Chen et al. (2022) Application of the vineyard data assimilation (VIDA) system to vineyard root-zone soil moisture monitoring in the California Central Valley

Identification

• Journal: Irrigation Science
• Year: 2022
• Authors: Fan Chen, Fangni Lei, Kyle Knipper, Feng Gao, L. McKee, María Mar Alsina, Joseph G. Alfieri, Martha C. Anderson, Nicolás Bambach, Sebastian J. Castro, Andrew J. McElrone, K. P. Alstad, Nick Dokoozlian, Felix Greifender, William P. Kustas, Claudia Notarnicola, Nurit Agam, John H. Prueger, Lawrence E. Hipps, Wade T. Crow
• DOI: 10.1007/s00271-022-00789-9

Short Summary

This study tested the Vineyard Data Assimilation (VIDA) system, which integrates 30 m resolution remote sensing data into a one-dimensional soil water balance model, demonstrating its capability to capture daily root-zone soil moisture (RZSM) variations (30–60 cm depth) in California vineyards, although it struggled to correct biases in assumed irrigation inputs during well-watered periods.

Objective

• To evaluate the performance and accuracy of the Vineyard Data Assimilation (VIDA) system for monitoring gridded root-zone soil moisture (RZSM) in vineyard environments.
• To assess the improvement in RZSM temporal accuracy achieved by assimilating high-resolution (30 m) Synthetic Aperture Radar (SAR) and Thermal-Infrared (TIR) remote sensing products into a soil water balance model.
• To identify the limitations of the VIDA system, particularly concerning its ability to correct biases in assumed irrigation applications.

Study Configuration

• Spatial Scale: Field scale (30 m resolution); tested retrospectively at two instrumented vineyard sites in the California Central Valley, part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX).
• Temporal Scale: Retrospective analysis covering four growing seasons (2017–2020); focus on capturing daily temporal variations in RZSM.

Methodology and Data

• Models used: Vineyard Data Assimilation (VIDA) system, which utilizes a one-dimensional soil water balance model coupled with a data assimilation scheme.
• Data sources: High-resolution (30 m) remote sensing products derived from Synthetic Aperture Radar (SAR) and Thermal-Infrared (TIR) sensors; In-situ RZSM measurements (for validation) collected at GRAPEX vineyard sites, specifically focusing on the 30 cm to 60 cm depth range.

Main Results

• The VIDA system generally captured the daily temporal variations in root-zone soil moisture (RZSM) for vertical depths of 30 cm to 60 cm beneath the vine row.
• The assimilation of high-resolution remote sensing products resulted in a modest improvement in the temporal accuracy of the VIDA RZSM estimates compared to the model-only simulation.
• VIDA demonstrated shortcomings in its ability to correct biases in assumed irrigation applications.
• This limitation was most pronounced during well-watered portions of the growing season when TIR-based evapotranspiration (ET) observations were not moisture limited and were therefore decoupled from RZSM dynamics.

Contributions

• Introduction and retrospective validation of the VIDA system, providing a novel, high-resolution (30 m) data assimilation framework specifically designed for RZSM monitoring in complex, drip-irrigated vineyard systems.
• Quantification of the effectiveness of assimilating combined SAR and TIR remote sensing data for improving RZSM temporal accuracy in agricultural settings.
• Identification of a critical limitation in data assimilation for irrigation management: the difficulty of correcting irrigation input biases when the land surface is not moisture-stressed (i.e., when ET is decoupled from RZSM).

Funding

• USDA Agricultural Research Service
• NASA Applied Sciences-Water Resources Program (Award NNH17AE39I)
• NASA Applied Science Award 80NSSC19K1247 ("High-Resolution Soil Moisture Monitoring for Improved Vineyard Water Resource Management")

Citation

@article{Chen2022Application,
  author = {Chen, Fan and Lei, Fangni and Knipper, Kyle and Gao, Feng and McKee, L. and Alsina, María Mar and Alfieri, Joseph G. and Anderson, Martha C. and Bambach, Nicolás and Castro, Sebastian J. and McElrone, Andrew J. and Alstad, K. P. and Dokoozlian, Nick and Greifender, Felix and Kustas, William P. and Notarnicola, Claudia and Agam, Nurit and Prueger, John H. and Hipps, Lawrence E. and Crow, Wade T.},
  title = {Application of the vineyard data assimilation (VIDA) system to vineyard root-zone soil moisture monitoring in the California Central Valley},
  journal = {Irrigation Science},
  year = {2022},
  doi = {10.1007/s00271-022-00789-9},
  url = {https://doi.org/10.1007/s00271-022-00789-9}
}

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