Water Science & Technology Vol 66 No 5 pp 1061–1068 © IWA Publishing 2012 doi:10.2166/wst.2012.281

Raw water quality weight factors: Vaal basin, South Africa

B. Dzwairo, F. A. O. Otieno, G. M. Ochieng and J. J. Bezuidenhout

Weight factors (WFs) were developed for surface raw water pollution indicator variables in Vaal River's Upper and Middle Vaal sub-basins, in South Africa. The overall objective was to formulate a quantifiable ranking system to indicate importance of pollutant variables given their established effects on human and environmental health. Multi-criteria decision analysis (MCDA) was applied to qualitative data that were obtained from South Africa's target water quality ranges as well as from literature which represented expert opinion. The human and environmental health effect choice sets were ranked from 1 to 5 on nine pollutant variable criteria: NH₃/NH₄⁺, Cl⁻, conductivity (EC), dissolved oxygen (DO), pH, F⁻, NO₃⁻/NO₂⁻, PO₄³⁻ and SO₄²⁻. The weighted-sum method (WSM) then assigned highest and lowest normalised weights (NWs) to F⁻ and Cl⁻, respectively, for human health effects (ɛ_hh) alternative. Highest and lowest NWs were assigned to NH₃/NH₄⁺ and EC, respectively, for environmental health effects (ɛ_eh) alternative. After aggregating the ɛ_hh and ɛ_eh WFs, resultant values ranked the variables from highest to lowest as follows: F⁻>NO₃⁻/NO₂⁻>/NH₃/NH₄⁺>DO>pH>SO₄²⁻>PO₄³⁻>EC>Cl⁻. The results represented the importance of variables given their established effects on human and environmental health. It was concluded that WFs provided a quantifiable barometer which could signal harmful exposure to elucidate negative effects of using polluted surface raw water in the study area. The values could be incorporated into water quality models like water quality indices. The approach could be used to develop WFs for other sites, taking into account issues like the site's pollution variables of concern as well as using a ranking key constructed from established literature.

Keywords: multi-criteria decision analysis; ranking; Vaal River; water pollution variables; weight factors; weighted-sum method

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