Eddy Covariance and Energy Balance Methods for Rapidly Estimating ET and Crop Coefficients in the Mississippi Delta Region.

Water levels in the Mississippi River Valley Alluvial Aquifer are fast declining due to its over-exploitation for crop irrigation in excess of its natural recharge level. Quantifying crop water requirements and providing crops with the right amount of water at the right time to optimize productivity holds the key to contain further depletion. Eddy covariance (EC) and residual energy balance (EB) methods offer two scientifically sound methods for measurements of water requirements of cropping systems. However, the EC method comes with inabilities in balancing the surface energy budget (non-closure problem) in the crop canopy system. The assumption in the EB method is that all the energies other than those used in the sensible and ground heat fluxes and measurable energy storages in the system are used in the evapotranspiration (ET), which can lead to overestimation of ET. In this scenario, we embarked on a research program to monitor ET from soybean using both EC and EB approaches, for comparison with each other and accounting for the uncertainties in these methods. In the EB method, a surface energy balance equation was applied to a soil-plant surface using ground-based and remote sensing measurements of the system variables, and LE was estimated as the residual term of the energy balance equation. The EC system consisted 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 in 30 min intervals. In this project, soybean was grown on a 40-ha field and equipped with EC and EB systems in 2016. In general, computed daily EB-ET were higher than EC-ET. The EC system showed an energy balance closure of about 85%. The EB-ET was on average 20% higher than EC-ET. Averages of ET estimated from the EC and EB methods were used in deriving grass- and alfalfa-reference crop coefficients for soybean and compared.