​​​​Overview of Sensor-Based Irrigation Scheduling

March 2013 | 27 min., 14 sec.
by Brian G. Leib
The University of Tennessee

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Optimum cotton irrigation is difficult to achieve in humid regions due to the variable rainfall patterns from year to year. To assist in adjusting for these variable conditions, sensors characterize the amount of water in the soil profile thus improving the ability to schedule cotton irrigation. This presentation describes how different types of sensors and configurations impact selection, placement, data collection, interpretation and the cost of sensors.

About the Presenter

Brian G. LeibBrian G. Leib is an Agricultural and Biological Systems Engineer and has been working in research and extension of irrigated agriculture for nearly 30 years. He has performed irrigation research projects in many crops: alfalfa, small grains, cantaloupe, apples, cherries, peaches, wine grapes, mint, tobacco, forage grasses, pumpkins, tomatoes, peppers, lettuce, cotton, and soybeans. These projects have been conducted in a variety of climates spanning arid and humid regions using many different types of irrigation systems including surface, sprinkler, and drip irrigation. He has also worked to improve water management through developing irrigation scheduling software, testing soil water sensors, establishing weather data networks, improving irrigation systems to control salinity, implementing deficit irrigation strategies, reducing erosion from furrow irrigation, and capturing rain water for utilization in high tunnel irrigation. He received his BS and PhD degrees from The Pennsylvania State University in Soil & Water Engineering and also an MS from Colorado State University in Irrigation Engineering. He has been a faculty member at Colorado State University and Washington State University. He is presently an Associate Professor in the Biosystems Engineering and Soil Science Department at the University of Tennessee.​​

Contact Information:
Email: bleib@utk.edu


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