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TECHNICAL REPORTS

Ground Water Quality

Field Evaluation of a Model for Predicting Nitrogen Losses from Drained Lands

^a Department of Biological and Agricultural Engineering., North Carolina State University, Raleigh, NC 27695
^b Department of Soil Science, North Carolina State University, Raleigh, NC 27695

^* Corresponding author (mohamed_youssef{at}ncsu.edu)

Received for publication June 22, 2005. The N simulation model, DRAINMOD-N II, was field-tested using a 6-yr data set from an artificially drained agricultural site located in eastern North Carolina. The test site is on a nearly flat sandy loam soil which is very poorly drained under natural conditions. Four experimental plots, planted to a corn (Zea mays)–wheat (Triticum aestivum L.)–soybean (Glycine max.) rotation and managed using conventional and controlled drainage, were used in model testing. Water table depth, subsurface drainage, and N concentration in drain flow were measured and meteorological data were recorded continuously. DRAINMOD-N II was calibrated using the data from one plot; data sets from the other three plots were used for model validation. Simulation results showed an excellent agreement between observed and predicted nitrate-nitrogen (NO₃–N) losses in drainage water over the 6-yr period and a reasonable agreement on an annual basis. The agreement on a monthly basis was not as good. The Nash-Sutcliffe modeling efficiency (EF) for monthly predictions was 0.48 for the calibration plot and 0.19, 0.01, and –0.02 for the validation plots. The value of the EF for yearly predictions was 0.92 for the calibration plot and 0.73, 0.62, and –0.10 for the validation plots. Errors in predicting cumulative NO₃–N losses over the 6-yr period were remarkably small; –1.3% for the calibration plot, –8.1%, –2.8%, and 4.0% for the validation plots. Results of this study showed the potential of DRAINMOD-N II for predicting N losses from drained agricultural lands. Further research is needed to test the model for different management practices and soil and climatological conditions.

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