Using machine learning methods to analyze drivers of water quality
Description
To increase our understanding of drivers of water quality.
Detailed example
Predicted measures of water quality (e.g., concentrations or HABs) and violations.
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
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Use of these methods will help better inform water quality management activities.
Audit / financial statement impact
The output of this AI use case does not serve as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.
Controls / human review
ATO: No; PIA: Not published
Data needed
Variables related to watershed land use, nutrient inputs, socioeconomic factors, climate, and other parameters