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Simulation of nitrate-N movement in southern Ontario,Canada with DRAINMOD-N
Authors:Chun-Chieh Yang  Shiv O Prasher  Shaoli Wang  Seung Hyun Kim  Chin S Tan  Craig Drury  Ramanbhai M Patel
Institution:1. Instrumentation and Sensing Laboratory USDA-ARS, Building #303 BARC-East Powder Mill Road Beltsville, MD 20705-2350, USA;2. Department of Bioresource Engineering, Macdonald Campus, McGill University, Ste-Anne-de-Bellevue, Que. H9X 3V9, Canada;3. Department of Irrigation and Drainage, China Institute of Water Resources and Hydropower Research, Beijing, China;4. Department of Environmental Engineering, College of Engineering, Yeungnam University, Kyungsan City 712-749, South Korea;5. Greenhouse and Processing Crops Research Center, Agriculture and Agri-Food Canada, Harrow, Ont. N0R 1G0, Canada;6. Department of Bioresource Engineering, Macdonald Campus, McGill University, Ste-Anne-de-Bellevue, Que. H9X 3V9, Canada
Abstract:DRAINMOD-N, a mathematical model to predict nitrate-N concentrations in surface runoff and drain outflows from subsurface-drained farmlands, has been tested against field data collected in southern Ontario. The data was collected in a corn field from 16 conventional drainage and subirrigation plots in Woodslee, Ontario, from 1992 to 1994. The model performance was evaluated by comparing the observed and simulated nitrate-N concentrations in surface runoff and drain outflows. A precise calculation of water-table depth is an essential prerequisite for a model to obtain a proper prediction of nitrate-N movement. For the simulation of water-table depth, the lowest root mean square error and the highest correlation coefficient of linear regression were 173 mm and 0.51 for the subirrigation plots; and 178 mm and 0.84 for the subsurface drainage plots. Therefore, the performance of DRAINMOD-N for soil hydrologic simulations was satisfactory and it could be used for assessing nitrogen fate and transport. For the simulation of nitrate-N losses in the subirrigation plots, the lowest root mean square error and the highest correlation coefficient of linear regression were 0.74 kg/ha and 0.98 for surface runoff; and 6.53 kg/ha and 0.91 for drain outflow. For the simulation in the subsurface drainage plots, the lowest root mean square error and the highest correlation coefficient of linear regression were 0.70 kg/ha and 0.96 for surface runoff; and 6.91 kg/ha and 0.92 for drain outflow. The results show that DRAINMOD-N can perform satisfactory simulation of soil hydrology and nitrate-N losses in surface runoff under various water-table management practices. The model can, therefore, be used to evaluate different water pollution scenarios and help in the development and testing of various pollution control strategies for fields in cold weather such as that in southern Canada.
Keywords:DRAINMOD-N  Nitrate  Pollution  Water-table management
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