A Dynamic Zero-Plane Displacement Height Approach to Improve Remote Sensing-Based Modeling of Actual Evapotranspiration in Maize

Accurate estimation of latent heat flux (LE) and sensible heat flux (H) is essential for determining actual crop evapotranspiration (ETa) and optimizing irrigation water management. However, uncertainties in characterizing the zero-plane displacement height (do) often limit H and LE model accuracy. This study introduces a novel approach to characterize do using a dynamic fractional vegetation cover and a new proposed canopy porosity (Φdp) term derived from Unmanned Aerial System (UAS) imagery. Field experiments were conducted in 2024 near Greeley, Colorado, USA, at a research farm using fully and deficit-irrigated maize fields. Eddy covariance (EC) systems, handheld multispectral radiometer, and PlanetDove mini-satellite imagery were used in the land surface energy balance (EB). A dynamic heat flux footprint area was implemented based on crop height, atmospheric stability, and wind conditions, to align and integrate those measurements with measured EC heat fluxes. Results indicated that both developed do models noticeably outperformed existing do methods. The new do models reduced the normalized root mean square errors (NRMSE) for H estimation by up to 21.1% in the fully irrigated (FI) field and by 16.9% in the deficit-irrigated (DI) field. Furthermore, a higher index of agreement of up to 0.74 reflected an improved do model vs. observation correlation. These findings highlight the potential of incorporating a dynamic canopy porosity and vegetation fractional cover to refine spatially distributed EB-based ETa modeling and advance agricultural irrigation water management based on remote sensing inputs.