Location: Hydrology and Remote Sensing LaboratoryTitle: Assessing winter cover crop nutrient uptake efficiency using water quality simulation model Author
Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/18/2013
Publication Date: 4/18/2013
Citation: Lee, S., Yeo, I., Beeson, P.C., Sadeghi, A.M., Hively, W.D., McCarty, G.W. 2013. Assessing winter cover crop nutrient uptake efficiency using water quality simulation model [abstract]. Abs. 27. BARC Poster Day. Interpretive Summary:
Technical Abstract: Winter cover crops are an important conservation practice with potential to improve water quality by reducing excess nitrogen (N), remaining during the winter/early spring in soil, from leaching, runoff, and sediment loss into surface waters after harvest of summer crops. Throughout the Chesapeake Bay watershed, cover crop use has been greatly emphasized and currently, federal and state cost-share programs are available for farmers to compensate for the costs of planting winter cover crops. However, the impacts of cover crop N uptake efficiencies at the landscape scale are little known, and more work is needed to evaluate how they affect the water budget and nutrient cycling at that scale. The objective of this study was to assess the effectiveness of the cover crop program at landscape scale, using a well-known USDA-ARS watershed simulation model, Soil and Water Assessment Tool (or SWAT). The study is being undertaken in German Branch (GB), a sub-basin within the larger Choptank River Watershed. The SWAT model will be carefully calibrated and validated using field observations from 1992-1995. A number of scenarios were developed to obtain the baseline information for nutrient losses under current condition, and to investigate how water budget, N uptake, and N leaching was affected by different planting dates, species, and amount of cover crop coverage. In addition, we conducted a geospatial analysis to identify critical areas for high N loading within the GB sub-basin. This provides important information for decision making to prioritize best management practices.