Abstract
Efforts to apply gridded root-zone soil moisture (RZSM) products for irrigation decision-support in vineyards are currently hampered by the difficulty of obtaining RZSM products that meet required accuracy, resolution, and data latency requirements. In particular, the operational application of soil water balance modeling is complicated by the difficulty of obtaining accurate irrigation inputs and representing complex sub-surface water-flow processes within vineyards. Here, we discuss prospects for addressing these shortcomings using the Vineyard Data Assimilation (VIDA) system based on the assimilation of high-resolution (30-m) soil moisture information obtained from synthetic aperture radar and thermal-infrared (TIR) remote sensing into a one-dimensional soil water balance model. The VIDA system is tested retrospectively (2017–2020) for two vineyard sites in the California Central Valley that have been instrumented as part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Results demonstrate that VIDA can generally capture daily temporal variations in RZSM for vertical depths of 30–60 cm beneath the vine row, and the assimilation of remote sensing products is shown to produce modest improvement in the temporal accuracy of VIDA RZSM estimates. However, results also reveal shortcomings in the ability of VIDA to correct biases in assumed irrigation applications—particularly during well-watered portions of the growing season when TIR-based evapotranspiration observations are not moisture limited and, therefore, decoupled from RZSM. Prospects for addressing these limitations and plans for the near-real-time operational application of the VIDA system are discussed.