Urban Resilience: Sustainable Stormwater Management

The impacts of climate change effects on urban environments are contextually dependent, as climate change interacts with regional landscapes and ecological processes, such as hydrological cycles and microclimates. Generally speaking, models indicate that we can expect to see a rise in sea level, increased weather severity, and changes in precipitation and temperature (Hoegh-Guldberg et al., 2018). In addition to increased frequency of storm events and greater precipitation volume and intensity, climate change can compound with urbanization to intensify climate change impacts at local levels (Yang et al., 2021). For example, the urban heat island effect can increase local rain volumes, resulting in a phenomenon known as the urban rain island effect (Yang et al., 2021). At the same time, urbanization leads to a decrease in pervious surface areas, which are areas that allow infiltration of water into the ground (Fletcher et al., 2013). This results in increased surface runoff which can overwhelm existing stormwater drainage systems, triggering urban floods (Eckart et al., 2017). Increases in urban floods are concerning, especially considering the projected growth of urbanization in this century, with an expected 60.4% of the world’s population living in cities by 2030 (United Nations, 2018), and an expected world population of 8.5 billion by the same year (United Nations, n.d.). The urgency of this issue requires assessments of climate mitigation strategies such as sustainable urban stormwater management, to minimize the effects of climate change and urbanization on urban environments. This urgency is reflected in the literature, as there is growing attention to rainfall-runoff analyses and discourse on stormwater mitigation strategies (Yang et al., 2021).

With increasing rates of urbanization around the world, emphasis on sustainable development is coming to the forefront of urban planning initiatives. The United Nations’ Sustainable Development Goals highlight this shift with the inclusion of ‘sustainable cities and communities’ (United Nations, n.d.). More recently, academic discussion is exploring the concept of resilience. Derived from ecological resilience theory, resilience can have different definitions between academic disciplines (Ernstson et al., 2010); This report will follow the definition of MacKinnon’s resilience: “[the] capacity to deal with external sources of stress and maintain or recover normal functioning,” (2015, p. 561). The concept of resilience has influenced urban planning to focus on the transformation of a city to use natural processes, instead of trying to change the physical environment to match the goals of development (Ernstson et al., 2010). An example of this lies with ‘sponge cities’ – these use a combination of traditional and green stormwater management approaches to reduce flood risks and store water for later use (Chan et al., 2022). Regardless of terms, there is a movement of urban planning initiatives toward using natural solutions and mimicking of natural hydrological cycles to increase urban resilience to climate change. 

The integration of nature into the urban landscape can increase the resilience of urban environments (Ernstson et al., 2010; Keeler et al., 2019). As such, there have been a series of movements and concepts introduced to urban stormwater management: best management practices (BMPs), integrated urban drainage system (IUDS), low impact development (LID), and green infrastructure (GI) (Yang et al., 2021). While there are some slight differences in meanings, they all are similar in application – often using natural stormwater control techniques (e.g., bioswales, green roofs) as a way to manage stormwater (Yang et al., 2021). LID and GI are the most ‘current’ terms in the literature, often used interchangeably (Fletcher et al., 2015). For our purposes, LID will be used as an umbrella term for sustainable urban stormwater management practices. LID controls include green roofs, bioswales, rain gardens, rain cisterns, permeable pavement systems, etc., and are often used as a retrofit measure to reduce flooding (Eckart et al., 2017).

LID controls have emerged as popular measures around the globe, with cities like London and Toronto implementing LID initiatives, with significant research highlighting their positive impacts (Yang et al., 2021). The key stormwater benefit includes the reduction in stormwater runoff volume, primarily by increasing the infiltration of water into the ground or retaining and slowing down the flow of water (Eckart et al., 2017). The increasing popularity of LID is further supported by the associated secondary benefits, including increases of green spaces, improvements in quality of life for residents, and increased biodiversity (Eckart et al., 2017).

The University of British Columbia (UBC), with its main campus being in Vancouver, has developed action plans in an effort to become a more sustainable campus within an urban environment. Currently, the university is enacting an engagement project to facilitate collaborative planning, called Campus Vision 2050. Campus Vision 2050 aims to expand on the pre-existing climate action plan. The current Climate Action Plan 2030 (UBC, n.d.) outlines UBC's many goals, including decarbonization, waste minimization, and energy efficiency, within their overarching objective to respond to climate change with mitigation, adaptation, and increased resiliency. UBC’s (2017) Integrated Stormwater Management Plan further highlights resilience and recommends the implementation of LID controls on campus. Specifically, the plan aims to reduce stormwater runoff while maintaining water quality (UBC, 2017). While this plan references LID, there has not yet been an analysis of optimal LID selection and location on campus, nor an analysis on the direct effects on stormwater management. This research project aims to address this knowledge gap, by assessing the effects of LID controls on stormwater runoff using a simulated stormwater management model. It aims to answer the questions: can LID improve the resiliency of UBC to climate change, by reducing stormwater runoff? And what combination of LID controls and LID locations result in the greatest improvements of stormwater resiliency?

The study area for the analysis involves 19 stormwater sub-catchments of UBC campus. The sub-catchments reside in the northern section of campus, around East Mall and the University Hill area. Native soils of the area are often heavy or silty clay, with a weak soil horizon A which presents risks of erosion (BC SIFT, 2018). As well, the soils belong to the Bose-Heron soil management group, meaning that the soils have low water-holding capacities and may need additional soil to improve drainage (Krzic et al., 2010).

UBC campus is located in Point Grey within the city of Vancouver. Being on a peninsula on the Pacific Ocean coastline, the campus often sees dry summers and wet winters. Under climate change scenarios, the average annual precipitation is expected to increase by 6% (Shepherd et al., 2014). With the increased precipitation comes increased intensity, presenting a risk of flash floods.

The graph on the right shows the projected intensity of rainfall during different duration storm events.

For more information on anticipated climate change effects for UBC campus:

A rainfall-runoff analysis was performed using the United States Environmental Protection Agency’s (EPA) Storm Water Management Model (SWMM). SWMM is a spatial simulation model that routes rainfall through an area’s sub-catchments and water infrastructure, allowing for the estimation of water flow rates, depths, and water quality, for a start. For this analysis, the SWMM model was used to assess runoff volumes and flooding risks for 19 hydrological sub-catchments on UBC campus.  

Factors were inputted to the SWMM model for each sub-catchment, with sub-catchments being determined by UBC’s stormwater infrastructure data:

1. Topographic conditions including slope and elevation.
2. Soil type as infiltration rates (mm/hr).
3. Land cover including percentage of pervious and impervious surfaces.
4. Current stormwater drainage infrastructure, including drains, manholes, water mains, outlets, and stormwater detention features.
5. Rainfall data as a time series.

As an emerging concept, there is currently no commonly used stormwater resiliency metric or method for quantification. As such, the study area’s overall resiliency to flooding is quantified using the runoff coefficient, the ratio of total runoff to total precipitation, produced by the SWMM rainfall-runoff analysis. The runoff coefficient acts as a proxy for resilience as it represents how much water in a sub-catchment cannot infiltrate into the ground or the stormwater system, in comparison to how much water the sub-catchment receives.  

To assess resilience to climate change, a total of six scenarios are used in the model based on projected precipitation duration and intensities for three different storm events.

• 2 year return events with storm durations of 10 minutes and 24 hours.
• 25 year return events with storm durations of 10 minutes and 24 hours.
• 100 year return events with storm durations of 10 minutes and 24 hours.

The overall resiliency of the study area to climate change scenarios and potential flooding events is compared across simulations. The aim of the comparison is to identify the optimal potential LID controls which can increase the resiliency of the study area to climate change effects. Optimal locations and types of LID practices are determined by the SWMM simulations and corresponding runoff coefficient.

To test to see if LID can increase the stormwater resilience of UBC campus, for each storm scenario, the model was repeated using six different layouts which include a variety of LID controls:

1. Baseline/current stormwater infrastructure.
2. Green roofs.
3. Permeable pavement.
4. Bioretention cells.
5. Permeable pavement and bioretention cells.
6. Green roofs, permeable pavement, and bioretention cells.

As an emerging concept, there is no standard measure for stormwater resilience. As such, the study area’s overall resiliency to flooding will be measured by the runoff coefficient, the ratio of total runoff to total precipitation, produced by the SWMM rainfall-runoff analysis. The runoff coefficient acts as a proxy for resilience as it represents how much water in a sub-catchment cannot infiltrate into the ground or into the stormwater system, in comparison to how much water the sub-catchment receives. However, other variables including total runoff volumes, the presence of flooding and flooding depths, and LID storage are also considered.

The results show that as a single LID, permeable pavements were most effective at reducing the runoff coefficient from the baseline scenario. However, the combination scenarios that contain a variety of LID controls performed best. The maps below show the relative performance of each layout at reducing runoff for one storm type.

Previous research has outlined LID as a tool to reduce large volumes of runoff and mitigate flooding (Eckart et al., 2017; Hu et al., 2019). The analysis builds on this research, finding that generally, LID is effective at reducing the runoff coefficient from UBC’s current infrastructure (see tables above). That said, the type of LID control had a significant effect on their performances and corresponding runoff coefficients. For this analysis, the green roofs acted as a flow reduction LID control, whilst permeable pavements acted as an infiltration LID control, and bioretention cells as an LID control acted as a combination of both infiltration and flow reduction (Eckart et al., 2017). Of the LID practices, permeable pavements had the lowest average runoff coefficients in contrast to both green roofs and bioretention cells. However, the optimal reduction of runoff coefficients was seen with both the scenarios that contain a combination of LID controls. Samouei & Özger (2020) similarly found a combination approach to be more effective in reducing runoff volumes, though claiming that reductions in runoff is linearly correlated with an increase in pervious surface area. In this study, it is unclear whether the increased performance of the LID combinations is simply due to a greater surface area that has been converted from impervious to pervious, or due to the presence of different types (infiltration or flow reduction) of LID controls.

LID controls were selected based on the subcatchment and the LID control requirements. Some subcatchments did not have an option for LID control implementation, as in some cases, buildings and other infrastructure has already been developed. In other cases, if there were reasonable open and flat roofs on the buildings, extensive green roofs were selected as a potential LID control. However, it is unknown if the buildings have the structural capacity or accessibility to successfully implement a green roof. In other subcatchments where there was a greater amount of open space available, permeable pavements were chosen to replace pre-existing paths and walkways. If a particularly large area was available (< 100 m ² ), there was the potential to replace the pavements with bioretention cells. Of the three LID controls implemented in these model scenarios, permeable pavements were deemed suitable most frequently.

All three layouts including permeable pavement would be suitable for UBC campus, as they saw the greatest reductions in runoff coefficients, runoff volumes, peak flows, and flooded nodes. Yet, the two combination scenarios performed more effectively than permeable pavement alone. For example, for a 10 minute, 2-year return event, the combination of LID controls further reduced the number of flooded nodes by 10 and 13 compared to permeable pavements as a single LID. Performances between the two combination scenarios were almost indistinguishable, suggesting that either would increase UBC’s campus resilience to climate change. However, since the two are virtually equal in their effects, it seems as if the addition of green roofs may be unnecessary. Thus, in the interest of cost effectiveness and conserving university resources, the optimal infrastructure layout for UBC campus would be the simpler of the two, which combines permeable pavements and bioretention cells.

In contrast to the current infrastructure, the inclusion of permeable pavement and bioretention cells has a positive impact on runoff volumes and flood risks. The baseline layout subcatchments generally reported substantially higher runoff coefficients than the optimal layout. Of particular concern are subcatchments 5, 15, and 19, as they reported the greatest runoff coefficients. Although subcatchments 5 and 19 were not deemed suitable for LID controls, subcatchment 19 still saw a reduced runoff coefficient under the optimal layout. This is likely owing to LID installations further upstream reducing the subcatchment’s received runoff; LID has been known to positively affect downstream and surrounding subcatchments (Alexander et al., 2019). Subcatchment 15, which had the second highest runoff coefficient with current infrastructure, had permeable pavements implemented in the combined LID layout. The results were impressive, as using the LID layout resulted in the subcatchment seeing the second greatest improvement in runoff coefficients, decreasing from 0.99 to 0.28. This is promising as it indicates that proper planning of LID implementation can have significant positive impacts on high-flood-risk areas.

The results of the model scenarios show that UBC campus could be improved by incorporating LID controls into campus planning initiatives. As a starting point for UBC campus planning, if the aim of the installation of LID controls is to reduce peak flow volumes, the extensive green roofs used in this analysis should not be considered. For increasing infiltration and reducing runoff, bioretention cells perform best. However, if the issue is that impervious surface runoff is particularly high, then permeable pavements are most recommended. For UBC campus, the best option for the reduction of surface runoff is a combination of both permeable pavements and bioretention cells.

However, under a moderate climate change emissions scenario, even the incorporation of LID controls may not be enough to adequately prevent flooding. Prior to further campus planning, UBC should investigate potential LID under different temporal patterns in precipitation, to assess the resilience to the more intense storm events that may occur more frequently with increased climate change effects.

In this analysis, we aimed to answer the questions:

• Can low impact development or LID controls increase the stormwater resilience of UBC’s campus?
• Which LID controls enhance the resilience most effectively?

In response to the first, the results show that LID can increase the resilience of the UBC campus to climate change, by reducing impervious runoff and peak runoff flows. In answer to the second question, the findings indicate that performance of LIDs for increasing resilience was varied. As a single LID control, permeable pavements are most effective for UBC campus. Yet the greatest reductions in runoff can be achieved using a combination of permeable pavements and bioretention cells. However, the results indicate that intense storms are likely to overwhelm UBC’s infrastructure, even with the implementation of LID controls. This research thus acts as a warning and a potential starting point for further analysis, prior to campus planning initiatives. Further investigation into mitigation efforts for flash flooding and peak flows would be beneficial for UBC’s resilience to the peaky storms expected with climate change. Overall, the research indicates that more sustainable stormwater management can mitigate the combined effects of urbanization and climate change which has promising implications for urban environments. Urban planning should continue to adopt low impact development as an innovative and successful approach to combatting climate change impacts.

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