2016
DOI: 10.5942/jawwa.2016.108.0003
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Short‐Term Forecasting Analysis for Municipal Water Demand

Abstract: 2 0 0 3 2 0 0 7 2 0 1 1 50 0 40 30 20 10 E28 2016

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Cited by 10 publications
(7 citation statements)
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“…Furthermore, we do not know how household incomes and expenses other than water will change over that period. We do note that Fullerton et al [ 38 ] found an elasticity of -0.32 (a 10% rate increase would produce a 3.2% decrease in water demand) for monthly water use in El Paso. They also found that, at least for monthly water use, water consumers tend to react more quickly to changes in climatic conditions than to changes in price, which could dampen the impact of price on reducing demand and heighten the impact of expected increases in temperature.…”
Section: Resultsmentioning
confidence: 62%
See 1 more Smart Citation
“…Furthermore, we do not know how household incomes and expenses other than water will change over that period. We do note that Fullerton et al [ 38 ] found an elasticity of -0.32 (a 10% rate increase would produce a 3.2% decrease in water demand) for monthly water use in El Paso. They also found that, at least for monthly water use, water consumers tend to react more quickly to changes in climatic conditions than to changes in price, which could dampen the impact of price on reducing demand and heighten the impact of expected increases in temperature.…”
Section: Resultsmentioning
confidence: 62%
“…An important limitation is that we do not incorporate price-demand responses in our analysis. As in most municipalities, water consumption in El Paso follows an inverse and inelastic relationship with price [ 38 ]. However, we did not have confidence in applying price-demand relationships because that would assume that drivers of water use would remain constant 50 years into the future.…”
Section: Resultsmentioning
confidence: 99%
“…Big data collected from sensors are a necessary food for DL to generate those predictions but, at the same time, are a challenge requiring decisions to choose only relevant data from a huge data set [141]. The dire need for the development of decision support systems came due to an explosive economic urban growth [142,143]. Sustainability of water resources entails a complex urban water management system, integrating new technologies and decision-making systems to facilitate data modeling and consumption efficiency [144,145].…”
Section: Decision Support Systemsmentioning
confidence: 99%
“…Given its prominence as a growing metropolitan economy located in a semi-arid desert setting, El Paso water consumption has been dissected in a number of empirical studies. Among the topics examined in these efforts are short-range consumption reactions to weather and economic stimuli [24], surface usage rights transfers [25], long-term historical forecast accuracy [26], and short-term consumption prediction accuracy during business cycle downturns [27]. Of course, El Paso still faces important policy questions regarding the provision of municipal water services.…”
Section: Previous Researchmentioning
confidence: 99%