This is a layer of water service boundaries for 44,919 community water systems that deliver tap water to 306.88 million people in the US. This amounts to 97.22% of the population reportedly served by active community water systems and 90.85% of active community water systems. The layer is based on multiple data sources and a methodology developed by SimpleLab and collaborators called a Tiered, Explicit, Match, and Model approach–or TEMM, for short. The name of the approach reflects exactly how the nationwide data layer was developed. The TEMM is composed of three hierarchical tiers, arranged by data and model fidelity. First, we use explicit water service boundaries provided by states. These are spatial polygon data, typically provided at the state-level. We call systems with explicit boundaries Tier 1. In the absence of explicit water service boundary data, we use a matching algorithm to match water systems to the boundary of a town or city (Census Place TIGER polygons). When a water system and TIGER place match one-to-one, we label this Tier 2a. When multiple water systems match to the same TIGER place, we label this Tier 2b. Tier 2b reflects overlapping boundaries for multiple systems. Finally, in the absence of an explicit water service boundary (Tier 1) or a TIGER place polygon match (Tier 2a or Tier 2b), a statistical model trained on explicit water service boundary data (Tier 1) is used to estimate a reasonable radius at provided water system centroids, and model a spherical water system boundary (Tier 3).

Several limitations to this data exist–and the layer should be used with these in mind. First, the case of assigning a Census Place TIGER polygon to multiple systems results in an inaccurate assignment of the same exact area to multiple systems; we hope to resolve Tier 2b systems into Tier 2a or Tier 3 in a future iteration. Second, matching algorithms to assign Census Place boundaries require additional validation and iteration. Third, Tier 3 boundaries have modeled radii stemming from a lat/long centroid of a water system facility; but the underlying lat/long centroids for water system facilities are of variable quality. It is critical to evaluate the "geometry quality" column (included from the EPA ECHO data source) when looking at Tier 3 boundaries; fidelity is very low when geometry quality is a county or state centroid– but we did not exclude the data from the layer. Fourth, missing water systems are typically those without a centroid, in a U.S. territory, or missing population and connection data. Finally, Tier 1 systems are assumed to be high fidelity, but rely on the accuracy of state data collection and maintenance.

All data, methods, documentation, and contributions are open-source and available here: https://github.com/SimpleLab-Inc/wsb.