Scale effects and implications of the stochastic structure of customer water demands

Sarai Díaz, Javier González, Kevin Lansey, Michael Pointl

Research output: Contribution to journalArticlepeer-review

Abstract

The effect of different temporal (from seconds to months) and spatial aggregation scales (from individual users to full urban areas) on water demand behavior has been explored to a limited degree. The effort described here extends those works by evaluating the scale effects of residential water consumption in a unique US data set that covers 10,000 households with a 1-gallon (3.79 L) hourly resolution over 2 years. A preliminary data analysis and a sequential Principal Component Analysis (PCA) is carried out to assess the effect of different temporal (weekly, daily, hourly) and spatial aggregation (individual meters and groups every 10, 100 and 1,000 meters) levels on demand. Results show that individual users act very differently from each other, and individual consumer variability is only canceled out when a significant number of households are aggregated. The implications of this finding are assessed from a hydraulic modeling perspective as the spatiotemporal scale of measurements may condition the type of analysis that can be carried out in practice. However, additional work is needed to explore the point at which it may be worth embracing a micro (per fixture/household) or a macro (per node/network) approach for different purposes.

Original languageEnglish (US)
Pages (from-to)1251-1272
Number of pages22
JournalJournal of Hydroinformatics
Volume26
Issue number6
DOIs
StatePublished - Jun 1 2024
Externally publishedYes

Keywords

  • COVID
  • hydraulic modeling
  • principal component analysis
  • scaling laws
  • water demand

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology
  • Geotechnical Engineering and Engineering Geology
  • Atmospheric Science

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