Characterizing Patterns and Drivers of Single‐Family Household Water Uses in Arizona Using High‐Resolution Smart‐Metered Data

ABSTRACT This study aims to characterize single‐family household water consumption utilizing smart‐metered subdaily water use data from more than 700 single‐family households across the state of Arizona in the United States for the water year 2022. Using statistical evidence, we identify factors that drive household water consumption such as the number of occupants, appliance efficiency, and the presence of a swimming pool. Furthermore, climate and other regional drivers of water use are investigated. The analysis encompasses mixed‐effects regression models to assess water use patterns on daily, weekly, monthly, and seasonal time‐steps. The findings show that approximately 64% of water consumption in Arizona was used for outdoor purposes. Households with a swimming pool use approximately 56% more water overall than those without a pool. Even indoor water use is nearly 26% greater in households with a swimming pool. Deep analysis of smart‐metered water use data offers greater insights into the efficiency levels of appliances in a household. Households with high‐efficiency appliances use about 18.5% less water than households without high‐efficiency appliances. Analysis indicates that log‐linear mixed‐effects regression models provide the most robust assessments for relating water consumption with household and regional factors. This study helps water managers identify and implement water conservation and demand reduction strategies in single‐family neighborhoods.

Authors

Institutions

Publication Details

Journal
JAWRA Journal of the American Water Resources Association
Published
2025-04-01
DOI
https://doi.org/10.1111/1752-1688.70016
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterizing Patterns and Drivers of Single‐Family Household Water Uses in Arizona Using High‐Resolution Smart‐Metered Data

Cibi Vishnu Chinnasamy, Mazdak Arabi, Péter Mayer, Travis Warziniack et al.
JAWRA Journal of the American Water Resources Association
Water resources management and optimization
article

Characterizing Patterns and Drivers of Single‐Family Household Water Uses in Arizona Using High‐Resolution Smart‐Metered Data

Cibi Vishnu Chinnasamy, Mazdak Arabi, Péter Mayer, Travis Warziniack, Grant Bernosky
article en

Abstract

ABSTRACT This study aims to characterize single‐family household water consumption utilizing smart‐metered subdaily water use data from more than 700 single‐family households across the state of Arizona in the United States for the water year 2022. Using statistical evidence, we identify factors that drive household water consumption such as the number of occupants, appliance efficiency, and the presence of a swimming pool. Furthermore, climate and other regional drivers of water use are investigated. The analysis encompasses mixed‐effects regression models to assess water use patterns on daily, weekly, monthly, and seasonal time‐steps. The findings show that approximately 64% of water consumption in Arizona was used for outdoor purposes. Households with a swimming pool use approximately 56% more water overall than those without a pool. Even indoor water use is nearly 26% greater in households with a swimming pool. Deep analysis of smart‐metered water use data offers greater insights into the efficiency levels of appliances in a household. Households with high‐efficiency appliances use about 18.5% less water than households without high‐efficiency appliances. Analysis indicates that log‐linear mixed‐effects regression models provide the most robust assessments for relating water consumption with household and regional factors. This study helps water managers identify and implement water conservation and demand reduction strategies in single‐family neighborhoods.

JAWRA Journal of the American Water Resources AssociationVol. 61(2)
US Forest Service (US), Rocky Mountain Research Station (US), Colorado State University (US)
National Science Foundation, U.S. Department of Agriculture
Openalex Percentile: Top 91%
Water resources management and optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.