Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling
Abstract
:1. Introduction
1.1. Science, Engineering, and Management Context
1.2. Study Site
1.3. Objectives and Approach
- Test model performance by comparing output to field measurements to establish the credibility and reliability required to support management decisions;
- Characterize dynamic plume behavior (e.g., variation in the direction of alongshore movement) as a determinant of plume dimensions;
- Evaluate POC footprint dimensions for their consistency with mixing zone guidelines for nearshore water quality management.
2. Methods
2.1. Field Sampling and Laboratory Methods
2.2. Hydrodynamic Modeling Methods
2.3. Soluble Tracer Sub-Model
2.4. Design of Numerical Experiments
2.4.1. Testing Model Performance by Comparison with Field Measurements
2.4.2. Characterizing Dynamic Plume Behavior
2.4.3. Evaluating POC Footprint Dimensions in a Regulatory Context
3. Results and Discussion
3.1. Testing Model Performance
3.1.1. Simulating Meteorological and Hydrodynamic Conditions
3.1.2. Simulating Tracer Plume Dimensions
3.2. Characterizing Dynamic Plume Behavior
3.2.1. Tributary Inputs
3.2.2. Point Source Inputs
3.2.3. Evaluating POC Footprint Dimensions in a Regulatory Context
4. Conclusions: Management Insights
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Flow (m3·s−1) | Location | |
---|---|---|
Tributaries 1 | ||
Rouge River | 4.31 | Scarborough/Pickering, ON |
Duffins Creek | 2.92 | Ajax/Pickering, ON |
Carruthers Creek | 0.39 | Ajax, ON |
Point Sources 2 | ||
Highland Creek WWTP | 1.97 | Scarborough, ON |
Duffin Creek WWTP | 3.97 | Pickering, ON |
Corbett Creek WWTP | 0.6 | Whitby, ON |
Ashbridges Bay WWTP | 7.31 | Toronto, ON |
Pickering Nuclear Generating Station 3 | ||
PNG A plus PNG B | 153.1 | Pickering, ON |
Sources | Daily Flow | Outfall Depth | Temp | NO3-N | |
---|---|---|---|---|---|
(m3·s−1) | (m) | (°C) | (µg·L−1) | ||
Tributaries | |||||
Rouge River | July | 0.66–2.37 | - | - | 444 |
Sept | 0.95–30.39 | - | 771 | ||
Duffins Creek | July | 1.32–1.74 | - | - | 323 |
Sept | 1.16–15.05 | - | 335 | ||
Carruthers Creek | July | 0.17–0.23 | - | - | 69 |
Sept | 0.15–1.99 | - | 79 | ||
Point Sources | |||||
Highland Creek WWTP | July | 1.9 | 11.9 | 23.1 | 18,600 |
Sept | 2.0 | 22.7 | 11,900 | ||
Duffin Creek WWTP | July | 3.7 | 10 | 21.1 | 16,500 |
Sept | 3.9 | 18.8 | 15,800 | ||
Corbett Creek WWTP | July | 0.5 | 9 | 19.5 | 20,800 |
Sept | 0.6 | 21.0 | 14,900 | ||
Ashbridges Bay WWTP | July | 7.31 | 11 | 20.9 | 18,500 |
Sept | 7.31 | 20.9 | 18,500 | ||
Pickering Nuclear Generation Station | |||||
PNG A | July | 49.7 | - | 22 | 450 |
Sept | 49.7 | 28.2 | 283 | ||
PNG B | July | 103.4 | - | 21 | 450 |
Sept | 103.4 | 28.2 | 283 | ||
Baseline Conditions | |||||
Open Lake | July | - | - | - | 355 |
Sept | - | - | 270 |
Constituent | Cstandard | Ceffluent | D |
---|---|---|---|
(mg·L−1) | (mg·L−1) | (%) | |
Total Ammonia Nitrogen, as N | 500 | 1800 | 72.2 |
Total Phosphorus, as P | 20 | 422 | 95.3 |
Soluble Reactive Phosphorus, as P | 1.5 | 232 | 99.4 |
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Huang, C.; Kuczynski, A.; Auer, M.T.; O’Donnell, D.M.; Xue, P. Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling. J. Mar. Sci. Eng. 2019, 7, 129. https://doi.org/10.3390/jmse7050129
Huang C, Kuczynski A, Auer MT, O’Donnell DM, Xue P. Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling. Journal of Marine Science and Engineering. 2019; 7(5):129. https://doi.org/10.3390/jmse7050129
Chicago/Turabian StyleHuang, Chenfu, Anika Kuczynski, Martin T. Auer, David M. O’Donnell, and Pengfei Xue. 2019. "Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling" Journal of Marine Science and Engineering 7, no. 5: 129. https://doi.org/10.3390/jmse7050129
APA StyleHuang, C., Kuczynski, A., Auer, M. T., O’Donnell, D. M., & Xue, P. (2019). Management Transition to the Great Lakes Nearshore: Insights from Hydrodynamic Modeling. Journal of Marine Science and Engineering, 7(5), 129. https://doi.org/10.3390/jmse7050129