B097-0012
Comparing In-Situ Evapotranspiration of Two Cherry Orchards in California’s Central Valley with ECOSTRESS ET Estimates and Modelled ET from a Higher-Order Closure, Multilayer Soil, Plant, and Atmosphere Model

Tuesday, 15 December 2020
Poster
Jenae Clay1, Kyaw Tha Paw U1, Dave Pyles2, Mary Rose Mangan3, Liyi Xu1 and Kosana Suvocarev4, (1)University of California Davis, Davis, CA, United States, (2)University of California Davis, Davis, United States, (3)University of California Davis, Land, Air and Water Resources, Davis, CA, United States, (4)University of California Davis, Land Air Water Resources, Davis, United States
Abstract:
Evapotranspiration (ET) measurements were recorded in two California Central Valley cherry orchards from May 2019 to Fall 2020 using eddy covariance-based energy budget residual and surface renewal methods. These in-situ measurements of actual ET and surface energy fluxes were compared with modeled actual ET and surface energy fluxes derived from the higher-order closure, multilayer model known as the Advanced Canopy Atmosphere and Soil Algorithm (ACASA). Canopy stages of the high planting density and low planting density cherry orchards are configured within the ACASA model by designing plant physiology packages of representative parameters such as the leaf area index (LAI) for each orchard during various seasons. ET is estimated by ACASA using meteorological data from the field site as input data and then simulating the energy fluxes between each layer of the soil, plant canopy (including the airspace within it), and the atmosphere above the canopy. LAI estimates are obtained by processing cloud-free images from the Landsat 8 platform throughout the field data collection period. The in-situ ET data are also compared with ET estimates derived from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission during the field campaign. This comparison of ECOSTRESS ET and ACASA ET with the in-situ measured ET allows an accuracy assessment of remotely sensed and modeled ET to be performed in order to help improve future ET estimates from other landscapes.