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Irrigation Science

, Volume 19, Issue 3, pp 107–114 | Cite as

Irrigation management for corn in the northern Great Plains, USA

  • Dean D. Steele
  • Earl C. Stegman
  • Raymond E. Knighton
ORIGINAL PAPER

Abstract

Irrigation management influences production costs and affects leaching of nutrients to groundwater. This study was conducted to compare irrigation scheduling techniques on a field-scale site and to determine whether significant irrigation water savings and equivalent yields could be achieved compared with the practices of other commercial growers in the local area. The effects of four irrigation scheduling techniques on seasonal irrigation water requirements and corn grain yields were studied for the 1990–1995 seasons at a field-scale (53.4 ha) site within the Oakes Test Area (OTA) of the Garrison Diversion Unit in southeastern North Dakota, USA. The four scheduling techniques, applied with field quadrants and seasons as dimensions of a modified Latin square statistical design, included irrigating based on tensiometer and infrared canopy temperature measurements, two water balance methods, and irrigating based on CERES–Maize estimates of plant-extractable soil water. No statistically significant differences in seasonal irrigation totals were found between irrigation scheduling methods or irrigation quadrants, while statistically significant differences were found for season. Corn grain yield was significantly affected by seasons, quadrants, and irrigation scheduling methods for both the current and previous seasons. Compared to other commercial growers in the OTA, this study maintained 5% higher yields and saved approximately 30% in irrigation inputs. Careful irrigation scheduling, based on any of the four techniques, offers the potential to reduce input costs for irrigated corn production in the area.

Keywords

Irrigation Schedule Irrigation Management Canopy Temperature Seasonal Irrigation Field Quadrant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Dean D. Steele
    • 1
  • Earl C. Stegman
    • 1
  • Raymond E. Knighton
    • 2
  1. 1.Agricultural and Biosystems Engineering Department, North Dakota State University, Fargo, ND 58105-5626, USA e-mail: steele@plains.nodak.eduUS
  2. 2.USDA/CSREES-NRE, 808 Aerospace Center, 901 D St. S.W., Washington, DC 20250, USAUS

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