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ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Soil, Water & Air Resources Research » Research » Publications at this Location » Publication #346189

Title: Long-term observations of crop water use with eddy covariance stations and coupling with crop simulation models

item Hatfield, Jerry
item BASSO, BRUNO - Michigan State University
item ARCHONTOULIS, SOTIRIOS - Iowa State University
item Prueger, John
item Sauer, Thomas - Tom

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/25/2017
Publication Date: 10/25/2017
Citation: Hatfield, J.L., Basso, B., Archontoulis, S., Prueger, J.H., Sauer, T.J. 2017. Long-term observations of crop water use with eddy covariance stations and coupling with crop simulation models. In: Proceedings of ASA-CSSA-SSSA Annual Meeting, October 20-26, 2017, Tampa, Florida.

Interpretive Summary:

Technical Abstract: Understanding crop water use is critical to being able to determine crop water requirements and when water is limiting crop productivity. There have been many different techniques used to quantify crop water use and the eddy covariance approach is one method that has the capacity to measure crop water use over short time intervals and can be integrated to determine water use across phenological stages for different crops. The drawbacks of this methodology are that it requires a large area to ensure the footprint of the instrument is within the field and does require careful attention to data screening for quality control and gap-filling. We have collected an 11 year data set of eddy covariance data over corn and soybean crops in central Iowa to determine the patterns in crop water use in relation to precipitation variation and variation in crop growth and productivity. These data allow for a direct comparison among years in the changes in water use efficiency of corn and soybean and the relationship to weather variation that affects the growth rate of the crops. These data are providing a database to evaluate crop simulation models that can be used to determine crop water use under different growing conditions. Combining experimental measurements with crop simulation models will provide new insights into potential improvements in crop management to offset weather variation during the growing season.