Assessment of Upscaling Methodologies for Daily Crop Transpiration using Sap-Flows and Two-Source Energy Balance Models in Almonds under Different Water Status and Production Systems

The daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies to retrieve Td in almond trees with different production systems and water status. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th-TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo) and potential evapotranspiration (ETp). These approaches were firstly evaluated with in situ sap flow (T-SF) data and then applied to the Th-TSEB. Daily T-SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T-SF, and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water stressed trees. However, the daily upscaling approaches applied in the TSEB (Td-TSEB) failed to detect differences between production systems. The lack of sensibility of Td-TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The improvement of ETp estimations or more sophisticated ETp models could solve this issue.