Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry

Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry

In California and other agricultural regions that are facing challenges with water scarcity, accurate estimates of crop evapotranspiration (ET_c) can support agricultural entities in ongoing efforts to improve on-farm water use efficiency. Remote sensing approaches for calculating ET_c can be used to support wide area mapping of crop coefficients and ET_c with the goal of increasing access to spatially and temporally distributed information for these variables, and advancing the use of evapotranspiration (ET) data in irrigation scheduling and management. We briefly review past work on the derivation of crop coefficients and ET_c data from satellite-derived vegetation indices (VI) and evaluate the accuracy of a VI-based approach for calculation of ET_c using a well instrumented, drip irrigated sugar beet (Beta vulgaris) field in the California Central Valley as a demonstration case. Sugar beets are grown around the world for sugar production, and are also being evaluated in California as a potential biofuel crop as well as for their ability to scavenge nitrogen from the soil, with important potential benefits for reduction of nitrate leaching from agricultural fields during the winter months. In this study, we evaluated the accuracy of ET_c data from the Satellite Irrigation Management Support (SIMS) framework for sugar beets using ET data from a weighing lysimeter and a flux station instrumented with micrometeorological instrumentation. We used the Allen and Pereira (A&P) approach, which was developed to estimate single and basal crop coefficients from crop fractional cover (f_c) and height, and combined with satellite-derived f_c data and grass reference ET (ET_o) data as implemented within SIMS to estimate daily ET_c from SIMS (ET_c-SIMS) for the sugar beet crop. The accuracy of the daily ET_c-SIMS data was evaluated against daily actual ET data from the weighing lysimeter (ET_a-lys) and actual ET calculated using an energy balance approach from micrometeorological instrumentation (ET_a-eb). Over the course of the 181-day production cycle, ET_c-SIMS totaled 737.1 mm, which was within 7.7% of total ET_a-lys and 3.7% of ET_a-eb. On a daily timestep, SIMS mean bias error was −0.31 mm/day relative to ET_a-lys, and 0.15 mm/day relative to ET_a-eb. The results from this study highlight the potential utility of applying satellite-based f_c data coupled with the A&P approach to estimate ET_c for drip-irrigated crops.

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TouYee Thao is a graduate student.

Wang, T., Melton, F. S., Pocas, I., Johnson, L. F., Thao, T., Post, K., & Cassel-Sharma, F. (2021). Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry. Agricultural Water Management, 244, 106533. https://doi.org/10.1016/j.agwat.2020.106533