Location: Soil and Water Management ResearchTitle: Sensor based variable rate irrigation
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/12/2020
Publication Date: 12/10/2020
Citation: O'Shaughnessy, S.A. 2020. Sensor based variable rate irrigation [abstract]. 32nd Annual Texas Plant Protection Conference (Virtual), December 8-10, 2020, Virtual. Paper No. 39.
Technical Abstract: Crop water productivity (CWP) can be improved at the field level by using variable rate irrigation (VRI) sprinklers to meet changing crop water needs over time and location within a field. However, sensor feedback is needed to detect variable crop water status and determine how much water to apply. The Agricultural Research Service developed an automated irrigation scheduling (AIS) system that uses a software program to integrate wireless sensor networks of canopy temperature, soil water sensing and local weather variables to build dynamic prescription maps and control VRI sprinklers. These systems were used for irrigation management of corn, soybean, cotton, and sorghum in humid and semi-arid regions. In Missouri, this system resulted in water savings of 1 to 2 acre-inches and greater levels of CWP (300 lbs/acre-inch) for cotton as compared with the Arkansas Irrigation Scheduling method, which resulted in 88.2 lbs/acre-inch. For soybeans grown in Mississippi, the AIS system resulted in CWP of 30 bu/acre-inch with a water savings of 3 to 4 acre-inches as compared with irrigation scheduling using soil water sensors to trigger irrigations using management allowable depletion, which resulted in only 15.1 bu/acre-inch. When the AIS system was used to manage corn in the semi-arid region of Bushland, Texas, and the humid region of South Carolina, CWP was on average 10 bu/acre-inch and similar to best management practices for each region. Sensor feedback for decision support could benefit producers through greater CWP without significantly lowering yields and could save producers time when making irrigation scheduling decisions.