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Artykuły w czasopismach na temat "Residential water demand"

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Tricarico, C., G. de Marinis, R. Gargano i A. Leopardi. "Peak residential water demand". Proceedings of the Institution of Civil Engineers - Water Management 160, nr 2 (czerwiec 2007): 115–21. http://dx.doi.org/10.1680/wama.2007.160.2.115.

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Bao, Keyu, Rushikesh Padsala, Daniela Thrän i Bastian Schröter. "Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model". ISPRS International Journal of Geo-Information 9, nr 11 (28.10.2020): 642. http://dx.doi.org/10.3390/ijgi9110642.

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Humans’ activities in urban areas put a strain on local water resources. This paper introduces a method to accurately simulate the stress urban water demand in Germany puts on local resources on a single-building level, and scalable to regional levels without loss of detail. The method integrates building geometry, building physics, census, socio-economy and meteorological information to provide a general approach to assessing water demands that also overcome obstacles on data aggregation and processing imposed by data privacy guidelines. Three German counties were used as validation cases to prove the feasibility of the presented approach: on average, per capita water demand and aggregated water demand deviates by less than 7% from real demand data. Scenarios applied to a case region Ludwigsburg in Germany, which takes the increment of water price, aging of the population and the climate change into account, show that the residential water demand has the change of −2%, +7% and −0.4% respectively. The industrial water demand increases by 46% due to the development of economy indicated by GDP per capita. The rise of precipitation and temperature raise the water demand in non-residential buildings (excluding industry) of 1%.
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Palencia, Lamberto C. "RESIDENTIAL WATER DEMAND IN METRO MANILA". Journal of the American Water Resources Association 24, nr 2 (kwiecień 1988): 275–79. http://dx.doi.org/10.1111/j.1752-1688.1988.tb02984.x.

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Lopez-Mayan, Cristina. "Microeconometric Analysis of Residential Water Demand". Environmental and Resource Economics 59, nr 1 (5.09.2013): 137–66. http://dx.doi.org/10.1007/s10640-013-9721-4.

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Gato, Shirley, Niranjali Jayasuriya i Peter Roberts. "Forecasting Residential Water Demand: Case Study". Journal of Water Resources Planning and Management 133, nr 4 (lipiec 2007): 309–19. http://dx.doi.org/10.1061/(asce)0733-9496(2007)133:4(309).

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Hung, Ming-Feng, Bin-Tzong Chie i Tai-Hsin Huang. "Residential water demand and water waste in Taiwan". Environmental Economics and Policy Studies 19, nr 2 (13.04.2016): 249–68. http://dx.doi.org/10.1007/s10018-016-0154-5.

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Metaxas, S., i E. Charalambous. "Residential price elasticity of demand for water". Water Supply 5, nr 6 (1.12.2005): 183–88. http://dx.doi.org/10.2166/ws.2005.0063.

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This paper presents an analysis on price elasticity of demand for water as a consequence of price increases. The objective of this research study is to estimate the residential price elasticities of demand for water for different regions, which may have different income levels. The general conclusion is that price elasticity for residential water use is inelastic (i.e. a given percentage of price increase results in a proportionally smaller decrease in quantity demanded) and it varies by consumer class and type of water use. The elasticity is not significantly affected by demographic and other factors.
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Lyman, R. Ashley. "Peak and off-peak residential water demand". Water Resources Research 28, nr 9 (wrzesień 1992): 2159–67. http://dx.doi.org/10.1029/92wr01082.

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Schleich, Joachim, i Thomas Hillenbrand. "Determinants of residential water demand in Germany". Ecological Economics 68, nr 6 (kwiecień 2009): 1756–69. http://dx.doi.org/10.1016/j.ecolecon.2008.11.012.

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Gargano, Rudy, Carla Tricarico, Giuseppe del Giudice i Francesco Granata. "A stochastic model for daily residential water demand". Water Supply 16, nr 6 (20.06.2016): 1753–67. http://dx.doi.org/10.2166/ws.2016.102.

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Residential water demand is a random variable which influences greatly the performance of municipal water distribution systems (WDSs). The water request at network nodes reflects the behavior of the residential users, and a proper characterization of their water use habits is vital for the hydraulic system modeling. This study presents a stochastic approach for the characterization of the daily residential water use. The proposed methodology considers a unique probabilistic distribution – mixed distribution – for any time during the day, and thus for any entity of the water demanded by the users. This distribution is obtained by the merging of two cumulative distribution functions taking into account the spike of the cumulative frequencies for the null requests. The methodology has been tested on three real water distribution networks, where the water use habits are different. Experimental relations are given to estimate the parameters of the proposed stochastic model in relation to the users number and to the average daily trend. Numerical examples for a practical application have shown the effectiveness of the proposed approach in order to generate the time series for the residential water demand.
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Rozprawy doktorskie na temat "Residential water demand"

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Gato, Shirley, i s3024038@rmit edu au. "Forecasting Urban Residential Water Demand". RMIT University. Civil, Environmental and Chemical Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070202.113452.

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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
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Dzisiak, Richard N. "The role of price in determining residential water demand, water pricing and residential water demand in municipalities in the Western Prairies". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0005/MQ41695.pdf.

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Gardner, Kerry. "Residential water demand modelling and behavioural economics". Thesis, University of East Anglia, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539372.

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Water supply-demand balances are becoming increasingly constrained around the world and in the United Kingdom. Although there has been a policy shift toward demand management policies to address this, demand modefling evidence is limited. This thesis makes qualitative, quantitative and behavioural contributions to this area. Qualitative and quantitative (meta-analytic) literature reviews are conducted. These indicate elasticity estimates are sensitive to methodological choices. Empiricafly it is identified that summer and long-run demand are more price and income responsive than their respective counterparts; lower income groups in developed countries are more price and less income responsive than higher income groups; and geographical demand differences exist. Publication bias tests reject bias, confirming that water is an economic good (price and income exert genuine effects on demand). A behavioural investigation of water consumers' price and consumption perceptions finds that systematic misperceptions of unit prices, consumption and tariff structures exist, regardless of which tariff structure operates. In contrast, bill perceptions are relatively accurate. This motivates a 'bill price' specification in addition to existing (marginal and average) price specifications. Perception inaccuracy is empiricafly tested against a simple explanatory framework of the costs and benefits of information acquisition. Price perceptions, but not consumption perceptions, broadly support this framework. Lastly, the first available price and wealth elasticity estimates for UK households are presented. These are -0.29 for price and +0.16 for wealth. These elasticities are generally smafler in magnitude than mean international price (-0.38) and income (+0.28) elasticities. Average and 'bill price' elasticities are significantly larger at around -0.S7. UK seasonal and income group differences appear to operate in the opposite direction to international trends (summer demand and lower income groups are less price responsive than their counterparts). Long-run UK demand appears more price responsive than the short-run. However, further research is required to develop consistent dynamic demand models in the presence of multiple endogenous variables.
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Du, Plessis Jacobus Lodewikus. "Estimating domestic outdoor water demand for residential estates". Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86695.

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Thesis (MEng)--Stellenbosch University, 2014.
ENGLISH ABSTRACT: The outdoor water consumption of residential properties is a major contributor to the seasonal fluctuation of the overall water consumption of these properties. The estimation of the relating outdoor water demand has become valuable to property developers and planners alike. This could enable designers to optimise designs of water distribution networks and assist in water resource planning and gaining legislative approvals. For the purposes of this study the outdoor water-use components were mathematically defined and combined to develop an outdoor water-demand model. In order to evaluate the results of an outdoor water demand model on a monthly temporal scale it was necessary to develop a proxy outdoor water consumption evaluation method based on the metered monthly consumption of residential properties. The method entailed verifying that the generally non-seasonal indoor water consumption as a function of the winter water consumption. This entailed analysis of the total monthly, indoor and outdoor water consumption data adopted from a noteworthy North American water end-use project. The indoor water consumption estimated in this manner could then be subtracted from the overall monthly water consumption to obtain estimated monthly outdoor water consumption data. The estimated outdoor consumption could be compared with the simulated outdoor water demand, as described by the model. The parameters that formed part of the mathematical outdoor water demand model were formulated from data available for residential estates, where conditions such as types of vegetation, irrigated area and size of pool could be prescribed in a constitution, usually instituted by a home owners association. The data was derived from one estate located in the Western Cape Province of South Africa. The mathematical model was simulated using the Monte Carlo method and the @Risk software. Three residential estates located in South Africa were subsequently modelled. Additionally, the model was employed to estimate outdoor water demand for houses located in Northern America for verification purposes. The Monte Carlo simulations of the outdoor water demand model presented in this study yielded realistic results when compared with the proxy outdoor consumption figures as well as the metered actual outdoor water consumption data analysed. The peak monthly outdoor water demand estimation results were particularly close to the consumption data. This study serves as a baseline for further research into outdoor water demand. Research into the effects of water restriction and conservation potential could follow from this work, especially in today’s environmentally conscious society.
AFRIKAANSE OPSOMMING: Die buite waterverbruik van residensiëel eiendomme dra grootliks by tot die seisoenale fluktuasie van die algehele water verbruik van hierdie eiendomme. Die beraming van die dienooreenkomstige buite wateraanvraag kan waarde toevoeg vir eiendomsontwikkelaars and beplanners, indien dit ontwerpers kan instaat stel om water verspreindingsnetwerke te optimeer en te help met water hulpbron beplanning en wetlikke goedkeurings. Vir die doeleindes van hierdie studie is die buite waterverbruik komponente wiskundig gedefinieër en gekombineer om ‘n buite wateraanvraag model te ontwikkel. Ten einde die resultate van ‘n buite water aanvraag model op ‘n maandelikse tydskaal te evalueer, was dit nodig om ‘n benaderingsmetode te ontwikkel, gebaseer of die gemeterde maandelikse water verbruike gebruik. Die metode behels dat die data, verkry van ‘n bekende Noord-Amerikaanse water eindverbruikprojek, van die algmeen nie-seisoenale binneshuise water verbruik vergelyk word met die maandelikse winter water verbruik. Derhalwe kon die binneshuise waterverbruik wat op hierdie manier beraam is afgetrek word van die algehel maandelikse waterverbruik om die maandelikse buitewater verbruik te beraam. Die beraamde buitewater verbruik kon sodoende vergelyk kan word met ‘n gesimuleerde buite wateraanvraag soos beskryf deur die gesimuleerde model. Die parameters wat deel uitgemaak het van die wiskundige buite waterverbuik model was gedefinieër uit data wat beskikbaar was vir residensiële ontwikkelings, waar voorwaardes soos plantegroei, besproeiingsarea of swembad grote dikwels voorgeskryf kan word in ‘n grondwet ingestel deur ‘n huiseienaarsvereniging. Die data wat in hierdie model gebuik word is hoofsaaklik afskomstig van ‘n landgoed geleë in die Weskaap provinsie, Suid-Afrika. Die wiskundige model was gesimuleer met behulp van die Monte Carlo metode en die @Risk sagteware. Drie residensiële landgoede geleë in Suid-Afrika was daaropvolgend gemodelleer. Daarbenewens is die model gebruik die buite watergebruik van groepe huise geleë in Noord-Amerika te beraam vir verifikasie doeleindes. Die Monte Carlo simulasies van die buite water aanvraag model van hierdie studie het realistiese resultate in vergelyking met die beraamde buite verbruike sowel as die werklike gemeterde buite water verbruiksdata opgelewer. Die piek maandelikse buite water aanvraag beramings resultate was veral vergelykbaar met die piek maandeliks waterverbruik data. Hierdie studie dien as 'n basis vir verdere navorsing in buite waterverbruik. Navorsing gefokus op die gevolge van water beperkings en bewaring potensiaal kan as aanvullende voordele van hierdie studie ontstaan, veral in vandag se omgewingsbewuste samelewing.
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Regli, Philip Warner. "Residential demand for water in the Phoenix metropolitan area". Thesis, The University of Arizona, 1985. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_1985_160_sip1_w.pdf&type=application/pdf.

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Boyce, Daniel J. B. "Micro-component water demand scenario modelling for catchment scale residential water use". Thesis, Cranfield University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.443748.

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AndrÃ, Diego de Maria. "Space and economic determinants of demand for residential water in fortaleza, cearÃ". Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7425.

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nÃo hÃ
This paper aims to estimate a residential water demand function for the city of Fortaleza (CearÃ), considering the potential impact of the spatial effects on water consumption. The analysis is developed from the investigation of presence of spatial autocorrelation in residential water consumption. For this, the tools of exploratory spatial data analysis (ESDA) were utilized. Subsequently, specific tests are performed to determine the sources of spatial autocorrelation, i.e., if the autocorrelation is caused by the spatial distribution of water consumption or by effects not modeled. Identified the sources of spatial autocorrelation, four water demand functions were estimated, which had as explanatory variables the average price, the difference, income, number of residents and the number of rooms, under different specifications. At first, we estimated a model without special effects; in the second, we estimated the specification of the spatial error model (SEM), which incorporates the spatial autocorrelation in the form of autocorrelation in the error terms; in the third, we estimated the spatial autoregressive model (SAR), where the spatial autocorrelation is incorporated through the spatial lag of the dependent variable; and finally, we estimated the spatial model autoregressive moving average (SARMA), which is the union of the two previous models. The results show that spatial autocorrelation exists in two forms (error and lag), indicating that the SARMA model is the most indicated to model the residential water demand in the city of Fortaleza, in contrast to suggested by Chang et al.(2010), House-Peters et al. (2010), Franczyk e Chang (2008), Ramachandran e Johnston (2011), which used the SEM model. It is concluded that it is important to consider the possibility of spatial effects in the estimation of a residential water demand function, once that not incorporate spatial effects in the analysis underestimate the effect of the variables average price and number of residents on residential water demand, while overestimating the effect of the variables income and number of rooms.
Esta dissertaÃÃo tem como objetivo estimar uma funÃÃo de demanda residencial por Ãgua para a cidade de Fortaleza (CearÃ), considerando o provÃvel impacto do efeito espacial no consumo de Ãgua. A anÃlise se desenvolve a partir da investigaÃÃo a respeito da presenÃa de autocorrelaÃÃo espacial no consumo residencial de Ãgua. Para tal, foram utilizadas as tÃcnicas de anÃlise exploratÃria espacial de dados (ESDA). Posteriormente, sÃo realizados testes especÃficos para determinar as fontes da autocorrelaÃÃo espacial, ou seja, identificar se a autocorrelaÃÃo à causada pela distribuiÃÃo espacial do consumo de Ãgua ou pelos efeitos nÃo modelados. Identificadas as fontes de autocorrelaÃÃo espacial, foram estimadas quatro funÃÃes de demanda de Ãgua, que tinham como variÃveis explicativas o preÃo mÃdio, a diferenÃa, a renda, o nÃmero de residentes e o nÃmero de cÃmodos, sob diferentes especificaÃÃes. Na primeira, utilizou-se um modelo sem efeitos espaciais; na segunda, utilizou-se a especificaÃÃo do modelo de erros espaciais (SEM), que incorpora a autocorrelaÃÃo espacial na forma de autocorrelaÃÃo nos termos de erro; na terceira, utilizou-se o modelo espacial autorregressivo (SAR), onde a autocorrelaÃÃo espacial à incorporada atravÃs da defasagem espacial da variÃvel dependente; e por Ãltimo, utilizou-se o modelo espacial autorregressivo de mÃdias mÃveis (SARMA), que à a uniÃo dos dois modelos anteriores. Os resultados mostram que existe autocorrelaÃÃo espacial nas duas formas (erro e defasagem), indicando que o modelo SARMA à o mais adequado para modelar a demanda residencial por Ãgua na cidade de Fortaleza, ao contrÃrio do proposto por Chang et al. (2010), House-Peters et al. (2010), Franczyk e Chang (2008), Ramachandran e Johnston (2011), que utilizaram o modelo SEM. Conclui-se, portanto, que à importante levar em consideraÃÃo a possibilidade de efeitos espaciais na estimaÃÃo de uma funÃÃo de demanda residencial por Ãgua, na medida que a nÃo incorporaÃÃo dos efeitos espaciais subestima o efeito das variÃveis preÃo mÃdio e nÃmero de residentes sobre a quantidade consumida de Ãgua, enquanto superestima o efeito das variÃveis renda e nÃmero de cÃmodos.
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Urban, Graeme John. "Probabalistic load modelling of electrical demand of residential water heating". Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/20071.

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Thesis (MScEng)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: Energy efficiency and the move to renewable energy resources are of vital importance in growing profitable and sustainable economies. In recent years, greater emphasis has been placed on institutions, companies and individuals to reduce their electrical energy demand through energy management. In an attempt to reduce the demand, the electrical power utility in South Africa, Eskom, has introduced Demand Side Management programs and substantial increases in electricity tariffs. In addition to these, tax incentives have been offered to help off-set the capital costs associated with the investments made in replacing old electrical equipment with new electrically efficient equipment. Thus the need for accurate Measurement and Verification of electrical energy demand reduction, to substantiate fiscal claims, has become imperative. The main purpose of Measurement and Verification is to investigate the actual monetary performance of an energy savings project. Energy savings assessments, based on purely deterministic baseline demand, do not adequately represent the statistical nature of the savings impacts of many practical load systems, as disclosed in a reporting period. This thesis presents the development of a generic probabilistic methodology to determine the demand profiles of preand post-Energy Conservation Measures (ECMs) for practical load systems. The difference between the simulated demand of the pre- and post-ECMs for a particular set of variables represent the electrical demand impact. The electrical demand of the pre- and post-ECMs is defined in terms of Probability Density Functions, and derived using a multivariate kernel density estimation algorithm. The approach is tested using a simulation model of a waterheating geyser implemented in MATLAB. Three different ECMs are simulated using the geyser model and demand density estimation. The results of the demand impacts of the ECMs are presented and evaluated. With regards to possible future research this methodology could be applied to the evaluation of the demand impacts of heat pump technologies and solar water heaters.
AFRIKAANSE OPSOMMING: en die skuif na hernubare energiebronne is van deurslaggewende belang vir die ontwikkeling van winsgewende en volhoubare ekonomieë. Onlangs is meer klem geplaas op instansies, maatskappye en individue om hul aanvraag na energie te verminder met behulp van energiebestuur. In ‘n poging om die aanvraag te verlaag, het Eskom, Suid-Afrika se elektrisiteitsverskaffer, aansienlike elektrisiteitstariefverhogings ingelyf en Aanvraagbestuursprogramme van stapel gestuur. Bykomend hiertoe is belastingaansporings ook aangebied, waarteen kapitale kostes, geassosieer met die vervanging van ou elektriese toerusting met nuwe elektries doeltreffende toerusting, afgeset kan word. Derhalwe het die behoefte aan akkurate Meting en Verifikasie van elektriese energie aanvraagvermindering, om finansiële eise te staaf, noodsaaklik geword. Die hoofdoel van Meting en Verifikasie is om die werklike finansiële prestasie van energiebesparingsprojek te ondersoek soos bekend gemaak word tydens ’n verslagdoeningstydperk. Energiebesparingassesserings wat slegs gebaseer word op die suiwer deterministiese basislyn aanvraag na elektrisiteit, verteenwoordig nie die werklike statistiese aard van die besparingsimpakte van baie praktiese lasstelsels nie. Hierdie tesis stel die ontwikkeling van generiese waarskynlikheids-metodologie voor, om die voor- en na- Energiebesparings-maatreëls se aanvraagprofiele vir sulke praktiese lasstelsels, vas te stel. Die verskil tussen die gesimuleerde aanvraag van die voor- en na- Energiebesparings-maatreëls vir spesifieke stel veranderlikes verteenwoordig die elektriese aanvraag impak. Die voor- en na- Energiebesparings-maatreëls van die energieverbruik profieldata word gedefinieer in terme van Waarskynlikheidsdigtheidsfunksies en afgelei deur gebruik te maak van meerveranderlike kerndigtheidafskattingsalgoritme. Die benadering is getoets deur gebruik te maak van simuleringsmodel van warmwaterstelsel geïmplimenteer in MATLAB. Drie verskillende voor- en na- Energiebesparings-maatreëls is gesimuleer met behulp van die warmwaterstelselmodel en aanvraag digtheidafskatting. Die resultate van die elektriese aanvraag impakte van die voor- en na- Energiebesparings-maatreëls word vervolgens bespreek en geëvalueer. Met betrekking tot moontlike toekomstige navorsing kan hierdie metodologie toegepas word om die aanvraag impakte van hittepomp- en sonwaterverwarmingstegnologieë te evalueer.
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Sawangchareon, Dumrongchai. "The Analysis of the Demand for Residential Water in the City of Denton". Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc500727/.

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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.
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Sadek, Eran Sadek Said Md. "Modellng residential water demand in Leeds using microsimulation incorporating behavioural data". Thesis, University of Leeds, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.581978.

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With an increasing world population and changing lifestyles, there is a relentless demand for water including for domestic water supplies. In order to manage water demand better, the amount of water used for domestic purposes must be estimated. A number of methods exist such as the micro-components method, which is recommended by the UK Environment Agency. Microsimulation of synthetic households is also used for demand estimation, which is an area of research that has a tradition in the School of Geography, University of Leeds. This research project follows in this tradition but extends the work by adding a behavioural component through information collected via a survey. Microsimulation is used to create a synthetic household population for the city of Leeds, which is the study area for this research. Using a Domestic Consumption Monitor (DCM) from Yorkshire Water, which contains the water consumption of a sample of households, water use is matched to the synthetic population to produce baseline demand for the city, which equates to 106 million litres per day or 148 litres per person per day, which approximates the UK average. The research then involved designing and administering a behavioural survey, which was informed by a review of other surveys that have been undertaken in the UK. The survey of more than 1,000 individuals was found to contain a representative sample by housing type and metered versus non-metered houses when compared to Leeds and England. Moreover, the number of water ecologists and water utilitarians was also evenly distributed. The results of the survey showed a number of findings regarding water conservation behaviour and measures that might encourage conservation. For example, water efficient showerheads, water displacement devices in a cistern, installing a water butt, installing a dual/low flush toilet and not washing food and vegetables under a tap are all behaviours that people would adopt in the future. The survey was then used to calculate the likelihood or probability that households would adopt a particular water conservation behaviour, disaggregated by different demographic variables such as housing type, tenure, age and social economic group. These probabilities formed the basis of scenarios in which the water savings from a particular behaviour were applied to the synthetic household population to determine overall water savings by ward and for the city of Leeds as a whole. Scenarios involving a single behavioural change and multiple behaviours together were investigated. A sensitivity analysis was applied to these results to consider over-estimation in both the probabilities of likely adoption of a particular behaviour in the future and the amount of water that would be saved by adopting the behaviour. The results showed that the maximum possible savings under the most optimistic multi-behavioural scenario is 30%. Given a more realistic scenario of adoption of the three most likely behaviours from the survey, the maximum potential savings are on the order of 7%.
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Książki na temat "Residential water demand"

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Walters, Laurie L. Economic factors affecting residential water demand in Colorado. Fort Collins, Colo: Colorado Water Resources Research Institute, Colorado State University, 1994.

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Munian, A. Dynamics of residential water demand and supply in India: A case study of Chennai City. New Delhi: Gyan Pub. House, 2010.

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Dale, Larry L. Price impact on the demand for water and energy in California residences: Final paper. Sacramento, Calif.]: California Energy Commission, 2009.

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Grima, Angelo P. Residential Water Demand: Alternative Choices for Management. University of Toronto Press, 2019.

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McDonald, A. D. Residential Water Demand: A Case Study in the Lower Hunter Valley (Agricultural Economics Bulletin). University of New England, 1995.

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Części książek na temat "Residential water demand"

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Koundouri, P., M. Stithou i P. Melissourgos. "Simulating Residential Water Demand and Water Pricing Issues". W Water Resources Management Sustaining Socio-Economic Welfare, 71–86. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7636-4_4.

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Di Mauro, A., G. F. Santonastaso, S. Venticinque i A. Di Nardo. "Open Datasets and IoT Sensors for Residential Water Demand Monitoring at the End-Use Level: A Pilot Study Site in Naples (Italy)". W Springer Water, 47–76. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95844-2_4.

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Garcia-Valiñas, Maria A., Roberto Martínez-Espiñeira i Hang To. "The Use of Non-pricing Instruments to Manage Residential Water Demand: What Have We Learned?" W Understanding and Managing Urban Water in Transition, 269–81. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9801-3_12.

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Vongtanaboon, Sukanya. "Water Resource Assessment and Management in Phuket, Thailand". W Interlocal Adaptations to Climate Change in East and Southeast Asia, 153–56. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81207-2_17.

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AbstractWithin the context of climate change, the province of Phuket in Thailand is the only province in Thailand without any large rivers, which means that it is potentially at risk from problems associated with water scarcity in the future. Phuket Island is also the largest island in Thailand with an area of 543 km2 comprised of three districts (Thalang, Muang and Kathu); 77% of the island is mountainous and 23% consists of plains, primarily in the central and eastern regions. Most water is derived from rainfall, which is stored in reservoirs, mine shafts, and groundwater sources. Due to geography, Phuket is a popular tourist destination. Rates of development in the hotel industry and residential areas, as well as the population, have been rapid in recent decades. However, these developments have severely degraded watershed areas. Economic growth and increases in the number of tourists has resulted in an increase in demand for water, and in the year 2020 consumption exceeded 100,000 m3/day (Provincial Waterworks Authority 2020). Moreover, trends of water use in Phuket are expected to increase by 12% annually, and it is forecasted that the water demand for local consumption and tourism will rise to 103.07 million m3/year in 2032 (Patong Municipality 2020). As the water supply in the three major reservoirs (Bang Wad, Bang Niew Dam and Klong Katha) are limited due to long periods of a dry weather (Provincial Waterworks Authority 2020), there are problems of water scarcity in Phuket and other areas with public water systems in the province. The droughts in 2002 and 2019–2020 caused severe water scarcity in Phuket, and this has become an important issue that the province needs to address.
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Renzetti, Steven. "Residential Water Demands". W The Economics of Water Demands, 17–34. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0865-6_3.

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Klassert, Christian, Erik Gawel, Katja Sigel i Bernd Klauer. "Sustainable Transformation of Urban Water Infrastructure in Amman, Jordan – Meeting Residential Water Demand in the Face of Deficient Public Supply and Alternative Private Water Markets". W Future City, 93–115. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59324-1_6.

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Tsimpo, Clarence, i Quentin Wodon. "Demand and Supply Constraints to Piped Water Coverage". W Residential Piped Water in Uganda, 27–46. The World Bank, 2018. http://dx.doi.org/10.1596/978-1-4648-0708-4_ch3.

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Ward, Michael, i Chris White. "Managing residential water demand in the OECD". W Global Water: Issues and Insights. ANU Press, 2014. http://dx.doi.org/10.22459/gw.05.2014.03.

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Renwick, Mary E., i Sandra O. Archibald. "Demand Side Management Policies for Residential Water Use: Who Bears the Conservation Burden?" W Economics of Water Resources, 373–89. Routledge, 2018. http://dx.doi.org/10.4324/9781351159289-24.

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Nieswiadomy, Michael L., i David J. Molina. "Comparing Residential Water Demand Estimates under Decreasing and Increasing Block Rates Using Household Data". W Economics of Water Resources, 363–72. Routledge, 2018. http://dx.doi.org/10.4324/9781351159289-23.

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Streszczenia konferencji na temat "Residential water demand"

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Gato-Trinidad, S., i K. Gan. "Characterizing maximum residential water demand". W Urban Water 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/uw120021.

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Alcocer, Y. V. H., V. G. Tzatchkov, S. G. Buchberger, F. I. Arreguin i D. Feliciano. "Stochastic Residential Water Demand Characterization". W World Water and Environmental Resources Congress 2004. Reston, VA: American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40737(2004)459.

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Gargano, R., C. Tricarico i G. de Marinis. "Residential Water Demand-Daily Trends". W 12th Annual Conference on Water Distribution Systems Analysis (WDSA). Reston, VA: American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/41203(425)118.

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Tanverakul, Stephanie A., i Juneseok Lee. "Historical Review of U.S. Residential Water Demand". W World Environmental And Water Resources Congress 2012. Reston, VA: American Society of Civil Engineers, 2012. http://dx.doi.org/10.1061/9780784412312.313.

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Pieterse-Quirijns, E. J., E. J. M. Blokker, J. H. G. Vreeburg i E. v.d. Blom. "Modelling Characteristic Values for Non-Residential Water Demand". W 12th Annual Conference on Water Distribution Systems Analysis (WDSA). Reston, VA: American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/41203(425)111.

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Tanverakul, Stephanie A., i Juneseok Lee. "Residential Water Demand Analysis Due to Water Meter Installation in California". W World Environmental and Water Resources Congress 2013. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784412947.090.

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Blokker, E. J. M., i J. H. G. Vreeburg. "Monte Carlo Simulation of Residential Water Demand: A Stochastic End-Use Model". W World Water and Environmental Resources Congress 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40792(173)34.

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Filion, Y. R., Z. Li i S. G. Buchberger. "Temporal and Spatial Scaling of Instantaneous Residential Water Demand for Network Analysis". W World Environmental and Water Resources Congress 2007. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)512.

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Filion, Y. R., B. W. Karney, L. Moughton, S. G. Buchberger i B. J. Adams. "Cross Correlation Analysis of Residential Demand in the City of Milford, Ohio". W Eighth Annual Water Distribution Systems Analysis Symposium (WDSA). Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40941(247)43.

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Yanhui, Dong, i Zhou Weibo. "Urban Residential Water Demand Forecasting in Xi'an Based on RBF Model". W 2009 International Conference on Energy and Environment Technology. IEEE, 2009. http://dx.doi.org/10.1109/iceet.2009.456.

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Raporty organizacyjne na temat "Residential water demand"

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Klaiber, H. Allen, V. Kerry Smith, Michael Kaminsky i Aaron Strong. Measuring Price Elasticities for Residential Water Demand with Limited Information. Cambridge, MA: National Bureau of Economic Research, sierpień 2012. http://dx.doi.org/10.3386/w18293.

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Frandsen, Martin, Jakob Vind Madsen, Rasmus Lund Jensen i Michal Zbigniew Pomianowski. Domestic water measurement in two Danish office and educational buildings - Data set description. Aalborg University, sierpień 2022. http://dx.doi.org/10.54337/aau481810642.

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Measurement data of domestic water in non-residential buildings is sparse. More data is needed to describe the non-residential buildings’ domestic hot water (DHW) demand and to be able to design more efficient DHW systems. This DCE Technical Report aims to present and describe the data set: “Data set - Domestic water at CREATE and TMV23”. This data set contains measurement data from two office and educational buildings in Aalborg, Denmark. The measurements in the building CREATE are conducted from October 2018 to January 2019 and in the building TMV23 from April 2021 to May 2021. The data set consists of water flow rates and temperatures for the domestic cold water, domestic hot water, district heating for DHW production, and DHW circulation circuit.
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Ally, M. R. Water and Energy Savings using Demand Hot Water Recirculating Systems in Residential Homes: A Case Study of Five Homes in Palo Alto, California. Office of Scientific and Technical Information (OSTI), listopad 2002. http://dx.doi.org/10.2172/885864.

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