Why is Water Sensitive Urban Design (WSUD) important? For most of us, when it appears that it will rain we need to consider questions such as “should I bring an umbrella?” But in the planning of urban spaces there are other concerns. Urban planners must consider questions such as “what happens when it rains?” and “how can we manage this rain?”
The traditional design of stormwater systems may not always be the best way to manage this rain. Alternative practices have emerged including WSUD. This introduces a new question for urban planners: “what is the best way to use WSUD?”
What happens when it rains?
Some rain will fall on the roof of a building. From there it will move through the gutters, through a downpipe, and out onto the street (Figure 1). Other rain might land on a driveway and from there it will runoff onto the street. Most water that falls on grass or garden areas will infiltrate into the ground. But any excess rain will runoff onto the street. And the street itself produces run-off.
Urbanisation increases the number of rooves, footpaths, driveways and roads (Figure 2). These surfaces do not allow infiltration of water into the ground and so they are impervious. Some cities now have greater than 60% impervious cover.
What are the implications of this increased imperviousness? We find that there is a much greater volume of run-off and pollution (as shown below). But how much urbanisation is occurring? Is it a problem? Over the next 30 years in Adelaide alone, construction of more than 250,000 houses will occur.
Traditionally, water enters the stormwater pipe system through pits in the ground (Figure 3). It is then transported by pipes to an outlet (usually a river or the ocean). These systems are inexpensive. But they also have downsides with pollution and with large volumes of runoff during big storms.
So how can we improve upon these systems? The hydrographs (flows during a storm) in Figure 4 indicate pre- and post-development conditions.
The system was fine with the pre-development conditions. But as development of the land occurs, the run-off increases (as shown below in Figures 4 and 5).
To improve this system, we can attempt to reduce the peak flow. We reduce the post-development hydrograph to that of the pre-development.
How can Water Sensitive Urban Design help?
Firstly, we must ask: “what is Water Sensitive Urban Design?” All types of Water Sensitive Urban Design (WSUD) use some combination of:
- retention (permanently removing water)
- detention (temporarily removing water)
- infiltration (allowing water to enter the ground)
The use of WSUD can occur at different scales of size. In this study, we only looked at the application of WSUD to individual houses. See Figure 6 for an example:
On the house in Figure 6, not all rain that falls on the roof will enter the gutters and go through the downpipe. The green roof will capture some of the rain. Routing of excess water from the green roof to a rainwater tank will occur. The rainwater tank will detain or retain the water. Any excess water from the rainwater tank is routed to permeable areas. This might include a rain garden, which will detain some water and allow infiltration.
On footpaths and driveways the use of permeable pavement will allow increased infiltration. Because of the WSUD there will be less runoff from this house.
Now more questions arise, such as:
- What would be the impact on run-off in a suburb if every house had a rainwater tank? (as is compulsory for all new houses in South Australia).
- What impact does the size of the rainwater tank have?
- Is a rainwater tank the best option? What is the difference between a rainwater tank and other types of WSUD? (eg bio-retention cells). Is a combination of multiple WSUD practices best?
- How can we apply optimisation to help inform these decisions for decision makers?
How do we apply optimisation to WSUD in a catchment?
We can use Evolutionary Algorithms (EAs) to optimise the WSUD. But what are EAs? Evolutionary Algorithms are algorithms based on concepts from nature such as evolution. Evolutionary Algorithms can utilise these concepts to evolve better solutions over time to meet some goal. This goal is generally to minimise the cost of the solution.
The application of EAs to the planning of stormwater systems has occurred for many years. Software such as Optimizer can do this. The software allows you to define options for the traditional infrastructure. This may include pipe size and detention storage size. It also allows you to set constraints such as ensuring no flooding and restricting the peak flow.
But what should the constraint for peak flow be? As mentioned before, we should match the peak flow with the pre-development peak flow. The pre-development peak flow is the peak flow before urbanisation of the land occurs. As an example, we used a case study from The University of Illinois (Figure 7).
The proposed site is approximately 10 ha of land that has not been previously developed. First, simulation of the pre-development flow occurs (we used SWMM by the U.S. EPA to do this). What happens if we add traditional stormwater infrastructure to the urbanised land? We can use built-in functionality from Optimizer to find what this looks like.
There are many different scenarios that we could consider for optimisation. For this case study we chose to look at three scenarios (Figure 8). What would be the best solution if we only used traditional stormwater infrastructure? We can also ask what might be different about the plan if we incorporate WSUD into the optimisation? WSUD utilises detention and retention. So we can also ask what would a solution look like if we incorporated WSUD but left out the detention storage?
What are the outcomes from optimising the WSUD?
Figure 9 is a side-by-side comparison of two optimised solutions. One solution is with only traditional stormwater infrastructure options (pipes and detention storage). The other is a solution that incorporates WSUD in the optimisation.
How did the plans differ? As seen in the plans above, when incorporating WSUD, smaller pipes are used. This is because the WSUD reduces the runoff. Thus there is less water entering the pipes and so the smaller (cheaper) pipes are selected. For similar reasons, the detention storage is also smaller when incorporating WSUD. The hydrographs below (Figure 10) show the difference in the flows from each solution. All peak flows were successfully constrained to the peak flow of the pre-development site.
How did the costs differ between solutions? The table below shows a cost comparison. The combined infrastructure had the lowest total cost.
As you can see in the cost comparison, using WSUD leads to cheaper solutions for this case study. There is an extra cost for the WSUD, but then smaller pipes and detention storage are used. This leads to a decrease in cost.
For the case study used, it is more effective to include WSUD in the optimisation. In future, it will be important to test the application of this method to more case studies. This would show that it is effective for a variety of conditions. The application of the method using multiple objectives (not just cost) is also important. It would enable decision makers to see a variety of trade-offs.
This research opens the possibility of using optimisation with WSUD and traditional stormwater infrastructure. This allows the development of more effective solutions in the planning of stormwater systems. Please contact me if you are looking for more details on this project.
This blog post uses content from a project that won the Hodgson Medal in 2015. The medal is awarded to the best undergraduate project in South Australia. The Australian Water Association (AWA) oversees this award. The project was also a finalist for the AWA National Undergraduate Prize in 2016.
Thank you to the supervisors of this project: Prof. Angus Simpson (University of Adelaide) and Dr. Joshua Cantone (Optimatics, Chicago). Their guidance helped with the success of this project. Thank you also to the other group members of the project: Sean Vial, Bonnie Heidrich, and Rebecca van der Pennen.
Thank you also to Optimatics who made their software freely available for this project.