Leveraging Machine Learning to Enhance Water Quality Predictions in Small Agricultural Streams
As part of the Lake Champlain Basin Program’s Opportunities for Action plan, Stone is developing a system for more accurate and timely characterization of phosphorus (P) loading from tributaries to the Northeast Arm of Lake Champlain.
This project addresses challenges that include the lack of monitoring data for small direct drainage streams (none were monitored prior to this study) and the high uncertainty in existing P load estimates in the Northeast Arm, a 370-square-kilometer region characterized by agricultural land use and dynamic hydrological conditions.