Towards the development of a multi-criteria decision support system for selecting stormwater best management practices.
The aim of this dissertation was to develop a multi-criteria decision support system (MCDSS) to allow a specified manager to select with confidence one or many of these BMPs for a particular site. The principal design approach was a review of South African and international literature pertaining to stormwater management techniques, in particular BMPs. This information was formulated into a primary matrix using a rank-and-weighting method. The scores were then checked against the literature to ensure that they were reasonable, culminating in the initial MCDSS. The MCDSS was then provided with seven scenarios, described in the literature, and the output reviewed. Although, the MCDSS would select appropriately when given few criteria for selection when these were increased, inappropriate outcomes resulted. Consequently, weighting factors were assigned to each criterion. The MCDSS was further tested using all the selection criteria and the output deemed satisfactory. The MCDSS was then tested in a case study of the Town Bush stream catchment at eleven sites along the river network and the results were adequate. Taking into consideration the economic aspects of BMP implementation a need also arose for the sites to be allocated to certain authorities depending upon ownership or responsibility. The sites were prioritised depending on potential threat to property and lastly by the hydrological nature of the stream at each site. A stormwater plan for the study area was also proposed. Although the MCDSS was functioning adequately it was not without its limitations. Limitations included the use of drainage areas as a surrogate measure for peak discharge thus, not allowing the user to design a series of BMPs or treatment chain. A second limitation was that initially the BMPs were designed as offline systems where stormwater is managed before entering the channel but in this study they were used as inline systems. Hence the ultimate selection was biased towards those BMPs able to deal with large drainage areas. Recommendations for further improvement include the development of a surrogate measure for drainage area thus allowing the user to design a treatment chain of BMPs; testing the MCDSS in more diverse circumstances; developing a more comprehensive set of selection criteria; and developing a clearer priority-setting model as the one used was rather simplistic. In conclusion the MCDSS provides the user with a useful tool where the selection and implementation of BMPs no longer has to take place in an ad hoc manner.