continued functioning of the infrastructure.

The technology used in digital twins is advancing rapidly; newer ones can provide even faster data than we’ve relied on before. Some digital twins are designed to predict changes gradually over time—monthly or yearly. Whereas faster digital twins can predict changes in the network almost instantaneously, allowing prompt responses to time-sensitive or emergency issues.