Location: Agroecosystems Management Research
Project Number: 5030-13000-012-026-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jul 1, 2026
End Date: Aug 30, 2027
Objective:
1. Perform integrative models of pollutant fate and transport in the South Fork of the Iowa River (SFIR) agricultural watershed using the Conservation Effects Assessment Project (CEAP) datasets. Use parameterized and validated integrated models to quantify the impacts of conservation practices and hydrologic processes on nutrient reduction.
2. Use machine learning models to analyze the long-term SFIR watershed water quantity and water quality data to determine trends and create useful spatial and temporal maps of sediment and nutrients over time as impacted by weather variability and land use changes.
3. Use corn hybrids database, sim model, and water quality datasets to perform simulation analyses to quantify the impact of corn improvement on water quality.
Approach:
The integrated Machine Learning-SWAT+ modeling framework will be parameterized and validated using the CEAP datasets and used to quantify the impact of conservation practices (such as bioreactors, cover crops, saturated buffers) and hydrologic processes on nutrient reduction at the SFIR CEAP watershed. Machine learning models will be used to analyze the long-term SFIR watershed water quantity and water quality data to determine trends and create useful spatial and temporal maps of sediment and nutrients over time as impacted by weather variability and land use changes. In addition, cooperator experimental database on corn hybrids, sim model, and water quality datasets from SFIR watershed will be used to conduct simulation analyses to quantify the impact of crop improvement through breeding and agronomic management on water quality.