FINAL REPORT

The key research questions for this project were: 

1) What are the key barriers hindering landowners’ and farmers’ adoption of critical edge-of-field practices?
2) What is the most effective education strategy embraced by landowners and farmers in promoting the edge-of-field practices?
3) What will persuade landowners and farmers to embrace the value of wetlands and how can we effectively incentivize their adoption? Read more about Identifying the barriers and strategies to accelerate adoption of critical edge-of-field conservation practices: A farmer-centric integrated research & extension approach Jul 2024

We developed an event-scale machine learning-based prediction tool, to estimate water quality and runoff, centered on a dynamic time window of hourly precipitation with corresponding sub-daily hydrological responses. We used close-interval water quality and flow monitoring data from four small, tile-drained catchments in Iowa placed predominantly in row-crop agriculture and with drainage areas ranging from 2.1 to 4.6 km2. Read more about Building cross-scale predictability of land-to-aquatic nitrogen loads in agriculture-dominated watersheds Apr 2024

In the US, we gathered a total of 1,574 observations from 119 papers that explored the impacts of cover crop planting on soil organic carbon (SOC) stock, crop yield and N2O emissions, with experimental durations ranging from 1 to 37 years. More measurement data on N leaching is being collected now. We also recorded various agronomic management practices that were implemented on the experimental fields, such as tillage, fertilizer application, irrigation, residue management, crop rotation and the planting and termination dates of cover crops. Read more about Spatially delineated carbon credit potential and implied nutrient reduction co-benefit: An assessment with integrated ecological and economic modeling framework Apr 2024

During the reporting period, researchers performed an extensive analysis of weather data used in the simulation model for the US Corn Belt. We found that weather data coming from the global climate models (which are the ones used for climate change predictions) are biased, especially with regards to maximum temperature. We caution the use of gridded weather products without checking because this has large impacts on the simulation outcomes, especially N leaching. 

Other activities

One related proposal was submitted to the Iowa N Initiative.  Read more about Modeling the Impacts of Historical Weather and Management on Nitrogen Loss Mar 2024

During this project period, researchers have continued to monitor nutrient loads and flow in the Walnut Creek watershed. We have made efforts to reach out to several additional landowners to attempt to establish new monitoring stations within the drainage system; several new sites may be established in 2024 resulting from these efforts.  Read more about Linking Agricultural Practices to Water Quality Improvement: The Importance of Scale in Accurately Characterizing Nonpoint Source Nutrient Loads in Iowa Streams Apr 2024