Characterising urban zinc generation to identify surface pollutant hotspots in a low intensity rainfall climate.

Characterising stormwater runoff quality provides useful insights into the dynamics of pollutant generation and wash off rates. These can be used to prioritise stormwater management strategies. This study examined the effects of a low intensity rainfall climate on zinc contributions from different impermeable urban surface types. First flush (FF) and steady state samples were collected from seven different surfaces for characterisation, and the data were also used to calibrate an event-based pollutant load model to predict individual 'hotspot' surfaces across the catchment. Unpainted galvanised roofs generated very high concentrations of zinc, primarily in the more biologically available dissolved form. An older, unpainted galvanised roof had FF concentrations averaging 32,338 µg/L, while the new unpainted roof averaged 4,782 µg/L. Roads and carparks also had elevated zinc, but FF concentrations averaged only 822-1,584 µg/L. Modelling and mapping expected zinc loads from individual impermeable surfaces across the catchment identified specific commercial roof surfaces to be targeted for zinc management. The results validate a policy strategy to replace old galvanised roof materials and avoid unpainted galvanised roofing in future urban development for better urban water quality outcomes. In the interim, readily-implemented treatment options are required to help mitigate chronic zinc impacts on receiving waterways.

A novel modelling framework to prioritize estimation of non-point source pollution parameters for quantifying pollutant origin and discharge in urban catchments.

Stormwater runoff in urban catchments contains heavy metals (zinc, copper, lead) and suspended solids (TSS) which can substantially degrade urban waterways. To identify these pollutant sources and quantify their loads the MEDUSA (Modelled Estimates of Discharges for Urban Stormwater Assessments) modelling framework was developed. The model quantifies pollutant build-up and wash-off from individual impervious roof, road and car park surfaces for individual rain events, incorporating differences in pollutant dynamics between surface types and rainfall characteristics. This requires delineating all impervious surfaces and their material types, the drainage network, rainfall characteristics and coefficients for the pollutant dynamics equations. An example application of the model to a small urban catchment demonstrates how the model can be used to identify the magnitude of pollutant loads, their spatial origin and the response of the catchment to changes in specific rainfall characteristics. A sensitivity analysis then identifies the key parameters influencing each pollutant load within the stormwater given the catchment characteristics, which allows development of a targeted calibration process that will enhance the certainty of the model outputs, while minimizing the data collection required for effective calibration. A detailed explanation of the modelling framework and pre-calibration sensitivity analysis is presented.

Contaminant removal and hydraulic conductivity of laboratory rain garden systems for stormwater treatment.

In order to evaluate the influence of substrate composition on stormwater treatment and hydraulic effectiveness, mesocosm-scale (180 L, 0.17 m(2)) laboratory rain gardens were established. Saturated (constant head) hydraulic conductivity was determined before and after contaminant (Cu, Zn, Pb and nutrients) removal experiments on three rain garden systems with various proportions of organic topsoil. The system with only topsoil had the lowest saturated hydraulic conductivity (160-164 mm/h) and poorest metal removal efficiency (Cu ≤ 69.0% and Zn ≤ 71.4%). Systems with sand and a sand-topsoil mix demonstrated good metal removal (Cu up to 83.3%, Zn up to 94.5%, Pb up to 97.3%) with adequate hydraulic conductivity (sand: 800-805 mm/h, sand-topsoil: 290-302 mm/h). Total metal amounts in the effluent were <50% of influent amounts for all experiments, with the exception of Cu removal in the topsoil-only system, which was negligible due to high dissolved fraction. Metal removal was greater when effluent pH was elevated (up to 7.38) provided by the calcareous sand in two of the systems, whereas the topsoil-only system lacked an alkaline source. Organic topsoil, a typical component in rain garden systems, influenced pH, resulting in poorer treatment due to higher dissolved metal fractions.