Evaluation of partitioned evaporation and transpiration estimates within the DisALEXI modeling framework over irrigated crops in California

Authors: Knipper, Kyle; Anderson, Martha; BAMBACH, NICOLAS - University Of California, Davis; Kustas, William - Bill; Gao, Feng; ZAHN, EINARA - Princeton University; HAIN, CHRISTOPHER - National Aeronautics And Space Administration (NASA); McElrone, Andrew; ROSARIO BELFIORE, OSCAR - The University Of Naples Federico Ii; CASTRO, SEBASTIAN - University Of California, Davis; ALSINA, M - E & J Gallo Winery; SAA, SEBASTIAN - Almond Board Of California

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2022
Publication Date: 12/23/2022
Citation: Knipper, K.R., Anderson, M.C., Bambach, N., Kustas, W.P., Gao, F.N., Zahn, E., Hain, C., McElrone, A.J., Rosario Belfiore, O., Castro, S., Alsina, M.M., Saa, S. 2022. Evaluation of partitioned evaporation and transpiration estimates within the DisALEXI modeling framework over irrigated crops in California. Remote Sensing. 15(1). Article 68. https://doi.org/10.3390/rs15010068.
DOI: https://doi.org/10.3390/rs15010068

Interpretive Summary: Accurate characterization of water use in the form of evapotranspiration (ET) is imperative in water-limited cropping systems such as California vineyards and almond orchards. Satellite-based ET modeling techniques have proven reliable in determining field scale ET. However, validation efforts focus on ET and omit the evaluation of partitioned evaporation (E) and transpiration (T). Evaluation of the partitioned estimates of E and T is important in these water limited systems because irrigation strategies are likely to focus on reducing water loss from E rather than T, since vegetation is linked to crop biomass production. This study evaluates a satellite-based ET model and its ability to estimate individual E and T amounts over vineyards and almond orchards for the year 2021 using Landsat satellite imagery. Vineyard and almond sites are being monitored as part of the Grape Remote Sensing Atmospheric Profile Evapotranspiration eXperiment (GRAPEX) and the Tree crop Remote sensing of Evapotranspiration eXperiment (T-REX). Results of the study are promising as the proposed change to the satellite-based ET modeling technique appears to more accurately partition E and T from all sites. When applied operationally, the model output will give growers more specific consumptive water use information, subsequently allowing for improved irrigation and water use efficiencies in these valuable water-limited systems.

Technical Abstract: 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) and associated flux disaggregation technique (DisALEXI), have proven reliable in determining field scale ET. However, validation efforts focus on ET and omit an evaluation of partitioned evaporation (E) and transpiration (T). ALEXI/DisALEXI is based on the Two-Source Energy Balance (TSEB) model, making it uniquely qualified to derive E and T individually. The current study evaluated E and T estimates derived using two formulations of DisALEXI; one based on Priestley-Taylor (DisALEXI-PT) and the other on Penman-Monteith (DisALEXI-PM). Modeled values were validated against partitioned fluxes derived from the Conditional Eddy Covariance (CEC) approach. Results indicated little difference between modeled total ET fluxes but suggest differences in partitioned values, with DisALEXI-PT overestimating E and underestimating T when compared to CEC estimates. Conversely, DisALEXI-PM agreed better with CEC-derived E and overestimated T estimates under non-advective conditions. Compared to one another, DisALEXI-PM estimated canopy temperatures ~5 C cooler and soil temperatures ~5 C warmer than DisALEXI-PT, causing differences in E and T of ''2.6 mm day''1 and +2.6 mm day''1, respectively. The evaluation of the iterative process required for DisALEXI indicates DisALEXI-PM ET values converge on ALEXI ET with proportionate adjustments to E and T, while DisALEXI-PT convergence is driven by adjustments to E. The analysis presented here can potentially drive improvements in the modeling framework to provide specific soil and canopy consumptive water use information in unique canopy structures, allowing for improved irrigation and water use efficiencies in these water-limited systems.