New Tools Are Needed To Make Water Affordable

Rising water prices are forcing many households in the United States to choose between rationing water or risking shutoff by leaving bills unpaid. A new study in Environmental Research Letters shows government agencies and water utilities may be underestimating the true number of households at risk of losing affordable access to basic water service - and offers a solution.

"Water affordability is a growing problem and we need new tools to better address it," said senior study author Sarah Fletcher, an assistant professor of civil and environmental engineering in the Stanford Doerr School of Sustainability and School of Engineering. Aging water infrastructure, climate change, extreme droughts, and increasing costs tied to water quality maintenance all threaten to exacerbate the challenge, which disproportionately affects low-income households and communities of color.

"Applying the methods we demonstrated in this study could provide a better sense of how many households are currently struggling to pay their water bills," said Aniket Verma, a PhD student in civil and environmental engineering who co-led the June 21 study with Jennifer Skerker, also a PhD student.

Water affordability is a growing problem and we need new tools to better address it."

Sarah FletcherAssistant Professor of Civil and Environmental Engineering

Accurate assessments of water affordability are important because they inform decisions about utility rates, assistance programs, and eligibility for government financing for infrastructure improvements. The U.S. Environmental Protection Agency, which sets limits for contaminants including dangerous "forever chemicals" in drinking water, considers affordability when evaluating the impact of new standards on water suppliers and when negotiating deadlines for wastewater treatment facilities to comply with regulations.

Problems with the affordability ratio

Water utilities, non-governmental organizations, and regulators generally assess water affordability by looking at total monthly water bills as a portion of household income, or what experts call the "affordability ratio."

The method has faced growing criticism because affordability ratios fail to capture a given household's actual water needs, which depend on family size, appliance efficiency, and other factors. Furthermore, the affordability ratio is usually obtained as an average or snapshot in time of a census block or city, meaning the metric is not specific to individual households or necessarily accurate over the longer term.

"The traditional metric compares a household's water bill to the household's income as a way of trying to assess the household's ability to pay, but there are important nuances that this metric cannot capture and it's not granular enough in many cases," said Fletcher, who is also a fellow at the Stanford Woods Institute for the Environment.

The new Stanford research suggests metrics based on past payment behavior at the individual household level can provide a clearer view for water planners and regulators, policymakers, and non-governmental organizations.

Moving beyond the status quo

To explore new ways of evaluating water affordability, the Stanford researchers drew upon 13 years of water billing data for about 40,000 households in Santa Cruz, a small coastal city in California with a wide income distribution.

Fourteen percent of households surveyed across the U.S. report that a $12 increase in monthly water bills would lead to cutbacks on other essential goods.

The researchers applied to this dataset a series of so-called delinquency metrics based on water bill payment patterns, similar to metrics used to assess housing and energy affordability. Unlike the standard water affordability ratio, these delinquency metrics are tied more to a household's day-to-day financial decisions.

"Delinquency metrics aim to gauge a given household's ability to pay based on how well that household has actually been able to pay in the past," said Skerker. "Our study is the first to compare potential delinquency metrics that might capture different aspects than the affordability ratio."

Fletcher and colleagues designed three delinquency metrics. The first is frequency, measuring how often, on average, a household falls behind on its water bill. The second metric is duration, capturing how long, on average, a household does not pay their bill. The third metric is severity, meaning how much water bill debt a household goes into when not paying the bill.

A new approach to ensuring water access

Intriguingly, the study revealed that census blocks with similar affordability ratios, which would ordinarily be lumped together, often displayed a wide range of delinquency behavior. This finding indicates that the widely used affordability ratio approach might gloss over subpopulations of households struggling to maintain access to water for drinking and sanitation, a fundamental human right.

Overall, the study suggests that delinquency metrics could reveal a lot more about water security in households than the standard approach.

One obstacle to applying these metrics more broadly is that household billing information is generally not publicly available and would require utility provision through data use agreements. However, Fletcher said many utilities are interested in targeting outreach to at-risk households to spread awareness of financial assistance and water-use-reducing appliance efficiency programs. In addition, the delinquency metrics could help inform the design of such programs.

"I see real potential value for uptake by the utilities themselves of the approaches evaluated in our study," said Fletcher. "Water security is a serious issue and any advances that can be made in addressing it could help a lot of people."

Study co-author Benjamin Rachunok worked on the study as a postdoctoral scholar in the Department of Civil and Environmental Engineering in the Stanford Doerr School of Sustainability and the School of Engineering, and is now affiliated with North Carolina State University. Additional co-authors are affiliated with University of Wisconsin-Madison.

This research was supported by Stanford Impact Labs and the Stanford UPS Endowment Fund.

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