ARS | Publication request: Quality assurance of weather data for agricultural system model input

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: April 14, 2011
Publication Date: September 1, 2011
Citation: Malone, R.W., Meek, D.W., Ma, L., Jaynes, D.B., Nolan, B.T., Karlen, D.L. 2011. Quality assurance of weather data for agricultural system model input. In: Ahuja, L.R., Ma, L., editors. Methods of Introducing System Models into Agricultural Research. Madison, WI: American Society of Agronomy, Crop Science of America and Soil Science Society of America. p. 283-296.

Technical Abstract: It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems associated with weather sensors include: electronic failure; rodent damage; activity of insects, spiders, and birds; poor location, calibration, and setup; and oxidation. Weather data bias of 10% in humidity, rainfall, and solar radiation results in long-term errors of over 40% for nitrate loss in tile drains from central Iowa Root Zone Water Quality Model (RZWQM) simulations. Actual weather records show measurement errors in rain, solar radiation, and humidity of 20%, 17%, and 10%. Quality assurance procedures are capable of detecting these erroneous measurements.