Lead Researchers: Cathie Lavis, Dale Bremer, Jack Fry and Jared Hoyle, Kansas State University;  Benjamin Wherley and Ambika Chandra, Texas A&M AgriLife Research;  Jay Ham, Tony Koski and Yaling Qian, Colorado State University
Contact: Jay Ham
Industry Partner: The Toro Company, USGA

Landscape irrigation strategies usually rely on calendar or evapotranspiration (ET) schedules that completely ignore soil moisture. Soil moisture sensors (SMS) may improve irrigation accuracy but are not widely used. Our proposed objectives are to: 1) Evaluate irrigation trigger thresholds by measuring turf canopy responses to soil moisture using SMS; and 2) Compare SMS-based irrigation scheduling effectiveness among several SMS types and with traditional and ET-based irrigation scheduling. The study would be comprised of three field studies, two under rainout shelters and a third in a larger, uncovered area, and would be conducted on three turfgrasses. The new, low-cost SMS with internet of things (IoT) connectivity (wireless underground sensor network, or WUSN), developed by Dr. Ham, CSU, will also be evaluated in our proposed studies. Our overall goal/outcome is to conserve water by accelerating wide-spread use of SMS for landscape irrigation control by reducing costs and complexity in their use. 

Soil moisture is an overlooked tool in creating landscape irrigation strategies. In order to widely adopt soil moisture into future management plans, identifying tigger thresholds is necessary. 

Study Goal: Develop an innovative irrigation scheduling approach that integrates all three components of the soil-plant-atmosphere continuum to generate turfgrass irrigation decisions.
Field Goal: To develop thresholds for triggering irrigation. 

Lab: Hyprop/WP4C measuring the full range moisture release curves were generated.
Field: External factors led to new field work being needed.