Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Engineering Science

Program

Civil and Environmental Engineering

Supervisor

Robinson, Clare

Abstract

Non-point source phosphorus (P) loads from urban watersheds can impair downstream water quality. Factors influencing P loads including land use and seasonality are currently not well understood. Further, the suitability of available modelling tools to predict these loads is unclear. In this study, the build-up wash-off model in the Storm Water Management Model (SWMM) was used to simulate total suspended solids (TSS), total phosphorus (TP), and soluble reactive phosphorus (SRP) loads from a mixed land use watershed. The model performed well for simulating event and seasonal loads but was less able to capture intra-event concentration variability, specifically for SRP. In warm-weather months, the model indicated different seasonal trends for urban and agricultural land uses between TSS, TP, and SRP loads. SRP loads were highest in the fall season, particularly from old low-density residential areas, and are predicted to increase with urbanization. The study findings can help inform future strategies to manage P loads from mixed land use watersheds.

Summary for Lay Audience

Phosphorus (P) is an essential nutrient for ecosystems, but when too much of it ends up in our lakes and rivers, it can lead to water pollution and harmful algal blooms. Algal blooms can damage ecosystems, affect water quality, and can cause human health risks. In urban areas, P can be delivered to nearby surface waters during rainfall and snowmelt events. Common sources of P in urban areas include fallen leaves, lawn fertilizers, and pet waste. However, we do not fully understand how much P comes from different urban land uses (e.g., residential, commercial areas, roads) and whether the amounts change seasonally. This information is important for deciding where to focus efforts to improve stormwater quality. Quantifying P inputs to surface waters is particularly challenging in watersheds with mixed urban and agricultural land uses. To address this, water quantity and quality computer models are often used to provide advanced interpretation of field data and to predict how much P is being delivered into rivers and lakes during rainfall or snowmelt events. Storm Water Management Model (SWMM) is a commonly used computer model for simulating urban stormwater quantity and quality, but its suitability for modeling P inputs to surface waters needs further exploration.

In this study, SWMM was used to model P exports from a watershed that includes urban and agricultural land use. The study focused on a 5.7 km² mixed land use watershed in London, Ontario, where monitored streamflow and stream water quality data were used to build the model. Results showed that while the model was not able to capture changes in P concentrations in stormwater during individual rain events, it performed well in estimating the total amount of P in the stormwater during an event.

Application of the model showed that different land uses contributed varying amounts of P to surface waters between summer and fall. During fall rain events, roads, commercial/industrial/institutional, and old low-density residential areas exported high P amounts, while agricultural areas were the largest contributor during summer months. Overall, the results show the suitability of SWMM to estimate P exports from mixed land use areas and provide useful information on which areas to focus on to improve water quality in our rivers and lakes.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Available for download on Tuesday, July 01, 2025

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