By Katherine Tse

Introduction

The Humber River Catchment (HRC), covering around 900 square kilometers, is the largest catchment managed by the Toronto and Region Conservation Authority (TRCA). Rapid urban development to accommodate population growth will likely impact the catchment's hydrology, sparking concerns about its resilience and response to increased impervious surfaces and stormwater runoff.

Under the guidance of Professor Adeyemi Olusola, my EUC Undergraduate Research Award project aimed to understand the role of runoff dynamics on catchment hydrology within the Black Creek using the Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS), a semi-distributed model capable of simulating hydrological processes in subbasins like Black Creek, a highly urbanized area within the HRC.

Aim

The project focused on modeling the Black Creek watershed's response to a significant rainstorm on July 16, 2024. This required a firm understanding of HEC-HMS, from setup and data processing to calibration, using advanced optimization techniques to enhance model accuracy.

Methodology

To construct an adequate model, we gathered essential hydrological data, including:

1. Runoff Records from Environment Canada,
2. Precipitation Data from the Toronto City Centre gauge, covering 24-hour storm profiles,
3. Land Use and Land Cover analysis was carried out using Google Earth Engine to aid in determining curve numbers

The HEC-HMS model setup used three main elements (Figure 1):

1. Subbasin, Representing Black Creek,
2. Reach, Linking upstream and downstream segments,
3. Sink, Collecting water flow from the subbasin to the outlet.

The model was configured with key parameters: flow direction, basin area, and runoff characteristics. Due to our focus on storm-event dynamics, the Soil Conservation Service Curve Number (SCS-CN) method was applied to estimate runoff losses, the SCS Unit Hydrograph for flow transformation, and leaving out baseflow modeling.

Initial model calibration involved iterative adjustments using optimization techniques, focusing on curve numbers, lag times, and initial abstraction values to minimize errors and improve model performance. Lag time, the delay between peak rainfall and peak runoff, proved particularly sensitive and significantly influenced the model's accuracy. The lag time was calculated using the formula:

T_lag = L^0.8  (S+1)^0.7/1900  y^0.5 …Equation 1

where L represents the length of the main channel in ft, S represents the potential maximum retention of runoff, and y represents the average watershed slope in percentage and

S = 1000/CN – 10 … Equation II where CN is the curve number estimation.

Outcome

Our model's responsiveness of lag time highlighted its importance as a predictive metric in the Black Creek watershed (Figure 2). Short lag times indicate rapid runoff and flow concentration in the creek, suggesting low infiltration rates and a high degree of impervious surfaces typical of urban catchments. By optimizing this parameter (Figure 3), we achieve better alignment between the observed and simulated hydrographs, improving peak flow accuracy and total runoff volume estimates (Figure 2).

The observed sensitivity of lag time offers insights into the urbanized character of the Black Creek watershed, where shorter lag times correspond to swift hydrologic responses; suggesting that urbanization has potentially increased flood risks due to quicker runoff, stressing natural drainage systems. The study's findings underscore the utility of HEC-HMS not only as a simulation tool but as a diagnostic resource to assess urban impact on watershed resilience.

Next Steps …

I aim to extend HEC-HMS applications across the entire Humber River Catchment, using optimized parameters to simulate flow, stage, and timing under various storm conditions. This will be particularly valuable for urban planning, stormwater management, and conservation efforts, providing predictive capabilities that help mitigate flood risks and improve sustainability as urbanization continues.

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Katherine Tse is a recipient of EUC's Undergraduate Research Award (EUCURA) in Summer 2024. She is in EUC's Environmental Science program where students explore the impact of human activities on the planet through the study of biology, chemistry, physics, and physical geography. She was part of the study on Lake Scugog where York University undergraduate students in the Environmental Science program partnered with the Scugog Lake Stewards to investigate lake ice decline on Lake Scugog as part of their Capstone learning experience. She is continually working with Professor Adeyemi Olusola in the Upper Humber River Catchment project.