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Field Testing of DRAINMOD-N II for North Carolina Soils

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  032368,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14989) @2003
Authors:   M. A. Youssef, R. W. Skaggs, G. M. Chescheir, J. W. Gilliam
Keywords:   DRAINMOD-N, DRAINMOD, simulation models, nitrogen, water quality, drainage

The nitrogen simulation model, DRAINMOD-N II, was field-tested using 6 years of data from an artificially drained site located in the North Carolina Lower Coastal Plain. The test site is nearly flat with a very poorly drained sandy loam soil under natural conditions. Four experimental plots, planted to a corn-wheatsoybean rotation and managed using conventional and controlled drainage, were used in this study. Simulation results showed fair to good agreement between observed and predicted annual nitrate-nitrogen (NO3-N) leaching losses. The absolute normalized error (NE)was less than 5% in 6 out of 24 simulated plot-years and less than 25% in 12 out of 24 simulated plot-years. The high errors in predicting annual NO3-N leaching losses were mostly induced by errors in predicting water table depth and drainage rates. DRAINMOD-N II did an excellent job in predicting cumulative NO3-N leaching losses over the whole simulated period. Cumulative NO3- N leaching losses over the six-year period was over-predicted by 2.1% for one plot and under-predicted by 5.9- 10.2%. The strong dependence of DRAINMOD-N II performance on the accuracy of the hydrologic simulation was manifested in the close association between predicted cumulative drainage and NO3-N leaching losses. Results of this study showed the potential of DRAINMOD-N II for simulating N dynamics and turnover in agroecosystems. However, this evaluation of DRAINMOD-N II should be regarded as incomplete since it relied primarily on literature rather than field and/or lab measurements to parameterize the model. Further research is needed to test DRAINMOD-N II based on independent measurement of model input parameters.

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