The city of Melbourne in Victoria, Australia has been recognised as having high quality drinking water, but like other urban cities in the world, its growing population means increasing water demand. Melbourne is also already on its eight year of dry climatic conditions and is currently experiencing a drought that forced water authorities to impose water restrictions after 20 years of unrestricted supply. The current drought, dwindling supplies and possible impact of climate change highlight the importance of making better use of this precious resource. The Water Resources Strategy has been developed for Melbourne, which serve as the basis for the Victorian Government to set per capita consumption reduction targets of 15%, 25% and 30% by 2010, 2015 and 2020 respectively. The strategy was developed to ensure a continuation of a safe, reliable and cost effective water supply that is environmentally sustainable in the long term. This is in recognition that population growth and water consumption will eventually require additional supplies of water (Water Resources Strategy Committee for the Melbourne Area 2002). One of the key findings of the National Land and Water Resources Audit's Australian Water Resources Assessment 2000 is the lack of detailed knowledge about the end use (Australian Water Association 2001). The

The water soft path (WSP) has been formulated as a progressive paradigm in water management. The WSP has four main principles: water should be viewed as a service; ecological sustainability is of utmost importance; water quantity and quality should be conserved; and planning should be done from the future backwards, not projected from the present. It may be possible to use conservation-based water pricing programs, especially at the residential level, in order to incrementally implement the WSP. Moreover, the implementation of residential seasonal water rates has been suggested as a method to curb peak demand in municipal water systems, thereby deferring infrastructure expansion. The purpose of this thesis is to answer the question: what are the barriers to implementing residential seasonal water rates in the Region of Waterloo? This question is addressed using a variety of data sources, with the majority of the information coming from academic and non-academic literature, and from interviews with water professionals and local councillors. The results provide a descriptive case study concerning the barriers to implementing seasonal water rates in one particular region of southwestern Ontario, but the conclusions can be generalized to describe some of the barriers to the implementation of seasonal water rates in Ontario. Results suggest that some barriers are more severe than others, and that the more serious ones may be addressed by: expounding the potential for seasonal water rates to curb peak demand; carefully designing a rate study to be administered with non-price programs; and implementing the designed rate structure as a pilot study. It is suggested that the implementation of seasonal water rates can be used as an incremental step towards the adoption of WSP principles, but not without first envisioning a desirable future.

The water soft path (WSP) has been formulated as a progressive paradigm in water management. The WSP has four main principles: water should be viewed as a service; ecological sustainability is of utmost importance; water quantity and quality should be conserved; and planning should be done from the future backwards, not projected from the present. It may be possible to use conservation-based water pricing programs, especially at the residential level, in order to incrementally implement the WSP. Moreover, the implementation of residential seasonal water rates has been suggested as a method to curb peak demand in municipal water systems, thereby deferring infrastructure expansion. The purpose of this thesis is to answer the question: what are the barriers to implementing residential seasonal water rates in the Region of Waterloo? This question is addressed using a variety of data sources, with the majority of the information coming from academic and non-academic literature, and from interviews with water professionals and local councillors. The results provide a descriptive case study concerning the barriers to implementing seasonal water rates in one particular region of southwestern Ontario, but the conclusions can be generalized to describe some of the barriers to the implementation of seasonal water rates in Ontario. Results suggest that some barriers are more severe than others, and that the more serious ones may be addressed by: expounding the potential for seasonal water rates to curb peak demand; carefully designing a rate study to be administered with non-price programs; and implementing the designed rate structure as a pilot study. It is suggested that the implementation of seasonal water rates can be used as an incremental step towards the adoption of WSP principles, but not without first envisioning a desirable future.

This study utilized (a) actual measured agricultural water use along with (b) geostatistical techniques, (c) crop simulation models, and (d) general circulation models (GCMs) to assess irrigation demand and the uncertainty associated with demand projections at spatial scales relevant to water resources management. In the first part of the study, crop production systems in Southwest Georgia are characterized and the crop simulation model error that may be associated with aggregated model inputs is estimated for multiple spatial scales. In the second portion of this study, a methodology is presented for characterizing regional irrigation strategies in the Lower Flint River basin and estimating regional water demand. Regional irrigation strategies are shown to be well represented with the moisture stress threshold (MST) algorithm, metered annual agricultural water use, and crop management data. Crop coefficient approaches applied at the regional scale to estimate agricultural water demand are shown to lack the interannual variability observed with this novel approach. In the third portion of this study, projections of regional agricultural demand under climate change in the Lower Flint River basin are presented. GCMs indicate a range of possible futures that include the possibility of relatively small changes in irrigation demand in the Lower Flint River basin. However, most of the GCMs utilized in this work project significant increases in median water demand towards the end of this century. In particular, results suggest that peak agricultural water demands in July and August may increase significantly. Overall, crop simulation models are shown to be useful tools for representing the intra-annual and interannual variability of regional irrigation demand. The novel approach developed may be applied to other locations in the world as agricultural water metering programs become more common.

Two broad surveys of community- level water consumption and pricing behavior are used to answer questions about water demand in a more flexible and dynamic context than is provided in the literature. Central themes of price representation, aggregation, and dynamic adjustment tie together three econometric demand analyses. The centerpiece of each analysis is an exogenous weighted price representation. A model in first-differences is estimated by ordinary least squares using data from a personally-conducted survey of Texas urban water suppliers. Annual price elasticity is found to vary with weather and income, with a value of -0.127 at the data mean. The dynamic model becomes a periodic error correction model when the residuals of 12 static monthly models are inserted into the difference model. Distinct residential, commercial, and industrial variables and historical climatic conditions are added to the integrated model, using new national data. Quantity demanded is found to be periodically integrated with a common stochastic root. Because of this, the structural monthly models must be cointegrated to be consistent, which they appear to be. The error correction coefficient is estimated at -0.187. Demand is found to be seasonal and slow to adjust to shocks, with little or no adjustment in a single year and 90% adjustment taking a decade or more. Residential and commercial demand parameters are found to be indistinguishable. The sources of price endogeneity and historical fixes are reviewed. Ideal properties of a weighted price index are identified. For schedules containing exactly two rates, weighting is equivalent to a distribution function in consumption. This property is exploited to derive empirical weights from the national data, using values from a nonparametric generalization of the structural demand model and a nonparametric cumulative density function. The result is a generalization of the price difference metric to a weighted level-price index. The validity of a uniform weighting is not rejected. The weighted price index is data intensive, but the payoff is increased depth and precision for the economist and accessibility for the practitioner.

This thesis describes a short term water demand forecasting application that is based upon a combination of a neural network forecast generator and a rule based system that modifies the resulting forecasts. Conventionally, short term forecasting of both water consumption and electrical load demand has been based upon mathematical models that aim to either extract the mathematical properties displayed by a time series of historical data, or represent the causal relationships between the level of demand and the key factors that determine that demand. These conventional approaches have been able to achieve acceptable levels of prediction accuracy for those days where distorting, non cyclic influences are not present to a significant degree. However, when such distortions are present, then the resultant decrease in prediction accuracy has a detrimental effect upon the controlling systems that are attempting to optimise the operation of the water or electricity supply network. The abnormal, non cyclic factors can be divided into those which are related to changes in the supply network itself, those that are related to particular dates or times of the year and those which are related to the prevailing meteorological conditions. If a prediction system is to provide consistently accurate forecasts then it has to be able to incorporate the effects of each of the factor types outlined above. The prediction system proposed in this thesis achieves this by the use of a neural network that by the application of appropriately classified example sets, can track the varying relationship between the level of demand and key meteorological variables. The influence of supply network changes and calendar related events are accounted for by the use of a rule base of prediction adjusting rules that are built up with reference to past occurrences of similar events. The resulting system is capable of eliminating a significant proportion of the large prediction errors that can lead to non optimal supply network operation.

Magister Scientiae - MSc / The Western Cape, a province of South Africa is facing increased pressure to develop new supplies of fresh water to cater for the regions rapidly growing demand. Groundwater is being explored as a possible contributor to the freshwater supply. Development of the resource has been slow despite the existence of significant potential groundwater resources in the form of several shallow primary aquifer systems and an extensive secondary aquifer formation known as the Table Mountain Group (TMG) Aquifer. This slow development may be attributed primarily to a lack of awareness amongst key stakeholders and general ignorance in the water market with regards to the potential of this resource.

Master of Science / Department of Agricultural Economics / Jeffrey M. Peterson / Understanding irrigation water demand is vital to policy decisions concerning water scarcity. This thesis evaluates irrigation water-use responses to changes in prices, while accounting for cross-sectional characteristics of irrigators’ resource settings. An irrigator’s profit-maximizing decision is modeled in two stages. In the first stage, he decides which crop to plant, and in the second stage he decides how much water to apply given the crop choice. This thesis employs an econometric modeling technique not previously used in the irrigation water demand literature, a multinomial logit selectivity model. This econometric technique allows the intensive (change in water use for each crop in the short run) and extensive (change in water use in the long run due to changes in crop-choice) margin effects to be computed in a simultaneous equation system. A multinomial logit selectivity model has applications to many resource issues in production agriculture where the two-stage decision process is common. The model is estimated from field-level data on water use and crop-choice for a 25-county region in western Kansas over the period 1991-2004. Water use was found to be highly inelastic to the price of natural gas, but becomes more elastic as the price increases. The intensive margin effect was significant for natural gas price. The extensive margin effect only comprised half the total effect under high natural gas prices and was negligible for low prices. However, the extensive margin effect under high natural gas prices declined over time due to more efficient irrigation systems and improved crop varieties. The intensive margin effect explained most of the water use response from changes in other variables, including corn price. An increase in corn price has a negligible extensive margin effect because corn is most often substituted with alfalfa, which has a similar water requirement. Inelastic demand implies that policies aiming to conserve the Ogallala Aquifer by increasing the price of water will not accomplish their purpose and will affect irrigators’ incomes. More effective policies would be voluntary or mandatory quantity restrictions. However, efficient restrictions would need to account for spatial variation in the rate of depletion and the remaining saturated thickness.

The main objective of this study is to analyze the demand for water in Denton. The data used for the study are obtained from the City of Denton Utilities Department, the Tax Appraisal District and government documents. The 121 households which have perfect ten years historical data of water consumption were selected to be the representatives of all households in Denton. The study reveals that the change in water consumption significantly relates to the change in marginal price. Furthermore, the weather variables also have strong effects on the water consumption, especially during summer. The coefficients of income and a "difference" variable are found to have the opposite sign but are not equal in magnitude. In fact, they should be equal in magnitude, but opposite in sign. While the estimated coefficients on all independent variables were highly significant statistically, the resulting coefficient on the house size variable was statistically insignificant in the model test. The results show that the difference variable is required in the model. It also had some effect on the water consumption. It is found that there is a small change in water consumption when the lot size is increased.

Yes / Simultaneous optimisation of design and operating parameters of MSF desalination process is considered here using MINLP technique within gPROMS software. For a fixed fresh water demand throughout the year and with seasonal variation of seawater temperature, the external heat input (a measure of operating cost) to the process is minimised. It is observed that seasonal variation in seawater temperature results in significant variation in design with minimum variation in operating conditions in terms of process temperatures. The results also reveal the possibility of designing stand-alone flash stages which would offer flexible scheduling in terms of the connection of various units (to build up the process) and efficient maintenance of the units throughout the year as the weather condition changes. In addition, operation at low temperatures throughout the year will reduce design and operating costs in terms of low temperature materials of construction and reduced amount of antiscaling and anti-corrosion agents.