Difference between revisions of "Climate change"

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'''Histogram of rainfall during a typical storm event overlaid with hydrographs showing:'''
 
'''Histogram of rainfall during a typical storm event overlaid with hydrographs showing:'''
 
<br />•pre-development (blue) peak discharge is low and creates the least amount of runoff
 
<br />•pre-development (blue) peak discharge is low and creates the least amount of runoff

Revision as of 17:30, 12 September 2025

Maps showing predicted increases in temperature and precipitation for Toronto Region over the 21st Century under the high GHG emission scenario. Adapted from TRCA (2025)[1]. Click on the image to go to TRCA's Watershed and Ecosystems Reporting Hub and explore future climate trends.

Overview[edit]

Climate change refers to long-term alterations in temperature, precipitation, wind patterns, and other aspects of the Earth’s climate system, largely driven by human activities. The dominant cause is the increased concentration of greenhouse gases, primarily from fossil fuel combustion, industrial processes, and land-use change (IPCC, 2021)[2].

Impacts of climate change include:

  • Changing rainfall patterns lead to more frequent extreme precipitation events which increase the risk of flooding (Foster et al., 2011)[3]
  • Increased temperature worsens heatwaves, which are compounded with the urban heat island effect and increased drought length and intensity (Foster et al., 2011)[3]
  • Disrupts groundwater recharge by altering the amount of soil infiltration (Wu et al., 2020)[4]
  • Changes in nutrient loading to waterbodies such as the Great Lakes (Fong et al., 2025; Robertson et al., 2016)[5][6]
  • Biodiversity loss and changes in species distribution (United Nations, 2025)[7]
  • Health impacts such as heat related illness during heatwaves (PPG, 2023a)[8]
  • Economic impacts such as higher cooling costs and post-flood repairs (PPG, 2023b)[9]

Climate change challenges for grey infrastructure & SWM[edit]

Click on the image to read a presentation on Urban Water Policies and Practices for a Changing Climate (2024).[11]
Traditional grey infrastructure focused on conveying stormwater to end-of-pipe storage facilities is not resilient to climate change. Urban areas should be retrofitted with green infrastructure which uses a distributed network of stormwater features to filter and infiltrate runoff at the source. Image adapted from Pennsylvania Wilds (2021) [12].

Stormwater dynamics are strongly influenced by land use and rainfall patterns, making them vulnerable to both climate change and urbanization. Canadian cities are experiencing climate change impacts at rates often exceeding the global average, as Canada is warming nearly twice as fast as the rest of the world (Bush & Lemmen, 2019)[13]. Traditional stormwater systems that focus on efficiently conveying stormwater were designed based on historical climate conditions. However, urbanization and climate change have intensified surface runoff by way of more frequent and intensive rainfall occurrences and increased impermeable land cover. This in turn creates challenges for urban drainage systems that lack sufficient adaptive capacity (Wang et al., 2023)[14]. Given these interconnected pressures, green infrastructure is increasingly essential for reducing flood risk, safeguarding water quality, and strengthening urban resilience. LID builds climate resilience by supplementing large end-of-pipe ponds with a distributed network of smaller-scale stormwater features throughout the catchment to retain and treat runoff as close to the source as possible (Canada in a Changing Climate, 2018)[15].

Storm Events During varying Development Phases & SWM Controls[edit]

Screenshot 2025-09-05 153152.png

Histogram of rainfall during a typical storm event overlaid with hydrographs showing:
pre-development (blue) peak discharge is low and creates the least amount of runoff
•post-development without SWM facilities (red) discharge responds quickly to rainfall and has high peak flow
•post-development with an end-of-pipe SWM pond (green) discharge reaches the same peak flow as pre-development conditions but produces more runoff The checkered yellow space between the blue and green lines shows the difference between the runoff volumes - this area is where LID can be used to reduce runoff by storing and infiltrating rainfall. Image credit: Daniel Filippi.]]}}

Stormwater as a valuable resource[edit]

Stormwater is increasingly seen as a resource rather than waste: harvesting excess runoff can reduce stream degradation while providing water for urban populations (Walsh et al., 2012)[16]. Over time, management has shifted from end-of-pipe disposal to decentralized LID strategies that infiltrate, store, and reuse stormwater (Fletcher et al., 2014)[17]. With climate change expected to reduce precipitation, stormwater will likely be a relatively reliable resource for cities (Walsh et al., 2016)[18]. This view is reflected in policies such as:

Adapting to climate change using LID[edit]

LID can help offset climate change impacts in urban environments (IISD, 2021) [23].

Research highlights LID, such as bioretention, infiltration, and rainwater harvesting, as a critical strategy for building climate-resilient cities. Studies show that LID can reduce runoff volumes during extreme events, decrease peak flows, reduce overflow of combined sewers, and promote groundwater recharge:

  • Modelled green roofs, permeable pavements, and bioretention cells were shown to increase resilience against combined sewer overflows during heavy future rainfall, helping prevent untreated sewage from being released (Rodriguez et al., 2024)[24].
  • LID with controlled outlets outperformed traditional grey infrastructure to decrease peak flow reduction and overflow volume which helps minimize nuisance flooding and erosive flows. LID was more resilient to increased flow intensity from climate change than grey infrastructure (Lucas and Sample, 2015)[25].
  • Vogel et al. (2015) documented that the use of LID in New York and Minnesota have the potential to reduce flood risks under climate change scenarios[26].
  • Infiltration-based LID practices promoted groundwater recharge during climate change-adjusted design storms more effectively than conventional SWM (Barbu et al., 2009)[27].
  • Vegetated LID features, such as green roofs and treed bioswales, provide natural cooling that helps regulate urban temperatures and reduce energy demand and costs (ECONorthwest, 2007)[28].

Although LID BMPs are primarily designed to manage water quantity and quality, they also provide additional co-benefits for climate adaptation:

  • Gill et al. (2007) demonstrated that increasing urban greenspace by 10% by installing green roofs could offset projected urban heat increases until the 2080s[29].
  • New York City’s Green Infrastructure Plan, launched in 2010, uses green roofs, rain gardens, and permeable pavements to reduce combined sewer overflows and improve water quality. By 2020, over 5,000 projects were managing more than 760 million liters of stormwater annually. Beyond stormwater benefits, these projects also improve air quality, support biodiversity, and create green spaces in underserved communities (Montazeri, 2024)[30].
  • LID practices contribute to climate change mitigation by sequestering carbon (Haque et al., 2025)[31].
A variety of LID features distributed across a catchment addresses climate vulnerabilities more effectively than traditional grey infrastructure. Image adapted from the CT Stormwater Quality Manual (2025) [32]
A stormwater retrofit in Scarborough captures roof runoff, directing it toward enhancing green space, irrigating landscaped areas, and infiltrating stormwater. This system diverts water from the municipal storm sewer, strengthening watershed resilience to climate change. With aging stormwater infrastructure in the area that no longer meets current standards, this project serves as a showcase for lot-level LID retrofits (STEP, 2019)[33].

These stormwater benefits and additional ecosystem services position LID as essential tools for cities facing intensifying climate change impacts.

Watershed scale approaches to LID[edit]

Watershed-scale implementation of LID is more effective than isolated measures, as single installations rarely address all climate risks. Combining multiple BMPs that are tailored to a site’s vulnerabilities in a treatment train approach creates broader urban climate resilience.

  • Ayalew et al. (2015) demonstrated that distributed stormwater retention ponds provide more widespread flood control benefits across a catchment than a single large pond at the outlet [34].
  • Hydrological models show that combinations of rain barrels and rain gardens reduce runoff more than either LID alone (Neupane et al., 2021)[35].

Retrofitting[edit]

Urban areas are constantly changing, and activities such as sewer upgrades and building renovations create opportunities to retrofit LID BMPs. Coordinating climate adaptation measures with these activities can help lower overall project implementation costs (Voskamp et al., 2015)[36].

  • Jarden et al., 2015 demonstrated that catchment-scale retrofits, such as a combination of street-connected bioretention cells (with and without underdrains), rain gardens, and rain barrels, can significantly reduce peak flows[37].
  • A cistern/irrigation system and soakaway ponds/infiltration trench retrofitted into an industrial-commercial lot in Toronto reduced runoff volume from their roof drainage areas by 64% (~650 m2 roof area) and 89% (~204 m2 roof area), respectively (STEP, 2019)[33].

Tailoring LID features to climate change[edit]

During Hurricane Hazel (a devastating event in 1954 where 81 lives were lost), the two-hour maximum precipitation was 91 mm and the total amount of rainfall was 285 mm over nearly two days (Toronto Star, 2013)[38]. Conventional municipal drainage systems could not carry stormwater away fast enough; roads and highways were overcome with floodwater closing major transportation corridors, GO Train passengers were stranded, and power outages and basement flooding were widespread with property damage of more than $1 billion (Upadhyaya et al., 2014). Hurricane Hazel served as a catalyst for change, revealing the urgent need for an overhaul of flood management practices (TRCA, 2024)[39]. Hurricane Hazel was larger than the 100-year design storm (Institute for Catastrophic Loss Reduction, 2000)[40]

Canadian cities typically experience three types of rainfall (City of Vancouver, 2025)[41]:

  1. light showers
  2. rainstorms
  3. extreme storms

Most precipitation events fall into the first category. However, climate change is intensifying storm severity, shifting more events into the second and third categories. One study reported increases in the intensity of 20- and 50-year return period winter precipitation events across the western United States. Another study projected rising intensity of annual maximum precipitation in Canada, with the greatest increases expected in Ontario, the Prairies, and Southern Quebec (Guinard et al., 2015)[42]. As these storm events grow more frequent and intense, much of our infrastructure faces conditions it was never designed to withstand (Government of Ontario, 2012)[43]. To remain effective, the design of LID features must account for these changing precipitation patterns. Go to Understanding rainfall statistics to learn more about rain event distributions.

Intensity-Duration-Frequency Curves[edit]

Reading IDF Curves: A precipitation event with a duration of 12 minutes, and intensity of 5 inches/hour is predicted to occur once every 5 years (Bentley, N.D) [44]
IDF curves may shift under future climate scenarios. In this example, the future 50-year storm is predicted to have a higher rate of rainfall than historical storms of the same return period. LID practices should be designed to accommodate this shift. Image credit: ECCC (2025) [45]

Intensity–Duration–Frequency (IDF) curves are a standard tool in hydrology that describe the statistical relationship between rainfall intensity, storm duration, and frequency of occurrence (return period) to determine the likelihood of extreme rainfall events (Martel et al., 2021)[46].

  • Intensity: the rate of rainfall (mm/hr)
  • Duration: the length of the rainfall event (minutes to days)
  • Frequency: how often a given storm is expected to occur (e.g., a 10-year storm has a 10% chance of occurring in any given year)

IDF curves are developed from long-term rainfall records and models and are widely used to estimate design storms for stormwater management. IDF curves are crucial for sizing LID BMPs because they:

  1. Define design storms: LIDs must be able to manage runoff from specific return-period events (e.g., 2-year or 10-year storms). IDF curves provide the rainfall intensity and depth to use for those design events.
  2. Determine runoff volumes: By applying rainfall depth (from IDF data) to a given catchment, engineers estimate the stormwater volume that LIDs need to capture, infiltrate, or detain (USDA, 2021)[47].
  3. Assess peak flows: LID facilities are often designed to reduce peak discharge. IDF curves help simulate storm hydrographs and assess how much peak flow reduction is required (City of Toronto, 2006) [48].
  4. Account for climate change: Historical data is no longer an accurate predictor of future extreme rainfall (CSA, 2025)[49]. Since IDF curves are based on historical data, climate change-scaled IDFs can be used to design LIDs that are resilient under future rainfall conditions (ECCC, 2025)[45].

Estimating future rainfall[edit]

When designing infrastructure with a service life longer than 10 years, future IDF curves must account for climate change impacts on the frequency and intensity of extreme rainfall. Future precipitation patterns are estimated to account for climate change impacts.

The atmosphere’s capacity to hold moisture, and thus the occurrence of extreme rainfall, increases with warming. The relationship between increases in rainfall extremes and temperature is called rainfall–temperature scaling. Future rainfall intensities can be estimated via rainfall-temperature scaling using the following equation (CSA, 2025)[49]:

the median estimate of the projected future rainfall intensity of duration D and return period RT
historical rainfall intensity, obtained from IDF data produced by Environment and Climate Change Canada using stations that are representative of the project site location and have at least 10 years of complete and validated observations. Refer to CSA 231:25 for details on calculating from alternative sources of rainfall observations, if required.
the rainfall-temperature scaling factor (typically 1.07 unless otherwise justified)
the projected change in local temperature (°C) between the reference and future time periods. The following procedure should be used to obtain :
  1. Select climate data source – Use a reputable, bias-corrected, high-resolution data source for Canada (e.g., climatedata.ca) covering at least 1950–2100
  2. Define reference period – Must overlap with the historical records used for IDF curves
  3. Define future period – Same length as the reference, with anticipated end of service life falling in the middle of the future projection period when possible
  4. Choose emissions scenarios – Use both a representative and a high scenario from the latest Coupled Model Intercomparison Project (CMIP) phase
  5. Select climate change scenarios – scenarios that correspond with emissions scenarios from step 4 should be chosen from the data source in step 1, ensuring they represent variability among global models and account for uncertainty
  6. Calculate projected temperature change – Determine mean annual temperature change between reference and future periods using climate change scenarios
  7. Summarize results – Report both the median and 75th percentile of projected temperature changes from all climate change scenarios for use in future IDF curve calculations.
Risk thresholds are a useful tool when prioritizing climate change impact management efforts. Low impact and low frequency events may not require management planning, while high impact and high frequency events require adaptation strategies (MECP, 2022)[50]

To read about IDF curves and best practices, learn how to integrate climate change into IDF curves, and download climate change-scaled IDF data, visit:

Climate risk and uncertainty[edit]

Risk[edit]

Historical (grey) global surface temperature compared to a range of projected future surface temperatures based on five emission scenarios (from very low to very high). Not only is the state of future emissions uncertain, but there is also uncertainty associated with each scenario – indicated by the red and blue shaded areas (City of Toronto, 2024)[51]

Risk is typically defined as a combination of the likelihood of failure and the consequences of that failure. More detailed frameworks also consider hazard (what could trigger damage), exposure (what is at stake), vulnerability (sensitivity to hazards), and resulting consequences. In the context of climate change, risk is often expressed as (CSA, 2024)[52]:

Risk = (Probability of Climate Event) × (Probability of Asset Failure Given Event) × (Consequences: a function of exposure and vulnerability)

Not all risks can be fully managed; therefore, management efforts are typically prioritized toward impacts that exceed established thresholds of severity and frequency. (MECP, 2022)

Uncertainty[edit]

Climate change is inherently characterized by uncertainty, particularly in projecting local impacts. This uncertainty poses challenges for engineers, making risk management a critical tool for prioritizing vulnerabilities and selecting effective risk reduction strategies. Uncertainty surrounding climate impacts underscores the need to build resilience through LID practices (MECP, 2022). The ”no regrets” strategy refers to actions, such as LID, that have positive benefits for people and the environment, regardless of how climate change unfolds.

Planning for climate change in LID design[edit]

Building climate change resiliency into a project is not a reactive process and should be undertaken during early project phase. Climate planning should first identify system vulnerabilities across a wide range of possible future climates, then evaluate the probability and severity of impacts, and finally design adaptation strategies for impacts that exceed the threshold level of risk. A four-step process can be applied to guide resilient LID design (MECP, 2022)[50]:

  1. Identifying climate change considerations
  2. Evaluating risk caused by climate change parameters
  3. Climate change impact management planning
  4. Monitoring and adaptive management

To learn more about each step and access climate assessment templates, scroll through the PDF below which displays chapter 6.8 of the Draft LID Stormwater Management Guidance Manual, written by MECP in 2022[50]. You can download (downward facing arrow on the top righthand side) and print (Printer emoticon on top right hand side) the PDF.

load PDF

Climate planning at different scales[edit]

TRCA’s regulatory flood plain map (TRCA, 2025)[53]. As directed by the Province, the regulatory flood event standard applicable within TRCA’s jurisdiction is the greater of Hurricane Hazel or the 100-year storm (TRCA, 2025)[54].

Site scale[edit]

Individual sites can be assessed for climate change risk by evaluating stormwater systems for components vulnerable to projected changes in precipitation patterns. This includes considering increased frequency or intensity of system responses beyond design expectations, such as pipe surcharging, nuisance flooding, overtopping of storage facilities, erosion, failure to meet water quality or temperature targets, impacts on sensitive wetlands, and interactions with wells and septic systems (MECP, 2022)[50].

For sites with an existing stormwater management plan, it can be valuable to assess how much resiliency was incorporated into the system at the time of design by evaluating these thresholds. For instance, pipes may have additional capacity beyond the design return period depending on their installed size (MECP 2022)[50].

Climate change and SWM LID BMPs will affect site land use types differently. To view different LID opportunities for each unique land use type, please view the subsequent pages linked below:

Watershed scale[edit]

Climate change is expected to alter overall watershed behavior, including snow accumulation, spring freshet timing, streamflow patterns, evapotranspiration, groundwater recharge, wetland hydroperiods, and the frequency and severity of drought. Hydrologic models can be developed and applied at the watershed or subwatershed scale to assess the impacts of climate change on both groundwater and surface water systems (MECP, 2022)[50].

Municipal and provincial scale[edit]

Watershed and sub-watershed plans, official land use plans, master drainage plans, and design standards should consider climate change impacts as they relate to (CSA, 2024)[52]:

  • identification of natural infrastructure and associated floodplain and hydrologic functions
  • delineation of floodplains and associated setbacks for development
  • design, modeling, sizing, and placement of minor and major systems
  • assessment of a balanced cut and fill approach on a reach basis to provide additional developable area

References[edit]

  1. TRCA. 2025. Watershed and Ecosystems Reporting Hub. https://storymaps.arcgis.com/collections/8c517b063c81449d8fba71ca02d4278f?item=6
  2. IPCC. 2021. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press
  3. 3.0 3.1 Foster, J., Lowe, A., Winkelman, S. 2011. The value of green infrastructure for urban climate adaptation. https://ggi.dcp.ufl.edu/_library/reference/The%20value%20of%20green%20infrastructure%20for%20urban%20climate%20adaptation.pdf
  4. Wu, WY., Lo, MH., Wada, Y.  2020. Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers. https://doi.org/10.1038/s41467-020-17581-y
  5. Fong, P., Shrestha, R., Liu, Y., Valipour, R. 2025. Climate change impacts on hydrology and phosphorus loads under projected global warming levels for the Lake of the Woods watershed, Journal of Great Lakes Research. https://doi.org/10.1016/j.jglr.2025.102636.
  6. Robertson, D., Saad, D., Christiansen, D., Lorenz, D. 2016. Simulated impacts of climate change on phosphorus loading to Lake Michigan. Journal of Great Lakes Research, Volume 42, Issue 3. https://doi.org/10.1016/j.jglr.2016.03.009
  7. United Nations. 2025. Biodiversity - our strongest natural defense against climate change. https://www.un.org/en/climatechange/science/climate-issues/biodiversity
  8. Partners in Project Green. 2023a. Impacts: Human Health. https://partnersinprojectgreen.com/resources/impact-human-health/
  9. Partners in Project Green. 2023. Impacts: Building and Infrastructure. https://partnersinprojectgreen.com/resources/impact-building-and-infrastructure/
  10. Tu, C., Milner, G., Lawrie, D., Shrestha, N., Hazen, S. 2017. Natural Systems Vulnerability to Climate Change in Peel Region. Technical Report. Toronto, Ontario: Toronto and Region Conservation Authority and Ontario Climate Consortium Secretariat. https://climateconnections.ca/app/uploads/2012/03/Final-Natural-Systems-VA.pdf
  11. Neukrug, H. 2024.Urban Water Policies and Practices for a Changing Climate. Source to Stream Conference Presentation. https://sourcetostream.com/app/uploads/2024/04/S2S-Day-1-Track1-Presentation1.pdf
  12. Pennsylvania Wilds. 2021. Just what is green infrastructure? https://pawilds.com/just-what-is-green-infrastructure/
  13. Bush, E., & Lemmen, D. 2019. Canada’s changing climate report.
  14. Wang, M., Liu, M., Zhang, D., Zhang, Y., Su, J., Zhou, S., Bakhshipour, A., Tan, S. 2023. Assessing hydrological performance for optimized integrated grey-green infrastructure in response to climate change based on shared socio-economic pathways. Sustainable Cities and Society, Volume 91. https://doi.org/10.1016/j.scs.2023.104436
  15. Canada in a Changing Climate. 2018. Evaluation of Retrofitted Low Impact Development Practices for Stormwater Management at an Industrial Site. https://changingclimate.ca/map/evaluation-of-retrofitted-low-impact-development-practices-for-stormwater-management-at-an-industrial-site/
  16. Walsh , C., Fletcher, TD., Burns, MJ. 2012. Urban Stormwater Runoff: A New Class of Environmental Flow Problem. PLOS ONE 7(9). https://doi.org/10.1371/journal.pone.0045814
  17. Fletcher, T.D., Vietz, G., Walsh, C.. 2014. Protection of stream ecosystems from urban stormwater runoff : The multiple benefits of an ecohydrological approach. https://doi.org/10.1177/0309133314537671
  18. Walsh, C., Booth, D., Burns, M., Fletcher, T, Hale, R., Hoang, L., Grant Livingston, G., Rippy, M., Roy, A., Scoggins, M., Wallace, A. 2016. Principles for urban stormwater management to protect stream ecosystems. https://faculty.washington.edu/dbooth/Walsh%20et%20al%20Principles%20for%20urban%20stormwater_Freshwater%20Science%202016.pdf
  19. City of Toronto. Toronto Official Plan. 2019. https://www.toronto.ca/wp-content/uploads/2019/06/8f06-OfficialPlanAODA_Compiled-3.0.pdf
  20. York Region. Official Plan. 2024. https://www.york.ca/media/120156/download?attachment
  21. MECP. 2022. Draft Low Impact Development Stormwater Management Guidance Manual. https://prod-environmental-registry.s3.amazonaws.com/2022-01/Draft%20LID%20Stormwater%20Management%20Guidance%20Manual%202022.pdf
  22. City of Vancouver. 2024. Climate Change Adaptation Strategy (2024-2025 ). https://vancouver.ca/files/cov/vancouver-climate-change-adaptation-strategy-2024-25.pdf
  23. International Institute for Sustainable Development. 2021. Natural Infrastructure Solutions for Climate Resilience. https://www.iisd.org/articles/explainer/natural-infrastructure-solutions-climate-resilience
  24. Rodríguez, M., Fu, G., Butler, D., Yuan, Z., & Cook, L. 2024. The effect of green infrastructure on resilience performance in combined sewer systems under climate change. Journal of Environmental Management, 353, 120229. https://doi.org/10.1016/j.jenvman.2024.120229
  25. Lucas, W., Sample, D.. 2015. Reducing combined sewer overflows by using outlet controls for Green Stormwater Infrastructure: Case study in Richmond, Virginia. Journal of Hydrology, Volume 520. https://doi.org/10.1016/j.jhydrol.2014.10.029.
  26. Vogel, J.R., Moore, T.L., Coffman, R.R., Rodie, S.N., Hutchinson, S.L., McDonough, K.R., McLemore, A.J., McMaine, J.T. 2015. Critical review of technical questions facing low impact development and green infrastructure: A perspective from the Great Plains. Water Environment Research, 87(9), pp.849-862. https://doi.org/10.2175/106143015X14362865226392
  27. Barbu, L. Ballestero, T. Roseen, R. 2009. LID-SWM Practices as a Means of Resilience to Climate Change and Its Effects on Groundwater Recharge. 1-10. 10.1061/41036(342)134.
  28. ECONorthwest. 2007. The Economics of Low-Impact Development: A Literature Review. https://www.epa.gov/sites/default/files/documents/LID_Economics_Literature_Review.pdf
  29. Gill, S. Handley, J.F. Ennos, R., Pauleit, S. 2007. Adapting Cities for Climate Change: The Role of the Green Infrastructure. Built Environment. 33. 115-133. DOI:10.2148/benv.33.1.115
  30. Montazeri , B. 2024. A Comparative Study of LID, Suds, and Sponge City Strategies: Case Study of Melbourne. Masters’s Thesis, Politecnico di Torino. https://webthesis.biblio.polito.it/secure/32417/1/tesi.pdf
  31. Haque, M. T., Geronimo, F. K. F., Robles, M. E. L., Vispo, C., & Kim, L.-H. 2025. Comparative evaluation of the carbon storage capacities in urban stormwater nature-based technologies. Ecological Engineering, 212, 107539. https://doi.org/10.1016/j.ecoleng.2025.107539
  32. CT Stormwater Quality Manual. 2025. LID Planning and Design Process. https://ctstormwatermanual.nemo.uconn.edu/lid-planning-and-design/
  33. 33.0 33.1 STEP. 2019. Evaluation of Retrofitted Stormwater Source Control Practices, Calstone Inc., Toronto. https://sustainabletechnologies.ca/home/urban-runoff-green-infrastructure/low-impact-development/evaluation-retrofitted-stormwater-source-control-practices-calstone-inc-toronto/
  34. Ayalew, T., Krajewski, W. Mantilla, R. 2015. Insights into Expected Changes in Regulated Flood Frequencies due to the Spatial Configuration of Flood Retention Ponds. Journal of Hydrologic Engineering. Volume 20, Issue 10. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001173
  35. Neupane, B., Vu, T. M., & Mishra, A. K. (2021). Evaluation of land-use, climate change, and low-impact development practices on urban flooding. Hydrological Sciences Journal, 66(12), 1729–1742. https://doi.org/10.1080/02626667.2021.1954650
  36. Voskamp, I. M., and F. H M Van de Ven. 2015. Planning Support System for Climate Adaptation: Composing Effective Sets of Blue-Green Measures to Reduce Urban Vulnerability to Extreme Weather Events. Building and Environment 83. Elsevier Ltd:159–67. https://doi.org/10.1016/j.buildenv.2014.07.018
  37. Jarden, Kimberly M., Anne J. Jefferson, and Jennifer M. Grieser. 2015. Assessing the Effects of Catchment-Scale Urban Green Infrastructure Retrofits on Hydrograph Characteristics. Hydrological Processes 30 (10):1536–50. https://doi.org/10.1002/hyp.10736
  38. Toronto Star. 2013. Monday’s storm vs. Hurricane Hazel. http://www.thestar.com/opinion/letters_to_the_editors/2013/07/14/mondays_storm_vs_hurricane_hazel.html
  39. TRCA. 2024. Hurricane Hazel’s Legacy. https://trca.ca/news/hurricane-hazel-70-years/
  40. Institute for Catastrophic Loss Reduction. 2000. Hurricane Hazel and Extreme Rainfall In Southern Ontario. https://www.iclr.org/wp-content/uploads/PDFS/hurricane-hazel-and-extreme-rainfall-in-southern-ontario.pdf.
  41. City of Vancouver. 2025. Climate adaptation and rainwater management. https://vancouver.ca/green-vancouver/climate-adaptation-and-rainwater-management.aspx
  42. Guinard, K., Mailhot, A. and Caya, D. 2015. Projected Changes in Characteristics of Precipitation Spatial Structures over North America. International Journal of Climatology 35 (4):596–612. https://doi.org/10.1002/joc.4006
  43. Government of Ontario. 2012. Climate Ready: Ontario’s Adaptation Strategy and Action Plan. Ministry of the Environment, 124p.
  44. Bentley StormCAD CONNECT Edition Help. N.D. I-D-F Curves.
  45. 45.0 45.1 Environment and Climate Change Canada (ECCC). 2025. IDF Data and Climate Change. https://climatedata.ca/resource/idf-data-and-climate-change/
  46. Martel, J.-L., Brissette, F. P., Lucas-Picher, P., Troin, M., & Arsenault, R. 2021. Climate change and rainfall intensity–duration–frequency curves: Overview of science and guidelines for adaptation. Journal of Hydrologic Engineering, 26(10), 03121001. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002122
  47. USDA. 2021. Estimating Runoff Volume and Peak Discharge. https://directives.nrcs.usda.gov/sites/default/files2/1712930818/31754.pdf
  48. City of Toronto. 2006. Wet Weather Flow Management. https://www.toronto.ca/wp-content/uploads/2017/11/9191-wwfm-guidelines-2006-AODA.pdf
  49. 49.0 49.1 CSA, 2025. CSA 231:25 Developing and interpreting intensity-duration-frequency (IDF) information under a changing climate. https://www.csagroup.org/store/product/2431590/?srsltid=AfmBOopkRT3cosyCstZMacCmlthJxgfo6w6aFIXyuEExGmyBT8zw1vMs
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  51. City of Toronto. 2024. Toronto’s Current and Future Climate. https://www.toronto.ca/wp-content/uploads/2024/12/949f-TorontosCurrentandFutureClimate-REPORT-Final.pdf
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