Academic literature on the topic 'End use water models'
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Journal articles on the topic "End use water models"
White, S., G. Milne, and C. Riedy. "End use analysis: issues and lessons." Water Supply 4, no. 3 (June 1, 2004): 57–66. http://dx.doi.org/10.2166/ws.2004.0043.
Full textCahill, R., J. R. Lund, B. DeOreo, and J. Medellín-Azuara. "Household water use and conservation models using Monte Carlo techniques." Hydrology and Earth System Sciences 17, no. 10 (October 15, 2013): 3957–67. http://dx.doi.org/10.5194/hess-17-3957-2013.
Full textCahill, R., J. R. Lund, B. DeOreo, and J. Medellín-Azuara. "Household water use and conservation models using Monte Carlo techniques." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 17, 2013): 4869–900. http://dx.doi.org/10.5194/hessd-10-4869-2013.
Full textSebri, Maamar. "ANN versus SARIMA models in forecasting residential water consumption in Tunisia." Journal of Water, Sanitation and Hygiene for Development 3, no. 3 (February 15, 2013): 330–40. http://dx.doi.org/10.2166/washdev.2013.031.
Full textRummukainen, M., J. Räisänen, D. Bjørge, J. H. Christensen, O. B. Christensen, T. Iversen, K. Jylhä, H. Ólafsson, and H. Tuomenvirta. "Regional Climate Scenarios for use in Nordic Water Resources Studies." Hydrology Research 34, no. 5 (October 1, 2003): 399–412. http://dx.doi.org/10.2166/nh.2003.0014.
Full textLee, Soo-Jin, You-Jeong Kim, Hye-Sun Jin, Sung-Im Kim, Soo-Yeon Ha, and Seung-Yeong Song. "Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis." Energies 12, no. 12 (June 18, 2019): 2327. http://dx.doi.org/10.3390/en12122327.
Full textMateus, Marcos, Ricardo Vieira, Carina Almeida, Miguel Silva, and Filipa Reis. "ScoRE—A Simple Approach to Select a Water Quality Model." Water 10, no. 12 (December 9, 2018): 1811. http://dx.doi.org/10.3390/w10121811.
Full textMundi, Gurvinder, Richard G. Zytner, Keith Warriner, Hossein Bonakdari, and Bahram Gharabaghi. "Machine Learning Models for Predicting Water Quality of Treated Fruit and Vegetable Wastewater." Water 13, no. 18 (September 10, 2021): 2485. http://dx.doi.org/10.3390/w13182485.
Full textLee, Sanghoon, Dugin Kaown, Eun‐Hee Koh, Kyung‐Seok Ko, and Kang‐Kun Lee. "Delineation of groundwater quality locations suitable for target end‐use purposes through deep neural network models." Journal of Environmental Quality 50, no. 2 (March 2021): 416–28. http://dx.doi.org/10.1002/jeq2.20206.
Full textKotowski, Jerzy, Jacek Oko, and Monika Żygadło. "Simulation of water supply networks using modern means of information technology." E3S Web of Conferences 44 (2018): 00076. http://dx.doi.org/10.1051/e3sconf/20184400076.
Full textDissertations / Theses on the topic "End use water models"
Gato, Shirley, and 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.
Full textScheepers, Hester Maria. "Deriving peak factors for residential indoor water demand by means of a probability based end-use model." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71639.
Full textENGLISH ABSTRACT: The expected peak water demand in a water distribution system (WDS) is an important consideration for WDS design purposes. In South Africa the most common method of estimating peak demand is by multiplying the average demand by a dimensionless peak factor. A peak factor is the ratio between the maximum flow rate (which refers to the largest volume of flow to be received during a relatively short time period, say , expressed as the average volume per unit time), and the average flow rate over an extended time period. The magnitude of the peak factor will vary, for a given daily water demand pattern, depending on the chosen value of . The design guidelines available give no clear indication of the time intervals most appropriate for different peak factor applications. It is therefore important to gain a better understanding regarding the effect of on the derived peak factor. A probability based end-use model was constructed as part of this study to derive diurnal residential indoor water demand patterns on a temporal scale of one second. These stochastically derived water demand patterns were subsequently used to calculate peak factors for different values of , varying from one second to one hour. The end-use model derived the water demand patterns by aggregating the synthesised end-use events of six residential indoor end-uses of water in terms of the water volume required, duration and the time of occurrence of each event. The probability distributions describing the end-use model parameters were derived from actual end-use measurements that had previously been collected in a noteworthy North-American end-use project (Mayer et al., 1999). The original comprehensive database, which included water measurements from both indoor and outdoor end-uses, was purchased for use in this project. A single execution of the end-use model resulted in the synthesised diurnal water demand pattern for a single household. The estimated water demand pattern for simultaneous water demand by groups of households was obtained by adding individual iterations of the end-use model, considering group sizes of between one and 2 000 households in the process. A total of 99 500 model executions were performed, which were statistically aggregated by applying the Monte Carlo method and forming 4 950 unique water demand scenarios representing 29 different household group sizes. For each of the 4 950 water demand scenarios, a set of peak factors was derived for eight selected values. The end-use model presented in this study yielded realistic indoor water demand estimations when compared to publications from literature. In agreement with existing knowledge, as expected, an inverse relationship was evident between the magnitude of the peak factors and . The peak factors across all time intervals were also found to be inversely related to the number of households, which agreed with other publications from literature. As the number of households increased, the degree to which the peak factor was affected by the time intervals decreased. This study explicitly demonstrated the effect of time intervals on peak factors. The results of this study could act as the basis for the derivation of a practical design guideline for estimating peak indoor flows in a WDS, and the work could be extended in future to include outdoor water demand and sensitivity to WDS pressure.
AFRIKAANSE OPSOMMING: Die verwagte water spitsaanvraag is ‘n belangrike oorweging in die ontwerp van ‘n waterverspreidingsnetwerk. Die mees algemene metode in Suid Afrika om spitsaanvraag te bereken is deur die gemiddelde wateraanvraag te vermeningvuldig met ‘n dimensielose spitsfaktor. ‘n Spitsfaktor is die verhouding tussen die maksimum watervloei tempo (wat verwys na die grootste volume water wat ontvang sal word tydens ‘n relatiewe kort tydsinterval, , uitgedruk as die gemiddelde volume per tyd eenheid), en die gemiddelde watervloei tempo gedurende ‘n verlengde tydsinterval. Die grootte van die spitsfaktor sal varieer vir ‘n gegewe daaglikse vloeipatroon, afhangende van die verkose waarde. Die beskikbare ontwerpsriglyne is onduidelik oor watter tydsintervalle meer geskik is vir die verskillende spitsfaktor toepassings. Daarom is dit belangrik om ‘n beter begrip te verkry ten opsigte van die effek van op die verkrygde spitsfaktor. ‘n Waarskynliksheidsgebaseerde eindverbruik model is opgestel om deel te vorm van hierdie studie, om daaglikse residensiële binnenshuise wateraanvraag patrone af te lei op ‘n temporale skaal van een sekonde. Die stogasties afgeleide wateraanvraag patrone is daarna gebruik om die verskeie spitsfaktore te bereken vir verskillende waardes van , wat varieer vanaf een sekonde tot een uur. Die eindverbruik model stel die daaglikse vloeipatroon van een huis saam deur die eindeverbruik gebeure van ses residensiële binnenshuise eindverbruike saam te voeg in terme van the vereiste water volume en die tyd van voorkoms van elke gebeurtenis. Die waarskynliksheids distribusie wat die eindverbruik model parameters omskryf is verkry van werklike gemete eindverbruik waardes, wat voorheen in ‘n beduidende Noord-Amerikaanse eindverbruik projek (Mayer et al. 1999) versamel is. Die oorspronklike en omvattende databasis, wat gemete waardes van binnenshuis en buite water verbruik ingesluit het, is aangekoop vir gebruik gedurende hierdie projek. ‘n Enkele uitvoering van die eindverbruik model stel gevolglik ‘n daaglikse wateraanvraag patroon saam vir ‘n elkele huishouding. Die wateraanvraag patroon vir gelyktydige water verbruik deur groepe huishoudings is verkry deur individuele iterasies van die eindverbruik model statisties bymekaar te tel met die Monte Carlo metode, terwyl groep groottes van tussen een en 2 000 huishoudings in die proses oorweeg is. ‘n Totaal van 99 500 model uitvoerings is gedoen, wat saamgevoeg is om 4 950 unieke watervraag scenarios voor te stel, wat verteenwoordigend is van 29 verskillende huishouding groep groottes. Vir elkeen van die 4 950 watervraag senarios, is ‘n stel spitsfaktore afgelei vir agt verkose waardes. Die eindverbruik model aangebied in hierdie studie lewer ‘n realistiese binnenshuise wateraanvraag skatting, wanneer dit vergelyk word met verslae in die literatuur. Ooreenkomstig met bestaande kennis is ‘n sterk inverse verhouding sigbaar tussen die grootte van die spitsfaktore en . Dit is ook gevind dat die spitsfaktore oor al die tydsintervalle ‘n inverse verband toon tot die aantal huishoudings, wat ooreenstemmend is met ander publikasies in die literatuur. Soos die aantal huishoudings toeneem, het die mate waartoe die spitsfaktor geaffekteer is deur die tydsintervalle afgeneem. Hierdie studie toon duidelik die effek van tydsintervalle op spitsfaktore. Die resultaat van hierdie studie kan dien as basis om praktiese ontwerpsriglyne te verkry in die skatting van binnenshuise spitsvloei in ‘n waterverspreidingsnetwerk, gegewe dat die werk in die toekoms uitgebrei kan word om ook buitenshuise waterverbruik in te sluit, asook sensitiwiteit tot druk in die waterverspreidingsnetwerk.
Zaman, Bushra. "Remotely Sensed Data Assimilation Technique to Develop Machine Learning Models for Use in Water Management." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/584.
Full textNorman, Laura Margaret. "Modeling Land Use Change and Associate Water Quality Impacts in the Ambos Nogales Watershed, US-Mexico Border." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1427%5F1%5Fm.pdf&type=application/pdf.
Full textHager, Christian Harding. "Ichthyofaunal and dietary analysis of sympatric piscivores in a Chesapeake Bay littoral zone: Including bioenergetic models of growth and diel temperature sanctuary use." W&M ScholarWorks, 2004. https://scholarworks.wm.edu/etd/1539616682.
Full textBoyd, Timothy David. "The Novel Use of Recombinant Granulocyte-Macrophage Colony-Stimulating Factor (GM-CSF) to Reverse Cerebral Amyloidosis and Cognitive Impairment in Alzheimer’s Disease Mouse Models: Insights from the Investigation of Rheumatoid Arthritis as a Negative Risk Factor for Alzheimer’s Disease." Scholar Commons, 2010. http://scholarcommons.usf.edu/etd/3571.
Full textDlamini, Musa V. "Short-Term Water Use Dynamics in Drainage Lysimeters." DigitalCommons@USU, 2003. https://digitalcommons.usu.edu/etd/5877.
Full textKane, Dellwyn. "Hydrograph separation using end member mixing models in the Oona Water river catchment, Co Tyrone." Thesis, University of Ulster, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529518.
Full textSmith, Kimberly C. (Kimberly Carolyn). "Evaluating PC-based water quality models as tools for land use planning." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/70200.
Full textMeeuwig, Jessica Jane. "All water is wet : predicting eutrophication in lakes and estuaries." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35918.
Full textBooks on the topic "End use water models"
E, Meena Hubert, ed. Dar es Salaam water demand: An end-use perspective. [Dar es Salaam]: Centre for Energy, Environment, Science, and Technology, 1998.
Find full textCalifornia. Department of Water Resources. Division of Planning. Central Valley future water supplies for use in DWRSIM. [Sacramento]: State of California, Resources Agency, Dept. of Water Resources, Division of Planning, 1995.
Find full textChowdhury, Nasima Tanveer. The relative efficiency of water use in Bangladesh agriculture. Kathmandu: South Asian Network for Development and Environmental Economics, 2010.
Find full textKeely, Joseph Francis. The use of models in managing ground-water protection programs. Ada, Okla: Office of Research and Development, U.S. Environmental Protection Agency, Robert S. Kerr Environmental Research Laboratory, 1987.
Find full textQueen, Rob. End-use efficient, environmentally friendly water-softening device: Independent assessment report. [Sacramento, Calif.]: California Energy Commission, 2007.
Find full textG, Cleveland Theodore, American Water Resources Association, and Boyle Engineering Corporation, eds. Advances in the development and use of models in water resources. Herndon, VA: AWRA, 1995.
Find full textBernier, L. Application of the water use analysis model to the Richelieu River Basin. Sainte-Foy, Quebec: Inland Waters Directorate, Quebec Region, Water Planning and Management Branch, 1990.
Find full textThe end of country. New York: Random House, 2011.
Find full textTate, Donald M. Alternative futures of Canadian water use, 1981-2011. [Ottawa]: Inquiry on Federal Water Policy, 1985.
Find full textTate, Donald M. Alternative futures of Canadian water use, 1981-2011. Hull: Inland Waters Directorate, 1985.
Find full textBook chapters on the topic "End use water models"
Novotny, Vladimir, and Andrea Capodaglio. "Use of Water Quality Models." In Remediation and Management of Degraded River Basins, 35–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-57752-9_2.
Full textNicks, A. D. "The Use of USLE Components in Models." In Modelling Soil Erosion by Water, 377–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58913-3_28.
Full textSiderius, Christian, Robel Geressu, Martin C. Todd, Seshagiri Rao Kolusu, Julien J. Harou, Japhet J. Kashaigili, and Declan Conway. "High Stakes Decisions Under Uncertainty: Dams, Development and Climate Change in the Rufiji River Basin." In Climate Risk in Africa, 93–113. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61160-6_6.
Full textRudra, R. P., W. T. Dickinson, and G. J. Wall. "Problems Regarding the Use of Soil Erosion Models." In Modelling Soil Erosion by Water, 175–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58913-3_13.
Full textOlesen, Emma T. B., Marleen L. A. Kortenoeven, and Robert A. Fenton. "Use of Genetic Models to Study the Urinary Concentrating Mechanism." In Sodium and Water Homeostasis, 43–72. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-3213-9_3.
Full textStöckle, Claudio O., Armen R. Kemanian, and Cristián Kremer. "On the Use of Radiation- and Water-Use Efficiency for Biomass Production Models." In Response of Crops to Limited Water, 39–58. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel1.c2.
Full textNadal-Sala, D., T. F. Keenan, S. Sabaté, and C. Gracia. "Forest Eco-Physiological Models: Water Use and Carbon Sequestration." In Managing Forest Ecosystems: The Challenge of Climate Change, 81–102. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28250-3_5.
Full textWesterhoff, Paul, and John Crittenden. "Urban Infrastructure and Use of Mass Balance Models for Water and Salt." In The Water Environment of Cities, 49–68. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-84891-4_4.
Full textGamboa, Reynato Andal, Chockalingam Aravind Vaithilingam, and Then Yih Shyong. "Cost Benefit Opportunity for End Use Segment Using Lighting Retrofit at Taylor’s University." In Practical Examples of Energy Optimization Models, 53–64. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2199-7_4.
Full textLeavesley, G. H., L. E. Hay, R. J. Viger, and S. L. Markstrom. "Use of a priori parameter-estimation methods to constrain calibration of distributed-parameter models." In Water Science and Application, 255–66. Washington, D. C.: American Geophysical Union, 2003. http://dx.doi.org/10.1029/ws006p0255.
Full textConference papers on the topic "End use water models"
Fu, Yang, and Wenyan Wu. "Behaviour interventions for water end use: An integrated model." In 2014 20th International Conference on Automation and Computing (ICAC). IEEE, 2014. http://dx.doi.org/10.1109/iconac.2014.6935498.
Full textBlokker, E. J. M., and J. H. G. Vreeburg. "Monte Carlo Simulation of Residential Water Demand: A Stochastic End-Use Model." In World Water and Environmental Resources Congress 2005. Reston, VA: American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40792(173)34.
Full textMusgrove, Rachel. "An End-Use Integrated Agent-Based Model to Simulate Consumer Demand for a Water Utility." In World Environmental and Water Resources Congress 2013. Reston, VA: American Society of Civil Engineers, 2013. http://dx.doi.org/10.1061/9780784412947.253.
Full textCarlevaro, Fausto, Stefano Cioncolini, Marzia Sepe, Ilaria Parrella, Carmine Allegorico, Laura De Stefanis, Mariagrazia Mastroianni, and Ernesto Escobedo. "Use of Operating Parameters, Digital Replicas and Models for Condition Monitoring and Improved Equipment Health." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-76849.
Full textRaneda, Albert, Mikko Siuko, and Tapio Virvalo. "Torque Control of a Water Hydraulic Vane Actuator Using Pressure Feedback." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39348.
Full textLeishear, Robert A. "Dynamic Pipe Stresses During Water Hammer: II — A Vibration Analysis." In ASME 2002 Pressure Vessels and Piping Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/pvp2002-1269.
Full textLyon, Geoff, Amip Shah, and Alan McReynolds. "Developing Resource Consumption Insights From Campus-Scale Water Monitoring Infrastructures." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88688.
Full textSheldon, Seth, and Ory Zik. "Water Scarcity: An Energy Problem." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88241.
Full textSumme, Alexander M., Douglas P. Munson, Kenneth Oliphant, and Sarah Chung. "Long Term Performance of PE4710 Materials in Disinfectant Treated Nuclear Raw Water Systems." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97477.
Full textYamamoto, Marcio, Tomo Fujiwara, Shigeo Kanada, Masao Ono, Satoru Takano, and Joji Yamamoto. "Experimental Analysis of Reduced-Scale Jumper for Deep-Sea Mining." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95990.
Full textReports on the topic "End use water models"
Jenicek, Elisabeth, Noah Garfinkle, Andy Hur, Bjorn Oberg, Nicholas Bartholomew, Sara Buchhorn, Kelly Chen, Lindsey Miller, and Munira Mithaiwala. Water Use Intensity at U.S. Army Facilities : An Investigation into Factors That Influence Potable Water End Use. Construction Engineering Research Laboratory (U.S.), August 2018. http://dx.doi.org/10.21079/11681/28040.
Full textKoomey, J. G., C. Dunham, and J. D. Lutz. The effect of efficiency standards on water use and water heating energy use in the US: A detailed end-use treatment. Office of Scientific and Technical Information (OSTI), May 1994. http://dx.doi.org/10.2172/10180643.
Full textSezgen, O., and J. G. Koomey. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/272538.
Full textBasch, Ethan, and Antonia Bennett. Development of Pain End Point Models for Use in Prostate Cancer Clinical Trials and Drug Approval. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada613282.
Full textFisher, Diane C., Camilla Dunham Whitehead, and Moya Melody. National and Regional Water and Wastewater Rates For Use inCost-Benefit Models and Evaluations of Water Efficiency Programs. Office of Scientific and Technical Information (OSTI), September 2006. http://dx.doi.org/10.2172/927324.
Full textPratt, R., and B. Ross. Measured electric hot water standby and demand loads from Pacific Northwest homes. End-Use Load and Consumer Assessment Program. Office of Scientific and Technical Information (OSTI), November 1991. http://dx.doi.org/10.2172/10105371.
Full textMarinshaw, Richard J., and Hazem Qawasmeh. Characterizing Water Use at Mosques in Abu Dhabi. RTI Press, April 2020. http://dx.doi.org/10.3768/rtipress.2020.mr.0042.2004.
Full textDay, St John, Tim Forster, and Ryan Schweitzer. Water Supply in Protracted Humanitarian Crises: Reflections on the sustainability of service delivery models. Oxfam, UNHCR, September 2020. http://dx.doi.org/10.21201/2020.6362.
Full textBitew, Menberu, and Rhett Jackson. Characterization of Flow Paths, Residence Time and Media Chemistry in Complex Landscapes to Integrate Surface, Groundwater and Stream Processes and Inform Models of Hydrologic and Water Quality Response to Land Use Activities; Savannah River Site. Office of Scientific and Technical Information (OSTI), February 2015. http://dx.doi.org/10.2172/1171150.
Full textSaville, Alan, and Caroline Wickham-Jones, eds. Palaeolithic and Mesolithic Scotland : Scottish Archaeological Research Framework Panel Report. Society for Antiquaries of Scotland, June 2012. http://dx.doi.org/10.9750/scarf.06.2012.163.
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