Well water data & methodology
Roughly 43 million Americans rely on private wells, which are not covered by the Safe Drinking Water Act โ testing is the owner's responsibility. To help owners gauge local risk before they test, we pair federal USGS groundwater models with EPA and USDA datasets to estimate county-area risk, and we are explicit about the limits.
These are area estimates โ not a test of your well
These figures are USGS area estimates: statistical groundwater models describing how likely elevated contaminant levels are across a county. They are not designed to predict the concentration in any single well. Only testing your own well reveals its water quality.
What we model
Arsenic โ probability of exceedance
A USGS national model estimates the probability that a private well in the county area exceeds 1, 5, and 10 ยตg/L (the EPA limit is 10 ยตg/L). The thresholds are fit as three independent models, so we only show the โฅ5 ยตg/L figure beneath the โฅ10 ยตg/L headline when the pair is coherent.
Nitrate โ predicted concentration
A USGS model predicts the nitrate (as N) concentration at domestic-supply depth for the county area. The EPA limit is 10 mg/L.
Private-well population
Modeled count of people and households on private (domestic) wells, from the USGS domestic-well population release combined with Census geography.
Uranium & radon (New Hampshire only)
New Hampshire publishes a state-specific groundwater model for uranium and radon; we surface it only for NH counties and label every other state as 'no state model available' rather than guess.
Primary aquifer
The dominant USGS principal aquifer mapped under the county โ area context for where wells draw from, not a determination for any single well.
Agricultural land use (crop pressure)
The row-crop fraction of the county area (USDA Cropland Data Layer). Intensive row-crop land raises nitrate risk, so it is a predictor we surface โ never a measurement of nitrate in a well.
PFAS โ public-system proxy
PFAS detections in nearby PUBLIC water systems under EPA's UCMR5 program. This is a regional proxy, explicitly NOT a measurement of any private well.
Observed samples & confidence
Reported monitoring samples from the EPA/USGS Water Quality Portal give a local-density signal that drives the per-page data-confidence chip (sparse vs. well-corroborated).
How we build & validate it
- County boundaries are reprojected into each raster's native coordinate system before zonal averaging, so every figure is read from the model exactly where the county sits.
- We never fabricate a number. A county missing a required national metric (arsenic, nitrate, or population) is not published at all; an optional layer with no real value is shown as "not available", never as zero.
- Every served county passes a schema + honesty validator before it can reach a page, so a malformed or partial record becomes a 404 rather than a misleading "0%".
- Community-contributed lab results are only ever shown as area-level aggregates once at least ten wells have reported โ never as an individual result.
Data sources
Every figure traces to a public federal dataset. The exact sources that contributed to a given county are listed on that county's page.
- USGS arsenic probability-of-exceedance modelCounty arsenic exceedance probabilities (1, 5, and 10 ยตg/L).
- USGS nitrate predicted concentration (domestic-supply depth)County predicted nitrate concentration.
- USGS domestic (private) well population densityEstimated people and households on private wells.
- USGS principal aquifersThe dominant principal aquifer mapped under each county.
- USGS New Hampshire uranium/radon groundwater modelNew Hampshire-only uranium and radon exceedance probabilities.
- USDA NASS Cropland Data Layer (CDL)Row-crop land-use fraction โ a nitrate-risk predictor, not a measurement.
- EPA UCMR5 (Fifth Unregulated Contaminant Monitoring Rule)PFAS occurrence in nearby PUBLIC water systems โ a regional proxy.
- EPA / USGS Water Quality PortalObserved monitoring samples used for local context + confidence.
- US Census TIGER/LineCounty boundaries / geography for the zonal models.
By TapWaterData Editorial.
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