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

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  • Wang, Tianxin
  • Melton, Forrest S.
  • Pôças, Isabel
  • Johnson, Lee F.
  • Thao, Touyee
  • Post, Kirk
  • Cassel-Sharma, Florence

Abstract

In California and other agricultural regions that are facing challenges with water scarcity, accurate estimates of crop evapotranspiration (ETc) can support agricultural entities in ongoing efforts to improve on-farm water use efficiency. Remote sensing approaches for calculating ETc can be used to support wide area mapping of crop coefficients and ETc 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 ETc data from satellite-derived vegetation indices (VI) and evaluate the accuracy of a VI-based approach for calculation of ETc 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 ETc 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 (fc) and height, and combined with satellite-derived fc data and grass reference ET (ETo) data as implemented within SIMS to estimate daily ETc from SIMS (ETc-SIMS) for the sugar beet crop. The accuracy of the daily ETc-SIMS data was evaluated against daily actual ET data from the weighing lysimeter (ETa-lys) and actual ET calculated using an energy balance approach from micrometeorological instrumentation (ETa-eb). Over the course of the 181-day production cycle, ETc-SIMS totaled 737.1 mm, which was within 7.7% of total ETa-lys and 3.7% of ETa-eb. On a daily timestep, SIMS mean bias error was −0.31 mm/day relative to ETa-lys, and 0.15 mm/day relative to ETa-eb. The results from this study highlight the potential utility of applying satellite-based fc data coupled with the A&P approach to estimate ETc for drip-irrigated crops.

Suggested Citation

  • Wang, Tianxin & Melton, Forrest S. & Pôças, Isabel & Johnson, Lee F. & Thao, Touyee & Post, Kirk & Cassel-Sharma, Florence, 2021. "Evaluation of crop coefficient and evapotranspiration data for sugar beets from landsat surface reflectances using micrometeorological measurements and weighing lysimetry," Agricultural Water Management, Elsevier, vol. 244(C).
    • Handle: RePEc:eee:agiwat:v:244:y:2021:i:c:s0378377420320801
    DOI: 10.1016/j.agwat.2020.106533
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    1. González-Dugo, M.P. & Escuin, S. & Cano, F. & Cifuentes, V. & Padilla, F.L.M. & Tirado, J.L. & Oyonarte, N. & Fernández, P. & Mateos, L., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale," Agricultural Water Management, Elsevier, vol. 125(C), pages 92-104.
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    2. He, Ruyan & Jin, Yufang & Jiang, Jinbao & Xu, Meng & Jia, Sen, 2022. "Sensitivity of METRIC-based tree crop evapotranspiration estimation to meteorology, land surface parameters and domain size," Agricultural Water Management, Elsevier, vol. 271(C).
    3. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Mota, M. & Wang, T., 2021. "Prediction of crop coefficients from fraction of ground cover and height: Practical application to vegetable, field and fruit crops with focus on parameterization," Agricultural Water Management, Elsevier, vol. 252(C).
    4. Wagner Wolff, & Francisco, João Paulo & Flumignan, Danilton Luiz & Marin, Fábio Ricardo & Folegatti, Marcos Vinícius, 2022. "Optimized algorithm for evapotranspiration retrieval via remote sensing," Agricultural Water Management, Elsevier, vol. 262(C).
    5. Pei Wang & Jingjing Ma & Juanjuan Ma & Haitao Sun & Qi Chen, 2021. "A Novel Approach for the Simulation of Reference Evapotranspiration and Its Partitioning," Agriculture, MDPI, vol. 11(5), pages 1-12, April.

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