The traditional approach for evaluating capital improvement options within networked hydraulic systems typically considers few alternatives.  These alternatives are often modeled to understand the benefits of each, estimate the planning-level costs for the most promising alternatives, and select the most cost-effective alternative for more detailed design. This approach works well if the assessed area is small or the number of potential alternatives is limited.  However, as the scale of master planning increases to include larger systems, watersheds, and entire towns, the need to evaluate many controls and conveyance systems result in a vast number of alternatives.  Determination of the potential combinations of green and grey infrastructure solutions to meet the growing number of municipal objectives such as water quality, flooding, and other environmental and social benefits while also considering cost-effectiveness is near impossible.  The required resources using more traditional manual methods is very challenging and often results in incomplete, partial, or no comparisons of alternatives, resulting in the selection of less cost-efficient projects. With advances in computing power and optimization algorithms, a more efficient and objective-based approach to assess hundreds of thousands of capital improvement alternatives is possible. 

To demonstrate the power of this approach, a case study using optimization software, costs, hydraulic performance, and considering environmental and social benefits (e.g., triple bottom line assessment) for the Renfrew Neighborhood pilot study within the City of Calgary will be presented to determine the potential least-cost alternatives scenarios that provide the greatest stormwater and conveyance systems benefits. This presentation will share the process for the development of optimized assessment. The presentation assesses infrastructure improvements that reduce localized flooding, eliminate basement back-ups, and improve downstream water quality using combinations of gray and green infrastructure. The project demonstrates how tailored algorithms and localized cost curves were used in conjunction with EPA SWMM and a triple bottom line post-processing step to determine cost-efficient infrastructure improvements to meet City objectives.

Register and learn more here:

https://www.wrc.umn.edu/news-events/mnswseries-4