The City of Vancouver retained GHD to advance watershed planning for the Hastings Sunrise sewershed, an urban area facing rapid growth, legacy combined and separated sewer infrastructure, and increasing rainfall intensity due to climate change. Traditional modelling approaches were no longer sufficient to fully understand how surface runoff interacts with the sewer system, where flooding originates, and how future servicing investments should be prioritized.

To address these challenges, GHD developed an integrated 1D–2D “One Model” that links surface runoff (rain on grid) with storm, sanitary, and combined sewer hydraulics. By explicitly representing how rainfall moves across streets and parcels before entering the sewer system, the model provides a more realistic depiction of overland flooding, inlet performance, and system capacity limitations. This approach enabled the City to move beyond isolated pipe analysis toward a watershed-scale understanding of flood hazards and combined sewer overflow (CSO).

The project established a robust technical foundation to support a long-term servicing strategy for Hastings Sunrise. Model results were used to identify flood-prone areas, distinguish surface drainage issues from pipe capacity constraints, and evaluate servicing options within a transparent and defensible framework. The work also supports coordination with stakeholders around key corridors, parks, and transportation infrastructure, ensuring that future investments are aligned with broader City objectives for resilience, livability, and climate adaptation.

The project began with the compilation and quality review of City of Vancouver’s GIS and monitoring datasets. GHD then developed an integrated InfoWorks ICM model that couples 1D storm, sanitary, and combined sewer networks with 2D surface runoff using a rain on grid approach. This integration significantly improves model calibration and confidence by capturing how runoff actually reaches catch basins, interacts with surface topography, and enters the sewer system under both frequent and extreme storm events.

Advances in automation, including coding and machine learning enabled workflows, were leveraged to efficiently process large spatial datasets and manage complex scenario modelling that would previously have been cost-prohibitive. The model was applied to historical events and design storms to assess existing system performance, identify areas susceptible to surface flooding, and diagnose whether observed flooding was driven by inlet limitations, surface flow paths, or downstream sewer capacity constraints.

Model outputs were translated into a phased servicing strategy through close collaboration with City staff. Technical workshops and iterative reviews were used to test servicing options, and align findings with broader City initiatives, including Green Rainwater Infrastructure (GRI) and Healthy Waters Plan. This collaborative process allows for effective decision-making and long term capital planning.

The project delivered an integrated 1D–2D watershed model and servicing strategy that improves understanding of flood risk and CSO drivers in Hastings Sunrise watershed. The work provides a defensible basis for identifying priority flood-prone areas, distinguishing surface drainage issues from sewer capacity constraints, and informing targeted, climate-resilient infrastructure upgrades and sequencing.