THE EFFECTWENESS OF PRICING AS A STAND-ALONE WATER CONSERVATION PROGRAM1

ABSTRACT: Economic theory clearly indicates that the use of increasing rate structures will reduce the demand for water and produce monetary incentives for consumers to conserve. One problem with estimating the effectiveness of using rate structures as a conservation program is that they are usually accompanied by other conservation efforts. Thus, it is difficult to determine the effectiveness of any one conservation component. This paper examines the effectiveness of increasing rate structures in a situation where no other conservation program was introduced. The paper uses customer data from the Spalding County (Georgia) Water Authority where an increasing rate structure replaced a descending rate structure in January 1991. Since the imposition of the increasing rate structure, the number of customers has increased 21 percent while total water demand has gone up only 15 percent and per customer water use has declined 5 percent. The daily water use per connection has declined from 243 gallons in 1990 to 231 in 1993, and monthly use has gone from 7,381 gallons to 7,028 per connection over the same period. Statistical tests indicate that water consumption during the two periods was significantly different while weather factors were not.     

Factors affecting the variability of household water use in Melbourne,Australia

This study investigates the variability of household water use in Melbourne with the aim of improving the current understanding of factors affecting residential water use. This understanding is critical to predicting household water demand, particularly at an appropriate spatial and temporal resolution to support Integrated Urban Water Management based planning and to improve the understanding on how different household water demands respond to demand management strategies. The study used two sets of data each collected from 837 households under significantly different water use conditions in the years 2003 and 2011. Data from each household consist of the household characteristics and quarterly metre readings. Ordinary Least Square regression analysis followed by detailed analysis of each factor was used to identify key factors affecting household water use. The variables studied are household size, typology of dwelling, appliance efficiency, presence of children under 12 years, presence of children aged between 12 and 18 years, tenancy, dwelling age, presence of swimming pool, evaporative cooler, and dishwasher. All of them except presence of children aged between 12 and 18 years, tenancy and dwelling age were identified as variables that contribute to the variability of household water use in Melbourne. The study also found that the explanatory capacity of these variables increases with decreasing water use. This paper also discusses the significance of the explanatory variables, their impact and how they vary over the seasons and years. The variables found in this study can be used to inform improved prediction and modelling of residential water demand. The paper also explores other possible drivers to explain residential water use in light of the moderate explanatory capacity of the variables selected for this study thus, provides useful insights into future research into water demand modelling.     

Analysis and Predictive Models of Single‐Family Customer Response to Water Curtailments During Drought1

Polebitski, Austin S. and Richard N. Palmer, 2012. Analysis and Predictive Models of Single‐Family Customer Response to Water Curtailments During Drought. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/j.1752‐1688.2012.00691.x Abstract: This research investigates customer response to demand management strategies during two drought periods in the City of Seattle. An analysis of customer response to voluntary water curtailments is conducted using k‐means clustering to identify like groups of customers and behavior patterns. The clustering method identified important variables (household income, lot size, living space, and family size) useful in determining customer response to water curtailments. Ordinary least squares and spatial lag regression models are estimated using the first and second principal components of variables identified in the clustering analysis. Larger values of income, lot size, and living space enhanced water reductions whereas larger family size tended to reduce the effectiveness of curtailments. Projections of changes in Seattle’s built environment and demographics between 2000 and 2030 were obtained from an urban simulation model (UrbanSim) and were processed through the regression models to investigate changes in future curtailment effectiveness. This research found that increasing household size hardened demands (decreased curtailment effectiveness) whereas decreasing household size increased per‐capita curtailment effectiveness. These results suggest that changes in the number of residents within a home is likely to be the most important factor in determining future curtailment effectiveness.     

USING A CHOICE MODELLING APPROACH FOR CUSTOMER SERVICE STANDARDS IN URBAN WATER1

ABSTRACT: A series of reforms in the water industry in Australia has created a demand from the industry and regulators for objective methodologies to evaluate incremental changes in the customer service standards. In this paper, the use of choice modeling for estimating implicit prices associated with urban water supply attributes is explored. Results from multinomial logit (MNL) and random parameters logit (RPL) models show that increases in annual water bills and the frequency of future interruptions were the most important attributes. Implicit price confidence intervals based on the best models suggest that people are willing to pay positive amounts to achieve a water supply that is less frequently interrupted. The provision of alternative water supplies during an interruption and notification of the interruption were found to be unimportant to respondents. Choice modeling proved to be a useful technique and provided the industry and regulators with additional information for standard setting.     

WATER CONSERVATION IN CASABLANCA,MOROCCO1

ABSTRACT: This study examines water consumption characteristics in Casablanca and analyzes approaches for sustainable water demand management. Research procedures involve the development and estimation of water demand models for the residential/commercial, industrial, and institutional sectors; forecasts of water demand to 2010; and simulation of the effects of a complex of water conservation methods on the forecasted demands. The results indicate that residential/commercial water demand is weakly responsive to price changes (elasticity =?0.448) while institutional water demand is slightly more responsive (elasticity =?0.648). The conservation approaches used in the simulations included public education, plumbing code revisions to require use of water conservation devices, leak detection and repair, pricing policy, metering, and pressure reduction. The results indicate that considerable saving in water use can be attained through a comprehensive water demand management program.     

WATER CONSTRAINTS ON ENERGY DEVELOPMENT: A FRAMEWORK FOR ANALYSIS1

ABSTRACT: The pressure on water resources from energy resource development and transformation is likely to be greater in the future than it has been in the past. A rational resolution of the political problems that this situation will generate requires that: 1) planning based on predictions of future energy supply and demand be replaced by scenario, or “what if?” analysis; 2) full attention be paid to the uncertainties in per-unit-energy water requirements; 3) suitable stochastic measures of water availability be used to compare water supply with water demand; 4) realistic ecological criteria, and other alternative use criteria, be developed for estimating impacts of water withdrawn or consurned for energy development; 5) human consequences of ecological impaccts are described in a manner that will allow the political process to intervene in an optimum manner to allocate water resources.     

WATER USE RELATIONSHIPS AND PROJECTION CORRESPONDING WITH REGIONAL GROWTH,SEATTLE REGION1

ABSTRACT: The paper outlines both the methods used and the results obtained in a study of the demand for municipal and industrial water for the Seattle region. The study was made as part of a regional water management study program, one objective of which is to “… identify, quantify, and set priorities for all current and future water uses …”. A basic concept in the study of municipal and industrial water use is that the demand for water is derived from the demand for output and the direct services that water provides. Principal characteristics of the study are: (1) Water use is studied by type - residential, commercial, industrial and public -with identification of factors affecting each; (2) Water demands are studied by season as well as on an annual basis; (3) Projections of future water use are tied directly to projections of economic change in the service area; and (4) The effects of alternative policies on water use are estimated. Water use levels are projected under alternative regional growth assumptions provided by the Puget Sound Governmental Conference, a regional planning agency. Thus, the water use planning is consistent with other regional planning programs in this respect. The results can be varied according to changes in specific factors affecting water use. The factors considered in the present study include: single-family residential lot size, distribution of population between single- and multi-family units, per capita water use by multi-family unit residents, and industrial and commercial water use per employee. An income elasticity of demand was estimated for single-family residential water use.     

Smart meters for enhanced water supply network modelling and infrastructure planning

To design water distribution network infrastructure, water utilities formulate daily demand profiles and peaking factors. However, traditional methods of developing such profiles and peaking factors, necessary to carry out water distribution network modelling, are often founded on a number of assumptions on how top-down bulk water consumption is attributed to customer connections and outdated demand information that does not reflect present consumption trends; meaning infrastructure is often unnecessarily overdesigned. The recent advent of high resolution smart water meters allows for a new novel methodology for using the continuous ‘big data’ generated by these meter fleets to create evidence-based water demand curves suitable for use in network models. To demonstrate the application of the developed method, high resolution water consumption data from households fitted with smart water meters were collected from the South East Queensland and Hervey Bay regions in Australia. Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters. The resulting modelled water demand patterns for AD, PD and MDMM had morning and evening peaks occurring earlier and lower main peaks (AD: 12%; PD: 20%; MDMM: 33%) than the currently used demand profiles of the regions’ water utility. The paper concludes with a discussion on the implications of widespread smart water metering systems for enhanced water distribution infrastructure planning and management as well as the benefits to customers.     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.     

WATER PRICE RESPONSIVENESS OF COMMERCIAL ESTABLISHMENTS1

ABSTRACT: Pricing policy in water allocation has become of more concern as some areas find water is indeed a scarce resource. Demand estimates, where the quantity purchased-value in use relationships are of concern, have been made in other studies for residential, industrial, and agricultural uses in many areas of the country. The price-quantity relations for water use in commercial firms are estimated and discussed for several different types of stores in this study. A derived demand model is used to estimate commercial demand in the Miami, Florida, area. The price elasticity was generally low (inelastic) for all groups studied except for department stores. This group was found to have an elastic demand for water at all prices above $0.93 per thousand gallons purchased per month, where the mean price for this part of the sample was $1.24. The major implication of the study is that commercial establishments may be responsive to price changes over the long run, much as has already been shown for other types of user groups in other studies.     

INPUT-OUTPUT AND BENEFIT-COST ANALYSIS FOR WATER RESOURCE DEVELOPMENT PROJECTS1

ABSTRACT: The proper use of input-output for estimating regional benefits and costs is described for instances where project outputs go to final or intermediate demand. How that estimation is affected by the method used to value the primary project benefits and by the sector content of the input-output model compared to the primary sector affected are discussed as are points of terminological confusion between the two methods.     

A METHOD FOR ESTIMATING PEAK WATER DEMAND OF MULTIFAMILY RESIDENCES1

ABSTRACT: The importance of estimating peak water demands for determining the dimensions of pipe size and meters which provide household water to multifamily residences is examined. Several methods utilized in North America and Europe are examined. The analysis makes clear the necessity of studying the peak water demand through statistics based on local data concerning multifamily residences. For different periods of return, the peak demand of a given apartment building is related to its size (the number of apartments) in order to compare the results obtained with existing formula. By use of Ridge-regression technique, the relationship between peak water demand, and building size (number of apartments) and available pressure is established. It can be concluded that peak demand can be estimated with the square root of number of apartment units in the building and the cube root of water pressure.     

PAST AND FUTURE OF ANALYSIS OF WATER RESOURCES TIME SERIES1

ABSTRACT: water resources supply and demand time series consist of several or all of the four basic characteristics: tendency, intermittency, periodicity and stochasticity. Their importance changes from one type of variables to another. Historic developments of analysis of time series in hydrology have varied significantly over the past, from the stress on search for periodicities and persistence in annual series to the emphasis on the series stochastic properties. Supply and demand series are often highly interrelated, which fact is most often neglected in planning water resources systems in general, and water storage capacities in particular. The future of series analysis in water resources will likely be by a joint use of physically-based structural analysis and the use of advanced methods of treating data by stochastic processes, statistical estimation and inference techniques. The most intriguing challenge of the future of this analysis may be the treatment of nonnormal, nonlinear and in general nonstationary hydrologic and water use time series. The proper treatment of complex multivariate processes will also challenge the specialists, especially for the purposes of transfer of information between data on variables at given points, or between data at several points of a given variable, or both.     

RURAL RESIDENTIAL WATER DEMAND: AN ECONOMETRIC AND SIMULATION ANALYSIS1

ABSTRACT: This study proposes that demand management through pricing policies can be used in conjunction with supply management to solve water supply problems. Economic principles are shown to apply to rural residential water use. A demand function for water was developed based on cross-sectional water use data collected in Kentucky. Price was found to be a significant determinant of the quantity of water demanded. A constant price elasticity of -0.92 was found. The demand function was used in a simulation analysis to determine reservoir capacity needed to supply water needs of a rural community. The simulation revealed that price can significantly affect required reservoir storage.     

RESIDENTIAL WATER DEMAND IN METRO MANILA1

ABSTRACT: An econometric demand function is estimated for residential water use in Metropolitan Manila. Regression results using annual time series data from 1970 to 1981 show that residential water consumption responds to changes in economic variables. Residential demand showed an income (household) elasticity of 0.542 and a combined price elasticity of -0.287. Implications for planning and management are discussed.     

Assessment of water quality and identification of pollution sources of plateau lakes in Yunnan (China)

The plateau lakes of Yunnan are important both ecologically and economically in China. Nevertheless, the human impact on water quality in these lakes has become increasingly highlighted. The water quality of 10 plateau lakes was monitored regularly over the period of 2000 through 2004 for 24 parameters. Multivariate statistical techniques, including cluster analysis (CA), factor analysis (FA), and principal component analysis (PCA), were employed to better interpret information about the water quality and its pollution sources. No obvious data reduction from CA/FA was found because three principal components (PCs) needed 14 variables to explain 85.01% of the total variance. However, three latent factors accounted for pollution mainly from the following sources: agricultural activities, residential activities and anthropogenic-toxic pollution from industrial effluents, or other special activities. Box-whiskers plots were employed to visually interpret the spatiotemporal variations of water quality variables, which were highly correlated with three PCs. Three types of water quality (i.e., low-, medium-, and high-polluted lakes) were determined through CA based on the similarity of water quality variables. Our results may provide helpful information for the authorities to effectively manage the water quality and make sound policies.     

A MUNICIPAL WATER DEMAND MODEL FOR THE CONTERMINOUS UNITED STATES1

With the increasing Federal role in all aspects of water resource planning, the need for a planning model to enable calculations of projected Municipal Water requirements has become evident. This study represents an initial effort at developing an econometric model of Municipal Water requirements which (1) incorporates variables (or proxies) reflecting the various factors affecting water demand (i.e., demographic, social, industrial), and (2) requires only readily available, published data for its use. This model permits determinations of the water requirements of 488 cities grouped into 19 geographic regions or “Pseudo States.” Separate regression functions have been fitted to the cities within each of the 19 regions. Derivation of the exact functions for each region entailed a cross section stepwise regression analysis in which some 18 different variables were examined. KEY WORDS: planning model; econometric model; initial effort; municipal water     

Evaluation of alternative water sources for commercial buildings: A case study in Brisbane,Australia

Commercial buildings are central to cities and contribute significantly to the urban demand for natural resources, including freshwater. Green building benchmarking tools include more efficient water use as key indicator of sustainability. This paper explores options for substituting mains drinking water with an alternative, non-potable water source on a fit for purpose basis. The research findings are based on a monitoring study of a commercial building in Brisbane, Australia that is harvesting rainwater for meeting non-potable water demand. The results demonstrated that the system is only achieving moderate reliability in meeting demand due to operational problems. The case study analysis has highlighted the need to include validation and monitoring to ensure the system is operating as per design intent. The paper also investigates the potential of other local, non-potable water sources for high-rise commercial buildings, in particular air conditioning condensate and groundwater inflow to a basement wet well. The paper concludes by comparing the advantages and disadvantages of different local water sources which highlights the need to undertake a site specific investigation to identify a suitable alternative water source, which considers O&M complexity and the capacity of facilities management.     

基于因子分析的BP神经网络对成都市需水量的预测

在对四川省成都市的水资源进行综合规划与评价的过程中,通过主成分因子分析可知人口、GDP、给排水管道长度等因素对需水量预测有较大影响,如何建立这些因素与需水量之间的数学关系是预测工作的重点。本文将介绍通过MATLAB数学分析软件建立BP神经网络预测模型,并对模型的预测结果进行评价。     

RESIDENTIAL WATER DEMAND: A POOLED,TIME SERIES,CROSS SECTION STUDY OF MALMÖ, SWEDEN1

Shortcoming associated with past water demand studies are evaluated. To overcome these shortcomings, pooled, time series, cross section data from -6, Sweden, are used in an ordinary Least squares analysis to estimate the demand for residential water. Elasticities for five variables, including price and income, are estimated. An approach for the conduct of future water demand studies is suggested.