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Title: Quantifying the impact of conservation practices at the Choptank watershed in Maryland using AnnAGNPS Model

Author
item Sadeghi, Ali
item GRAFF, CARRIE - LIMNO TECH.
item McCarty, Gregory
item McConnell, Laura
item Hively, Wells - Dean

Submitted to: Soil and Water Conservation Society
Publication Type: Proceedings
Publication Acceptance Date: 7/21/2007
Publication Date: 7/21/2007
Citation: Sadeghi, A.M., Graff, C., McCarty, G.W., McConnell, L.L., Hively, W.D. 2007. Quantifying the impact of conservation practices at the Choptank watershed in Maryland using AnnAGNPS Model. In: Proceedings of the ARS-Conservation Effects Assessment Project Annual Meeting, July 21-25, 2007, Tampa, Florida. 2007 CDROM.

Interpretive Summary:

Technical Abstract: This study is being conducted at the Choptank watershed under the USDA-CEAP program with the objective of quantifying the environmental benefits of conservation practices such as cover crops using AnnAGNPS (Annualized Agricultural Non-Point Source) model. Choptank is nearly 800 square miles watershed and is considered as the smallest of the nine Chesapeake Bay tributary basins in Maryland. Major landuse are: agriculture, with 58 percent; forest, with 33 percent; and urban, with nine percent. The watershed is located solely within the Coastal Plain physiographic region of Maryland. Crop rotation is dominated by corn and soybeans and poultry manure is used heavily thus, nitrogen and phosphorous are being considered as major pollutant loads into the surface water resources. Five years of detailed database is being used to provide baseline calibration and validation of the model. Our preliminary model simulation results, for evaluating the effect of cover crops on nutrient loads, showed a drastic reductions in the total N from watershed outlet when the winter wheat cover crop acreage increased from 40% to 75%. Whether or not these reductions are realistic is a question for future modeling simulation efforts. The details of our modeling approach as well as the model calibrations and validations procedures, and their predictive capabilities will be presented and discussed.