This data set is a national map of predicted probability of nitrate contamination of shallow ground waters based on a logistic regression (LR) model. The LR model was used to predict the probability of nitrate contamination exceeding 4 mg/L in predominantly shallow, recently recharged ground waters of the United States.

The model contains variables representing (1) nitrogen (N) fertilizer loading, (2) percent cropland-pasture, (3) natural log of human population density, (4) percent well-drained soils, (5) depth to the seasonally high water table, and (6) presence or absence of unconsolidated sand and gravel aquifers. Observed and average predicted probabilities associated with deciles of risk are well correlated (r2 = 0.875), indicating that the LR model fits the data well. The likelihood of nitrate contamination is greater in areas with high N loading and well-drained surficial soils over unconsolidated sand and gravels. The LR model correctly predicted the status of nitrate contamination in 75 percent of wells in a validation data set from the National Water-Quality Assessment (NAWQA) program. Considering all wells used in both calibration and validation, observed median nitrate concentration increased from 0.24 to 8.30 mg/L as the mapped probability of nitrate exceeding 4 mg/L increased from less than or equal to 0.17 to greater than 0.83.