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This thesis recognises the implicit shortfalls in the current methods of noise barrier development. An holistic and integrative methodology was devised, which can be potentially incorporated into general practise, without the unnecessary burdens of excessive cost and environmental impacts. In essence the thesis defines, 'a sustainable approach to environmental noise barrier design'. The importance of sustainability as a key determinant of a noise barrier's success is demonstrated through the impacts of public participation on the acceptance of a noise barrier. This was achieved through the triangulation of a grounded theory, formulated through the qualitative analysis of a real case study and then tested quantitatively on a larger representative sample. The theory explored the impact of ineffective public participation on the perceived success of a noise barrier. Noise maps were developed for the comparison of subjective opinions with objective facts. This also illustrated how this technology can be manipulated to focus public participation, and increase success. Demonstrating the utility of this growing resource beyond its current scope. A methodology for assessing the embodied impacts of noise barrier structures was also devised. By addressing the current lack of availability of a specific model, the means of choosing a noise barrier based on sustainable assets was revealed. Finally, the thesis concluded with a laboratory experiment, which utilised a RAVE facility and revealed the extent to which preconceptions play a role in the perception of a noise barriers' effectiveness. Revealing that regardless of which noise barrier is presented, that preconceptions of a materials' ability to attenuate noise are imbedded. The thesis contributed to several areas through the illustration of a sustainable approach to environmental noise barrier design. The methods highlighted, demonstrate how those responsible for building noise barriers, can improve the acceptance by the public and decrease the environmental impacts associated with the construction of these structures.

The operation of multiple reservoir systems for sometimes conflicting purposes can be a complex process because of the involvement of a large number of decision variables and constraints. Dynamic programming (DP) has long been recognised as a powerful approach in the analysis of water resource systems. The usefulness of DP for multi-reservoir systems is, however, limited by the huge demand that it can induce on computational resources. Many forms of DP have been developed to alleviate the problem of dimensionality with varying degrees of success but no general algorithm exists. This thesis describes the development and application of Genetic Algorithms (GA) for the optimisation of multi-reservoir systems. The GA approach is validated through applications to a number of problems with known solutions. Several alternative formulations of a GA for reservoir systems are evaluated using the four-reservoir problem. This has been done with a view to presenting fundamental guidelines for implementation of the approach to practical problems. Alternative representation, selection, crossover, and mutation schemes are considered. The most promising GA approach comprises real-value coding, tournament selection, uniform crossover, and modified uniform mutation. A non-linear four-reservoir problem was also solved, along with a problem with extended time horizons. A more complex ten-reservoir problem was also successfully solved. The practicality of the developed GA approach in the determination of optimal reservoir operating rules is considered through application to a reservoir system in Indonesia. Optimal operating rules have been derived for the existing development situation in the basin, and also for two future water resource development scenarios using the critical period hydrology. A comparison of the GA results with those produced by Discrete Differential DP is also presented. The application of GA approach to real time operations with stochastically generated inflows is also demonstrated for a Lake system in Uganda. A methodology for forecasting reliable power that can be produced over different durations of time has also been developed using a GA. For the problems considered in this study, the GA solutions are very close to the optimum. The results demonstrate that the approach is robust and is easily applied to complex systems. It has potential as an alternative to stochastic DP approaches.

The aim of this research was to assess the treatment efficiencies for concentrated stormwater runoff (gully pot liquor) of experimental vertical-flow constructed wetland filters containing common reed and different aggregates. For two years, six out of twelve filters received inflow water spiked with hydrated nickel and copper nitrate to simulate contaminated primary treated storm runoff. For those six constructed filters, an obvious breakthrough of dissolved nickel was recorded after road salting during the first winter. However, a breakthrough of nickel was not observed since the inflow pH was raised to eight after the first year of operation. During the second year, reduction efficiencies of heavy metals, five-day biochemical oxygen demand (BOD) and suspended solids (SS) improved considerably. Concentrations of BOD were frequently <20 mg/l, an international threshold for secondary wastewater treatment. This is likely due to biomass maturation and the increase of pH. Machine learning techniques such as K-nearest neighbours, support vector machine and self-organizing map were applied to predict BOD and SS, and to demonstrate an alternative method of analyzing water quality performance indicators. The results suggest that BOD and SS can be efficiently estimated by applying machine learning tools with cost-effective input variables such as redox potential and conductivity, which can be monitored in real time. Their performances are encouraging and support the potential for future use of these models as management tools for the day-to-day process control of constructed wetlands and other ‘black box’ systems.

Acid tars are waste residues of obsolete benzole refining, oil re-refining and white oil production processes. They are black, acidic, viscous semi-liquids comprising an extremely complex mixture of water, sulfuric acid and a large range of organic compounds. Acid tars were often dumped into excavations and existing holes in the ground together with various co-disposed materials without any treatment or engineered lining system leaving a legacy of acid tar lagoons. Acid tars may pose potential risks to human health and the environment because of their acidity, volatiles and other hazardous components. The major contamination pathways of acid tar lagoons are considered to be direct contact, gas emission, bulk tar migration offsite, and surface and ground water contamination. The leaching, weathering and migration behaviours of acid tars were investigated by carrying out a series of batch, cascade and flow cell tests. The results demonstrated that acid tars are capable of leaching Significant levels of contaminants if disturbed, while the leaching level is Significantly lower under simulated groundwater flow in a model soil. The time scale to leaching stabilization was of the order of months in the model soil and is expected to significantly exceed that in the natural environment. To support this work a nubmber of analytical methods for determining physical and chemical properties of acid tars had to be adapted from standard techniques. These modified techniques are described in detail together with recommendations for data integration and correlation of all analyses to form a better understanding of acid tars and their potential environmental impact. The overall findings of the research were integrated to generate a conceptual model of acid tar lagoon processes to assist in assessment. Monitored Natural Attenuation was evaluated and is considered to be a potentially viable approach to the environmental management of some acid tar lagoons.

It is well known that turbulence can be used as a measure of the effectiveness of promoting flocculation, an extensively used and most important method of water treatment. Although the overall turbulence should be the integration of the turbulence intensity at each individual point in the flocculator rather than an average velocity gradient, the average velocity gradient has generally been employed as the turbulence parameter in assessing flocculation efficiency and designing the flocculation process as it can be evaluated relatively simply. With the use of Computational Fluid Dynamics (CFD), this study was able to provide the value of turbulence at any point in a channel flocculator. Comparisons between the model simulation and the experimental results obtained from Laser Doppler Anemometry (LDA) show that the model can reproduce the main features of flow in flocculators. The relationships between turbulence and velocity and the nominal velocity and the number of channels in a hydraulic flocculator, as found in this study, could substantially save the lead time and the costs of new flocculator designs. The effect of the geometry of the flocculator on flocculation efficiency was also studied. A modified Argaman's equation (1968) is proposed to calculate the flocculation in relation to turbulence in an accurate and easy way based on the relationships mentioned above. Aggregation and breakup constants during flocculation were determined by experiments. Flocculation and settling performance under various flow rates, initial concentrations, retention times, coagulants, flocculator geometry and arrangements of settling were also investigated in the laboratory and the flocculation experimental results were used to verify the corresponding modelling. The flocculation efficiency in terms of not only turbidity removal but also floc characteristics was investigated by means of video imaging techniques.

An optimisation approach based on Genetic Algorithms (GAs) is developed for real time allocation of irrigation water supplies. Appropriate objective functions for the water allocation problem have been derived previously and solved using quadratic programming (QP). There had been concerns that the QP approach may become computationally bounded for large systems. It was also thought that the approach would be difficult to apply to water scheduling problems. This research describes work on the development of a GA for the water allocation problem. Although GAs have been actively researched for 30 years, only one previous application to an irrigation problem has been found in the literature. The GA approach is very flexible, and is easily set up for a wide range of linear and non-linear objective functions. In developing the GA solver the intention was to have a generic code easily adapted and used. This has been achieved and the same core routine are used for a wide range of problems. Applied to the water allocation problem, the GA approach can provide solutions that are similar to those produced by QP. It is, however, sensitive to string length, and has difficulty in meeting nodal water balance constraints. It is concluded that the GA approach offers no advantage over QP for the water allocation problem. Further development of a Genetic Algorithm (GA) to solve an irrigation water scheduling problem is described. The objective is to optimise the utilisation of water resources during water stress periods in irrigation systems operating on a rotational basis. Objective functions for the water scheduling problem are developed. Solutions are presented using a GA, and the advantages and shortcomings of different approaches are discussed. The objective is to minimise the irrigation water supply to the system when adequate supplies exist, and to distribute crop stress in an equitable manner in periods of water shortage. It was demonstrated that a formulation called the "Zero-1" approach was most effective in solving the problem, performing significantly better than traditional systems, and more recent scheduling developments. A number of practical applications are presented that demonstrate the effectiveness of the GA approach.

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