Digital twins in water: Turning infrastructure data into better decisions

Digital twin technologies are already delivering measurable benefits in water systems around the world.  One of the advantages of working globally is the ability to apply lessons learned in one region to challenges in another. By coordinating expertise across North America, Asia, Australia, and beyond, WSP can bring well-established approaches, tested methodologies, and best practices to each new project rather than starting from scratch. This allows utilities and municipalities to implement digital solutions more quickly, reduce risk, and benefit from innovations that have already been validated elsewhere.

One example comes from the City of Toronto and York Region water supply system in Canada, which delivers treated water from Lake Ontario through a network of major transmission pipelines and pumping stations serving approximately four million residents across 2,400 square kilometres. With aging infrastructure and increasing demand, both utilities recognized the need to better understand hydraulic transients—the rapid pressure fluctuations often referred to as “water hammer”—which can contribute to pipe breaks, leaks, and long-term deterioration of pipelines.

To better manage these risks, WSP worked with Toronto Water and York Region to update and enhance their hydraulic models using detailed operational data. Existing SCADA sensors were combined with high-frequency transient pressure sensors capable of recording pressure changes at hundredth-of-a-second intervals. These sensors captured real-world system responses during events such as pump shutdowns or power failures, allowing engineers to calibrate the models to reflect actual network behaviour.

Using these enhanced models, around 300 transient scenarios were simulated to analyze how pressure waves propagate through tens of thousands of pipes during events such as pump failures, valve operations, or hydrant use during firefighting. The resulting pressure patterns were correlated with historical pipe-break data to identify areas of elevated infrastructure risk. Today, these models serve as long-term digital assets used by Toronto Water and York Region engineers to guide preventative maintenance strategies, support operational decisions, and plan the continued growth of the regional water system.

Across the Pacific, WSP is applying similar digital approaches in Australia, where water utilities are investing in digital twins to improve infrastructure planning and operational efficiency. Working with Digital Twin Victoria, WSP is helping integrate water, wastewater, and broader infrastructure datasets into a unified digital platform that supports regional infrastructure planning and asset management. By connecting SCADA data, operational information, and engineering models, utilities can simulate system performance, evaluate operational scenarios, and identify potential issues before they escalate into major service disruptions. This also helps the teams better consider trade-offs between operational maintenance costs and capital investment when it comes to near-and longer-term planning needs across strategic renewal programs. 

Additionally, the platform is used to analyze flood impacts on critical infrastructure and support groundwater management decisions, helping utilities strengthen resilience while improving long-term sustainability. Early trials have indicated both water savings and operational cost reductions, highlighting the potential for digital twin technologies to deliver measurable benefits at system scale.

WSP is also advancing digital water management in Hong Kong, where digital twin technologies are being used to support the operation of complex urban water systems. By integrating real-time data streams—including water levels, pressures, and pipeline capacities—into a unified digital model, utilities can monitor infrastructure performance and simulate operational scenarios before implementing changes. These models allow operators to test strategies such as reservoir cycling or pump scheduling to reduce energy consumption while maintaining reliable supply. Digital twin tools also support “what-if” analysis, allowing engineers to evaluate system responses to events such as pipe breaks or demand fluctuations. Working alongside local initiatives led by Hong Kong’s Water Supplies Department, WSP is helping develop cloud-based monitoring systems that improve asset health tracking, leak detection, and long-term infrastructure planning. These capabilities can help utilities reduce water loss, improve operational efficiency, and lower the carbon footprint of water supply operations.

Taken together, these projects show how global coordination strengthens the delivery of digital water solutions. Experience gained managing hydraulic risks in Toronto can inform infrastructure planning in Australia, while lessons from Hong Kong’s real-time operational systems can help improve network monitoring elsewhere. By connecting expertise across regions, WSP can bring the right specialists, technologies, and best practices to each client more efficiently, accelerating implementation and helping utilities achieve better outcomes with less risk.

Digital twin implementation requires more than simply installing new software platforms. Successful digital water programs combine engineering expertise, operational knowledge, and high-quality data. Turning raw system data into meaningful intelligence requires specialists who understand both the digital tools and the complex infrastructure they represent.

Utilities often collect large volumes of operational information, but that data must be structured, validated, and interpreted before it can support predictive modelling.

Strategic sensor placement is also critical. Monitoring points must be located where they provide meaningful insight into system behaviour without requiring sensors throughout the entire network.

Visualization tools then translate this information into operational dashboards that allow operators to quickly understand system conditions and respond effectively. The goal is not simply to collect more data, but to convert data into actionable insight that improves decision-making.