This cooperative agreement, funded with $448,056 from the infrastructure investment and jobs act, provides the pennsylvania state university with incremental funding of $298,299 to support the…

This cooperative agreement, funded with $448,056 from the infrastructure investment and jobs act, provides the pennsylvania state university with incremental funding of $298,299 to support the integration of machine learning approaches into modeling of the chesapeake BAY watershed. Federal funds of $149,757 are contingent upon availability. Activities:the tasks that will be completed under this agreement include development of machine learning models to assess the effects of fine-scale landforms and land use on nutrient and sediment delivery potential to the chesapeake BAY watershed stream system at the NHD100K scale; use of machine learning methods to temporally downscale long-term estimations to hourly estimates of flow, temperature, and concentration at the NHD100K scale; and development of approaches to integrate the methods or findings of these activities into the chesapeake BAY program partnership's phase 7 watershed model to predict the effects of management on temperature, nutrients, and sediment. Subrecipient:no subawards are included in this assistance agreement.outcomes:this project supports achievement of the goals and outcomes of the chesapeake BAY watershed agreement. The expected outcome is improved decision-making and leadership in setting future nutrient reduction goals as a result of increased knowledge and understanding of watershed processes. Beneficiaries include the chesapeake BAY program partnership and environmental decision-makers and leaders in the chesapeake BAY watershed.