The Scientific World Journal

The Scientific World Journal / 2001 / Article
Special Issue

Optimizing Nitrogen Management in Food and Energy Production and Environmental Protection: 2nd International Nitrogen Conference 2001

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Research Article | Open Access

Volume 1 |Article ID 848159 | https://doi.org/10.1100/tsw.2001.355

E.C. Huffman, J.Y. Yang, S. Gameda, R. de Jong, "Using Simulation and Budget Models to Scale-Up Nitrogen Leaching from Field to Region in Canada", The Scientific World Journal, vol. 1, Article ID 848159, 8 pages, 2001. https://doi.org/10.1100/tsw.2001.355

Using Simulation and Budget Models to Scale-Up Nitrogen Leaching from Field to Region in Canada

Academic Editor: Joe Wisniewski

Abstract

Efforts are underway at Agriculture and Agri-Food Canada (AAFC) to develop an integrated, nationally applicable, socioeconomic/biophysical modeling capability in order to predict the environmental impacts of policy and program scenarios. This paper outlines our Decision Support System (DSS), which integrates the IROWCN (Indicator of the Risk of Water Contamination by Nitrogen) index with the agricultural policy model CRAM (Canadian Regional Agricultural Model) and presents an outline of our methodology to provide independent assessments of the IROWCN results through the use of nitrogen (N) simulation models in select, data-rich areas. Three field-level models — DSSAT, N_ABLE, and EPIC — were evaluated using local measured data. The results show that all three dynamic models can be used to simulate biomass, grain yield, and soil N dynamics at the field level; but the accuracy of the models differ, suggesting that models need to be calibrated using local measured data before they are used in Canada. Further simulation of IROWCN in a maize field using N_ABLE showed that soil-mineral N levels are highly affected by the amount of fertilizer N applied and the time of year, meaning that fertilizer and manure N applications and weather data are crucial for improving IROWCN. Methods of scaling-up simulated IROWCN from field-level to soil-landscape polygons and CRAM regions are discussed.


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