TY - GEN
T1 - Irrigation Scheduling using Hybrid Remote Sensing-Based Evapotranspiration Model Informed by Unmanned Aerial System Acquired Multispectral and Thermal Imagery
AU - Maguire, Mitchell S.
AU - Neale, Christopher M.U.
N1 - Funding Information:
Funding for the project was provided through the USDA AFRI Foundational and Applied Science Program (Award # 2017-67021-26249) and the Daugherty Water for Food Global Institute at the University of Nebraska. We thank Mr. Mark Schroeder, Director of the ENREC facility, his team, and others at the ENREC for their support of this research. We are grateful for those who helped with data collection, laboratory work, field operations, and advisory input. They include Alan Boldt, Keith Stewart, Pradhyun Kashyap Suresh, Jasreman Singh, Eric Wilkening, Jake Richardson, Ashish Manish, Sandeep Bhatti, Tyler Frederick, and Keena Crone. We also thank the NU-AIRE laboratory at the University of Nebraska Lincoln for providing the UAS remote sensing system.
Publisher Copyright:
© 2022 SPIE.
PY - 2022
Y1 - 2022
N2 - Estimating daily crop evapotranspiration (ET) is a critical component in tracking soil water availability for near real-time irrigation management. Energy and water balance models are two common approaches for estimating daily crop ET. These models informed with remotely sensed imagery can estimate crop ET spatially aiding both uniform and spatial irrigation management. A hybrid remote sensing-based ET model consisting of the two-source energy balance and water balance models was used in scheduling variable rate and uniform irrigation in maize and soybean fields. Variable rate irrigation was scheduled using two approaches: 1) a hybrid model informed with calibrated high resolution unmanned aerial system multispectral reflectance and thermal infrared imagery and 2) a water balance model informed with satellite multispectral reflectance imagery. The variable rate irrigation approaches were compared to uniform and non-irrigated approaches to quantify the effects on dry grain yield and net irrigation applied when managing variable rate irrigation using the hybrid and water balance models. A separate field study was completed to assess how well the remote sensing-based ET model could schedule uniform irrigations of an entire field.
AB - Estimating daily crop evapotranspiration (ET) is a critical component in tracking soil water availability for near real-time irrigation management. Energy and water balance models are two common approaches for estimating daily crop ET. These models informed with remotely sensed imagery can estimate crop ET spatially aiding both uniform and spatial irrigation management. A hybrid remote sensing-based ET model consisting of the two-source energy balance and water balance models was used in scheduling variable rate and uniform irrigation in maize and soybean fields. Variable rate irrigation was scheduled using two approaches: 1) a hybrid model informed with calibrated high resolution unmanned aerial system multispectral reflectance and thermal infrared imagery and 2) a water balance model informed with satellite multispectral reflectance imagery. The variable rate irrigation approaches were compared to uniform and non-irrigated approaches to quantify the effects on dry grain yield and net irrigation applied when managing variable rate irrigation using the hybrid and water balance models. A separate field study was completed to assess how well the remote sensing-based ET model could schedule uniform irrigations of an entire field.
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U2 - 10.1117/12.2623262
DO - 10.1117/12.2623262
M3 - Conference contribution
AN - SCOPUS:85135770299
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII
A2 - Thomasson, J. Alex
A2 - Torres-Rua, Alfonso F.
PB - SPIE
T2 - Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VII 2022
Y2 - 6 June 2022 through 12 June 2022
ER -