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TECHNICAL REPORTS

Surface Water Quality

Evaluation of the ADAPT Model for Simulating Nitrogen Dynamics in a Tile-Drained Agricultural Watershed in Central Illinois

Dep. of Natural Resources and Environmental Sci., Univ. of Illinois at Urbana-Champaign, W503 Turner Hall, 1102 South Goodwin Ave., Urbana, IL 61801 (Senior Author now at the School of Agronomy, Université de Lomé, B.P.1515 Lomé, Togo, West Africa)

^* Corresponding author (gmcisaac{at}uiuc.edu)

Received for publication October 3, 2005. Assessing the accuracy of agronomic and water quality simulation models in different soils, land-use systems, and environments provides a basis for using and improving these models. We evaluated the performance of the ADAPT model for simulating riverine nitrate-nitrogen (NO₃-N) export from a 1500-km² watershed in central Illinois, where approximately 85% of the land is used for maize-soybean production and tile drainage is common. Soil chemical properties, crop nitrogen (N) uptake coefficient, dry matter ratio, and a denitrification reduction coefficient were used as calibration parameters to optimize the fit between measured and simulated NO₃-N load from the watershed for the 1989 to 1993 period. The applicability of the calibrated parameter values was tested by using these values for simulating the 1994 to 1997 period on the same watershed. Willmott's index of agreement ranged from 0.91 to 0.97 for daily, weekly, monthly, and annual comparisons of riverine nitrate N loads. Simulation accuracy generally decreased as the time interval decreased. Willmott's index for simulated crop yields ranged from 0.91 to 0.99; however, observed crop yields were used as input to the model. The partial N budget results suggested that 52 to 72 kg N ha^–1 yr^–1 accumulated in the soil, but simulated biological N fixation associated with soybeans was considerably greater than literature values for the region. Improvement of the N fixation algorithms and incorporation of mechanisms that describe soybean yield in response to environmental conditions appear to be needed to improve the performance of the model.

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