Location: Soil and Water Management ResearchTitle: Water vapor density and turbulent fluxes from three generations of infrared gas analyzers
|KUTIKOFF, SETH - Kansas State University|
|LIN, XIAOMAO - Kansas State University|
|Evett, Steven - Steve|
|Brauer, David - Dave|
|MOORHEAD, JED - Lindsay Corporation|
|AIKEN, ROB - Kansas State University|
|XU, LIUKANG - Licor Biosciences|
|OWENSBY, CLENTON - Kansas State University|
Submitted to: Atmospheric Measurement Techniques
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/20/2020
Publication Date: 2/18/2021
Citation: Kutikoff, S., Lin, X., Evett, S.R., Gowda, P.H., Brauer, D.K., Moorhead, J., Marek, G.W., Colaizzi, P.D., Aiken, R., Xu, L., Owensby, C. 2021. Water vapor density and turbulent fluxes from three generations of infrared gas analyzers. Atmospheric Measurement Techniques. 14:1253-1266. https://doi.org/10.5194/amt-14-1253-2021.
Interpretive Summary: In water-limited regions such as the Southern High Plains, the need to conserve water resources, such as the Ogallala (High Plains) aquifer, motivates agricultural producers to know the crop water use for daily irrigation scheduling. Current crop production involves innovative water saving measures, such as variable rate irrigation management and subsurface drip irrigation, and it requires high quality evapotranspiration (ET) data to aid efforts to calculate the correct amount of water to apply to crops. The eddy covariance (EC) method is a standard way to monitor ET but can be in error by 10 to 20%. ARS scientists at Bushland, Texas, cooperated with Kansas State University researchers to study three alternative EC systems in order to find out why errors occur and if the newer systems could reduce error. ET estimated by the three systems was largely in agreement with each other, and the oldest design estimated ET values that were the closest to direct measurements of ET in a corn field. Although EC system design has improved over the years, ET data estimated by these systems is still less than what is directly measured and the errors change over the growing season. Eddy covariance systems are still not as reliable for determining crop water use as is the direct measurement using a large weighing lysimeter.
Technical Abstract: Fast-response infrared gas analyzers (IRGAs) have been widely used in many ecosystems for long-term monitoring of water vapor fluxes in the surface layer of the atmosphere over three decades. While some of the early IRGA sensors are still used in these national and/or regional eco-flux networks, optically improved IRGA sensors are newly employed in the same networks. The purpose of this study was to evaluate the performance of water vapor density and flux data from three generations of IRGAs – LI-7500, LI-7500A, and LI-7500RS (LI-COR Bioscience, Inc., Nebraska, USA) – over the course of a growing season, conducted in Bushland, Texas, USA, in an irrigated maize canopy for 90 days. The energy balance ratio, which is the sum of turbulent fluxes divided by the sum of surface available energy, was used to assess systematic biases of the IRGA sensors for evapotranspiration (ET). Water vapor density measurements were in generally good agreement, but temporal drift occurred in different directions and magnitudes. While means exhibited mostly shift changes that do not impact the flux magnitudes, variances of water vapor density fluctuations were occasionally in poor agreement, especially following rainfall events. LI-7500 variances were largest compared to recent LI-7500RS and LI-7500A, manifesting in widened cospectra, especially under unstable and neutral static stability. Agreement among the sensors was best under the typical irrigation-cooled boundary layer, with inter-instrument coefficient of variability of 14% under advective conditions. Generally, the smallest variances occurred with the LI-7500RS, and high-frequency spectral corrections were larger for these measurements, which resulted in similar fluxes between the LI-7500A and LI-7500RS. Fluxes from the LI-7500 were best representative of growing season ET based on a world-class lysimeter reference measurement but using energy balance ratio as an estimate of systematic bias corrected most of the differences among measured fluxes.