Evaluation of Partitioned Evaporation and Transpiration Estimates within the DisALEXI Modeling Framework over Irrigated Crops in California

Accurate characterization of evapotranspiration (ET) is imperative in water-limited cropping systems such as California vineyards and almond orchards. Satellite-based ET modeling techniques, including the atmosphere–land exchange inverse model (ALEXI) associated flux disaggregation technique (DisALEXI), have proven reliable determining field scale ET. However, validation efforts typically focus on omit an evaluation partitioned evaporation (E) transpiration (T). ALEXI/DisALEXI based two-source energy balance (TSEB) model, making it uniquely qualified to derive E T individually. The current study evaluated estimates derived using two formulations DisALEXI; one Priestley-Taylor (DisALEXI-PT) other Penman-Monteith (DisALEXI-PM). modeled values were validated against fluxes from conditional eddy covariance (CEC) approach EC towers three wine grape orchards for year 2021. Modeled Landsat 8 Collection 2 thermal infrared surface reflectance imagery well Harmonized Sentinel-2 datasets input into DisALEXI. results indicated that total similar between methods, but diverged, with DisALEXI-PT overestimating slightly underestimating when compared CEC estimates. Conversely, DisALEXI-PM agreed better CEC-derived overestimated under non-advective conditions. Compared another, estimated canopy temperatures ~5 °C cooler soil warmer than DisALEXI-PT, causing differences ?2.6 mm day?1 +2.6 day?1, respectively. iterative process required DisALEXI indicates converge ALEXI proportionate adjustments T, while convergence driven by E. analysis presented here can potentially drive improvements framework provide specific consumptive water use information unique structures, allowing improved irrigation efficiencies these systems.