Journal or Book Title
Journal of Soil and Water Conservation
Research Focus Area(s)
Land and Water Resources Engineering
This paper describes a dataset relating management to nitrogen (N) loading and crop yields from 1990 to 2003 on 36, 0.4 ha (1 ac) individually tile-drained plots on the Northeast Research and Demonstration Farm near Nashua, Iowa, United States. The field-measured data were used to calibrate the Root Zone Water Quality Model (RZWQM), and the results were summarized in a special issue ofGeoderma (Ahuja and Hatfield 2007). With a comprehensive, long-term measured dataset and a model that simulates many of the components of the agricultural system, one can begin to understand the effects of management practices on N loading, crop yields, and net income to the farmers. Other researchers can use this dataset to assess the effects of management on similar tile-drained systems occurring some distance from Nashua, under alternative climates and soils, with other management systems, or with simulation models using different process representations. By integrating the understanding developed at Nashua with datasets from other highly monitored sites and other sources, progress can be made in addressing problems related to excessive N fluxes in the Mississippi Basin. An example 30-year RZWQM simulation of 18 management systems implies that significant management changes are needed to meet the goal of reducing N loads to the Gulf of Mexico by 45%. This paper and the associated datasets are intended to be used in conjunction with the analyses and process descriptions presented in the Geoderma special issue. The datasets and additional explanatory materials are available for download at http://apps.tucson.ars.ag.gov/nashua.
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Heilman, Philip; Kanwar, Rameshwar S.; Malone, Robert W.; Ma, Liwang; Hatfield, Jerry L.; and Boyle, Kevin P., "The Nashua agronomic, water quality, and economic dataset" (2012). Agricultural and Biosystems Engineering Publications. 566.