Research

Speaker: Jason Kelley - University of Idaho

Techniques to measure fluxes of energy and trace gas near the surface have emerged from decades of experimentation and theory. The historical development of turbulent flow theory and near surface boundary layer formulations rely on simplifying assumptions essential to analytic solutions for flow equations. However, the true complexity of heterogeneous landscapes and biophysical mechanisms are neglected in these simplifications. This presentation will survey results from eddy-covariance and other experimental techniques conducted across many types of farm landscapes ranging from mature citrus, nut orchards, and vines to irrigated alfalfa, annual crops, and dryland pasture. In each case, site-specific physical mechanisms are shown to affect the resulting estimates of flux, suggesting where and when simplifying assumptions might need to be relaxed or reformulated to reflect actual conditions. Fundamental assumptions and methods to be shown include: closure of the surface energy budget; frequency dependencies such as diurnal variability and sensor response; spatial footprints; and energy relations resulting from phase changes in water. After exploring case studies, new techniques will be shown that integrate measurements from heterogeneous field conditions and during episodic and extreme events. Results from machine learning applications will be shown, along with comparisons to first-principles methods such as gradient-flux measurements and simple low cost sensors. A good understanding of the relationship between site-specific physical mechanisms and generalized techniques is important to the global development of flux networks such as Ameriflux. These concerns are key to adaptable and robust procedures in network standardized quality control and the uniform reporting of flux. Reconciling different approaches will be shown as a framework to grapple with the complexity of real-world flux measurement.