WCW26

Whitehorse’s stormwater system operates under a challenging mix of steep terrain, cold-climate hydrology, and limited monitoring data; conditions that demand a modelling approach beyond typical urban drainage assumptions. This work developed a city-wide stormwater modelling framework for the City of Whitehorse, including catchment delineation, construction of an integrated PCSWMM model, and advanced GIS workflows to evaluate drainage performance under historical conditions, climate change, and rain-on-snow scenarios. More than 850 catchments and 150 drainage networks were generated using high-resolution elevation and infrastructure datasets, revealing technical challenges related to snowmelt representation, parameter selection, connectivity assumptions, and large dataset management. Results identified capacity constraints, localized flooding mechanisms, culvert bottlenecks, and sediment-sensitive conveyance issues. Recommendations focus on improving GIS-based asset inventories, expanding long-term monitoring to support calibration, refining modelling methods for northern conditions, and strengthening defensible stormwater planning for cold-climate municipalities.

Each wastewater treatment facility faces unique influent characteristics, making site-specific screening evaluations critical for optimizing headworks performance. At Alexandria Renew Enterprises (AlexRenew), field testing was performed to assess existing coarse and fine mechanical screens and evaluate alternative configurations.
Using on-site screening capture testing, various combinations of coarse and fine sieve openings and geometries were tested under average dry-weather conditions. Results showed the existing coarse screens removed an average of 0.7 cubic feet of solids per million gallons (CF/MG). In contrast, a configuration of a 19 mm slotted coarse screen followed by a 6 mm perforated plate fine screen achieved an average Screen Capture Ratio of 52%—a projected threefold increase in solids removal.
Beyond capture efficiency, testing provided valuable insight into screen hydraulics, blinding tendencies, and compatibility with existing infrastructure. This approach demonstrates how field data can guide screen selection, improve debris removal, reduce downstream maintenance, and extend equipment service life.
The case underscores the value of empirical testing in headworks design. By quantifying capture rates, headloss behavior, and solids characteristics, utilities can make more informed upgrade decisions tailored to their specific flow conditions and operational priorities.

In several Saskatoon neighbourhoods built after 2004, homeowners have raised concerns with the perpetual operation of foundation drainage sump pumps. Continuous pumping to the surface has created year-round issues such as algae growth, ice buildup and drainage onto driveways, sidewalks, lanes and adjacent parks.
The current workaround permits discharge of sump pump effluent into the sanitary sewer system during the winter months, resulting in reduction of sanitary sewer capacity and water being unnecessarily treated by the WWTP at additional cost. This does not address the summer discharge concerns and enforcement is lacking for switching back to surface discharge in the summer.


This has been an issue in Saskatoon for many years with previous mitigation strategies producing limited or short-term success. To address this, the City of Saskatoon launched a comprehensive review project in 2025. The project has completed a review of how other municipalities manage the issue, conducted a residential survey and completed an internal multi-departmental workshop to brainstorm solutions. 
Ongoing work includes feasibility assessments for the preferred options and once completed, engagement with the land development and home building industry will occur to understand the impacts of the preferred options. 


The presentation will provide a history of how this multi-decade issue was created, the results from the municipal scan and the residential survey. The preferred options will be presented and their positives and negatives discussed. If industry engagement is completed before the conference, these results will also be shared along with the project’s next steps towards a long-term resolution.

Advanced Metering Infrastructure (AMI) is rapidly evolving from a billing-focused technology into a foundational data source for utility-wide operational intelligence. As utilities expand metering programs and pursue digital transformation initiatives, the next generation of AMI—AMI 2.0—enables organizations to leverage high-resolution consumption data to address persistent challenges such as non-revenue water, leak detection, and system inflow and infiltration (I&I) awareness.


By integrating AMI data with operational, hydraulic, and environmental datasets, Utilities can generate actionable insights across both customer and system levels. By integrating AMI data with operational, hydraulic, and environmental datasets, Utilities can generate actionable insights across both customer and system levels. Influenced by implementation work with the City of Immokalee, Florida, this approach demonstrates how continuous meter analytics can identify abnormal flow patterns, persistent consumption, and nighttime flow conditions that indicate leaks or operational inefficiencies.  When aggregated and contextualized, meter data also provides valuable system-level indicators that help utilities better understand flow anomalies and potential I&I impacts, enabling more targeted investigation and response.


AMI 2.0 shifts the role of smart meters from passive measurement devices ('cash registers') to active components of a utility’s digital ecosystem. By combining advanced analytics, data integration, and scalable enterprise architecture, utilities can move beyond reactive workflows toward proactive operations that improve water accountability, optimize field resources, and strengthen infrastructure planning.


As water metering adoption accelerates across regions such as Western Canada, utilities have an opportunity to design programs that maximize long-term value from the outset. Leveraging AMI data for both leak detection and broader system intelligence supports improved resiliency, operational efficiency, and measurable return on investment while establishing a scalable foundation for future analytics and AI-driven applications.

We are inundated with information in all ways, shapes, and forms; from our cell phones, televisions, and computers, isolating information and presenting what information requires action has become essential. Standardized SCADA alarm systems are powerful tools that can be utilized in this process. It is imperative to provide warnings about developing situations so Operators can take timely corrective action. Alarms can be interruptive by nature and must be carefully managed to minimize the number of nuisance alarm activations. Unnecessary alarm activations can significantly drain operational staff resources in terms of staff time, after-hours call-outs, and workload in each plant's control room.
The International Society of Automation 18.2 describes systematically reviewing and documenting alarms to help diagnose and respond to abnormal situations. The standard outlines mandatory and recommended practices for a lifecycle approach to alarm management. Standardized work processes are used to design, implement, maintain, and monitor the alarm system.