Quantifying crop water requirements in the MS Delta using eddy covariance and energy balance methods

Author(s): Anapalli, S.; Fisher, D.; Reddy, K.; Ruixiu, S.

With competing demands for fresh water from human, urban, and industrial sectors, water available for irrigated agriculture is rapidly declining; this calls for a more judicious use of the limited share of water available for crop irrigations. Accurately quantifying crop water requirements and providing crops with the right amount of water at the right time to optimize crop water productivity holds the key to addressing this challenge. While large field lysimeters allow us to grow crops for quantifying ET directly from the crop-field, they are expensive and time-consuming to install successfully and maintain for long-term data collection for analyzing climate variability impacts on crop water requirements. Eddy covariance (EC) and energy balance (EB) methods are easier to install in crop fields and are portable, and provide two scientifically sound methods for indirect, accurate measurements of water requirements (ET; evapotranspiration) of cropping systems. Nonetheless, the EC method has been widely known to have energy balance closure problems — imbalance in matching energy inputs to the outputs. In the evolving scenario, we embarked on a research program for monitoring ET from corn and soybean crops using both EC and EB approaches, for comparison with each other and accounting for energy balance non-closure artifacts on the EC data generated. In the EB method for quantifying ET, a surface energy balance equation is applied to a soil-plant surface using ground-based and remote-sensing measurements of the system variables, and ET (expressed as latent heat flux) is estimated as the residual term of the energy balance equation when other fluxes in the equation are either measured or calculated. The EC system consists of an omnidirectional sonic anemometer and an open-path infrared gas analyzer with data recorded at a frequency of 10 Hz on a data logger and analyzed with Smartflux software (LiCor, Lincoln, NE, USA). In this project, crops were grown in 40-ha fields planted to soybean and equipped with the EC and EB systems in 2016. In general, computed daily values of ET from EB and EC methods deviated from the computed short grass (ETo) and alfalfa (ETr) reference crop ET. However, total seasonal ET from both EB and EC methods were comparable with ETr and ETo. The EC and EB methods tested show high potential for quantifying crop ET in cropping systems in the MS Delta region.

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