Modeling Nitrogen Transport and Transformations in High Water Table Soils

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Title: Modeling Nitrogen Transport and Transformations in High Water Table Soils
Author: Youssef, Mohamed A.
Advisors: John E. Parsons, Committee Member
George M. Chescheir, Committee Member
R. Wayne Skaggs, Committee Chair
J. Wendell Gilliam, Committee Member
Abstract: Development of management practices that reduce nitrogen (N) losses from agricultural lands has been the focus of research over many years. Development and testing of such practices is a complex task since it requires understanding of N dynamics in the soil-water-plant system, which is regulated by a large number of interacting physical, chemical, and biological processes. Nitrogen models are useful tools for developing and evaluating management practices for sustainable agriculture. The model, DRAINMOD-N was originally developed to simulate N dynamics in artificially drained soils. However, the model was based on a simplified N cycle, which restricted its applicability. A new version of DRAINMOD-N, referred to as DRAINMOD-N II, was developed and field-tested in this study. DRAINMOD-N II simulates N dynamics and turnover in the soil-water-plant system under different management practices and soil conditions. It considers a detailed N cycle, adds a simplified carbon cycle, and operates at different levels of complexity according to the conditions of the system being simulated. Processes considered in the model are atmospheric deposition, application of mineral N fertilizers, soil amendment with organic N sources, plant uptake, mineralization, immobilization, nitrification, denitrification, ammonia volatilization, and N losses due to leaching and surface runoff. DRAINMOD-N II driving hydrologic variables are predicted by the water management model DRAINMOD 5.1. DRAINMOD-N II was tested with a six-year data set from the North Carolina Lower Coastal Plain. The experimental site consists of eight 1.7-hectare instrumented, subsurface drained plots. The site was planted to a corn-wheat-soybean rotation. Water table depth (WTD) midway between the drains, subsurface drainage flow rates, and meteorological data were automatically measured and recorded. Flow proportional drainage water quality samples were collected and analyzed to determine N concentrations and loads. Results of the simulations showed good agreement between predicted and observed WTD. On average, predicted WTD was within 11.8 to 13.9 cm of observed values. The average coefficient of determination (R2) for WTD was in the range of 0.71 to 0.77. There was also good agreement between predicted and observed subsurface drainage rates. On average, predicting annual subsurface drainage was within 5.7-12.1% of observed values. The average R2 values for predicted versus observed subsurface drainage ranged from 0.65 to 0.73. The DRAINMOD-N II simulations showed good agreement between predicted annual nitrate-nitrogen (NO3-N) drainage losses and observed values. On average, predicted annual NO3-N leaching losses were in the range of 19.9-46.0%. The high errors in predicting annual NO3-N leaching losses were mostly induced by errors in predicting WTD and drainage rates. The model did an excellent job in predicting cumulative drainage and NO3-N leaching losses over the whole simulated period. Cumulative drainage and NO3-N leaching losses over the six-year period was within 1.3-13.2% and 2.2-10.1% of observed values, respectively. In spite of relatively large discrepancies on an annual basis, in some years, errors in predicting cumulative NO3-N losses over the six-year period were remarkably small. Results of this study indicate that DRAINMOD-N II can be reliably used to simulate N dynamics and turnover in agroecosystems. However, this evaluation of the model should be regarded as an incomplete test because it relied primarily on the 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 the model input parameters.
Date: 2004-02-03
Degree: PhD
Discipline: Biological and Agricultural Engineering

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