OMB Individually Reported
PFAS Groundwater Model
Low riskExact public inventory row
Description
We are building a model (likely random forest or boosted regression tree) to predict PFAS concentrations in groundwater supplies in the US.
Detailed example
prediction
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Predictions of PFAS in groundwater across the US. The intention is that the results can serve to inform states where sampling is needed and to reduce costs associated with sampling areas that aren't likely to have PFAS.
Controls / human review
ATO: No; PIA: Not published