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Influence of modeling domain and meteorological forcing data on daily evapotranspiration estimates from a Shuttleworth–Wallace model using Sentinel-2 surface reflectance data

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Abstract

Sustainable use of available water resources in viticulture can be aided by frequent high-resolution information on vineyard water status. Recently, a new Shuttleworth–Wallace evapotranspiration (ET) model, which uses a contextual framework to determine dry and wet extremes from the Sentinel-2 surface reflectance data (SW-S2), showed promising results when tested over a GRAPEX (Grape Remote-sensing Atmospheric Profile and ET eXperiment) site in California. However, current knowledge on its applicability across the climate gradient in California and how the selections of modeling domain and meteorological data influence model outputs are limited. This study expands the evaluation of the SW-S2 model across multiple domains and meteorological inputs covering all three GRAPEX sites over the 2018–2020 growing seasons. In comparison with flux tower observations, the size of the modeling domain did not have a strong influence on model performance, although the model performed marginally better under a larger domain (yielding root mean square error within 1.03–1.11 mm d−1 and mean biases within 2%). The source and quality of meteorological forcing data, in particular vapor pressure deficit (VPD) and wind speed (u), were found to have a strong influence on model output as indicated by the poor performance of the model with less accurate regional and coarse-scale gridded meteorological inputs. Results suggest that simple regression for local bias correction of VPD and u significantly improved model performance. Overall, this study supports future research aiming to merge outputs from more frequent spectral and less frequent thermal-based ET models and reduce latency in ET monitoring of California vineyards.

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Funding

Funding and logistical support for the GRAPEX project were provided by E. & J. Gallo Winery and from the NASA Applied Sciences-Water Resources Program (Grant No. NNH17AE39I). This research was also supported in part by the U.S. Department of Agriculture, Agricultural Research Service. In addition, we thank the staff of Viticulture, Chemistry and Enology Division of E. & J. Gallo Winery for the collection and processing of field data and the cooperation of the vineyard management staff at the SLM, BAR, and RIP vineyard site locations for logistical support and coordinating field operations with the GRAPEX team. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

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Authors and Affiliations

  1. USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA

    Nishan Bhattarai, William P. Kustas, Martha Anderson, Kyle R. Knipper, Feng Gao, Lynn Mckee & Joseph G. Alfieri

  2. Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy

    Guido D’Urso & Oscar R. Belfiore

  3. Department of Land, Air and Water Resources, University of California, Davis, CA, USA

    Mahyar Aboutalebi

  4. E and J Gallo Winery, Viticulture, Chemistry and Enology, Modesto, CA, USA

    N. Bambach-Ortiz & Maria M. Alsina

  5. USDA-ARS Crops Pathology and Genetics Research Unit, Davis, CA, 95616, USA

    Andrew J. McElrone

  6. Department of Viticulture and Enology, University of California, Davis, CA, 95616, USA

    Andrew J. McElrone

  7. USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA, 50011, USA

    John H. Prueger

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  1. Nishan Bhattarai
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Bhattarai, N., D’Urso, G., Kustas, W.P. et al. Influence of modeling domain and meteorological forcing data on daily evapotranspiration estimates from a Shuttleworth–Wallace model using Sentinel-2 surface reflectance data. Irrig Sci 40, 497–513 (2022). https://doi.org/10.1007/s00271-022-00768-0

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