Acknowledgements
4. Methods
4.5 Development of SuDS scenarios
ZA Ghoor: Managing nutrient flows into the Zandvlei Estuary, Cape Town using Sustainable Drainage Systems (SuDS)
Chapter 4: Methods
ZA Ghoor: Managing nutrient flows into the Zandvlei Estuary, Cape Town using Sustainable Drainage Systems (SuDS)
Chapter 4: Methods
4.5.1 SuDS selection and placement
In this study, the greatest factors influencing SuDS selection and placement were the distribution of poor water quality, the availability of open space where SuDS might fit, and existing resources such as wetland areas.
Typically, SuDS are designed as treatment trains, usually consisting of a mixture of source, local and regional controls (see Figure 2-3). SuDS philosophy encourages the use of on-site controls as the best first line of defence (Armitage et al., 2013). However, source controls implemented at private residence level, such as green roofs and rainwater harvesting, are difficult to model at the scale of this project; thus the modelling of SuDS measures was focused on local and regional controls.
The first step in selecting SuDS measures was locating areas with sufficient space, and comparing those locations to where SuDS measures were needed – ideally downstream of suspected sources of elevated nutrients.
After areas were selected for SuDS modelling, the choice of potential SuDS measures was determined by what would be suitable considering the space available. For example, long narrow vegetated areas are suitable for swales. These initial choices would then be refined based on other site characteristics – in the previous example, even if a swale fits in an area, the site would be unsuitable if the slope is too steep since swales require slower runoff velocities to encourage infiltration and prevent erosion.
Once a SuDS component was selected, it was sized (Section 4.5.2) and then modelled (Section 6.3). In the model, SuDS were checked to ensure they adhered to the basic design standards and produced ‘realistic’ pollutant reductions – such as expected SuDS removal percentage ranges from Armitage et al., (2013) Table 2-3). Where modelled results appeared unrealistic, the model was checked for errors; the errors were typically found to be disconnected nodes in the model. After each SuDS component was modelled with the identified errors corrected, different combinations of SuDS were modelled as scenarios. Figure 4-14 summarises the steps leading to modelling the SuDS scenarios.
The following scenarios were created in the model:
• Current Scenario: the model was set up using data that represents the current catchment (Section 4.4). The Current Scenario was used to gain an understanding, however approximate, of the existing water quantity and quality in the study area. This scenario was also used as a baseline to compare the relative pollutant removal of the various SuDS scenarios. The Current Scenario is further discussed in Section 6.1.
• Pre-development Scenario: The Pre-development Scenario was used to give an indication of how current water quantity conditions differ from what they might possibly have been before the area was developed and urbanised. One of the goals of the SuDS philosophy is to control peak runoff rates so that the rate of runoff is limited to what it would have been
ZA Ghoor: Managing nutrient flows into the Zandvlei Estuary, Cape Town using Sustainable Drainage Systems (SuDS)
Chapter 4: Methods
Figure 4-14: Brief process leading up to formulating SuDS scenarios
prior to development (Woods Ballard et al., 2015). The Pre-development Scenario is further explained in Section 6.2.
• SuDS Scenarios: Individual SuDS components were chosen and modelled as described in the paragraphs above. In locations where different SuDS options were modelled, the one with the greater pollutant removal was selected to be grouped in a scenario. SuDS scenarios were then created from various groupings of these individual SuDS components. The different scenarios and how they were grouped are discussed further in Section 6.3.
4.5.2 Sizing of SuDS
For this study, SuDS were sized based on the water quality volume (WQV) required for treatment; the aim of modelling SuDS in the study area was to assess pollutant removal capability rather than reduce flow volumes, since the area is already equipped with a functional drainage system (this would not be the case for new developments). The WQV is defined as the volume of water from smaller storm events where the focus is on water quality treatment (Armitage et al., 2013). WQV can be estimated in a variety of ways; for this study, the WQV was the runoff associated with the 1 in 6 month, 24-hour storm – based on recommendations by Armitage et al.
(2013).
Rainfall frequency data for 24-hour storm durations were obtained from the CCT (Section 4.3.9). The dataset contains rainfall depths for 2- to 200-year recurrence interval (RI) storms for various locations throughout the study area. These data points were plotted as a
ZA Ghoor: Managing nutrient flows into the Zandvlei Estuary, Cape Town using Sustainable Drainage Systems (SuDS)
Chapter 4: Methods
logarithmic function for each location, from which the 1 in 6 month, 24-hour storm depth was extrapolated for each location – giving rainfall depths that varied between 24-47 mm across the study area. SuDS components were sized to store the volume associated with this storm depth.
Based on the eight years of data that was collected, this depth is greater than that associated with the first significant rainfalls of the wet season which typically flush pollutants down the catchment – i.e. the modelled SuDS measures will be theoretically able to accommodate the first flush rainfall.
The SuDS components were sized according to specifications outlined by Woods Ballard et al. (2015) and Armitage et al. (2013). The modelled SuDS measures are described in Section 6.3, and details on the relevant design standards and equations, as well as diagrams, are displayed in Appendix E.
4.5.3 SuDS treatment objectives
The study area falls within the jurisdiction of the CCT Municipality who have developed a policy framework regarding stormwater management objectives (CCT, 2009). This document outlines criteria that any implemented SuDS intervention must adhere to; the stipulated water quality objectives are a 45% reduction in TP and an 80% reduction in TSS.
South African aquatic guidelines classify the eutrophic status of rivers based on the average summer concentrations of inorganic phosphorus and inorganic nitrogen, over at least 4 weeks (DWAF, 1996). This data was not available, therefore the eutrophic status of the rivers in the study area could not be classified. In terms of SRP and TIN removal, the objective was for modelled SuDS to reduce SRP and TIN concentrations to below the eutrophic threshold.