Using high-spatiotemporal thermal satellite ET retrievals for near-real time water use and stress monitoring in a California vineyard

Authors: Knipper, Kyle; Kustas, William - Bill; Anderson, Martha; ALSINA, M. - E & J Gallo Winery; HAIN, C. - Goddard Space Flight Center; Alfieri, Joseph; Prueger, John; Gao, Feng; McKee, Lynn; SANCHEZ, L. - E & J Gallo Winery

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/9/2019
Publication Date: 9/12/2019
Citation: Knipper, K.R., Kustas, W.P., Anderson, M.C., Alsina, M., Hain, C., Alfieri, J.G., Prueger, J.H., Gao, F.N., McKee, L.G., Sanchez, L. 2019. Using high-spatiotemporal thermal satellite ET retrievals for near-real time water use and stress monitoring in a California vineyard. Remote Sensing. 11(18):2124. https://doi.org/10.3390/rs11182124.
DOI: https://doi.org/10.3390/rs11182124

Interpretive Summary: Efficient use of agricultural water resources through irrigation scheduling is predicated on the accurate prediction and constant monitoring of evapotranspiration (ET) at the field or sub-field scale. This is especially true in viticulture, where both the amount and timing of irrigation applications is specifically used to control vine growth and manage grape yield and quality. Ground-based solutions can offer reliable localized ET estimates; however, their utility is limited by high maintenance cost and challenges in upscaling to vineyard or multi-vineyard scales. Satellite-based remote sensing methods, on the other hand, routinely provide spatial information useful for determining regional to field scale heterogeneity in vine conditions, water status and ET making them more suitable for large-area irrigation management. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. While the thermal-based data fusion system provided valuable information on ET and vine stress, latency in current satellite data availability does impact near-real-time applications in an operational setting over the course of a growing season. Multi-sensor data fusion methods are currently being developed as more satellites having thermal sensors are being deployed to reduce the impact of latency in satellite information.

Technical Abstract: In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in mapping of evapotranspiration (ET) at field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery in near-real-time over a vineyard in the Central Valley of California equipped with a Variable Rate Drip Irrigation (VRDI) system which enables differential water applications at the 30 x 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals in near real-time, the vineyard was sub-divided into 4 blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts near-real-time applications in an operational setting over the course of a growing season.