Understanding urban residential end uses of water

2011 ◽  
Vol 64 (1) ◽  
pp. 36-42 ◽  
Author(s):  
Shirley Gato-Trinidad ◽  
Niranjali Jayasuriya ◽  
Peter Roberts
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Water Usage ◽  
Single Family ◽  
Washing Machines ◽  
Consumption Data ◽  
Household Water ◽  
Family Home ◽  
End Use ◽  
End Uses

The ‘end use’ of water is a breakdown of the total household water usage such as water used for toilets, showers, washing machines, taps, lawn watering, etc. Understanding end uses of water will enable water planners, water authorities and household owners determine where water is used/wasted, how much and how often. This paper describes the end uses of water from a number of single-family homes in Greater Melbourne, Australia. The study involves the analysis of water consumption data recorded at 5-s intervals from logged households collected by Yarra Valley Water in Melbourne in 2004. The study determines how much water is used for outdoor and indoor purposes in a single-family home in Melbourne and compares the water usage during winter and summer. Hourly patterns of major end uses of water are also developed. The aim of this study is to improve the understanding of the end uses of water and to assist where to focus water conservation efforts that would be most effective financially and environmentally, and be acceptable to everyone.

Aligning theory and measurement in behavioral models of water conservation

Water Policy ◽  
2014 ◽  
Vol 17 (4) ◽  
pp. 762-776 ◽  
Author(s):  
Bradley S. Jorgensen ◽  
John F. Martin ◽  
Meryl W. Pearce ◽  
Eileen M. Willis
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Behavioral Intentions ◽  
Habit Strength ◽  
Behavioral Models ◽  
Individual Level ◽  
Single Person ◽  
Consumption Data ◽  
Household Water

Discussion in the water literature has called for research on the role of behavioral intentions in explanations of both water demand and water conservation. But previous research has suggested that individual-level motivations are not good predictors of metered household water consumption. Two possible reasons for the lack of association between intentions and actual water conservation are that: (i) conservation behaviors are habitual and (ii) conservation behaviors and intention are measured at different levels of analysis. These explanations were tested in a sample of 415 residential households who provided permission to access their water consumption billing records. The effects of intentions, habit strength, and their interaction were examined in single-person households where the alignment of theory and measurement were the same. While behavioral intentions were associated with self-reports of past water conservation and habit strength, none of these variables were good predictors of water conservation. The implications of these results for the development of attitude theory using metered consumption data are discussed.

Developing a demand model integrating end uses of water (DMEUW): structure and process of integration

2015 ◽  
Vol 71 (4) ◽  
pp. 529-537 ◽  
Author(s):  
R. C. Sarker ◽  
S. Gato-Trinidad
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Water Demand ◽  
Daily Rainfall ◽  
Demand Model ◽  
Data Set ◽  
Residential Water Consumption ◽  
End Use ◽  
Hypertext Markup Language ◽  
End Uses

The process of developing an integrated water demand model integrating end uses of water has been presented. The model estimates and forecasts average daily water demand based on the end-use pattern and trend of residential water consumption, daily rainfall and temperature, water restrictions and water conservation programmes. The end-use model uses the latest end-use data set collected from Yarra Valley Water, Australia. A computer interface has also been developed using hypertext markup language and hypertext pre-processor. The developed model can be used by water authorities and water resource planners in forecasting water demand and by household owners in determining household water consumption.

scholarly journals The Effect of Variations in Micro-components of Domestic Water Consumption Data on the Classification of Excessive Water Usage

2015 ◽  
Vol 195 ◽  
pp. 1865-1871 ◽  
Author(s):  
Nor Salyana Mohd Salleh ◽  
Khairul A. Rasmani ◽  
Nur Izzah Jamil
Keyword(s):  
Water Consumption ◽  
Water Usage ◽  
Domestic Water ◽  
Consumption Data ◽  
Domestic Water Consumption ◽  
Excessive Water

Water Utilization in Data Center Infrastructure

2010 ◽  
Author(s):  
Ratnesh Sharma ◽  
Rocky Shih ◽  
Alan McReynolds ◽  
Cullen Bash ◽  
Chandrakant Patel ◽  
...  
Keyword(s):  
Power Generation ◽  
Water Quality ◽  
Water Consumption ◽  
Data Center ◽  
Data Centers ◽  
Cooling Towers ◽  
Power Demand ◽  
Water Usage ◽  
Water Treatment Plants ◽  
End Use

Fresh water is one of the few resources which is scarce and has no replacement; it is also closely coupled to energy consumption. Fresh water usage for power generation and other cooling applications is well known and accounts for 40% of total freshwater withdrawal in the U. S[1]. A significant amount of energy is embedded in the consumption of water for conveyance, treatment and distribution of water. Waste water treatment plants also consume a significant amount of energy. For example, water distribution systems and water treatment plants consume 1.3MWh and 0.5MWh[2], respectively, for every million gallons of water processed. Water consumption in data centers is often overlooked due to low cost impact compared to energy and other consumables. With the current trend towards local onsite generation[3], the role of water in data centers is more crucial than ever. Apart from actual water consumption, the impact of embedded energy in water is only beginning to be considered in water end-use analyses conducted by major utilities[4]. From a data center end-use perspective, water usage can be characterized as direct, for cooling tower operation, and indirect, for power generation to operate the IT equipment and cooling infrastructure[5]. In the past, authors have proposed and implemented metrics to evaluate direct and indirect water usage using an energy-based metric. These metrics allow assessment of water consumption at various power consumption levels in the IT infrastructure and enable comparison with other energy efficiency metrics within a data center or among several data centers[6]. Water consumption in data centers is a function of power demand, outside air temperature and water quality. While power demand affects both direct and indirect water consumption, water quality and outside air conditions affect direct water consumption. Water from data center infrastructure is directly discharged in various forms such as water vapor and effluent from cooling towers. Classification of direct water consumption is one of the first steps towards optimization of water usage. Subsequently, data center processes can be managed to reduce water intake and discharge. In this paper, we analyze water consumption from data center cooling towers and propose techniques to reuse and reduce water in the data center.

scholarly journals Extracting household water use event characteristics from rudimentary data

2020 ◽  
Vol 69 (4) ◽  
pp. 387-397 ◽  
Author(s):  
Bettina Elizabeth Meyer ◽  
Heinz Erasmus Jacobs ◽  
Adeshola Ilemobade
Keyword(s):  
High Resolution ◽  
Water Use ◽  
Service Providers ◽  
Flow Measurements ◽  
High Resolution Data ◽  
High Resource ◽  
Smart Water ◽  
Household Water ◽  
End Use ◽  
End Uses

Abstract Household water end-uses have been extracted from high-resolution smart water meter data in various earlier studies. However, research on end-use disaggregation from rudimentary data is limited. Rudimentary data is defined as data recorded in intervals longer than 1 min, or data recorded with resolutions larger than 0.1 L/pulse. Developing countries typically deal with rudimentary data, due to the high cost and high resource investment associated with high-resolution data. The aim of this study was to extract useful event characteristics from rudimentary data, without identifying the actual end-uses per se. A case study was conducted in the City of Johannesburg, South Africa, where 63 homes were equipped with iPERL smart water meters. The meters recorded flow measurements every 15 s at a 1 L/pulse resolution, rendering the recorded data rudimentary. A total of 1,107,547 event pulses were extracted over the 217-day study period. Although the method presented is limited in the sense that water use events cannot be identified, the method allows for disaggregation of event pulses in the presence of rudimentary data. Using this tool, it is possible to lift valuable information from rudimentary data that would subsequently benefit service providers in setting water demand strategies.

scholarly journals Household water use and conservation models using Monte Carlo techniques

2013 ◽  
Vol 10 (4) ◽  
pp. 4869-4900 ◽  
Author(s):  
R. Cahill ◽  
J. R. Lund ◽  
B. DeOreo ◽  
J. Medellín-Azuara
Keyword(s):  
Monte Carlo ◽  
Water Use ◽  
Water Conservation ◽  
Water Demand ◽  
Cost Effective ◽  
Mixed Integer ◽  
Residential Neighborhood ◽  
Household Water ◽  
End Use ◽  
Conservation Model

Abstract. The increased availability of water end use measurement studies allows for more mechanistic and detailed approaches to estimating household water demand and conservation potential. This study uses, probability distributions for parameters affecting water use estimated from end use studies and randomly sampled in Monte Carlo iterations to simulate water use in a single-family residential neighborhood. This model represents existing conditions and is calibrated to metered data. A two-stage mixed integer optimization model is then developed to estimate the least-cost combination of long- and short-term conservation actions for each household. This least-cost conservation model provides an estimate of the upper bound of reasonable conservation potential for varying pricing and rebate conditions. The models were adapted from previous work in Jordan and are applied to a neighborhood in San Ramon, California in eastern San Francisco Bay Area. The existing conditions model produces seasonal use results very close to the metered data. The least-cost conservation model suggests clothes washer rebates are among most cost-effective rebate programs for indoor uses. Retrofit of faucets and toilets is also cost effective and holds the highest potential for water savings from indoor uses. This mechanistic modeling approach can improve understanding of water demand and estimate cost-effectiveness of water conservation programs.

How Trust and Risk Perception Affect Household Water Use

2021 ◽  
Author(s):  
Raymond Yu Wang ◽  
Xiaofeng Liu
Keyword(s):  
Risk Perception ◽  
Water Use ◽  
Water Consumption ◽  
Water Conservation ◽  
Tap Water ◽  
Demand Management ◽  
Management Strategies ◽  
Social Groups ◽  
Recycled Water ◽  
Household Water

Household water use accounts for an important portion of water consumption. Notably, different households may behave differently regarding how water is used in everyday life. Trust and risk perception are two significant psychological factors that influence water use behavior in households. Since trust and risk perception are malleable and subject to construction, they are useful for developing effective demand management strategies and water conservation policies. The concepts of trust and risk perception are multidimensional and interconnected. Risk perception varies across social groups and is often shaped by subjective feelings toward a variety of activities, events, and technologies. Risk perception is also mediated by trust, which involves a positive expectation of an individual, an organization, and/or an institution that derives from complex processes, characteristics, and competence. Likewise, different social groups’ trust in various entities involved in household water use is subject to the significant and far-reaching impact of risk perception. The complexity of the two notions poses challenges to the measurement and exploration of their effects on household water use. In many cases, risk perception and trust can influence people’s acceptance of water sources (e.g., tap water, bottled water, recycled water, and desalinated water) and their conservation behavior (e.g., installing water-saving technologies and reducing water consumption) in household water use. Trust can affect household water use indirectly through its influence on risk perception. Moreover, trust and risk perception in household water use are neither given nor fixed; rather, they are dynamically determined by external, internal, and informational factors. A coherent, stable, transparent, and fair social and institutional structure is conducive to building trust. However, trust and risk perception differ among groups with diverse household and/or individual demographic, economic, social, and cultural characteristics. Direct information from personal experiences and, more importantly, indirect information from one’s social network, as well as from mass media and social media, play an increasingly important role in the formation and evolution of trust and risk perception, bringing a profound impact on household water use in an era of information. Future directions lie in new dynamics of risk perception and trust in the era of information explosion, the coevolution mechanism of risk perception and trust in household water use, the nuanced impacts of different types of risks (e.g., controllable and uncontrollable) on household water use, and the interactive relations of risk perception and trust across geographical contexts.

Micro-component survey of residential water consumption in Hanoi

2013 ◽  
Vol 13 (2) ◽  
pp. 469-478 ◽  
Author(s):  
Y. Otaki ◽  
M. Otaki ◽  
P. N. Bao ◽  
T. T. V. Nga ◽  
T. Aramaki
Keyword(s):  
Water Consumption ◽  
Basic Unit ◽  
Water Usage ◽  
Total Water Consumption ◽  
Domestic Use ◽  
Residential Water Consumption ◽  
Economic Perspectives ◽  
End Use ◽  
Policy Direction ◽  
Efficient Water Use

Daily total water consumption per capita has been used as a basic unit for the future planning of water supply for domestic use. However, for innovative water utilization designs that consider various scenarios, including the effects of policy direction and global warming, and more strategic and efficient water use, it is absolutely essential to consider water usage divided by residential activities, such as toilet flushing, cooking, clothes washing, and bathing. We collected micro-component data by direct measurement from each household outlet, and developed small accumulative meters. Measurements were conducted at 56 households for 2 months in Hanoi, Vietnam, and the average consumption was 18.6 L/p/d for toilet, 16.2 L/p/d for laundry, 10.4 L/p/d for bath, and 15.7 L/p/d for kitchen. We then analyzed the representative values and the distribution of water consumption for every usage from social and economic perspectives. In addition, we compared the results in Hanoi with those in Chiang Mai, Thailand, where we investigated water consumption a few years ago, and their value seemed similar except for bathroom use, but the substance was different. One distinct outcome of our investigation was the recognition of the cultural and methodological challenges to end-use assessment of water consumption in modernizing Asian communities.

scholarly journals ESTIMATION OF DAILY HOUSEHOLD WATER CONSUMPTION USING METERED WATER CONSUMPTION DATA

2016 ◽  
Vol 72 (6) ◽  
pp. II_79-II_85
Author(s):  
Morimasa TSUDA ◽  
Yoichi IWAMI
Keyword(s):  
Water Consumption ◽  
Consumption Data ◽  
Household Water

Water demand: the Austrian end-use study and conclusions for the future

2013 ◽  
Vol 14 (2) ◽  
pp. 205-211 ◽  
Author(s):  
Roman Neunteufel ◽  
Laurent Richard ◽  
Reinhard Perfler
Keyword(s):  
Climate Change ◽  
Water Consumption ◽  
Water Demand ◽  
Personal Information ◽  
Residential Buildings ◽  
Meteorological Data ◽  
Age Distribution ◽  
Household Consumption ◽  
Single Family ◽  
End Use

Demographic and climate change will affect in the long term the total water consumption and therefore the planning and management of the related infrastructures. End-use studies provide information on water consumption and its influencing factors. However the availability of such detailed data is very limited. The research project carried out was based on total daily water consumption collected from 12 Austrian water supply areas for periods covering up to 10 years. The general data were complemented with high resolution measurements (ranging from day to 10 second intervals) of household consumption of residential buildings, semi-detached houses, single family homes, and weekend cottages as well as with meteorological data and comprehensive socio-economic and personal information. The major factors influencing residential household consumption are: demographic dynamics; age distribution; household size/family size; living conditions; and regional economic development. In the short term, water consumption is influenced by temperature, precipitation, day of the week and time. For residential consumption, these last parameters were found to be the main causes for the existing peak demands. Modernisation will lead to a further decrease of the indoor per capita water demand. The outdoor demand and its peaks are expected to increase due to climate change.

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