Water Demand Management

The purpose of this study was to explore the predominant determinants of shower end use consumption and to find an overarching research design for building a residential water end use demand forecasting model using aligned socio-demographic and natural science data sets collected from 200 households fitted with smart water meters in South-east Queensland, Australia. ANOVA as well as multiple regression analysis statistical techniques were utilised to reveal the determinants (e.g. household makeup, shower fixture efficiency, income, education, etc.) of household shower consumption. Results of a series of one-way independent ANOVA extended into linear multiple regression models revealed that females, children in general and teenagers in particular, and the showerhead efficiency level were statistically significant determinants of shower end use consumption. Eight-way independent factorial ANOVA extended into a three-tier hierarchical linear multiple regression model, was used to create a shower end use forecasting model, and indicated that household size and makeup, as well as the showerhead efficiency rating, are the most significant predictors of shower usage. The generated multiple regression model was deemed reliable, explaining 90.2% of the variation in household shower end use consumption. The paper concludes with a discussion on the significant shower end use determinants and how this statistical approach will be followed to predict other residential end uses, and overall household consumption. Moreover, the implications of the research to urban water conservation strategies and policy design, is discussed, along with future research directions.

With growing demand and highly variable inter-annual water supplies, California's water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as " lowest of the low " and " highest of the high " anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm 3) in the lowest of the low scenario and decreased 0.8 Bm 3 in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm 3), high agricultural expansion (+4.6 Bm 3), and high urbanization (+2.1 Bm 3) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories.

Groundwater potential mapping and its sustainable development are an important aspect in Leh valley due to an increase of tourists and the local population. In the present study, the groundwater potential zones were delineated by adopting a frequency ratio (FR) model. Land use and land cover, hydro geomorphology, slope, geology, lineament density, drainage density, spring well locations and ground water level were the thematic factors considered for groundwater potential zone mapping. There are 86 spring wells located in the study area, of which 60 wells were considered for success rate and remaining 26 wells considered for prediction rate in the FR model. The final groundwater potential map was classified into five zones as very high, high, moderate, low, and very low. The success and prediction rates of FR model were measured as 81.25% and 77.23% respectively. Water budget of the valley was also calculated on the basis of consumption, demand and supply of water by taking account of the floating population. There is a huge demand of water supply requirement during the tourist season from May to September months and deficiency of water in the area was calculated as 4,224,557 (in l). Finally, suitable sites for artificial recharge for sustainable groundwater management were identified. The sites were selected on the basis of depth of groundwater level, source of spring well locations and gradient from natural spring to selected recharge wells.

The beliefs underlying the water supply-management, demand-management, and soft-path paradigms are examined. Two questions are considered. First, can social psychology’s insights on mortality salience help explain the desire to control water and the dominant water supply-management paradigm? Second, can those insights also help explain the limited progress of demand management and water soft paths? We propose that mortality salience helps explain why individuals and societies seek to control water supply and, by extension, deny their connection to nature and limit consciousness of physical vulnerability. We briefly consider the implications of this perspective for water research, advocacy and policy.

Water is now considered a scarce but essential resource, which should be managed in an integrated manner. The traditional approaches of resource development are now considered as unsustainable. Water demand management (WDM), the new approach, aims at influencing demand, thus improving distribution efficiency. Leakage control and pressure management are some of the WDM strategies.

This paper presents a computational framework performing, in two stages: urban water demand pattern characterization through
time series clustering and reliable hourly water demand forecasting for the entire day based on Support Vector Machine (SVM)
regression. An SVM regression model is trained for each cluster identified and for each hour of the day, taking the hourly water
demand data acquired at the very first m hours of the day. The approach has been validated on a real case study that is the urban
water demand of the Water Distribution Network (WDN) in Milan, managed by Metropolitana Milanese, one of the partner of the
EU-FP7-ICT ICeWater project.

Water Demand management has received much emphasis from development agencies in the last decade. The concept stemmed from a growing awareness of the externalities of large scale water resources development and of an assumed state of wastage in the use of water by many sectors, notably agriculture. The paper examines critically the scope for saving water in water short basins. It argues that because of the closing/closed nature of such basins, the gains that can be achieved through demand management have been much overestimated. It shows that demand management interventions result in some users being able to increase their water use to the detriment of downstream users and that most interventions result in spatial shifts of water use rather than savings. Water pricing is often proposed as a way to curb water use but its introduction in irrigated agriculture is shown to be problematic. The economic argument for re-allocation to higher value uses is distinct from the discussion of water savings in this paper and is not considered in any detail. The paper also suggests that supply management remains indeed the most effective way to reduce water use, and that in many cases supply augmentation cannot be avoided.

Increasing draught seasons and lack of access to potable water reserves have been the major risks threatening water authorities and governments over the recent years. Therefore, long term water forecasts are receiving much more attention nowadays. Unlike the conventional projection of historical water demand, researchers have tried to implement sophisticated mathematical models to predict demand of water. Gene expression programming (GEP), as a relatively new forecasting technique, remains to be explored in this endeavor. The main purpose of this research was to assess the performance of GEP models using wavelet decomposition with 2 transfer functions (db2 and haar) and 3 levels. Results of this study showed GEP models can be highly sensitive to wavelet decomposition if all combinations of proper lag times are used as inputs feeding these models.

Given the increasing trend in water scarcity, which threatens a number of regions worldwide, governments and water distribution system (WDS) operators have sought accurate methods of estimating water demands. While investigators have proposed stochastic and deterministic techniques to model water demands in urban WDS, the performance of soft computing techniques [e.g., Genetic Expression Programming (GEP)] and machine learning methods [e.g., Support Vector Machines (SVM)] in this endeavour remains to be evaluated. The present study proposed a new rationale and a novel technique in forecasting water demand. Phase space reconstruction was used to feed the determinants of water demand with proper lag times, followed by development of GEP and SVM models. The relative accuracy of the three best models was evaluated on the basis of performance indices: coefficient of determination (R 2 ), mean absolute error (MAE), root mean square of error (RMSE), and Nash-Sutcliff coefficient (E). Results showed GEP models were highly sensitive to data classification, genetic operators, and optimum lag time. The SVM model that implemented a Polynomial kernel function slightly outperformed the GEP models. This study showed how phase space reconstruction could potentially improve water demand forecasts using soft computing techniques.

This Guide lays out a way to undertake urban water planning, using a consistent framework, which creates benefits for the whole community. It was originally developed by the Institute for Sustainable Futures (ISF) at the University of Technology Sydney for the Water Services Association of Australia (WSAA) and has been updated with the support of the Australian Government’s National Water Commission (NWC). The Guide is intended for both WSAA members and the broader Australian water industry.

Integrated Resource Planning (IRP) is the foundation of the Guide. Internationally, IRP is considered a best practice planning framework for urban water. It has been used to varying extents by water utilities, councils and water resource managers across Australia since the early 1990s. In several Australian jurisdictions, IRP is embedded as a policy and/or regulatory requirement.

IRP considers both demand and supply-side options and treats them equally when determining how to close the supply–demand gap. The Australian water industry is now experiencing a growing need to better understand the demand for water. Specifically, practitioners need new skills in detailed demand forecasting and how to develop, implement and evaluate demand management options. In response to this, the Guide presents introductory material on these subjects within the context of an overall IRP process.

Full text available: http://www.water-alternatives.org/index.php/alldoc/articles/vol11/v11issue3/472-a11-3-25/file

Reimagining spaces of innovation for water efficiency and demand management: An exploration of professional practices in the English water sector. Water Alternatives 11(3): 957-978 Hoolohan and Browne: An exploration of professional practices in the English water sector ABSTRACT: Social practice theories have established an important counter narrative to conventional accounts of demand. The core argument of this body of research is that, having focused on informing and incentivising behavioural change, demand management has largely neglected the social and material dimensions of everyday action that shape how and why resources are used. Despite making a compelling case for reframing demand management, there is limited evidence of practice-based approaches having gained a foothold in policy and business practices. This raises important questions regarding how and why certain modes of intervention are pursued at the expense of others and, more broadly, the factors that shape the pace and direction of innovation in demand management. In this paper we turn a practice-lens towards the professional practices of demand management. Using mixed methods, we demonstrate how specific modes of intervention emerge as priorities within a social, political, semiotic and material landscape of professional practice. Our empirical analysis highlights four particular contingencies of demand management that constrain the scope of interventions pursued. These are industry expectations and ideals; modes of collaboration; processes of evidencing action; and hydrosocial disturbances. We discuss the implications of these findings, making suggestions as to how innovation in the practices of demand management might be facilitated, and the role of academic research in this process.

The forecasting of future value of water consumption in an urban area is highly complex and nonlinear. It often exhibits a high degree of spatial and temporal variability. It is a crucial factor for long-term sustainable management and improvement of the operation of urban water allocation system. This chapter will study the application of two preprocessing phase space reconstruction (PSR) and wavelet decomposition transform (WDT) methods to investigate the behavior of time series to forecast short-term water demand value of Kelowna City (BC, Canada). The research proposes two pre-process technique to improve the accuracy of the models. Artificial neural networks (ANNs), gene expression programming (GEP) and multi linear regression (MLR) methods are the tools that considered for forecasting the demand values. Evaluation of the tools is based on two steps with and without applying the pre-processing methods. Moreover, auto correlation function (ACF) is used to calculate the lag time. Correlation dimension is used to study the chaotic behavior of the dataset. The models’ relative performance is compared using three different fitness indexes; coefficient of determination (CD), root mean square error (RMSE)
and mean absolute error (MAE). The results showed how pre-processing combination of WDT and PSR improved the performance of the models in forecasting short-term demand values.

Evaluation of supply chain of water consumption contributes toward reducing water scarcity, as it allows for increased water productivity in the agricultural sector. Water Footprint (WF) is a powerful tool for water management; it accounts for the volume of water consumption at high spatial and temporal resolution. The objective of this research is to investigate the water footprint trend of crop production in Tehran from 2008 to 2015 and to assess blue water scarcity in the agricultural sector. Water consumption of crop production was evaluated based on the WF method. Evapotranspiration was evaluated by applying the CROPWAT model. Blue water scarcity was evaluated using the blue water footprint-to-blue water availability formula. The results demonstrate that pistachio, cotton, walnut, almond, and wheat have a large WF, amounting to 11.111 m 3 /kg, 4,703 m 3 /kg, 3,932 m 3 /kg, 3,217 m 3 /kg, and 1.817 m 3 /kg, respectively. Agricultural blue water scarcity amounted to 0.6 (severe water stress class) (2015-2016). Agricultural water consumption in Tehran is unsustainable since it contributes to severe blue water scarcity. Tehran should reduce agricultural water scarcity by reducing the water footprint of the agricultural sector.

Water demand forecasting is a nonlinear and non-stationary process. Different variables affect the value of demand directly or indirectly. These variables have non-stationary behavior relates to the demand time series, which should be considered in forecasting of water demand. Thus, in the first stage, chaotic behavior of water demand data was investigated to determine the number of effective variables by the value of correlation exponent. Then, the nonlinear process of water demand was forecasted by nonlinear local approximation (NLA) method using reconstructed phase space of input variables. Next, to improve the accuracy of the method, selected embedding dimension of input variables was decomposed by wavelet transformers. The application of phase space reconstruction (PSR) and wavelet decomposition were compared with the results of the models without pre-processing to evaluate their application in improving the models' accuracy in forecasting water consumption of Kelowna City (BC, Canada). The results showed that NLA forecasted more accurate than the results in previous literature in the same case study.

A comprehensive understanding of water demand and its availability is essential for decision-makers to manage their resources and understand related risks effectively. Historical data play a crucial role in developing an integrated plan for management of water distribution system. The key is to provide high-resolution temporal-scale of demand data in urban areas. In the literature, many studies on water demand forecasting are available; most of them were focused on monthly-scales. Since monitoring of time series is a prolonged and costly procedure, the popularity of disaggregation methods is a most recent desirable trend. The objective of this research is to transfer low-resolution into high-resolution temporal scale using random cascade disaggregation and non-linear deterministic methods. This study defines a new technique to apply previously proposed random cascade method to disaggregate continuous data of the city of Peachland. The accuracy of the results is more than 90%. It represents a satisfactory application of the models. The proposed approach helps operators to have access to daily demand without acquiring high-resolution temporal scale values. Although the disaggregated values may not be precisely equal with observed values, it offers a practical solution for the low equipped WDS and leads to lesser number of drinking water-related problems.

This research report “Assessment of Future Water Efficiency Measures” has been developed by the Institute for Sustainable Futures (ISF), University of Technology Sydney, on behalf of the three Melbourne retailers, Melbourne Water, Barwon Water and the Department of Environment, Land, Water and Planning. The rapid study does not aim to be exhaustive but to begin to gather information to assist in taking stock of the current efficiency situation and to look on the horizon in terms of how efficiency might change. It aims to gather information that will be useful to assist in testing alternative potential scenarios of long term demand forecasts and new potential short and long term efficiency program opportunities that can be actioned when deemed appropriate into the future. There is significant additional conservation potential available as we look to the future in terms of new more efficient appliances and ways to interact with customers by tapping into new technical and behavioural opportunities.

The rapid study has scanned and collated information on the programs undertaken both in Victoria and interstate, and to a limited extent internationally, together with information on the latest innovations in terms of water efficient appliances, behaviour change and digital metering interfaces. The research draws on recent research conducted by ISF, information provided by the funding agencies, information gleaned from ISF’s international network of advisors, and interviews with water efficiency experts, manufacturers and practitioners.

Les conséquences du séisme du 12 janvier 2010 ont montré la faible maîtrise de l'espace dans l'établissement des habitats et l'implantation des projets territoriaux en Haïti. Dans cet article nous voulons revisiter le rôle de la géographie scolaire pour aider à développer une compréhension dynamique de tels enjeux et élaborer des stratégies d'adaptation efficaces pour réduire la vulnérabilité des biens et des services et finalement pour mieux protéger les individus et les populations à risques.

In view of the water crises historically experienced by Brazil's semi-arid region, it is necessary to search for methodological tools that allow us to propose efficient alternatives for managing water demand. In this regard, the present study developed and applied a hybrid approach of flow network modeling and the Analytic Hierarchy Process (AHP) combined with Shannon's entropy for simulating and prioritizing water demand management alternatives in the Epitácio Pessoa Reservoir in the Brazilian semiarid region. The approach initially performed simulations of the hydro system flow network to explore rational alternatives that evaluated the following criteria: meet the demands of human supply, meet the demands for irrigation, maintain the reservoir above the target volume, and reduce consumption. Subsequently, Shannon's entropy was used to assess the importance of the criteria and the multicriteria analysis of ranking of alternatives was built. Finally, a sensitivity analysis of the model was performed regarding the dependence on respective weights of the criteria. The results made enabled evaluation of the hydro system's water security, highlighting insufficient supply by the single measure of water management transposition of the São Francisco River, and based on the hierarchy of alternatives, suggesting actions to improve the sustainability of water use, such as reuse of water, reduction of losses in supply systems and increasing irrigation efficiency. The proposed hybrid approach permitted the synthesis of the simulation's results, which may simplify and support the decision-making process in water-demand management.

Modelos de previsão de demanda de água podem ser utilizados como ferramentas de gestão e planejamento por agências reguladoras de recursos hídricos, companhias de abastecimento de água e tratamento de esgoto, profissionais da construção civil e gestores prediais. Este estudo teve como objetivo identificar os métodos e analisar os diferentes modelos de previsão de demanda de água em estabelecimentos assistenciais de saúde. Para tanto, foi realizado um levantamento bibliográfico exploratório de pesquisas científicas que apresentaram modelos de previsão de demanda de água em estabelecimentos assistenciais de saúde em diferentes países. Em geral, estudos prévios apresentaram modelos matemáticos baseados em regressão linear bivariada, correlacionando o consumo predial de água de hospitais com o número de leitos, área construída ou número de funcionários separadamente. A maioria dos trabalhos analisados utilizaram testes estatísticos para verificar se as amostras eram normalmente distribuídas e apresentavam homogeneidade das variâncias. No entanto, verificamos limitações nos modelos existentes, podendo não ser aplicáveis à realidade Brasileira. Variáveis relacionadas às atividades e serviços de saúde oferecidos em países em desenvolvimento podem indicar diferentes padrões de consumo nos diferentes tipos de edificações de saúde. Pois, além de hospitais, o Brasil possui diferentes tipos de edificações, como unidades básicas de saúde e unidades de pronto atendimento (cada um prestando diferentes tipos de serviços de saúde), sendo necessárias novas pesquisas nestas tipologias para análise do consumo e modelagem da demanda de água.
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Water demand forecasting models can be used as management and planning tools by water regulatory agencies, water supply and sewage treatment companies, construction professionals and building managers. The objective of this review was to identify existing water demand forecasting models for different types of health care establishments and to understand the methods used to build them. With this in mind, an exploratory literature review of previous studies regarding water demand prediction models of healthcare facilities was carried out. Overall, previous works present models based on bivariate linear regression, correlating hospital water consumption with number of beds, built area or number of employees, separately. Most of the studies reviewed, used statistical tests to check whether the samples were normally distributed and showed homogeneity of variances. However, we verified limitations in the existing models, which may not be applicable to the Brazilian reality. Variables related to health care services offered in developing countries may indicate different consumption patterns for the different types of health care buildings. Furthermore, in addition to hospitals, Brazil has different types of buildings, such as basic health units and emergency care units (that provide different health care services) and further research is needed within these built types.

Mulch: Amulchisa layer of material applied to the surface of soil. Reasons for applying mulch include conservation of soil moisture, improving fertility and health of the soil, reducing weed growth, and enhancing the visual appeal of the area. Amulchisusually,butnotexclusively,organic in nature. It may be permanent (e.g., plastic
sheeting) or temporary (e.g., bark chips). It may be applied to bare soil or around existing plants. Mulches of manure or compost will be incorporated naturally into the soil by the activity of worms and other organisms. The process is used both in commercial crop production and in gardening and, when applied correctly, can dramatically improve soil productivity. As the population in tertiary education is continuing to grow, this has increased the demand for food, thus adding pressure to the food supply system. At the same time, food producers are experiencing great competition for land, water, and energy (Godfray et al. 2010). Overarching all of these issues is the threat of climate change andconcernsabouthowmitigationandadaptation measures may affect the food system. Agriculture as their mainfood source in higher education institutions relies on water for the survival of crops. However, it is severely affected by frequent droughts which leads to crop failure, hunger, poverty, and pests and disease outbreaks. Identifying ways to mitigate drought and stabilize yields by encouraging smallholder farmers to adopt best management practices is fundamental to realizing food security and improved livelihoods (Shen et al. 2012; Bhardwaj 2013).

The water services system is unsustainable in its current form as it does not make sustainable use of the water resource, nor is the service economically and socially sustainable (Naidoo, 1999). Any Local Agenda 21 programme undertaken by any local authority in South Africa will have to
acknowledge that current water use patterns need to be audited and changed to render them sustainable. Auditing and changing the way in which water is used in South Africa should be done within the framework of water demand management and least cost integrated planning. Both the
compelling reasons for water demand management and least cost integrated planning, as well as the constraints to their implementation in urban areas are outlined. Policies designed to overcome these constraints will have to be drawn up in order to ensure that environmental, social and economic sustainability is achieved.

Quantitative research was undertaken in Gauteng to establish the current baseline of water conservation knowledge and practice amongst urban South African children, in both high and low income groups. It was found that most children do not seriously engage in any water conservation activities. The success of numerous water education programmes aimed at this target group was impeded by the failure of the programmes to consider sound social marketing theory, most notably in terms of the community environment in which the children reside and thus the programmes do not attempt to counter or alter the normative influence of the neighbourhood or society.

Based on panel data from the City of Davis, California, comprising more than 15,000 urban water consumption units and 81 billing periods over 13 years, this study investigates residential water demand and the effectiveness of three structural water conservation measures. An instrumental fixed effects regression analysis results in a price elasticity of -0.19 for residential consumers. The data also suggests that all structural tariff adjustments were effective, even if data for the general economic situation was included. This is the first study which demonstrates the effectiveness of coupling the sewer rate with a proxy for indoor water consumption on a household level.

The paper proposes a reassessment of the hopes vested in pricing mechanisms to regulate water diversions in the irrigation sector, focusing on large scale (surface) public irrigation. It first lists a series of major constraints that explain why the economic rationale applied to urban water supply cannot readily be transposed to surface irrigation. It then offers a review of situations where water is scarce and where irrigation schemes are able to distribute water volumetrically, either at the bulk or individual level. Such situations are relatively rare at the world level but they provide the context where volumetric pricing policies can be implemented and can demonstrate their potential for putting demand and use in line with supply. The review provides clear evidence that, instead of administered prices, quotas are almost invariably chosen as the main regulation mechanism, with prices mostly used to regulate use at the margin, beyond the quota, rather than for rationing scarce water.