Comparison of modeled evapotranspiration from the SETMI hybrid model informed with multispectral and thermal infrared imagery acquired with an unmanned aerial system

Mitch Maguire; Christopher M. U. Neale; Wayne Woldt

doi:10.1117/12.2604207

12 September 2021 Comparison of modeled evapotranspiration from the SETMI hybrid model informed with multispectral and thermal infrared imagery acquired with an unmanned aerial system

Mitch Maguire, Christopher M. U. Neale, Wayne Woldt

Author Affiliations +

Proceedings Volume 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII; 118560J (2021) https://doi.org/10.1117/12.2604207
Event: SPIE Remote Sensing, 2021, Online Only

Abstract

Estimating actual crop evapotranspiration (ETc) is a critical component in tracking soil water availability and managing near real-time irrigation scheduling. Energy and water balance models are two common approaches for estimating daily crop ETc. The Spatial EvapoTranspiration Modeling Interface (SETMI) hybrid model combines these two approaches and has been used to increase the accuracy of modeled ETc and soil water content by assimilating actual ET values to update the soil water balance. In this study, modeled daily ETc from the two-source energy balance (TSEB), root zone water balance, and the hybrid modeling approach were compared to measured ETc from eddy covariance flux tower systems to quantify model accuracy. The TSEB model used the Priestly-Taylor approximation for estimating ETc and the water balance model was updated with reflectance-based crop coefficients. The models were informed with UAS acquired multispectral reflectance and thermal infrared imagery collected over irrigated and rainfed maize and soybean fields during the 2018-2020 growing seasons.

Conference Presentation

Citation Download Citation

Mitch Maguire, Christopher M. U. Neale, and Wayne Woldt "Comparison of modeled evapotranspiration from the SETMI hybrid model informed with multispectral and thermal infrared imagery acquired with an unmanned aerial system", Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 118560J (12 September 2021); https://doi.org/10.1117/12.2604207

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