115 resultados para Water-supply engineering.


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In the recent manuscript published by Egodawatta et al. (2013), the authors investigated the build-up process of heavy metals (HMs) associated with road-deposited sediment (RDS) on residential road surfaces, and presented empirical models for the prediction of both the surface loads and build-up rates of HMs on these surfaces...

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The effectiveness of structural elements employed for stormwater mitigation such as bioretention basins and constructed wetlands depend on the compatibility between their design specifications and actual stormwater quality and quantity characteristics. These structural elements are commonly designed to accommodate the initial portion of runoff considering the occurrence of first flush. Therefore, the effectiveness of stormwater quality treatment primarily depends on the in-depth knowledge of the first flush phenomenon and the ability to provide appropriate treatment. The current scientific knowledge relating to first flush is limited primarily due to research investigations being undertaken based on lumped rainfall and runoff parameters. This paper presents the outcomes of an in-depth study undertaken of the first flush phenomenon using a set of indicators which are not only innovative, but is also able to accurately represent the characteristics of the different sectors in a runoff hydrograph. The analysis undertaken confirmed that pollutant wash-off during the initial 10% of runoff volume was critical for the occurrence of first flush. Typically first flush was found to last up to 40% of the runoff volume. The study outcomes provide new knowledge to enhance the effectiveness of structural stormwater treatment measures.

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Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

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The 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 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.

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The 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.

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The validity of using rainfall characteristics as lumped parameters for investigating the pollutant wash-off process such as first flush occurrence is questionable. This research study introduces an innovative concept of using sector parameters to investigate the relationship between the pollutant wash-off process and different sectors of the runoff hydrograph and rainfall hyetograph. The research outcomes indicated that rainfall depth and rainfall intensity are two key rainfall characteristics which influence the wash-off process compared to the antecedent dry period. Additionally, the rainfall pattern also plays a critical role in the wash-off process and is independent of the catchment characteristics. The knowledge created through this research study provides the ability to select appropriate rainfall events for stormwater quality treatment design based on the required treatment outcomes such as the need to target different sectors of the runoff hydrograph or pollutant species. The study outcomes can also contribute to enhancing stormwater quality modelling and prediction in view of the fact that conventional approaches to stormwater quality estimation is primarily based on rainfall intensity rather than considering other rainfall parameters or solely based on stochastic approaches irrespective of the characteristics of the rainfall event.

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Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in 4 different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations in road dust differ considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.

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Sediment samples from 13 sampling sites in Deception Bay, Australia were analysed for the presence of heavy metals. Enrichment factors, modified contamination indices and Nemerow pollution indices were calculated for each sampling site to determine sediment quality. The results indicate significant pollution of most sites by lead (average enrichment factor (EF) of 13), but there is also enrichment of arsenic (average EF 2.3), zinc (average EF 2.7) and other heavy metals. The modified degree of contamination indices (average 1.0) suggests that there is little contamination. By contrast, the Nemerow pollution index (average 5.8) suggests that Deception Bay is heavily contaminated. Cluster analysis was undertaken to identify groups of elements. Strong correlation between some elements and two distinct clusters of sampling sites based on sediment type was evident. These results have implications for pollution in complex marine environments where there is significant influx of sand and sediment into an estuarine environment.

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The design of society’s major infrastructure systems are generally based on anthropogenic learnings and seldom encapsulate learning from nature. This results from a pervading attitude of superiority of human-designed systems, particularly since the Industrial Revolution. Problems created by such behaviours have previously not been thought to present a serious threat to humanity. However, many built environment professionals are now reconsidering the impact of such systems on the environment and their vulnerability to issues such as climate change. This paper presents an approach to delivering sustainable urban infrastructure that addresses 21st Century needs by emulating natural form, function and process - biomimicry – in infrastructure design. The analysis reveals the context for infrastructure change and the need for sustainable solutions, detailing the current inquiry into biomimicry informed design and highlighting potential applications from literature that demonstrate precedence for nature to inspire the design of urban infrastructure, in particular water and energy systems.

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In Mitchell Contractors Pty Ltd v Townsville-Thuringowa Water Supply Joint Board [2004] QSC 329, Douglas J considered the issue of broad significance for litigation practitioners of whether draft expert reports fall within the description in r212(2) of the Uniform Civil Procedure Rules 1999 (Qld) of documents "consisting of a statement or report of an expert" and are therefore not privileged from disclosure.

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Using a case study approach, this paper presents a robust methodology for assessing the compatibility of stormwater treatment performance data between two geographical regions in relation to a treatment system. The desktop analysis compared data derived from a field study undertaken in Florida, USA, with South East Queensland (SEQ) rainfall and pollutant characteristics. The analysis was based on the hypothesis that when transposing treatment performance information from one geographical region to another, detailed assessment of specific rainfall and stormwater quality parameters is required. Accordingly, characteristics of measured rainfall events and stormwater quality in the Florida study were compared with typical characteristics for SEQ. Rainfall events monitored in the Florida study were found to be similar to events that occur in SEQ in terms of their primary characteristics of depth, duration and intensity. Similarities in total suspended solids (TSS) and total nitrogen (TN) concentration ranges for Florida and SEQ suggest that TSS and TN removal performances would not be very different if the treatment system is installed in SEQ. However, further investigations are needed to evaluate the treatment performance of total phosphorus (TP). The methodology presented also allows comparison of other water quality parameters.

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Stormwater bioretention basins are subjected to spontaneous intermittent wetting and drying, unlike water treatment filter systems that are subjected to continuous feed. Drinking water filters when constructed new or after back-wash, are subjected to a phase of stabilization. Experiments show that bioretention basins are similarly impacted by intermittent wetting and drying. The common parameter monitored in the stabilisation of filters is the concentration of total solids in the outflow. Filter media in bioretention basins however, consists of a mix of particulate organic matter and fine sand. Organic carbon and solids are therefore needed to be monitored. Four Perspex bioretention filter columns of 94 mm (ID) were packed with a filter layer (800 mm), transition layer and a gravel layer and operated with synthetic stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. Synthetic stormwater was prepared by adding NH4NO3 (ammonium nitrate) and C2H5NO2 (glycine) and a mixture of kaolinite and montmorillonite clay, to tapwater. The columns were fed with synthetic stormwater with different Antecedent Dry Days (ADD) (0 – 25 day) and constant inflow concentration (2 ppm: nitrate-nitrogen, 1.5 ppm: ammonium-nitrogen, 2.5 ppm: organic-nitrogen 100 ppm: total suspended solids and 7 ppm: organic carbon) at a feed rate of 100mL.min (85.7cm/h). Samples were collected from the outflow at different time intervals between 2 – 150 min from the start of outflow and were tested for Total Suspended Solids (TSS) and Total Organic Carbon (TOC). Both TSS and TOC concentrations in the outflow were observed to be much higher than the concentration of both the parameters in the inflow during the stabilisation period indicating a phase of wash-off (first flush) which lasted for approximately 30 min for both parameters at the beginning of each storm event. The wash-off of TSS and TOC were found to be highly variable depending on the age of the filter and the number of antecedent dry days. The duration of stabilisation phase in the experiments is significant compared with many of the stormwater events. A computational analysis on total mass of each pollutant further affirmed the significance of the first flush of an event on removal of these pollutants. Therefore, the kinetics of the first flush in the stabilisation phase needs to be considered in the performance analysis of the systems.

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Stormwater 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.

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Nitrogen is an important nutrient that can impact the quality of aquatic environments when present in high concentration. Even though low concentration levels of ammonium-nitrogen have been observed in laboratory studies in bioretention basins, poor removal or even the production of nitrate-nitrogen within the filter is often recorded in such studies. Ten Perspex biofilter columns of 94 mm (internal diameter) were packed with a filter layer, transition layer and a gravel layer. While the filter layer was packed to a height of 800 mm, transition and gravel layers were packed to a composite height of 220 mm and operated with simulated stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. The columns were operated with different antecedent dry days (0 d to 21 d) and constant inflow concentration at a feed rate of 100 mL/min. Samples were collected from the outflow at different time intervals, between 2 min and 150 min from the start of outflow, and were tested for nitrate-nitrogen and total organic carbon. Washoff of organic carbon from the filter layer was observed to occur for 30 min of outflow. This indicated washoff of organic carbon from the filter itself. At the same time, a very low concentration of nitrate-nitrogen was recorded at the beginning of the outflow, indicating the effective removal of nitrate-nitrogen. We conclude that the removal of nitrate-nitrogen is insignificant during the wetting phase of a rainfall event and the process of denitrification is more pronounced during the drying phase of a rainfall event. Thus intermittent wetting and drying is crucial for the removal of nitrate-nitrogen in bioretention basins.

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Treatment 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.