Modeling the impact of LID for stormwater quality management in the Bongani stream catchment, Knysna, South Africa

Calvin David van der Merwe and Neil Philip Armitage


The Bongani Stream is a primary pollutant source of surface water runoff discharging into the Ashmead Channel, a shallow portion of the Knysna Estuary situated on the south coast of South Africa (Harvey, 2019). The Ashmead Channel is experiencing persistent macroalgal blooms which threaten the ecosystem’s biodiversity.

A hydrological model of the Bongani Stream was developed with the objective of investigating the feasibility of reducing pollutant loads using Low Impact Development (LID). It was developed in PCSWMM (Personal Computer Stormwater Management Model) that was calibrated using flow data collected during the study. Water quality was indicated through the use of event mean concentration (EMC) wash-off parameters for Total Nitrogen (TN), Total Phosphorus (TP), and Total Settleable Solids (TSS) which were estimated from an analysis of grab samples. The calibrated model was designated as the Current Scenario and was compared to the following additional scenarios:

  • Pre-development Scenario – the Current Scenario modified to serve as an idealised best-case situation.
  • Settlement Upgrade Scenario – incorporating the potential upgrading of the low-income areas to that more akin to typical suburban conditions.
  • Tributary Management Scenario – incorporating a detention wetland on the western tributary and a retention wetland on the eastern tributary of the Bongani Stream to manage pollution from the low-income settlements.
  • Bongani Wetland Scenario – incorporating a constructed wetland near the discharge point as a regional control for the entire catchment.

The Settlement Upgrade Scenario suggested that the TN and TP loads would be reduced by 79-82% and 73-80% respectively, performing better than the other LID intervention scenarios. The Bongani Wetland Scenario indicated the greatest reduction of TSS (by 49-50%) and total flow volumes (by 77%).

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