Drivers of Spatiotemporal Variability in Drinking Water Quality in the United States

Approximately
10% of community water systems in the United States
experience a health-based violation of drinking water quality; however,
recently allocated funds for improving United States water infrastructure
($50 billion) provide an opportunity to address these issues. The
objective of this study was to examine environmental, operational,
and sociodemographic drivers of spatiotemporal variability in drinking
water quality violations using geospatial analysis and data analytics.
Random forest modeling was used to evaluate drivers of these violations,
including environmental (e.g., landcover, climate, geology), operational
(e.g., water source, system size), and sociodemographic (social vulnerability,
rurality) drivers. Results of random forest modeling show that drivers
of violations vary by violation type. For example, arsenic and radionuclide
violations are found mostly in the Southwest and Southcentral United
States related to semiarid climate, whereas disinfection byproduct
rule violations are found primarily in Southcentral United States
related to system operations. Health-based violations are found primarily
in small systems in rural and suburban settings. Understanding the
drivers of water quality violations can help develop optimal approaches
for addressing these issues to increase compliance in community water
systems, particularly small systems in rural areas across the United
States.