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Urbanisation significantly impacts on water environments with increased runoff and the degradation of water quality. The management of quantity impacts are straight forward, but quality impacts are far more complex. Current approaches to safeguard water quality are largely ineffective and guided by entrenched misconceptions with a primary focus on 'end-of-pipe' solutions. The outcomes of a research study presented in the paper, which investigated relationships between water quality and six different land uses offer practical guidance in the planning of future urban developments. In terms of safeguarding water quality, high density residential development which results in a relatively smaller footprint would be the preferred option. The research study outcomes bring into question a number of fundamental concepts and misconceptions routinely accepted in stormwater quality management. The research findings confirmed the need to move beyond customary structural measures and identified the key role that urban planning can play in safeguarding urban water environments.Keywords: multivariate analysis, stormwater quality management, urban water quality, water quality impacts 3

In this study, the microbiological quality of roof-harvested rainwater was assessed by monitoring the concentrations of Escherichia coli, enterococci, Clostridium perfringens, and Bacteroides spp. in rainwater obtained from tanks in Southeast Queensland, Australia. Samples were also tested using real-time PCR (with SYBR Green I dye) for the presence of potential pathogenic microorganisms. Of the 27 rainwater samples tested, 17 (63%), 21 (78%), 13 (48%), and 24 (89%) were positive for E. coli, enterococci, C. perfringens, and Bacteroides spp., respectively. Of the 27 samples, 11 (41%), 7 (26%), 4 (15%), 3 (11%), and 1 (4%) were PCR positive for the Campylobacter coli ceuE gene, the Legionella pneumophila mip gene, the Aeromonas hydrophila lip gene, the Salmonella invA gene, and the Campylobacter jejuni mapA gene. Of the 21 samples tested, 4 (19%) were positive for the Giardia lamblia ␤-giardin gene. The binary logistic regression model indicated a positive correlation (P < 0.02) between the presence/absence of enterococci and A. hydrophila. In contrast, the presence/ absence of the remaining potential pathogens did not correlate with traditional fecal indicators. The poor correlation between fecal indicators and potential pathogens suggested that fecal indicators may not be adequate to assess the microbiological quality of rainwater and consequent health risk.

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In the context of stormwater quality modelling, an in-depth understanding of underlying physical processes and the availability of reliable and accurate mathematical equations, which can replicate pollutant processes are essential. Stormwater pollutants undergo three primary processes, namely, build-up, wash-off and transport, before accumulating into receiving waters. These processes are expressed mathematically by equations in stormwater quality models. Among the three processes, wash-off is the least investigated. This paper presents the outcomes of an in-depth investigation of pollutant wash-off processes on typical urban road surfaces. The study results showed that a storm event has the capacity to wash-off only a fraction of pollutants available and this fraction varies primarily with rainfall intensity, kinetic energy of rainfall and characteristics of the pollutants. These outcomes suggest that the exponential equation commonly used for mathematically defining pollutant wash-off would need to be modified in order to incorporate the wash-off capacity of rainfall. Consequently, the introduction of an additional term referred to as the 'capacity factor'C(F) is recommended. C(F) primarily varies with rainfall intensity. However, for simplicity three rainfall intensity ranges were identified where the variation of C(F) can be defined. For rainfall intensities less than 40 mm/h, C(F) varies linearly from 0 to 0.5. For rainfall intensities from 40 to around 90 mm/h, C(F) is a constant around 0.5. Beyond 90 mm/h, C(F) varies between 0.5 and 1.