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Impact Statement: 'A Dynamic Variable Rate Irrigation System for Center Pivots'

Statement Details

Brief Title
Variable Rate Irrigation System

Title
A Dynamic Variable Rate Irrigation System for Center Pivots

Author
Vellidis, George

Year
2015

Geographic Scope
National

County
Calhoun

Location
 

Your Unit/Department/Group
UGA Precision Agriculture Team

Summary
Variable rate irrigation (VRI) for center pivots was developed by the University of Georgia Precision Agriculture Team. The technology is now widely offered by most pivot manufacturers. VRI allows pivots to vary the amount of water they apply along the length of the irrigation system to address the variability within fields. We developed a soil moisture sensing system which provides real-time information to the pivot so that it can change the amount of water it applies in response to actual crop needs. We demonstrated and evaluated this dynamic control system in a 230 acre field in Calhoun County. The system has the potential to greatly increase agricultural water use efficiency and how much crop we get for every drop of irrigation water we apply.

Situation
VRI irrigation water application rates are controlled by an application or prescription map. Prescription maps are developed by dividing fields into irrigation management zones (IMZs) and assigning irrigation water application rates to each of the IMZs. At the moment, the prescription maps are static. In other words, the application rates are assigned once and used thereafter and thus do not respond to environmental variables such as weather patterns and other factors which affect soil moisture condition and crop growth rates. So although VRI is a great leap forward in improving water use efficiency, the system could be greatly enhanced by having real-time information on crop water needs to drive the application rates. One approach for creating dynamic prescription maps is to use soil moisture sensors to estimate the amount of irrigation water needed to return each IMZ to an ideal soil moisture condition.

Response
We developed the University of Georgia Smart Sensor Array which is an inexpensive wireless soil moisture sensing system that allows for a high density of smart soil moisture sensors – a feature needed to enable dynamic prescription maps. Two to three smart sensors are installed in each IMZ to monitor soil moisture. The smart sensors wirelessly transmit soil moisture data to a web server where the data are processed and converted to recommended irrigation application rates for each IMZ. These recommendations are converted into daily prescription maps which can be downloaded remotely to a VRI controller thus creating a dynamic VRI control system. As a result, when an irrigation event is initiated, the VRI-enabled pivot applies water to meet actual soil moisture needs. During 2015, we conducted an experiment to assess our system in a 230 acre field in Calhoun County, Georgia.

Impact
The dynamic variable rate irrigation control system performed well throughout the growing season. The VRI controls allowed us to not irrigate non-farmed areas within the field thus saving significant amounts of irrigation water. In addition, the control system allowed us to irrigate some areas off the field more frequently and other areas less frequently based on actual crop water needs. Because of this the system has the potential to greatly increase agricultural water use efficiency and how much crop we get for every drop of irrigation water we apply. This technology may be a powerful tool for increasing agricultural productivity without increasing irrigation water demand.

State Issue
Conservation & Management of Natural Resources

Program Function(s)

  • Research

Program Area(s)

  • Agriculture & Natural Resources

Funding Source(s)

  • Hatch Act Funds
  • State Appropriated Funds
  • Federal Grants
  • Commodity Commission Grants

Collaborator(s)

CAES Collaborator(s)
  • Hill , Rodney W.
  • Perry , Calvin D.
  • Tucker , Michael Andrew
  • Porter , Wesley
  • Cofield , Marcus Nathaniel
  • Pavlou , Dimitrios
  • Orfanou , Anna
Non-CAES Collaborator(s)
  • Adam McLendon