Physically decentralised water management systems may contribute to improving the sustainability of urban water management. Any shift toward decentralised systems needs to consider not just physical system design but also social values, knowledge frames, and organisations, and their interconnections to the physical technology. Four cases of recent Australian urban water management improvement projects were researched using qualitative methods. Three cases were of decentralised water management innovation. The other was of a centralised system, although decentralised options had been considered. These cases were studied to identify institutional barriers and enablers for the uptake of decentralised systems, and to better understand how emerging environmental engineering knowledge might be applied to overcome an implementation gap for decentralised urban water technologies. Analysis of each case focused on the institutional elements of urban water management, namely: the values, knowledge frames and organisational structures. These elements were identified through in-depth interviews, document review, and an on-line survey. The alignment of these elements was identified as being a significant contributor to the stability of centralised systems, or to change toward decentralised systems. A new organisational home for innovative knowledge was found to be common to each case where decentralised innovation occurred. ??Institutional entrepreneurs??, strong stakeholder engagement, and inter-organisational networks were all found to be linked to the creation of shared meaning and legitimacy for organisational and technological change. Existing planning frameworks focus on expert justification for change rather than institutional support for change. Institutional factors include shared understandings, values and organisational frameworks, and the alignment of each factor. Principles for, and examples of, appropriate organisational design for enabling and managing decentralised technological innovation for urban water management are proposed. This research contributes to the understanding of the institutional basis and dynamics of urban water management, particularly in relation to physical centralisation and decentralisation of urban water management technologies and, to a lesser extent, in relation to user involvement in urban water management. Understanding of factors that contribute to enabling and constraining decentralised technologies is extended to include institutional and organisational factors. New and practical pathways for change for the implementation of decentralised urban water systems are provided.

Historical water quality databases from two South Australian drinking water reservoirs were used, in conjunction with various computational modelling methods for the ordination, clustering and forecasting of complex ecological data. Techniques used throughout the study were: Kohonen artificial neural networks (KANN) for data categorisation and the discovery of patterns and relationships, recurrent supervised artificial neural networks (RANN) for knowledge discovery and forecasting of algal dynamics and hybrid evolutionary algorithms (HEA) for rule-set discovery and optimisation for forecasting algal dynamics. These methods were combined to provide an integrated approach to the analysis of algal populations including interactions within the algal community and with other water quality factors, which results in improved understanding and forecasting of algal dynamics. The project initially focussed on KANN for the patternising and classification of the historical data to reveal links between the physical, chemical and biological components of the reservoirs. This offered some understanding of the system and relationships being considered for the construction of the forecasting models. Specific investigations were performed to examine past conditions and the impacts of different management regimes, as well as to discover sets of conditions that correspond with specific algal functional groups. RANN was then used to build models for forecasting both Chl-a and the main nuisance species, Anabaena, up to 7 days in advance. This method also provided sensitivity analyses to demonstrate the relationship between input and output variables by plotting the reaction of the output to variations in the inputs. Initially one year from the data set was selected for the testing of a model, as per the split-sample technique. To further test the models, it was later decided to select several years for testing to ensure the models were useful under changed conditions, and that test results were not misleading regarding the models true capabilities. RANN were firstly used to create reservoir specific or ad-hoc models. Later, the models were trained with the merged data sets of both reservoirs to create one model that could be applied to either reservoir. Another method of forecasting was trialled and compared to RANN. HEA was found to be equal or superior to RANN in predictive power, also allowed sensitivity analysis and provided an explicit, portable rule set. The HEA rule sets were initially tested on selected years of data, however to fully demonstrate the models potential, a process for k-fold cross-validation was developed to test the rule-set on all years of data. To further extend the applicability of the HEA rule-set; the idea of rule-based agents for specific lake ecosystem categories was examined. The generality of a rule-based agent means that, after successful validation on several lakes from one category, the agent could then be applied to other water bodies from within that category that had not been involved in the training process. The ultimate test of the rule-based agent for the warm monomictic and eutrophic lake ecosystem category was to be applied to a real-time monitoring and forecasting situation. The agent was fed with online, real-time data from a reservoir that belonged to the same ecosystem category but was not used in the training process. These preliminary experiments showed promising results. It can be concluded that the concept of rulebased agents will facilitate real-time forecasting of algal blooms in drinking water reservoirs provided on-line monitoring of relevant variables has been implemented. Contributions of this research include: (1) to offer insight into the capabilities of 3 kinds of computational modelling techniques applied to complex water quality data, (2) novel applications of KANN including the division of data into separate management periods for comparison of management efficiency, (3) to both qualitatively and quantitatively elucidate relationships between water quality parameters, (4) research toward the development of a forecasting tool for algal abundance 7 days in advance that could be generic for a particular lake ecosystem category and implemented in real-time, and (5) to suggest a thorough testing method for such models (k-fold cross validation). / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1331584 / Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2008

Includes bibliographical references (leaves [268]-285) / xiv, 285, [85] leaves : ill. (some folded), maps (col., folded) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Geographical and Environmental Studies, 2002

The necessity of cost effective, environmentally friendly technology has become increasingly important to remediate persistent organic pollutants in the environment. The emerging greener ultrasound technology has the potential to serve the remediation industry. In this study, the use of low power, high frequency (HF) ultrasound (1.6 MHz, 145 W/L) has been shown to effectively remediate DDT (90% of 8 mg/L) in water and sand slurries. Addition of iron powder accelerated DDT degradation in the sand slurry under ultrasonication. The potential of HF ultrasound (1.6 MHz, 160 W/L) in degradation of the non-volatile, polar model compound methylene blue (MB) was studied in MB spiked demineralised water and wastewater. A 70 % of 0.4 mg/L of MB was degraded in demineralised water whereas only 54% of MB degraded in MB spiked wastewater. There was a decrease in MB degradation rate with an increase in MB concentration. High power, low frequency (LF) ultrasound (20 kHz, 932 W/L) was used to desorb 400 mg/L of DDT added to three different natural soil slurries at 5, 10, 15 and 20 wt. % each. Each soil slurry was prepared in 0.1% v/v SDS surfactant solution, soaked for 30 min. and heated for another 30 min. at 40 oC before sonication. For the neutral pH soil slurry with higher dissolved organic carbon, the desorption efficiency achieved was over 80% in 30 s sonication. Alkaline soil with higher surface area than neutral soil indicated 60% desorption efficiency while the acidic soil, with the highest surface area and a higher amount of non-soluble organic matter, yielded 30% desorption efficiency under similar desorption conditions. Coconut fibre, used to biosorb the desorbed DDT in the decanted solution, was found to have over 25 g/kg of biosorption capacity for DDT. The surfactant SDS and associated DDT were completely separated from decanted liquid of the desorbed slurry with alum using adsorptive micellar flocculation in 60 min. settling. Acidic pH and molar concentration ratio of Al3+/SDS = 0.5 was used to completely remove the DDT. Using 20 kHz, 1125 W/L of sonication in an 80 mL reactor with air saturated 50 mg/L DDT at 20oC, the DDT removal efficiency achieved was 80% in 20 min. With zero valent iron addition, DDT removal efficiency in 15 min. is 100% with 15 and 22 mg/L of initial DDT concentrations. The settled DDT slurrywas remediated using 20 kHz at 240 W/L achieving DDT removal efficiency of 87% in 15 min. Also LF ultrasound was found to be effective in remediating chloroform (8 mg/L in 60 min) from spiked demineralised water and contaminated groundwater in both batch (120 W/L) and flow cell (6000 W/L) modes. Modeling and simulation of the ultrasonic reactor under 20 kHz ultrasonication was performed for various shape reactors using commercially available software. For almost all reactors, the highest ultrasonic intensity was observed near the transducer???s vibrating area. It was found that the highest acoustic pressure distribution, which is critical to the performance of the reactor, occurred in the conical reactor and flow cell configuration. / Thesis (PhD)--University of South Australia, 2010

The quantity of stormwater runoff from the city of Adelaide almost matches the demand for drinking water. It therefore becomes increasingly important as an alternative source for water supply. This research focused at the Parafield Stormwater Harvesting Facility near Adelaide in order to better understand: (1) nutrient dynamics between the water column, sediments and plant community, (2) allochthonous and autochthonous sources of nutrients and (3) nutrient retention capacity of the reed bed. A weekly monitoring programme for the physical and chemical parameters of the water column, sediment and plant community was carried out over three years for specific locations within the reed bed. Ordination and clustering of the time series data revealed distinctive seasonal and spatial nutrient patterns. The concentrations for total nitrogen (TN) showed high concentrations for the summer period (1.04 to 1.86 mg/L) and low concentration for the winter season (0.25 to 0.46 mg/L). For the other nitrogen fractions in form of nitrate (NO₃⁻) and ammonium (NH₄⁺) the seasonal patterns were different to that of TN. In NO₃⁻ the concentrations were high during the summer and winter seasons and NH₄⁺ showed high concentration during the spring. The seasonality for total phosphorus (TP) showed high concentration for the spring period (0.049 to 0.163 mg/L) and low concentration for the other seasons (0.01 to 0.019 mg/L). A similar pattern has been observed for phosphate (PO₄³ ⁻) as well. The dissolved organic carbon (DOC) concentrations showed high concentrations during the summer period (21.36 to 31.64 mg/L) and low concentration during the winter seasons (5.48 to 7.14 mg/L). The seasonal pattern for the nutrient contents of the plant community showed highest concentrations during summer (5.5 to 34.2 gTN/kg) and lowest concentrations in winter (0.2 to 7.7 gTN/kg). Nutrient concentrations in the sediments were highest during the non-growing seasons (autumn and winter). This result indicated that the function of sediments changes seasonally from being a sink during the non-growing season by accumulating both allochthonous and autochthonous nutrients in the rainy season, and becoming a source during the growing seasons due to nutrient release from anaerobic sediments supporting the growth of the macrophyte community. Overall the function of sediment in reed bed pond of the Stormwater Harvesting Facility was to be a source of nutrients and therefore no accumulation of nutrients occurred during the study period. The research has demonstrated that the reed bed currently performs as a reasonable nutrient retention system with following nutrient removal rates: 0.85 mg TN /m²/day, 0.79 mg NO₃⁻ /m²/day, 0.28 mg NH₄⁺/m²/day, 0.05 mg TP /m²/day, 0.04 mg PO₄³ ⁻ /m²/day, and 5.75 mg DOC /m²/day. Seasonal difference in the water retention time showed that the for most of the nutrients the removal performance was most effective during autumn and winter with the exception of the removal performance of P forms, which most effective during spring and summer. For TN, NO₃⁻ and DOC the RE was most efficient at a residence time > 15days, for TP and PO₄³ ⁻ it is 5-10 days and for NH₄⁺ it is <;5days. Time–series modelling of the monitoring data resulted in rule-based prediction models for the different nutrients. Sensitivity analyses of the models revealed key driving variables for the nutrient dynamics of the reed bed. The prediction results revealed that the DO was the key driving variable influencing the nutrient concentrations in the water column and therefore to improve the water quality of the treatment water DO levels have to maintained above the threshold of 4 mg/L. Beside DO other key driving variables were turbidity, ORP and the nutrient levels from the previous site. Therefore the control of these parameters would be the start to develop a management plan for best-practice management in terms of water quality at the Parafield Stormwater Harvesting Facility. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1458926 / Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Science, 2010

University of Macau / Faculty of Law

Nutrient limitation in aquatic ecosystems results from a deficiency in nitrogen or phosphorus levels relative to cellular growth needs. Nutrient limitation of freshwater systems is a function of biotic and abiotic factors. Biotic factors include vascular and nonvascular plant community composition. Abiotic factors include underlying bedrock and land-use activities (e.g. agriculture, septic systems). Nutrient availability directly affects growth, productivity, and community structure of primary producers. The purpose of this study was two-fold: (1) to assess the relationship between ambient algal biomass. and in-stream nutrient levels along the longitudinal course of a river through a transition from weak to well-developed underlying karst bedrock, and (2) experimentally assess if periphyton was nitrogen or phosphorous limited between weak and well-developed karst sites. Sestonic and filamentous biomass (= chlorophyll-a) levels increased monthly along the longitudinal gradient. In contrast, periphyton biomass levels increased minimally monthly and displayed no longitudinal pattern. Nitrate and soluble reactive phosphorus levels exhibited distinct longitudinal increases, whereas total phosphorous displayed minimal change and ammonia levels decreased in the downstream direction. Total nitrogen (TN) levels increased upstream but decreased sharply in the well-developed downstream karst sites. The nutrient limitation assays revealed that the highest periphyton levels were with N + P treatments at the most upstream sites. Overall, in Kentucky's Green River algal biomass accrual appears to be mainly P-limited but likely also by TN availability during late summer.

No description available.

Partnerships are a recognized tool for addressing local level environmental problems. They involve knowledge-sharing and decision-making by both local authorities and communities. Two different partnerships developed in Durban's KwaMashu Township with a view to addressing environmental problems associated with a degraded small stream viz, the KwaMashu Development Association (KDA) and the KwaMashu Development Initiative (KDI). This thesis describes a study carried out on these two partnerships, comparing their efficacy in resolving the problems and the factors that contributed to the pollution of the stream. Specific environmental circumstances conducive to the degradation of the stream, as well as measures put in place to address them, were identified during a field survey. Semi-structured questionnaires were then used to interview members of the two partnerships to obtain information on how they developed and functioned as a unit. Information was also obtained from respective individuals, regarding their perception of the factors that contributed to the stream degradation and the effectiveness of their rehabilitation efforts. Although the study found both partnerships to be of the leverage type, there were significant differences between the socio-economic profile and political affiliations of members. The KDA partnership received funding for the project whereas the KDI received no funding, but had a vision. The Keep Durban Beautiful Association created an awareness relating to waste and open space management which was imparted to the KDT members and this enabled them to achieve the goals of the project. These different baselines clearly contributed to the differences in the effectiveness of the partnerships. / Thesis (M.Sc.)-University of Natal, Durban, 2002.

The past few decades have seen, amongst other topical environmental issues, increased concerns regarding the imminent threat of global warming and the consequential impacts of climate change on environmental, social and economic systems. Numerous groundbreaking studies conducted independently and cooperatively have provided abundant and conclusive evidence that global climates are changing and that these changes will almost certainly impact natural and socio-economic systems. Increased global change pressures, which include, inter alia, climate change, have increased concerns over the supply of adequate quality freshwater. There is an inadequate body of knowledge pertaining to linking basic hydrological processes which drive water quality (WQ) variability with projected climate change. Incorporating such research into policy development and governance with the intention of developing adaptive WQ management strategies is also overlooked. Thus, the aim of this study was the assessment of projected climate change impacts on selected WQ constituents in the context of agricultural non-point source pollution and the development of the necessary adaptation strategies that can be incorporated into WQ management, policy development and governance. This assessment was carried out in the form of a case study in the Mkabela Catchment near Wartburg in KwaZulu-Natal, South Africa. The research involved applying climate change projections derived from seven downscaled Global Circulation Models (GCMs) used in the Fourth Intergovernmental Panel on Climate Change (IPCC) Assessment Report, in the ACRU-NPS water quality model to assess the potential impacts on selected water quality constituents (viz. sediment, nitrogen and phosphorus). Results indicated positive correlations between WQ related impacts and contaminant migration as generated from agricultural fertilizer applications. ACRU-NPS simulations indicated increases in runoff and associated changes in WQ variable generation and migration from upstream sources in response to downscaled GCM projections. However, there was limited agreement found between the simulations derived from the various downscaled GCM projections in regard to the magnitude and direction (i.e. percent changes between present and the future) of these changes in WQ variables. The rainfall distribution analyses conducted on a daily time-step resolution for each selected GCM also showed limited consistency between the GCM projections regarding rainfall changes between the present and the future. The implication was that since hydrological and climate change modelling can inform adaptation under climate change. However, adaptation to climate change in water quality management and policy development is going to require approaches that fully recognise the uncertainties presented by climate change and the associated modelling thereof. It was also considered crucial that equal attention be given to both climate change and natural variability, in order to ensure that adaptation strategies remain robust and effective under conditions of climate change and its respective uncertainties. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.