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Biomedical subjects

Gregory F McIsaac

Publications and source records attributed to Gregory F McIsaac.

3 recordsLinked to original sources
PubMed2006

Evaluation of the ADAPT model for simulating nitrogen dynamics in a tile-drained agricultural watershed in central Illinois.

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.

Algorithms↗
PubMedDate not supplied

Relating net nitrogen input in the Mississippi River basin to nitrate flux in the lower Mississippi River: a comparison of approaches.

A quantitative understanding of the relationship between terrestrial N inputs and riverine N flux can help guide conservation, policy, and adaptive management efforts aimed at preserving or restoring water quality. The objective of this study was to compare recently published approaches for relating terrestrial N inputs to the Mississippi River basin (MRB) with measured nitrate flux in the lower Mississippi River. Nitrogen inputs to and outputs from the MRB (1951 to 1996) were estimated from state-level annual agricultural production statistics and NOy (inorganic oxides of N) deposition estimates for 20 states that comprise 90% of the MRB. A model with water yield and gross N inputs accounted for 85% of the variation in observed annual nitrate flux in the lower Mississippi River, from 1960 to 1998, but tended to underestimate high nitrate flux and overestimate low nitrate flux. A model that used water yield and net anthropogenic nitrogen inputs (NANI) accounted for 95% of the variation in riverine N flux. The NANI approach accounted for N harvested in crops and assumed that crop harvest in excess of the nutritional needs of the humans and livestock in the basin would be exported from the basin. The U.S. White House Committee on Natural Resources and Environment (CENR) developed a more comprehensive N budget that included estimates of ammonia volatilization, denitrification, and exchanges with soil organic matter. The residual N in the CENR budget was weakly and negatively correlated with observed riverine nitrate flux. The CENR estimates of soil N mineralization and immobilization suggested that there were large (2000 kg N ha-1) net losses of soil organic N between 1951 and 1996. When the CENR N budget was modified by assuming that soil organic N levels have been relatively constant after 1950, and ammonia volatilization losses are redeposited within the basin, the trend of residual N closely matched temporal variation in NANI and was positively correlated with riverine nitrate flux in the lower Mississippi River. Based on results from applying these three modeling approaches, we conclude that although the NANI approach does not address several processes that influence the N cycle, it appears to focus on the terms that can be estimated with reasonable certainty and that are correlated with riverine N flux.

Agriculture↗