Sensitivity Analysis of Using Municipal Boundaries as a Proxy for Service Area Boundaries When Calculating Water Affordability Metrics
Water is essential for life, and yet one of the nation’s most pressing water challenges has become ensuring that water services are affordable for households and communities. While there has been growing attention and concern around affordable water services, the actual scale of the problem remains poorly understood, in part because of the lack of data availability. The Nicholas Institute’s Water Affordability Dashboard was developed to provide several affordability metrics pulling together publicly available data from different sources: census data, rates data, and digital service area boundaries. As of January 2022, the dashboard provided affordability metrics for over 3,000 utilities located within 10 states, showing that between a tenth to a third of households struggle with affording water services. The ability to understand affordability challenges in other states is limited in states without digital service area boundaries. Digital service area boundaries are used to identify which communities are served by drinking water and wastewater utilities. A recent inventory by McDonald et al. (2022) shows that over half of the states do not have digital water service area boundaries. This study sought to determine if municipal boundaries could be used as a proxy for service area boundaries when calculating water affordability metrics. We explored several proxy (substitute) geographical boundaries by using different methods to (1) identify municipalities served by water service providers, (2) obtain the digital proxy boundaries (i.e., state provided municipal boundaries or nationally available census places), and (3) account for “outside” service areas for utilities for utilities that charge different rates to customers located outside municipal boundaries (Table ES1). Four affordability metrics were estimated using five different proxies for service area boundaries across 154 utilities representing a sample of states (California, New Jersey, New Mexico, North Carolina, Pennsylvania, Texas, and Washington), system size (small, medium, medium-large, large, and very large), and ownership type (public and private). There was good correlation (Spearman > 0.95) between affordability metrics using service area boundaries and all proxy geographical boundaries. The overall results indicate that municipal boundaries may serve as a proxy for digital service areas for calculating affordability metrics for public municipal water systems, with a median difference for all affordability metrics within ±0.30% of metrics when calculated using service area boundaries.
