Department of Civil Engineering
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Item Enhancing water sensitive urban design (WSUD) practices to mitigate urban stormwater pollution and reuse potential(National Environmental Engineering Research Institute (NEERI), 2011) Goonetilleke, AshanthaWater Sensitive Urban Design (WSUD) practices such as wetlands, bioretention systems and swales are widely implemented in Australia’s urban areas for the mitigation of stormwater pollution and to enhance its reuse potential. In-depth research undertaken has confirmed that these systems do not always perform according to design expectations due to a diversity of reasons. To deliver anticipated benefits, it is critical that they are designed in conformity with catchment and rainfall characteristics and pollutant processes. This in turn entails an in-depth understanding of key pollutant processes. This paper presents the outcomes of extensive research investigations on pollutant characterisation and stormwater pollutant processes on urban catchment surfaces. Outcomes from the research studies revealed the complexities in physical and chemical characteristics of pollutants originating from urban catchments which are strongly influenced by rainfall and catchment characteristics. Based on the research outcomes, recommendations are provided to enhance stormwater treatment performance and to enhance its reuse potential.Item Uncertainty analysis of pollutant build-up modelling based on a Bayesian weighted least squares approach(Elsevier, 2013-04) Goonetilleke, AshanthaReliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality datasets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares regression and Bayesian weighted least squares regression for the estimation of uncertainty associated with pollutant build-up prediction using limited datasets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.Item Characterising metal build-up on urban road surfaces(Elsevier, 2013-05) Goonetilleke, AshanthaReliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12–50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.Item Characterising nutrients wash-off for effective urban stormwater treatment design(Elsevier, 2013-05) Goonetilleke, AshanthaThis paper characterises nitrogen and phosphorus wash-off processes on urban road surfaces to create fundamental knowledge to strengthen stormwater treatment design. The study outcomes confirmed that the composition of initially available nutrients in terms of their physical association with solids and chemical speciation determines the wash-off characteristics. Nitrogen and phosphorus wash-off processes are independent of land use, but there are notable differences. Nitrogen wash-off is a “source limiting” process while phosphorus wash-off is “transport limiting”. Additionally, a clear separation between nitrogen and phosphorus wash-off processes based on dissolved and particulate forms confirmed that the common approach of replicating nutrients wash-off based on solids wash-off could lead to misleading outcomes particularly in the case of nitrogen. Nitrogen is present primarily in dissolved and organic form and readily removed even by low intensity rainfall events, which is an important consideration for nitrogen removal targeted treatment design. In the case of phosphorus, phosphate constitutes the primary species in wash-off for the particle size fraction <75 μm, while other species are predominant in particle size range >75 μm. This means that phosphorus removal targeted treatment design should consider both phosphorus speciation as well as particle size.Item Adsorption of heavy metals by road deposited solids(IWA, 2013-06) Goonetilleke, AshanthaThe research study discussed in the paper investigated the adsorption/desorption behaviour of heavy metals commonly deposited on urban road surfaces, namely, Zn, Cu, Cr and Pb, for different particle size ranges of solids. The study outcomes, based on field studies and batch experiments, confirmed that road deposited solids particles contain a significantly high amount of vacant charge sites with the potential to adsorb additional heavy metals. Kinetic studies and adsorption experiments indicated that Cr is the most preferred metal element to associate with solids due to the relatively high electronegativity and high charge density of trivalent cation (Cr3+). However, the relatively low availability of Cr in the urban road environment could influence this behaviour. Comparing total adsorbed metals present in solids particles, it was found that Zn has the highest capacity for adsorption to solids. Desorption experiments confirmed that a low concentration of Cu, Cr and Pb in solids was present in water-soluble and exchangeable form, whilst a significant fraction of adsorbed Zn has a high likelihood of being released back into solution. Among heavy metals, Zn is considered to be the most commonly available metal among road surface pollutants.Item Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics(Elsevier, 2014-03) Goonetilleke, AshanthaThe study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values which indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.Item Time as the critical factor in the investigation of the relationship between pollutant wash-off and rainfall characteristics(Elsevier, 2014-03) Goonetilleke, AshanthaThe approach adopted for investigating the relationship between rainfall characteristics and pollutant wash-off process is commonly based on the use of parameters which represent the entire rainfall event. This does not permit the investigation of the influence of rainfall characteristics on different sectors of the wash-off process such as first flush where there is a high pollutant wash-off load at the initial stage of the runoff event. This research study analysed the influence of rainfall characteristics on the pollutant wash-off process using two sets of innovative parameters by partitioning wash-off and rainfall characteristics. It was found that the initial 10% of the wash-off process is closely linked to runoff volume related rainfall parameters including rainfall depth and rainfall duration while the remaining part of the wash-off process is primarily influenced by kinetic energy related rainfall parameters, namely, rainfall intensity. These outcomes prove that different sectors of the wash-off process are influenced by different segments of a rainfall event.Item Assessing uncertainty in pollutant wash-off modelling via model validation(Elsevier, 2014-11) Goonetilleke, AshanthaStormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.Item Adsorption and mobility of metals in build-up on road surfaces(Elsevier, 2015-01) Goonetilleke, AshanthaThe study investigated the adsorption and bioavailability characteristics of traffic generated metals common to urban land uses, in road deposited solids particles. To validate the outcomes derived from the analysis of field samples, adsorption and desorption experiments were undertaken. The analysis of field samples revealed that metals are selectively adsorbed to different charge sites on solids. Zinc, copper, lead and nickel are adsorbed preferentially to oxides of manganese, iron and aluminium. Lead is adsorbed to organic matter through chemisorption. Cadmium and chromium form weak bonding through cation exchange with most of the particle sizes. Adsorption and desorption experiments revealed that at high metal concentrations, chromium, copper and lead form relatively strong bonds with solids particles while zinc is adsorbed through cation exchange with high likelihood of being released back into solution. Outcomes from this study provide specific guidance for the removal of metals from stormwater based on solids removal.Item Performance characterisation of a stormwater treatment bioretention basin(Elsevier, 2015-03) Goonetilleke, AshanthaTreatment performance of bioretention basins closely depends on hydrologic and hydraulic factors such as rainfall characteristics and inflow and outflow discharges. An in-depth understanding of the influence of these factors on water quality treatment performance can provide important guidance for effective bioretention basin design. In this paper, hydraulic and hydrologic factors impacting pollutant removal by a bioretention basin were assessed under field conditions. Outcomes of the study confirmed that the antecedent dry period plays an important role in influencing treatment performance. A relatively long antecedent dry period reduces nitrite and ammonium concentrations while increasing the nitrate concentration, which confirms that nitrification occurs within the bioretention basin. Additionally, pollutant leaching influences bioretention basin treatment performance, reducing the nutrients removal efficiency, which was lower for high rainfall events. These outcomes will contribute to a greater understanding of the treatment performance of bioretention basins, assisting in the design, operation and maintenance of these systems.